This study explored spatial explicit multiple cropping efficiency(MCE) of China in 2005 by coupling time series remote sensing data with an econometric model-stochastic frontier analysis(SFA).We firstly extracted mult...This study explored spatial explicit multiple cropping efficiency(MCE) of China in 2005 by coupling time series remote sensing data with an econometric model-stochastic frontier analysis(SFA).We firstly extracted multiple cropping index(MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer(MODIS) enhanced vegetation index(EVI) value.Then,SFA model was employed to calculate MCE,by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output.The result showed that 46% of the cultivated land in China in 2005 was multiple cropped,including 39% doublecropped land and 7% triple-cropped land.Most of the multiple cropped land was distributed in the south of Great Wall.The total efficiency of multiple cropping in China was 87.61% in 2005.Southwestern China,Ganxin Region,the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE.Fragmental terrain,soil salinization,deficiency of water resources,and loss of labor force were the obstacles for MCE promotion in different zones.The method proposed in this paper is theoretically reliable for MCE extraction,whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.展开更多
Studies of wind erosion based on Geographic Information System(GIS) and Remote Sensing(RS) have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been condu...Studies of wind erosion based on Geographic Information System(GIS) and Remote Sensing(RS) have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been conducted to estimate the intensity of large-scale wind erosion in Inner Mongolia,China.In the present study,a new model based on five factors including the number of snow cover days,soil erodibility,aridity,vegetation index and wind field intensity was developed to quantitatively estimate the amount of wind erosion.The results showed that wind erosion widely existed in Inner Mongolia.It covers an area of approximately 90×104 km2,accounting for 80% of the study region.During 1985–2011,wind erosion has aggravated over the entire region of Inner Mongolia,which was indicated by enlarged zones of erosion at severe,intensive and mild levels.In Inner Mongolia,a distinct spatial differentiation of wind erosion intensity was noted.The distribution of change intensity exhibited a downward trend that decreased from severe increase in the southwest to mild decrease in the northeast of the region.Zones occupied by barren land or sparse vegetation showed the most severe erosion,followed by land occupied by open shrubbery.Grasslands would have the most dramatic potential for changes in the future because these areas showed the largest fluctuation range of change intensity.In addition,a significantly negative relation was noted between change intensity and land slope.The relation between soil type and change intensity differed with the content of Ca CO3 and the surface composition of sandy,loamy and clayey soils with particle sizes of 0–1 cm.The results have certain significance for understanding the mechanism and change process of wind erosion that has occurred during the study period.Therefore,the present study can provide a scientific basis for the prevention and treatment of wind erosion in Inner Mongolia.展开更多
Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environment...Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.展开更多
Land use and land cover (LULC) represent the ongoing challenge of environmental variation. The understanding of the level and process of its change is the basis for any environmental planning and management. In Morocc...Land use and land cover (LULC) represent the ongoing challenge of environmental variation. The understanding of the level and process of its change is the basis for any environmental planning and management. In Morocco, as everywhere in the world, human population densities are constantly increasing on the coastal zones. This results in a continuous and rapid acceleration of the use of coastal space and an increase in pressures on ecosystems and the different species they contain. The purpose of this study is the analysis of the changes in LULC from 1985 to 2017 in the coastal area of Sebou estuary, situated in the Northwest of the Moroccan Atlantic coast. The changes were identified and assessed after classifying a series of Landsat images taken during 1985, 2002 and 2017. The algorithm used for the classification is the Support Vector Machine (SVM), which yielded results with accuracy higher than 85%. The results of the land use land cover change describe phenomenal urbanization and deforestation, as well as an evolution of the agricultural sector, indicating the impact of anthropization in this vulnerable environment.展开更多
Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and a...Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteenlevel(FLFL) satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level(FLTL) remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.展开更多
Aiming for the restoration of degraded ecosystems, many ecological engineering projects have been implemented around the world. This study investigates the ecological engineering project effectiveness on vegetation re...Aiming for the restoration of degraded ecosystems, many ecological engineering projects have been implemented around the world. This study investigates the ecological engineering project effectiveness on vegetation restoration in the Beijing-Tianjin Sand Source Region(BTSSR) from 2000 to 2010 based on the rain use efficiency(RUE) trend in relation to the land cover. More than half of the BTSSR experienced a vegetation productivity increase from 2000 to 2010, with the increasing intensity being sensitive to the indicators chosen. A clear tendency towards smaller increasing areas was shown when using the net primary productivity(NPP, 51.30%) instead of the accumulated normalized difference vegetation index(59.30%). The short-term variation in the precipitation and intra-seasonal precipitation distribution had a great impact on the remote sensing-based vegetation productivity. However, the residual trends method(RESTREND) effectively eliminated this correlation, while incorporating the variance and skewness of the precipitation distribution increased the models′ ability to explain the vegetation productivity variation. The RUE combined with land cover dynamics was valid for the effectiveness assessment of the ecological engineering projects on vegetation restoration. Particularly, the result based on growing season accumulated normalized difference vegetation index(ΣNDVI) residuals was the most effective, showing that 47.39% of the BTSSR experienced vegetation restoration from 2000 to 2010. The effectiveness of the ecological engineering projects differed for each subarea and was proportional to the strength of ecological engineering. The water erosion region dominated by woodland showed the best restoration, followed by the wind-water erosion crisscross regions, while the wind erosion regions dominated by grassland showed the worst effect. Seriously degraded regions still cover more area in the BTSSR than restored regions. Therefore, more future effort should be put in restoring degraded land.展开更多
Synthetic aperture radar(SAR) is an effective and important technique in monitoring crop and other agricultural targets because its quality does not depend on weather conditions. SAR is sensitive to the geometrical st...Synthetic aperture radar(SAR) is an effective and important technique in monitoring crop and other agricultural targets because its quality does not depend on weather conditions. SAR is sensitive to the geometrical structures and dielectric properties of the targets and has a certain penetration ability to some agricultural targets. The capabilities of SAR for agriculture applications can be organized into three main categories: crop identification and crop planting area statistics, crop and cropland parameter extraction, and crop yield estimation. According to the above concepts, this paper systematically analyses the recent progresses, existing problems and future directions in SAR agricultural remote sensing. In recent years, with the remarkable progresses in SAR remote sensing systems, the available SAR data sources have been greatly enriched. The accuracies of the crop classification and parameter extraction by SAR data have been improved progressively. But the development of modern agriculture has put forwarded higher requirements for SAR remote sensing. For instance, the spatial resolution and revisiting cycle of the SAR sensors, the accuracy of crop classification, the whole phenological period monitoring of crop growth status, the soil moisture inversion under the condition of high vegetation coverage, the integrations of SAR remote sensing retrieval information with hydrological models and/or crop growth models, and so on, still need to be improved. In the future, the joint use of optical and SAR remote sensing data, the application of multi-band multi-dimensional SAR, the precise and high efficient modeling of electromagnetic scattering and parameter extraction of crop and farmland composite scene, the development of light and small SAR systems like those onboard unmanned aerial vehicles and their applications will be active research areas in agriculture remote sensing. This paper concludes that SAR remote sensing has great potential and will play a more significant role in the various fields of agricultural remote sensing.展开更多
Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carb...Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carbon and forest aboveground biomass(FAGB).Different levels of detail are needed to estimate FAGB at local,regional and national scales.Multi-scale remote sensing analysis from high,medium and coarse spatial resolution data,along with field sampling,is one approach often used.However,the methods developed are still time consuming,expensive,and inconvenient for systematic monitoring,especially for developing countries,as they require vast numbers of field samples for upscaling.Here,we recommend a convenient two-scale approach to estimate FAGB that was tested in our study sites.The study was conducted in the Chitwan district of Nepal using GeoEye-1(0.5 m),Landsat(30 m)and Google Earth very high resolution(GEVHR)Quickbird(0.65 m)images.For the local scale(Kayerkhola watershed),tree crowns of the area were delineated by the object-based image analysis technique on GeoEye images.An overall accuracy of 83%was obtained in the delineation of tree canopy cover(TCC)per plot.A TCC vs.FAGB model was developed based on the TCC estimations from GeoEye and FAGB measurements from field sample plots.A coefficient of determination(R2)of 0.76 was obtained in the modelling,and a value of 0.83 was obtained in the validation of the model.To upscale FAGB to the entire district,open source GEVHR images were used as virtual field plots.We delineated their TCC values and then calculated FAGB based on a TCC versus FAGB model.Using the multivariate adaptive regression splines machine learning algorithm,we developed a model from the relationship between the FAGB of GEVHR virtual plots with predictor parameters from Landsat 8 bands and vegetation indices.The model was then used to extrapolate FAGB to the entire district.This approach considerably reduced the need for field data and commercial very high resolution imagery while achieving two-scale forest information and FAGB estimates at high resolution(30 m)and accuracy(R2=0.76 and 0.7)with minimal error(RMSE=64 and 38 tons ha-1)at local and regional scales.This methodology is a promising technique for cost-effective FAGB and carbon estimations and can be replicated with limited resources and time.The method is especially applicable for developing countries that have low budgets for carbon estimations,and it is also applicable to the Reducing Emissions from Deforestation and Forest Degradation(REDD?)monitoring reporting and verification processes.展开更多
In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were c...In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.展开更多
The support given by Earth observation data and Earth system science play an increasingly important role in global change,regional sustainable development,extreme events,and the development of social and economic need...The support given by Earth observation data and Earth system science play an increasingly important role in global change,regional sustainable development,extreme events,and the development of social and economic needs.This field is also moving towards systematization,platforms,and standardized development.In December 2015,nearly 200 parties of the United Nations Framework Convention on Climate Change agreed in Paris to make arrangements for global action in response to climate change by 2020.China jointly issued a climate change adaptation strategy for cities in 2016 and then elevated national action to respond to climate change.China's Earth Observation and Earth Science development is facing new challenges as it supports the national civil space infrastructure and high-resolution Earth observation system.展开更多
Wetlands are highly productive natural ecosystems, providing valuable goods and services. There is growing interest in transferring ecosystem service value from the existing wetlands studied to other wetlands ecosyste...Wetlands are highly productive natural ecosystems, providing valuable goods and services. There is growing interest in transferring ecosystem service value from the existing wetlands studied to other wetlands ecosystems at a large geographic scale. The benefit transfer method uses the known values from wetlands to predict the value of other wetland sites. This methodology requires only limited time and resources. The present study calculated the value of the ecological services provided by lake and marsh wetlands in China in terms of biodiversity indices, water quality indices and economic indices. Basic data on wetlands were obtained through remote sensing images. The results show that: 1) The total ecosystem service value of the lake and marsh wetlands in 2008 was calculated to be 8.1841 × 1010 United States Dollars(USD), with the marsh and lake wetlands contributing 5.6329 × 1010 and 2.5512 × 1010 USD, respectively. Values of marsh ecosystem service were concentrated in Heilongjiang Province(2.5516 × 1010 USD), Qinghai Province(1.2014 × 1010 USD), and Inner Mongolia Autonomous Region(1.1884 × 1010 USD). The value of the lakes were concentrated in Tibet Autonomous Region(6.223 × 109 USD), Heilongjiang(5.810 × 109 USD), and Qinghai(5.500 × 109 USD). 2) Waste treatment and climate regulation services contributed to 26.29% and 24.74% respectively, of the total ecosystem service value of the marsh wetlands. Hydrological regulation and waste treatment contributed to 41.39% and 32.75%, respectively, of the total ecosystem service value of the lake wetlands. 3) The total ecological service value of the lake and marsh wetlands was 54.64% of the total service value of natural grassland ecosystems and 30.34% of the total service value of forests ecosystems in China.展开更多
The Yalu Tsangpo River basin is a typical semi-arid and cold region in the Qinghai-Tibet Plateau, where significant climate change has been detected in the past decades. The objective of this paper is to demonstrate h...The Yalu Tsangpo River basin is a typical semi-arid and cold region in the Qinghai-Tibet Plateau, where significant climate change has been detected in the past decades. The objective of this paper is to demonstrate how the regional vegetation, especially the typical plant types, responds to the climate changes. In this study, the model of gravity center has been firstly introduced to analyze the spatial-temporal relationship between NDVI and climate factors considering the time-lag effect. The results show that the vegetation grown has been positively influenced by the rainfall and precipitation both in moving tracks of gravity center and time-lag effect especially for the growing season during the past thirteen years. The herbs and shrubs are inclined to be influenced by the change of rainfall and temperature, which is indicated by larger positive correlation coefficients at the 0.05 confidence level and shorter lagging time. For the soil moisture, the significantly negative relationship of NDV-PDI indicates that the growth and productivity of the vegetation are closely related to the short-term soil water, with the correlation coefficients reaching the maximum value of 0.81 at Lag 0-1. Among the typical vegetation types of plateau, the shrubs of low mountain, steppe and meadow are more sensitive to the change of soil moisture with coefficients of-0.95,-0.93,-0.92, respectively. These findings reveal that the spatial and temporal heterogeneity between NDVI and climatic factors are of great ecological significance and practical value for the protection of eco-environment in Qinghai-Tibet Plateau.展开更多
The vegetation ecosystem of the Qinghai–Tibet Plateau in China,considered to be the′′natural laboratory′′of climate change in the world,has undergone profound changes under the stress of global change.Herein,we a...The vegetation ecosystem of the Qinghai–Tibet Plateau in China,considered to be the′′natural laboratory′′of climate change in the world,has undergone profound changes under the stress of global change.Herein,we analyzed and discussed the spatial-temporal change patterns and the driving mechanisms of net primary productivity(NPP)in the Qinghai–Tibet Plateau from 2000 to 2015 based on the gravity center and correlation coefficient models.Subsequently,we quantitatively distinguished the relative effects of climate change(such as precipitation,temperature and evapotranspiration)and human activities(such as grazing and ecological construction)on the NPP changes using scenario analysis and Miami model based on the MOD17A3 and meteorological data.The average annual NPP in the Qinghai–Tibet Plateau showed a decreasing trend from the southeast to the northwest during 2000–2015.With respect to the inter-annual changes,the average annual NPP exhibited a fluctuating upward trend from 2000 to 2015,with a steep increase observed in 2005 and a high fluctuation observed from 2005 to 2015.In the Qinghai–Tibet Plateau,the regions with the increase in NPP(change rate higher than 10%)were mainly concentrated in the Three-River Source Region,the northern Hengduan Mountains,the middle and lower reaches of the Yarlung Zangbo River,and the eastern parts of the North Tibet Plateau,whereas the regions with the decrease in NPP(change rate lower than–10%)were mainly concentrated in the upper reaches of the Yarlung Zangbo River and the Ali Plateau.The gravity center of NPP in the Qinghai–Tibet Plateau has moved southwestward during 2000–2015,indicating that the increment and growth rate of NPP in the southwestern part is greater than those of NPP in the northeastern part.Further,a significant correlation was observed between NPP and climate factors in the Qinghai–Tibet Plateau.The regions exhibiting a significant correlation between NPP and precipitation were mainly located in the central and eastern Qinghai–Tibet Plateau,and the regions exhibiting a significant correlation between NPP and temperature were mainly located in the southern and eastern Qinghai–Tibet Plateau.Furthermore,the relative effects of climate change and human activities on the NPP changes in the Qinghai–Tibet Plateau exhibited significant spatial differences in three types of zones,i.e.,the climate change-dominant zone,the human activity-dominant zone,and the climate change and human activity interaction zone.These research results can provide theoretical and methodological supports to reveal the driving mechanisms of the regional ecosystems to the global change in the Qinghai–Tibet Plateau.展开更多
Urban areas and its evolution are important anthropogenic indicators and human ecological footprints, and play decisive roles in environmental change analysis, global geo-conditional monitoring, and sustainable develo...Urban areas and its evolution are important anthropogenic indicators and human ecological footprints, and play decisive roles in environmental change analysis, global geo-conditional monitoring, and sustainable development. China has the highest rate of urban expansion and has emerged as an urban expansion hotspot worldwide. In this paper, the progress of studies on Chinese urban expansion based on remote sensing technology are summarized and analyzed from the aspects of urban area definition, remotely sensed imagery applied in urban expansion, monitoring methods of urban expansion, and urban expansion applications. Existing issues and future directions of Chinese urban expansion are discussed and proposed. Results indicate that: 1) The fusion of multi-source remotely sensed imagery is imperative to meet the needs of urban expansion with various monitoring terms and frequencies on different scales and dimensions. 2) To guarantee the classification accuracy and efficiency and describe urban expansion and its influences on local land use simultaneously, the combination of visual interpretation and automatic classification is the tendency of future monitoring methods of urban areas. 3) Urban expansion data have become the prerequisite for recognizing the urban development process, excavating its driving forces, simulating and predicting the future development directions, and also is conducive to revealing and explaining urban ecological and environmental issues. 4) In the past decades, Chinese scholars have promoted the application of remote sensing technology in the urban expansion field, with data construction, methods and models developing from the quotation stage to improvement and innovation stage; however, an independent and consistent urban expansion data on the national scale with long-term and high-frequency(such as annual monitoring) monitoring is still lacking.展开更多
Sand and dust storms(SDS) are common phenomena in arid and semi-arid areas. In recent years, SDS frequencies and intensities have increased significantly in Iran. A research on SDS sources is important for understandi...Sand and dust storms(SDS) are common phenomena in arid and semi-arid areas. In recent years, SDS frequencies and intensities have increased significantly in Iran. A research on SDS sources is important for understanding the mechanisms of dust generation and assessing its socio-economic and environmental impacts. In this paper, we developed a new approach to identify SDS source areas in Iran using a combination of nine related datasets, namely drought events, temperature, precipitation, location of sandy soils, SDS frequency, human-induced soil degradation(HISD), human influence index(HII), rain use efficiency(RUE) and net primary productivity(NPP) loss. To identify SDS source areas, we firstly normalized these datasets under uniform criteria including layer reprojection using Lambert conformal conic projection, data conversion from shapefile to raster, Min-Max Normalization with data range from 0 to 1, and data interpolation by Kriging and images resampling(resolution of 1 km). After that, a score map for the possibility of SDS sources was generated through overlaying multiple datasets under average weight allocation criterion, in which each item obtained weight equally. In the score map, the higher the score, the more possible a specific area could be regarded as SDS source area. Exceptions mostly came from large cities, like Tehran and Isfahan. As a result, final SDS source areas were mapped out, and Al-Howizeh/Al-Azim marshes and Sistan Basin were identified as main SDS source areas in Iran. The SDS source area in Al-Howizeh/Al-Azim marshes still keeps expanding. In addition, Al-Howizeh/Al-Azim marshes are now suffering rapid land degradation due to natural and human-induced factors and might totally vanish in the near future. Sistan Basin also demonstrates the impacts of soil degradation and wind erosion. With appropriate intensity, duration, wind speed and altitude of the dust storms, sand particles uplifting from this area might have developed into extreme dust storms, especially during the summer.展开更多
As is well known,clouds impact the radiative budget,climate change,hydrological processes,and the global carbon,nitrogen and sulfur cycles.To understand the wide-ranging effects of clouds,it is necessary to assess cha...As is well known,clouds impact the radiative budget,climate change,hydrological processes,and the global carbon,nitrogen and sulfur cycles.To understand the wide-ranging effects of clouds,it is necessary to assess changes in cloud cover at high spatial and temporal resolution.In this study,we calculate global cloud cover during the day and at night using cloud products estimated from Moderate Resolution Imaging Spectroradiometer(MODIS)data.Results indicate that the global mean cloud cover from 2003 to 2012 was 66%.Moreover,global cloud cover increased over this recent decade.Specifically,cloud cover over land areas(especially North America,Antarctica,and Europe)decreased(slope=–0.001,R^2=0.5254),whereas cloud cover over ocean areas(especially the Indian and Pacific Oceans)increased(slope=0.0011,R^2=0.4955).Cloud cover is relatively high between the latitudes of 36°S and 68°S compared to other regions,and cloud cover is lowest over Oceania and Antarctica.The highest rates of increase occurred over Southeast Asia and Oceania,whereas the highest rates of decrease occurred over Antarctica and North America.The global distribution of cloud cover regulates global temperature change,and the trends of these two variables over the 10-year period examined in this study(2003–2012)oppose one another in some regions.These findings are very important for studies of global climate change.展开更多
Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual plants.An accurate estimation of LCC can therefore provide valuable information for precision field manage...Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual plants.An accurate estimation of LCC can therefore provide valuable information for precision field management.Red-edge information from hyperspectral data has been widely used to estimate crop LCC.However,after the advent of red-edge bands in satellite imagery,no systematic evaluation of the performance of satellite data has been conducted.Toward this end,we analyze herein the performance of winter wheat LCC retrieval of currant and forthcoming satellites(RapidEye,Sentinel-2 and EnMAP)and their new red-edge bands by using partial least squares regression(PLSR)and a vegetation-indexbased approach.These satellite spectral data were obtained by resampling ground-measured hyperspectral data under various field conditions and according to specific spectral response functions and spectral resolution.The results showed:1)This study confirmed that RapidEye,Sentinel-2 and EnMAP data are suitable for winter wheat LCC retrieval.For the PLSR approach,Sentinel-2 data provided more accurate estimates of LCC(R2=0.755,0.844,0.805 for 2002,2010,and 2002+2010)than do RapidEye data(R2=0.689,0.710,0.707 for 2002,2010,and 2002+2010)and EnMAP data(R2=0.735,0.867,0.771 for 2002,2010,and 2002+2010).For index-based approaches,the MERIS terrestrial chlorophyll index,which is a vegetation index with two red-edge bands,was the most sensitive and robust index for LCC for both the Sentinel-2 and EnMAP data(R2≥0.628),and the indices(NDRE1,SRRE1 and CIRE1)with a single red-edge band were the most sensitive and robust indices for the RapidEye data(R2≥0.420);2)According to the analysis of the effect of the wavelength and number of used red-edge spectral bands on LCC retrieval,the short-wavelength red-edge bands(from 699 to 734 nm)provided more accurate predictions when using the PLSR approach,whereas the long-wavelength red-edge bands(740 to 783 nm)gave more accurate predictions when using the vegetation indice(VI)approach.In addition,the prediction accuracy of RapidEye,Sentinel-2 and EnMAP data was improved gradually because of more number of red-edge bands and higher spectral resolution;VI regression models that contain a single or multiple red-edge bands provided more accurate predictions of LCC than those without red-edge bands,but for normalized difference vegetation index(NDVI)-,simple ratio(SR)-and chlorophyll index(CI)-like index,two red-edge bands index didn’t significantly improve the predictive accuracy of LCC than those indices with a single red-edge band.Although satellite data with higher spectral resolution and a greater number of red-edge bands marginally improve the accuracy of estimates of crop LCC,the level of this improvement remains insufficient because of higher spectral resolution,which results in a worse signal-to-noise ratio.The results of this study are helpful to accurately monitor LCC of winter wheat in large-area and provide some valuable advice for design of red-edge spectral bands of satellite sensor in future.展开更多
Glaciers play an important role in the climate system. The elevation change of a glacier is an important parameter in studies of glacier dynamics. Only a few ground-based measurements of high mountain glaciers are ava...Glaciers play an important role in the climate system. The elevation change of a glacier is an important parameter in studies of glacier dynamics. Only a few ground-based measurements of high mountain glaciers are available due to their remoteness, high elevation, and complex topography. The acquisition from the German Tan DEM-X(Terra SAR-X add-on for Digital Elevation Measurement) SAR imaging configuration provides a reliable data sources for studying the elevation change of glaciers. In this study, the bistatic Tan DEM-X data that cover the Geladandong Mountain on the Tibetan Plateau were processed with SAR interferometry technique and the elevation changes of the mountain's glaciers during 2000–2014 were obtained. The results indicated that although distinct positive and negative elevation changes were found for different glacier tongues, the mean elevation change was about-0.14±0.26 m a-1. Geoscience Laser Altimeter System(GLAS) data were obtained for comparison and verification. The investigation using GLAS data demonstrated the efficacy of the proposed method in determining glacier elevation change. Thus, the presented approach is appropriate for monitoring glacier elevation change and it constitutes a valuable tool for studies of glacier dynamics.展开更多
Understanding the effects of land use changes on the spatiotemporal variation of soil organic carbon(SOC)can provide guidance for low carbon and sustainable agriculture.In this paper,based on the large-scale datasets ...Understanding the effects of land use changes on the spatiotemporal variation of soil organic carbon(SOC)can provide guidance for low carbon and sustainable agriculture.In this paper,based on the large-scale datasets of soil surveys in 1982 and 2009 for Pinggu District—an urban-rural ecotone of Beijing,China,the effects of land use and land use changes on both temporal variation and spatial variation of SOC were analyzed.Results showed that from 1982 to 2009in Pinggu District,the following land use change mainly occurred:Grain cropland converted to orchard or vegetable land,and grassland converted to forestland.The SOC content decreased in region where the land use type changed to grain cropland(e.g.,vegetable land to grain cropland decreased by 0.7 g kg^(-1);orchard to grain cropland decreased by 0.2 g kg^(-1)).In contrast,the SOC content increased in region where the land use type changed to either orchard(excluding forestland)or forestland(e.g.,grain cropland to orchard and forestland increased by 2.7 and 2.4 g kg^(-1),respectively;grassland to orchard and forestland increased by 4.8 and 4.9 g kg^(-1),respectively).The organic carbon accumulation capacity per unit mass of the soil increased in the following order:grain cropland soikvegetable land/grassland soikorchard soikforestland soil.Therefore,to both secure supply of agricultural products and develop low carbon agriculture in a modern city,orchard has proven to be a good choice for land using.展开更多
基金supported by the National Natural Science Foundation of China (41001277)the National 973 Program of China (2010CB95090102)
文摘This study explored spatial explicit multiple cropping efficiency(MCE) of China in 2005 by coupling time series remote sensing data with an econometric model-stochastic frontier analysis(SFA).We firstly extracted multiple cropping index(MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer(MODIS) enhanced vegetation index(EVI) value.Then,SFA model was employed to calculate MCE,by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output.The result showed that 46% of the cultivated land in China in 2005 was multiple cropped,including 39% doublecropped land and 7% triple-cropped land.Most of the multiple cropped land was distributed in the south of Great Wall.The total efficiency of multiple cropping in China was 87.61% in 2005.Southwestern China,Ganxin Region,the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE.Fragmental terrain,soil salinization,deficiency of water resources,and loss of labor force were the obstacles for MCE promotion in different zones.The method proposed in this paper is theoretically reliable for MCE extraction,whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
基金supported by the National Natural Science Foundation of China (41201441,41371363,41301501)Foundation of Director of Institute of Remote Sensing and Digital Earth,Chinese Academy of Science (Y4SY0200CX)Guangxi Key Laboratory of Spatial Information and Geomatics (1207115-18)
文摘Studies of wind erosion based on Geographic Information System(GIS) and Remote Sensing(RS) have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been conducted to estimate the intensity of large-scale wind erosion in Inner Mongolia,China.In the present study,a new model based on five factors including the number of snow cover days,soil erodibility,aridity,vegetation index and wind field intensity was developed to quantitatively estimate the amount of wind erosion.The results showed that wind erosion widely existed in Inner Mongolia.It covers an area of approximately 90×104 km2,accounting for 80% of the study region.During 1985–2011,wind erosion has aggravated over the entire region of Inner Mongolia,which was indicated by enlarged zones of erosion at severe,intensive and mild levels.In Inner Mongolia,a distinct spatial differentiation of wind erosion intensity was noted.The distribution of change intensity exhibited a downward trend that decreased from severe increase in the southwest to mild decrease in the northeast of the region.Zones occupied by barren land or sparse vegetation showed the most severe erosion,followed by land occupied by open shrubbery.Grasslands would have the most dramatic potential for changes in the future because these areas showed the largest fluctuation range of change intensity.In addition,a significantly negative relation was noted between change intensity and land slope.The relation between soil type and change intensity differed with the content of Ca CO3 and the surface composition of sandy,loamy and clayey soils with particle sizes of 0–1 cm.The results have certain significance for understanding the mechanism and change process of wind erosion that has occurred during the study period.Therefore,the present study can provide a scientific basis for the prevention and treatment of wind erosion in Inner Mongolia.
基金supported by the project of 2017 Directional Task of Earthquake Tracking of CEA(Grant No.2017010406)the project of Youth Foundation of CENC(Grant No.QNJJ201603)
文摘Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.
基金Acknowledgments This work was supported by the National Natural Science Foundation of China （Grant No. 41271427） and the National Key Technology R＆D Program （Grant No. 2012BAH27B05）.
文摘Land use and land cover (LULC) represent the ongoing challenge of environmental variation. The understanding of the level and process of its change is the basis for any environmental planning and management. In Morocco, as everywhere in the world, human population densities are constantly increasing on the coastal zones. This results in a continuous and rapid acceleration of the use of coastal space and an increase in pressures on ecosystems and the different species they contain. The purpose of this study is the analysis of the changes in LULC from 1985 to 2017 in the coastal area of Sebou estuary, situated in the Northwest of the Moroccan Atlantic coast. The changes were identified and assessed after classifying a series of Landsat images taken during 1985, 2002 and 2017. The algorithm used for the classification is the Support Vector Machine (SVM), which yielded results with accuracy higher than 85%. The results of the land use land cover change describe phenomenal urbanization and deforestation, as well as an evolution of the agricultural sector, indicating the impact of anthropization in this vulnerable environment.
基金financially supported by the funding appropriated from USDA-ARS National Program 305 Crop Productionthe 948 Program of Ministry of Agriculture of China (2016-X38)
文摘Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteenlevel(FLFL) satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level(FLTL) remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.
基金Under the auspices of National Natural Science Foundation of China(No.41571421)National Science and Technology Major Project of China(No.21-Y30B05-9001-13/15)
文摘Aiming for the restoration of degraded ecosystems, many ecological engineering projects have been implemented around the world. This study investigates the ecological engineering project effectiveness on vegetation restoration in the Beijing-Tianjin Sand Source Region(BTSSR) from 2000 to 2010 based on the rain use efficiency(RUE) trend in relation to the land cover. More than half of the BTSSR experienced a vegetation productivity increase from 2000 to 2010, with the increasing intensity being sensitive to the indicators chosen. A clear tendency towards smaller increasing areas was shown when using the net primary productivity(NPP, 51.30%) instead of the accumulated normalized difference vegetation index(59.30%). The short-term variation in the precipitation and intra-seasonal precipitation distribution had a great impact on the remote sensing-based vegetation productivity. However, the residual trends method(RESTREND) effectively eliminated this correlation, while incorporating the variance and skewness of the precipitation distribution increased the models′ ability to explain the vegetation productivity variation. The RUE combined with land cover dynamics was valid for the effectiveness assessment of the ecological engineering projects on vegetation restoration. Particularly, the result based on growing season accumulated normalized difference vegetation index(ΣNDVI) residuals was the most effective, showing that 47.39% of the BTSSR experienced vegetation restoration from 2000 to 2010. The effectiveness of the ecological engineering projects differed for each subarea and was proportional to the strength of ecological engineering. The water erosion region dominated by woodland showed the best restoration, followed by the wind-water erosion crisscross regions, while the wind erosion regions dominated by grassland showed the worst effect. Seriously degraded regions still cover more area in the BTSSR than restored regions. Therefore, more future effort should be put in restoring degraded land.
基金supported in part by the National Natural Science Foundation of China (61661136006 and 41371396)
文摘Synthetic aperture radar(SAR) is an effective and important technique in monitoring crop and other agricultural targets because its quality does not depend on weather conditions. SAR is sensitive to the geometrical structures and dielectric properties of the targets and has a certain penetration ability to some agricultural targets. The capabilities of SAR for agriculture applications can be organized into three main categories: crop identification and crop planting area statistics, crop and cropland parameter extraction, and crop yield estimation. According to the above concepts, this paper systematically analyses the recent progresses, existing problems and future directions in SAR agricultural remote sensing. In recent years, with the remarkable progresses in SAR remote sensing systems, the available SAR data sources have been greatly enriched. The accuracies of the crop classification and parameter extraction by SAR data have been improved progressively. But the development of modern agriculture has put forwarded higher requirements for SAR remote sensing. For instance, the spatial resolution and revisiting cycle of the SAR sensors, the accuracy of crop classification, the whole phenological period monitoring of crop growth status, the soil moisture inversion under the condition of high vegetation coverage, the integrations of SAR remote sensing retrieval information with hydrological models and/or crop growth models, and so on, still need to be improved. In the future, the joint use of optical and SAR remote sensing data, the application of multi-band multi-dimensional SAR, the precise and high efficient modeling of electromagnetic scattering and parameter extraction of crop and farmland composite scene, the development of light and small SAR systems like those onboard unmanned aerial vehicles and their applications will be active research areas in agriculture remote sensing. This paper concludes that SAR remote sensing has great potential and will play a more significant role in the various fields of agricultural remote sensing.
基金supported by the CAS Strategic Priority Research Program(No.XDA19030402)the National Key Research and Development Program of China(No.2016YFD0300101)+2 种基金the Natural Science Foundation of China(Nos.31571565,31671585)the Key Basic Research Project of the Shandong Natural Science Foundation of China(No.ZR2017ZB0422)Research Funding of Qingdao University(No.41117010153)
文摘Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carbon and forest aboveground biomass(FAGB).Different levels of detail are needed to estimate FAGB at local,regional and national scales.Multi-scale remote sensing analysis from high,medium and coarse spatial resolution data,along with field sampling,is one approach often used.However,the methods developed are still time consuming,expensive,and inconvenient for systematic monitoring,especially for developing countries,as they require vast numbers of field samples for upscaling.Here,we recommend a convenient two-scale approach to estimate FAGB that was tested in our study sites.The study was conducted in the Chitwan district of Nepal using GeoEye-1(0.5 m),Landsat(30 m)and Google Earth very high resolution(GEVHR)Quickbird(0.65 m)images.For the local scale(Kayerkhola watershed),tree crowns of the area were delineated by the object-based image analysis technique on GeoEye images.An overall accuracy of 83%was obtained in the delineation of tree canopy cover(TCC)per plot.A TCC vs.FAGB model was developed based on the TCC estimations from GeoEye and FAGB measurements from field sample plots.A coefficient of determination(R2)of 0.76 was obtained in the modelling,and a value of 0.83 was obtained in the validation of the model.To upscale FAGB to the entire district,open source GEVHR images were used as virtual field plots.We delineated their TCC values and then calculated FAGB based on a TCC versus FAGB model.Using the multivariate adaptive regression splines machine learning algorithm,we developed a model from the relationship between the FAGB of GEVHR virtual plots with predictor parameters from Landsat 8 bands and vegetation indices.The model was then used to extrapolate FAGB to the entire district.This approach considerably reduced the need for field data and commercial very high resolution imagery while achieving two-scale forest information and FAGB estimates at high resolution(30 m)and accuracy(R2=0.76 and 0.7)with minimal error(RMSE=64 and 38 tons ha-1)at local and regional scales.This methodology is a promising technique for cost-effective FAGB and carbon estimations and can be replicated with limited resources and time.The method is especially applicable for developing countries that have low budgets for carbon estimations,and it is also applicable to the Reducing Emissions from Deforestation and Forest Degradation(REDD?)monitoring reporting and verification processes.
基金Under the auspices of Major State Basic Research Development Program of China(No.2007CB714407)National Natural Science Foundation of China(No.40801070)Action Plan for West Development Program of Chinese Academy of Sciences(No.KZCX2-XB2-09)
文摘In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.
文摘The support given by Earth observation data and Earth system science play an increasingly important role in global change,regional sustainable development,extreme events,and the development of social and economic needs.This field is also moving towards systematization,platforms,and standardized development.In December 2015,nearly 200 parties of the United Nations Framework Convention on Climate Change agreed in Paris to make arrangements for global action in response to climate change by 2020.China jointly issued a climate change adaptation strategy for cities in 2016 and then elevated national action to respond to climate change.China's Earth Observation and Earth Science development is facing new challenges as it supports the national civil space infrastructure and high-resolution Earth observation system.
基金Under the auspices of Forestry Public Interest Research Program(No.201204201)National Natural Science Foundation of China(No.41171415)
文摘Wetlands are highly productive natural ecosystems, providing valuable goods and services. There is growing interest in transferring ecosystem service value from the existing wetlands studied to other wetlands ecosystems at a large geographic scale. The benefit transfer method uses the known values from wetlands to predict the value of other wetland sites. This methodology requires only limited time and resources. The present study calculated the value of the ecological services provided by lake and marsh wetlands in China in terms of biodiversity indices, water quality indices and economic indices. Basic data on wetlands were obtained through remote sensing images. The results show that: 1) The total ecosystem service value of the lake and marsh wetlands in 2008 was calculated to be 8.1841 × 1010 United States Dollars(USD), with the marsh and lake wetlands contributing 5.6329 × 1010 and 2.5512 × 1010 USD, respectively. Values of marsh ecosystem service were concentrated in Heilongjiang Province(2.5516 × 1010 USD), Qinghai Province(1.2014 × 1010 USD), and Inner Mongolia Autonomous Region(1.1884 × 1010 USD). The value of the lakes were concentrated in Tibet Autonomous Region(6.223 × 109 USD), Heilongjiang(5.810 × 109 USD), and Qinghai(5.500 × 109 USD). 2) Waste treatment and climate regulation services contributed to 26.29% and 24.74% respectively, of the total ecosystem service value of the marsh wetlands. Hydrological regulation and waste treatment contributed to 41.39% and 32.75%, respectively, of the total ecosystem service value of the lake wetlands. 3) The total ecological service value of the lake and marsh wetlands was 54.64% of the total service value of natural grassland ecosystems and 30.34% of the total service value of forests ecosystems in China.
基金funded by the National Natural Science Foundation of China (Grant No. 41201441, No. 41371363, and No. 41301501)Guangxi Key Laboratory of Spatial Information and Geomatics (Grant No. 1207115-18)the knowledge innovation project of the Chinese academy of sciences (Grant Nos. KZCX2YW-333, KZCXZ-EW-317)
文摘The Yalu Tsangpo River basin is a typical semi-arid and cold region in the Qinghai-Tibet Plateau, where significant climate change has been detected in the past decades. The objective of this paper is to demonstrate how the regional vegetation, especially the typical plant types, responds to the climate changes. In this study, the model of gravity center has been firstly introduced to analyze the spatial-temporal relationship between NDVI and climate factors considering the time-lag effect. The results show that the vegetation grown has been positively influenced by the rainfall and precipitation both in moving tracks of gravity center and time-lag effect especially for the growing season during the past thirteen years. The herbs and shrubs are inclined to be influenced by the change of rainfall and temperature, which is indicated by larger positive correlation coefficients at the 0.05 confidence level and shorter lagging time. For the soil moisture, the significantly negative relationship of NDV-PDI indicates that the growth and productivity of the vegetation are closely related to the short-term soil water, with the correlation coefficients reaching the maximum value of 0.81 at Lag 0-1. Among the typical vegetation types of plateau, the shrubs of low mountain, steppe and meadow are more sensitive to the change of soil moisture with coefficients of-0.95,-0.93,-0.92, respectively. These findings reveal that the spatial and temporal heterogeneity between NDVI and climatic factors are of great ecological significance and practical value for the protection of eco-environment in Qinghai-Tibet Plateau.
基金supported by the Natural Science Foundation of Shandong Province(ZR2018BD001)the Project of Shandong Province Higher Educational Science and Technology Program(J18KA181)+4 种基金the Key Research Program of Frontier Science of Chinese Academy of Sciences(QYZDY-SSW-DQC007)the Open Fund of Key Laboratory of Geographic Information Science(Ministry of Education),East China Normal University(KLGIS2017A02)the Open Fund of State Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(17I04)the Open Fund of Key Laboratory of Geomatics and Digital Technology of Shandong Provincethe National Key R&D Program of China(2017YFA0604804)
文摘The vegetation ecosystem of the Qinghai–Tibet Plateau in China,considered to be the′′natural laboratory′′of climate change in the world,has undergone profound changes under the stress of global change.Herein,we analyzed and discussed the spatial-temporal change patterns and the driving mechanisms of net primary productivity(NPP)in the Qinghai–Tibet Plateau from 2000 to 2015 based on the gravity center and correlation coefficient models.Subsequently,we quantitatively distinguished the relative effects of climate change(such as precipitation,temperature and evapotranspiration)and human activities(such as grazing and ecological construction)on the NPP changes using scenario analysis and Miami model based on the MOD17A3 and meteorological data.The average annual NPP in the Qinghai–Tibet Plateau showed a decreasing trend from the southeast to the northwest during 2000–2015.With respect to the inter-annual changes,the average annual NPP exhibited a fluctuating upward trend from 2000 to 2015,with a steep increase observed in 2005 and a high fluctuation observed from 2005 to 2015.In the Qinghai–Tibet Plateau,the regions with the increase in NPP(change rate higher than 10%)were mainly concentrated in the Three-River Source Region,the northern Hengduan Mountains,the middle and lower reaches of the Yarlung Zangbo River,and the eastern parts of the North Tibet Plateau,whereas the regions with the decrease in NPP(change rate lower than–10%)were mainly concentrated in the upper reaches of the Yarlung Zangbo River and the Ali Plateau.The gravity center of NPP in the Qinghai–Tibet Plateau has moved southwestward during 2000–2015,indicating that the increment and growth rate of NPP in the southwestern part is greater than those of NPP in the northeastern part.Further,a significant correlation was observed between NPP and climate factors in the Qinghai–Tibet Plateau.The regions exhibiting a significant correlation between NPP and precipitation were mainly located in the central and eastern Qinghai–Tibet Plateau,and the regions exhibiting a significant correlation between NPP and temperature were mainly located in the southern and eastern Qinghai–Tibet Plateau.Furthermore,the relative effects of climate change and human activities on the NPP changes in the Qinghai–Tibet Plateau exhibited significant spatial differences in three types of zones,i.e.,the climate change-dominant zone,the human activity-dominant zone,and the climate change and human activity interaction zone.These research results can provide theoretical and methodological supports to reveal the driving mechanisms of the regional ecosystems to the global change in the Qinghai–Tibet Plateau.
基金Under the auspices of National Major Science and Technology Program for Water Pollution Contro and Treatment(No.2017ZX07101001)International Partnership Program of Chinese Academy of Sciences(No.131C11KYSB20160061)
文摘Urban areas and its evolution are important anthropogenic indicators and human ecological footprints, and play decisive roles in environmental change analysis, global geo-conditional monitoring, and sustainable development. China has the highest rate of urban expansion and has emerged as an urban expansion hotspot worldwide. In this paper, the progress of studies on Chinese urban expansion based on remote sensing technology are summarized and analyzed from the aspects of urban area definition, remotely sensed imagery applied in urban expansion, monitoring methods of urban expansion, and urban expansion applications. Existing issues and future directions of Chinese urban expansion are discussed and proposed. Results indicate that: 1) The fusion of multi-source remotely sensed imagery is imperative to meet the needs of urban expansion with various monitoring terms and frequencies on different scales and dimensions. 2) To guarantee the classification accuracy and efficiency and describe urban expansion and its influences on local land use simultaneously, the combination of visual interpretation and automatic classification is the tendency of future monitoring methods of urban areas. 3) Urban expansion data have become the prerequisite for recognizing the urban development process, excavating its driving forces, simulating and predicting the future development directions, and also is conducive to revealing and explaining urban ecological and environmental issues. 4) In the past decades, Chinese scholars have promoted the application of remote sensing technology in the urban expansion field, with data construction, methods and models developing from the quotation stage to improvement and innovation stage; however, an independent and consistent urban expansion data on the national scale with long-term and high-frequency(such as annual monitoring) monitoring is still lacking.
基金funded by the Small Scale Funding Agreement (UNEP/ROWA)
文摘Sand and dust storms(SDS) are common phenomena in arid and semi-arid areas. In recent years, SDS frequencies and intensities have increased significantly in Iran. A research on SDS sources is important for understanding the mechanisms of dust generation and assessing its socio-economic and environmental impacts. In this paper, we developed a new approach to identify SDS source areas in Iran using a combination of nine related datasets, namely drought events, temperature, precipitation, location of sandy soils, SDS frequency, human-induced soil degradation(HISD), human influence index(HII), rain use efficiency(RUE) and net primary productivity(NPP) loss. To identify SDS source areas, we firstly normalized these datasets under uniform criteria including layer reprojection using Lambert conformal conic projection, data conversion from shapefile to raster, Min-Max Normalization with data range from 0 to 1, and data interpolation by Kriging and images resampling(resolution of 1 km). After that, a score map for the possibility of SDS sources was generated through overlaying multiple datasets under average weight allocation criterion, in which each item obtained weight equally. In the score map, the higher the score, the more possible a specific area could be regarded as SDS source area. Exceptions mostly came from large cities, like Tehran and Isfahan. As a result, final SDS source areas were mapped out, and Al-Howizeh/Al-Azim marshes and Sistan Basin were identified as main SDS source areas in Iran. The SDS source area in Al-Howizeh/Al-Azim marshes still keeps expanding. In addition, Al-Howizeh/Al-Azim marshes are now suffering rapid land degradation due to natural and human-induced factors and might totally vanish in the near future. Sistan Basin also demonstrates the impacts of soil degradation and wind erosion. With appropriate intensity, duration, wind speed and altitude of the dust storms, sand particles uplifting from this area might have developed into extreme dust storms, especially during the summer.
基金Under the auspices of the National Key Project of China(No.2018YFC1506602,2018YFC1506502)National Natural Science Foundation of China(No.41571427)+1 种基金the Anhui Natural Science Foundation(No.1808085MF195)Open Fund of State Key Laboratory of Remote Sensing Science(No.OFSLRSS201708)
文摘As is well known,clouds impact the radiative budget,climate change,hydrological processes,and the global carbon,nitrogen and sulfur cycles.To understand the wide-ranging effects of clouds,it is necessary to assess changes in cloud cover at high spatial and temporal resolution.In this study,we calculate global cloud cover during the day and at night using cloud products estimated from Moderate Resolution Imaging Spectroradiometer(MODIS)data.Results indicate that the global mean cloud cover from 2003 to 2012 was 66%.Moreover,global cloud cover increased over this recent decade.Specifically,cloud cover over land areas(especially North America,Antarctica,and Europe)decreased(slope=–0.001,R^2=0.5254),whereas cloud cover over ocean areas(especially the Indian and Pacific Oceans)increased(slope=0.0011,R^2=0.4955).Cloud cover is relatively high between the latitudes of 36°S and 68°S compared to other regions,and cloud cover is lowest over Oceania and Antarctica.The highest rates of increase occurred over Southeast Asia and Oceania,whereas the highest rates of decrease occurred over Antarctica and North America.The global distribution of cloud cover regulates global temperature change,and the trends of these two variables over the 10-year period examined in this study(2003–2012)oppose one another in some regions.These findings are very important for studies of global climate change.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19080304)the Agricultural Science and Technology Innovation of Sanya, China (2015KJ04)+4 种基金the Natural Science Foundation of Hainan Province, China (20164179, 2016CXTD015)the Technology Research, Development and Promotion Program of Hainan Province, China (ZDXM2015102)the Hainan Provincial Department of Science and Technology, China (ZDKJ2016021)the National Natural Science Foundation of China (41601466)the Youth Innovation Promotion Association of Chinese Academy of Sciences (CAS) (2017085)
文摘Leaf chlorophyll content(LCC)is an important physiological indicator of the actual health status of individual plants.An accurate estimation of LCC can therefore provide valuable information for precision field management.Red-edge information from hyperspectral data has been widely used to estimate crop LCC.However,after the advent of red-edge bands in satellite imagery,no systematic evaluation of the performance of satellite data has been conducted.Toward this end,we analyze herein the performance of winter wheat LCC retrieval of currant and forthcoming satellites(RapidEye,Sentinel-2 and EnMAP)and their new red-edge bands by using partial least squares regression(PLSR)and a vegetation-indexbased approach.These satellite spectral data were obtained by resampling ground-measured hyperspectral data under various field conditions and according to specific spectral response functions and spectral resolution.The results showed:1)This study confirmed that RapidEye,Sentinel-2 and EnMAP data are suitable for winter wheat LCC retrieval.For the PLSR approach,Sentinel-2 data provided more accurate estimates of LCC(R2=0.755,0.844,0.805 for 2002,2010,and 2002+2010)than do RapidEye data(R2=0.689,0.710,0.707 for 2002,2010,and 2002+2010)and EnMAP data(R2=0.735,0.867,0.771 for 2002,2010,and 2002+2010).For index-based approaches,the MERIS terrestrial chlorophyll index,which is a vegetation index with two red-edge bands,was the most sensitive and robust index for LCC for both the Sentinel-2 and EnMAP data(R2≥0.628),and the indices(NDRE1,SRRE1 and CIRE1)with a single red-edge band were the most sensitive and robust indices for the RapidEye data(R2≥0.420);2)According to the analysis of the effect of the wavelength and number of used red-edge spectral bands on LCC retrieval,the short-wavelength red-edge bands(from 699 to 734 nm)provided more accurate predictions when using the PLSR approach,whereas the long-wavelength red-edge bands(740 to 783 nm)gave more accurate predictions when using the vegetation indice(VI)approach.In addition,the prediction accuracy of RapidEye,Sentinel-2 and EnMAP data was improved gradually because of more number of red-edge bands and higher spectral resolution;VI regression models that contain a single or multiple red-edge bands provided more accurate predictions of LCC than those without red-edge bands,but for normalized difference vegetation index(NDVI)-,simple ratio(SR)-and chlorophyll index(CI)-like index,two red-edge bands index didn’t significantly improve the predictive accuracy of LCC than those indices with a single red-edge band.Although satellite data with higher spectral resolution and a greater number of red-edge bands marginally improve the accuracy of estimates of crop LCC,the level of this improvement remains insufficient because of higher spectral resolution,which results in a worse signal-to-noise ratio.The results of this study are helpful to accurately monitor LCC of winter wheat in large-area and provide some valuable advice for design of red-edge spectral bands of satellite sensor in future.
基金supported by the National Science Foundation of China (41590852, 41001264)the International Science & Technology Cooperation Program of China (2010DFB23380)+1 种基金International Partnership Program of Chinese Academy of Sciences (131C11KYSB20160061)supported by the DLR AO project (GEOL0447)
文摘Glaciers play an important role in the climate system. The elevation change of a glacier is an important parameter in studies of glacier dynamics. Only a few ground-based measurements of high mountain glaciers are available due to their remoteness, high elevation, and complex topography. The acquisition from the German Tan DEM-X(Terra SAR-X add-on for Digital Elevation Measurement) SAR imaging configuration provides a reliable data sources for studying the elevation change of glaciers. In this study, the bistatic Tan DEM-X data that cover the Geladandong Mountain on the Tibetan Plateau were processed with SAR interferometry technique and the elevation changes of the mountain's glaciers during 2000–2014 were obtained. The results indicated that although distinct positive and negative elevation changes were found for different glacier tongues, the mean elevation change was about-0.14±0.26 m a-1. Geoscience Laser Altimeter System(GLAS) data were obtained for comparison and verification. The investigation using GLAS data demonstrated the efficacy of the proposed method in determining glacier elevation change. Thus, the presented approach is appropriate for monitoring glacier elevation change and it constitutes a valuable tool for studies of glacier dynamics.
基金supported by the Hundred Talent Program of the Chinese Academy of Sciences(Huang Wenjiang)the Innovation“135”Program from Chinese Academy of Sciences(Y3SG0100CX)the Science&Technology Basic Research Program of China(2014FY210100)
文摘Understanding the effects of land use changes on the spatiotemporal variation of soil organic carbon(SOC)can provide guidance for low carbon and sustainable agriculture.In this paper,based on the large-scale datasets of soil surveys in 1982 and 2009 for Pinggu District—an urban-rural ecotone of Beijing,China,the effects of land use and land use changes on both temporal variation and spatial variation of SOC were analyzed.Results showed that from 1982 to 2009in Pinggu District,the following land use change mainly occurred:Grain cropland converted to orchard or vegetable land,and grassland converted to forestland.The SOC content decreased in region where the land use type changed to grain cropland(e.g.,vegetable land to grain cropland decreased by 0.7 g kg^(-1);orchard to grain cropland decreased by 0.2 g kg^(-1)).In contrast,the SOC content increased in region where the land use type changed to either orchard(excluding forestland)or forestland(e.g.,grain cropland to orchard and forestland increased by 2.7 and 2.4 g kg^(-1),respectively;grassland to orchard and forestland increased by 4.8 and 4.9 g kg^(-1),respectively).The organic carbon accumulation capacity per unit mass of the soil increased in the following order:grain cropland soikvegetable land/grassland soikorchard soikforestland soil.Therefore,to both secure supply of agricultural products and develop low carbon agriculture in a modern city,orchard has proven to be a good choice for land using.
