[Objective] Calculation of winter wheat acreage in Henan Province using EOS/MODIS-NDVI data at different time sequences. [Method] After process of EOS/MODIS images, geographical adjustment, wave band combination, norm...[Objective] Calculation of winter wheat acreage in Henan Province using EOS/MODIS-NDVI data at different time sequences. [Method] After process of EOS/MODIS images, geographical adjustment, wave band combination, normal difference vegetation index (NDVI) was obtained. Based on the wide spectrum measurement, the processed data were supervisedly classified, thus the acreage of winter wheat in Henan Province in 2005 was acquired. [Result] Total 92208 pixels were observed for the winter wheat in Henan Province, and the plantation acreage was 5 760 thousand hm2. Compared with the data from statistical department, the error of this method was about 9.66%. [Conclusion] The method introduced in the present study could be applied in monitoring winter wheat acreage.展开更多
Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information syst...Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.展开更多
This paper proposes an enhanced Edge Matching Rate (EMR) to gain good image regis-tration based on Generalized Acreage (GA). Traditional EMR considers only matched pixels sum without concerns of the cause of unmatched...This paper proposes an enhanced Edge Matching Rate (EMR) to gain good image regis-tration based on Generalized Acreage (GA). Traditional EMR considers only matched pixels sum without concerns of the cause of unmatched pixels and the relationship between matched pixels. The modified EMR introduces the new concept of generalized acreage to measure the overlaying parts between the target image and the model. It also defines similarity of local occlusion and of local dithering to measure interference degree. Not only edge points are considered but also non-edge points, occlusion, and dithering. Using the same preprocessing, the experiments match images based on tra-ditional EMR and the proposed EMR separately. Based on the proposed EMR the paper achieves more stable registration and higher precision.展开更多
Various indicators derived from thematic maps have been widely used to determine the strata needed to perform stratified sampling.However,these indicators typically do not quantify the spatial errors in the crop thema...Various indicators derived from thematic maps have been widely used to determine the strata needed to perform stratified sampling.However,these indicators typically do not quantify the spatial errors in the crop thematic maps that are needed to reduce the uncertainty.To address this lack of error information,this paper introduces a hybrid entropy indicator(HEI).Two conventional indicators,the acreage indicator(AI)and the fragmentation indicator(FI),were also evaluated to compare the results of the three indicators in a homogeneous agricultural area(Pinghu,PH)and a heterogeneous agricultural area(Zhuji,ZJ).The results show that HEI performs the best in heterogeneous areas with the lowest coefficient of variation(CV)(as low as 1.59%)and also has the highest estimation accuracy with the lowest standard deviation of estimation.For both areas,the performances of HEI and AI are very similar,and better than FI.These results highlight that the HEI should be considered as an effective indicator and used in place of AI and FI to help improve sampling efficiency of crop acreage estimation,while FI is not recommended.Furthermore,the positive performance achieved using HEI indicates the potential for incorporating thematic map uncertainty information to improve sampling efficiency.展开更多
Agriculture plays a vital role in the growth and development of the High Plains Region of the United States. With the development and adoption of irrigation technology, this region was transformed into one of the most...Agriculture plays a vital role in the growth and development of the High Plains Region of the United States. With the development and adoption of irrigation technology, this region was transformed into one of the most agriculturally productive regions in the world [1]. The primary source of irrigation in this region is the Ogallala Aquifer. Currently, water from the aquifer is being used at a much faster rate than natural recharge can occur, resulting in a high rate of depletion from this finite resource. Depletion of scarce water resources will have a significant economic impact on the long-term sustainability of the region. The objective of this study is to evaluate the impact alternative prices and discount rates have on groundwater policy recommendations. Deterministic models of groundwater withdrawals were developed and used in order to analyze and evaluate the impact of high, average, and low crop prices in a status quo scenario as well as a policy scenario reducing irrigated acreage allocation. Furthermore, this study analyzes the effects and associated consequences of alternative discount rates on net and total revenue. As indicated by results of this study, alternative prices, costs, and discount rates utilized in a model have an effect on policy effectiveness.展开更多
Bangladesh is one of the most vulnerable countries to natural disasters such as droughts in the world.The pre-monsoon Aus rice in Bangladesh depends on rainfall and is threatened by increasing droughts.However,limited...Bangladesh is one of the most vulnerable countries to natural disasters such as droughts in the world.The pre-monsoon Aus rice in Bangladesh depends on rainfall and is threatened by increasing droughts.However,limited information on the changes in Aus rice as well as droughts hamper our understanding of the country’s agricultural resilience and adaption to droughts.Here,we collected all the official statistical data of Aus rice at the district level from 1980 to 2018,and examined the interannual variations of area,yield,and production.The results showed both area and production of Aus rice decreased significantly(61.58×103 ha yr-1 and 17.21×103 M.tons yr-1,respectively),while yield increased significantly(0.03 M.tons ha-1 yr-1).We also found a significantly increasing trend of droughts in 88%of area based on the Palmer Drought Severity Index(PDSI)data,especially in those rainfed agricultural areas.Moreover,we found significant positive correlations between PDSI and Aus rice area(production)in 33(25)out of 64 districts.There is hardly a relationship between PDSI and yield,likely due to the improved management and increasing irrigated areas.Implementing continuous drought monitoring,combined irrigation(surface and groundwater)systems,and conservation and precision agriculture are highly recommended in these drought-prone districts to ensure food security in Bangladesh.展开更多
文摘[Objective] Calculation of winter wheat acreage in Henan Province using EOS/MODIS-NDVI data at different time sequences. [Method] After process of EOS/MODIS images, geographical adjustment, wave band combination, normal difference vegetation index (NDVI) was obtained. Based on the wide spectrum measurement, the processed data were supervisedly classified, thus the acreage of winter wheat in Henan Province in 2005 was acquired. [Result] Total 92208 pixels were observed for the winter wheat in Henan Province, and the plantation acreage was 5 760 thousand hm2. Compared with the data from statistical department, the error of this method was about 9.66%. [Conclusion] The method introduced in the present study could be applied in monitoring winter wheat acreage.
基金financially supported by the National Natural Science Foundation of China (41471365,41531179)
文摘Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.
基金Supported by the National Natural Science Foundation of China(No.60802045)the Fundamental Research Funds for the Central Universities(No.2009JBM020)the Strategy Alliance of Chinese Academy of Sciences for Guangdong Province(No.2010B090301014)China
文摘This paper proposes an enhanced Edge Matching Rate (EMR) to gain good image regis-tration based on Generalized Acreage (GA). Traditional EMR considers only matched pixels sum without concerns of the cause of unmatched pixels and the relationship between matched pixels. The modified EMR introduces the new concept of generalized acreage to measure the overlaying parts between the target image and the model. It also defines similarity of local occlusion and of local dithering to measure interference degree. Not only edge points are considered but also non-edge points, occlusion, and dithering. Using the same preprocessing, the experiments match images based on tra-ditional EMR and the proposed EMR separately. Based on the proposed EMR the paper achieves more stable registration and higher precision.
基金the National Natural Science Foundation of China[grant number 41301444]China Scholarship Council Qinggu Program[grant number 201406045036]+1 种基金the Major Project of High-Resolution Earth Observation System,China[grant number 20-Y30B17-9001-14/16]the China Scholarship Council(CSC).
文摘Various indicators derived from thematic maps have been widely used to determine the strata needed to perform stratified sampling.However,these indicators typically do not quantify the spatial errors in the crop thematic maps that are needed to reduce the uncertainty.To address this lack of error information,this paper introduces a hybrid entropy indicator(HEI).Two conventional indicators,the acreage indicator(AI)and the fragmentation indicator(FI),were also evaluated to compare the results of the three indicators in a homogeneous agricultural area(Pinghu,PH)and a heterogeneous agricultural area(Zhuji,ZJ).The results show that HEI performs the best in heterogeneous areas with the lowest coefficient of variation(CV)(as low as 1.59%)and also has the highest estimation accuracy with the lowest standard deviation of estimation.For both areas,the performances of HEI and AI are very similar,and better than FI.These results highlight that the HEI should be considered as an effective indicator and used in place of AI and FI to help improve sampling efficiency of crop acreage estimation,while FI is not recommended.Furthermore,the positive performance achieved using HEI indicates the potential for incorporating thematic map uncertainty information to improve sampling efficiency.
文摘Agriculture plays a vital role in the growth and development of the High Plains Region of the United States. With the development and adoption of irrigation technology, this region was transformed into one of the most agriculturally productive regions in the world [1]. The primary source of irrigation in this region is the Ogallala Aquifer. Currently, water from the aquifer is being used at a much faster rate than natural recharge can occur, resulting in a high rate of depletion from this finite resource. Depletion of scarce water resources will have a significant economic impact on the long-term sustainability of the region. The objective of this study is to evaluate the impact alternative prices and discount rates have on groundwater policy recommendations. Deterministic models of groundwater withdrawals were developed and used in order to analyze and evaluate the impact of high, average, and low crop prices in a status quo scenario as well as a policy scenario reducing irrigated acreage allocation. Furthermore, this study analyzes the effects and associated consequences of alternative discount rates on net and total revenue. As indicated by results of this study, alternative prices, costs, and discount rates utilized in a model have an effect on policy effectiveness.
基金National Natural Science Foundation of China(41871349)The Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19040301)。
文摘Bangladesh is one of the most vulnerable countries to natural disasters such as droughts in the world.The pre-monsoon Aus rice in Bangladesh depends on rainfall and is threatened by increasing droughts.However,limited information on the changes in Aus rice as well as droughts hamper our understanding of the country’s agricultural resilience and adaption to droughts.Here,we collected all the official statistical data of Aus rice at the district level from 1980 to 2018,and examined the interannual variations of area,yield,and production.The results showed both area and production of Aus rice decreased significantly(61.58×103 ha yr-1 and 17.21×103 M.tons yr-1,respectively),while yield increased significantly(0.03 M.tons ha-1 yr-1).We also found a significantly increasing trend of droughts in 88%of area based on the Palmer Drought Severity Index(PDSI)data,especially in those rainfed agricultural areas.Moreover,we found significant positive correlations between PDSI and Aus rice area(production)in 33(25)out of 64 districts.There is hardly a relationship between PDSI and yield,likely due to the improved management and increasing irrigated areas.Implementing continuous drought monitoring,combined irrigation(surface and groundwater)systems,and conservation and precision agriculture are highly recommended in these drought-prone districts to ensure food security in Bangladesh.
