Natural soil-forming factors such as landforms, parent materials or biota lead to high variability in soil properties. However, there is not enough research quantifying which environmental factor(s) can be the most re...Natural soil-forming factors such as landforms, parent materials or biota lead to high variability in soil properties. However, there is not enough research quantifying which environmental factor(s) can be the most relevant to predicting soil properties at the catchment scale in semi-arid areas. Thus, this research aims to investigate the ability of multivariate statistical analyses to distinguish which soil properties follow a clear spatial pattern conditioned by specific environmental characteristics in a semi-arid region of Iran. To achieve this goal, we digitized parent materials and landforms by recent orthophotography. Also, we extracted ten topographical attributes and five remote sensing variables from a digital elevation model(DEM) and the Landsat Enhanced Thematic Mapper(ETM), respectively. These factors were contrasted for 334 soil samples(depth of 0–30 cm). Cluster analysis and soil maps reveal that Cluster 1 comprises of limestones, massive limestones and mixed deposits of conglomerates with low soil organic carbon(SOC) and clay contents, and Cluster 2 is composed of soils that originated from quaternary and early quaternary parent materials such as terraces, alluvial fans, lake deposits, and marls or conglomerates that register the highest SOC content and the lowest sand and silt contents. Further, it is confirmed that soils with the highest SOC and clay contents are located in wetlands, lagoons, alluvial fans and piedmonts, while soils with the lowest SOC and clay contents are located in dissected alluvial fans, eroded hills, rock outcrops and steep hills. The results of principal component analysis using the remote sensing data and topographical attributes identify five main components, which explain 73.3% of the total variability of soil properties. Environmental factors such as hillslope morphology and all of the remote sensing variables can largely explain SOC variability, but no significant correlation is found for soil texture and calcium carbonate equivalent contents. Therefore, we conclude that SOC can be considered as the best-predicted soil property in semi-arid regions.展开更多
In the light of an increasing demand for staple food, especially rice, in southeast China, investigations on the specific site potential expressed as the relationship between soil and crop yield parameters gain increa...In the light of an increasing demand for staple food, especially rice, in southeast China, investigations on the specific site potential expressed as the relationship between soil and crop yield parameters gain increasing importance. Soil texture and several soil chemical parameters as well as plant properties such as crop height, biomass and grain yield were investigated along two terraced catenas with contrasting soil textures cropped with wet rice. We were aiming at identifying correlative relationships between soil and crop properties. Data were analyzed both statistically and geostatistically on the basis of semivariograms. Statistical analysis indicated a significant influence of the relief position on the spatial distribution of soil texture, total carbon and total nitrogen contents. Significant correlations were found for the catena located in a sandstone area (Catena A) between rice yield and silt as well as total nitrogen content. Corresponding relationships were not detectable for paddy fields that developed from Quaternary clays (Catena B). As suggested by the nugget to sill ratio, spatial variability of soil texture, total carbon and nitrogen was mainly controlled by intrinsic factors, which might be attributed to the erosional transport of fine soil constituents, indicating the importance of the relief position and slope in soil development even in landscapes that are terraced. The crop parameters exhibited short ranges of influence and about one third of their variability was unexplained. Comparable ranges of selected crop and soil parameters, found only for Catena A, are indicative of close spatial interactions between rice yield and soil features. Our findings show that especially in sandstone-dominated areas, a site-specific management can contribute to an environmentally safe rice production increase.展开更多
The role of soil moisture in the survival and growth of trees cannot be over-emphasized and it contributes to the net productivity of the forest. However, information on the spatial distribution of the soil moisture c...The role of soil moisture in the survival and growth of trees cannot be over-emphasized and it contributes to the net productivity of the forest. However, information on the spatial distribution of the soil moisture content regarding the tree volume in forest ecosystems especially in Nigeria is limited. Therefore, this study combined spatial and ground data to determine soil moisture distribution and tree volume in the International Institute of Tropical Agriculture (IITA) forest, Ibadan. Satellite images of 1989, 1999, 2009 and 2019 were obtained and processed using topographic and vegetation-based models to examine the soil moisture status of the forest. Satellite-based soil moisture obtained was validated with ground soil moisture data collected in 2019. Tree growth variables were obtained for tree volume computation using Newton’s formular. Forest soil moisture models employed in this study include Topographic Wetness Index (TWI), Temperature Dryness Vegetation Index (TDVI) and Modified Normalized Difference Wetness Index (MNDWI). Relationships between index-based and ground base Soil Moisture Content (SMC), as well as the correlation between soil moisture and tree volume, were examined. The study revealed strong relationships between tree volume and TDVI, SMC, TWI with R<sup>2</sup> values of 0.91, 0.85, and 0.75, respectively. The regression values of 0.89 between in-situ soil data and TWI and 0.83 with TDVI ascertain the reliability of satellite data in soil moisture mapping. The decision of which index to apply between TWI and TDVI, therefore, depends on available data since both proved to be reliable. The TWI surface is considered to be a more suitable soil moisture prediction index, while MNDWI exhibited a weak relationship (R<sup>2</sup> = 0.03) with ground data. The strong relationships between soil moisture and tree volume suggest tree volume can be predicted based on available soil moisture content. Any slight undesirable change in soil moisture could lead to severe forest conditions.展开更多
Conventional soil maps generally contain one or more soil types within a single soil polygon.But their geographic locations within the polygon are not specified.This restricts current applications of the maps in site-...Conventional soil maps generally contain one or more soil types within a single soil polygon.But their geographic locations within the polygon are not specified.This restricts current applications of the maps in site-specific agricultural management and environmental modelling.We examined the utility of legacy pedon data for disaggregating soil polygons and the effectiveness of similarity-based prediction for making use of the under-or over-sampled legacy pedon data for the disaggregation.The method consisted of three steps.First,environmental similarities between the pedon sites and each location were computed based on soil formative environmental factors.Second,according to soil types of the pedon sites,the similarities were aggregated to derive similarity distribution for each soil type.Third,a hardening process was performed on the maps to allocate candidate soil types within the polygons.The study was conducted at the soil subgroup level in a semi-arid area situated in Manitoba,Canada.Based on 186 independent pedon sites,the evaluation of the disaggregated map of soil subgroups showed an overall accuracy of 67% and a Kappa statistic of 0.62.The map represented a better spatial pattern of soil subgroups in both detail and accuracy compared to a dominant soil subgroup map,which was commonly used in practice.Incorrect predictions mainly occurred in the agricultural plain area and the soil subgroups that are very similar in taxonomy,indicating that new environmental covariates need to be developed.We concluded that the combination of legacy pedon data with similarity-based prediction is an effective solution for soil polygon disaggregation.展开更多
A method is proposed for the prospecting prediction of subsurface mineral deposits based on soil geochemistry data and a deep convolutional neural network model.This method uses three techniques(window offset,scaling,...A method is proposed for the prospecting prediction of subsurface mineral deposits based on soil geochemistry data and a deep convolutional neural network model.This method uses three techniques(window offset,scaling,and rotation)to enhance the number of training data for the model.A window area is used to extract the spatial distribution characteristics of soil geochemistry and measure their correspondence with the occurrence of known subsurface deposits.Prospecting prediction is achieved by matching the characteristics of the window area of an unknown area with the relationships established in the known area.This method can efficiently predict mineral prospective areas where there are few ore deposits used for generating the training dataset,meaning that the deep-learning method can be effectively used for deposit prospecting prediction.Using soil active geochemical measurement data,this method was applied in the Daqiao area,Gansu Province,for which seven favorable gold prospecting target areas were predicted.The Daqiao orogenic gold deposit of latest Jurassic and Early Jurassic age in the southern domain has more than 105 t of gold resources at an average grade of 3-4 g/t.In 2020,the project team drilled and verified the K prediction area,and found 66 m gold mineralized bodies.The new method should be applicable to prospecting prediction using conventional geochemical data in other areas.展开更多
土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获...土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获取、三维空间推测、三维数据模型、三维模型构建和可视化方法等方面的研究。本文对三维空间土壤推测与土壤模型构建的已有方法进行梳理和评述,以期为三维数字土壤制图的应用和发展提供建议。以三维土壤制图、三维GIS、三维数据模型、三维地质建模、三维可视化、土壤空间变异、空间推测、克里格插值、土壤-景观分析、深度函数、机器学习、地统计学、随机模拟等为关键词检索Web of Science数据库,基于相关度、引用率和文献来源等因素进一步筛选出重点文献进行分析。归纳整理了土壤空间变异性、三维空间土壤推测、三维空间数据模型和三维模型构建等关键技术的现有研究体系,对各种三维推测和建模方法的优缺点和适用场景作出评价。针对目前研究中存在的垂直方向土壤数据稀少、土壤三维推测精度低、三维模型质量待提高等问题,提出一些可行的研究思路。展开更多
This review article presents a comprehensive overview of the current status of the Landsat program and its applications in soil erosion modelling and assessment within arid environments.Literature for the period betwe...This review article presents a comprehensive overview of the current status of the Landsat program and its applications in soil erosion modelling and assessment within arid environments.Literature for the period between 1972 and 2022 was retrieved using directed search strategies and keywords.A total of 170 journal articles were gathered and analyzed.The literature analysis reveals that 27(16%)of the publications fall within the period from 2007 to 2011,marking the highest occurrence within a five-year interval.The scrutinized literature was classified into ten distinct periods,or“pentades,”to accommodate the evolving applications of the Landsat program in response to advancements in remotely sensed data quality.This review article underscores the substantial contribution of Landsat data to the monitoring and assessment of soil erosion attributed to the action of water.Numerous studies have been conducted to model soil erosion using the Revised Universal Soil Loss Equation(RUSLE)model,facilitated by Geographic Information Systems(GIS)and remote sensing technologies.Nonetheless,the integration of Landsat data does present some challenges.Notably,the limitations of coarse resolution and data loss,particularly the scan line issues affecting Landsat 7,have hindered the full potential of the affected satellite datasets.As a solution,a multi-source approach that amalgamates diverse datasets is advocated to bridge data gaps and address disparities in spatial and temporal resolutions.To conclude,the Landsat mission has indisputably emerged as an indispensable instrument for facilitating the assessment and monitoring of soil erosion in resource-constrained communities.To advance this field,there is need to bolster storage infrastructure to manage large datasets,ensuring continuity for these sensor outputs,presenting a promising path for future research.展开更多
土壤盐渍化是干旱半干旱区土地退化的主要形式之一,其发生发展是一个复杂的非线性动力学过程。该文通过对吉林省长岭县土壤盐渍化成因及特征分析,确定土壤盐渍化影响因子及动态机制,并利用地理元胞自动机对复杂系统时空动态演化过程具...土壤盐渍化是干旱半干旱区土地退化的主要形式之一,其发生发展是一个复杂的非线性动力学过程。该文通过对吉林省长岭县土壤盐渍化成因及特征分析,确定土壤盐渍化影响因子及动态机制,并利用地理元胞自动机对复杂系统时空动态演化过程具有较强的计算及模拟能力特点,在G IS与RS支持下,建立土壤盐渍化CA动态模型,即土壤盐渍化地理元胞自动机模型(G eoCA-Sa lin ization),并结合相关属性数据和空间数据,模拟长岭县土壤盐渍化发生发展的时空动态规律,并对今后的可能发展做出预测。结果表明:基于G eoCA-Sa lin ization模型对长岭县土壤盐渍化时空演变进行的模拟与实际情况基本吻合,同时基于该模型的土壤盐渍化时空演变预测符合当前的发展态势。与其他方法相比,该方法能更好地实现任意有效离散时间距与瞬时动态可视化表达的结合,是土壤盐渍化时空演变模拟与预测较为有效的方法。展开更多
基金financial support of Isfahan University of Technology (IUT) for this research
文摘Natural soil-forming factors such as landforms, parent materials or biota lead to high variability in soil properties. However, there is not enough research quantifying which environmental factor(s) can be the most relevant to predicting soil properties at the catchment scale in semi-arid areas. Thus, this research aims to investigate the ability of multivariate statistical analyses to distinguish which soil properties follow a clear spatial pattern conditioned by specific environmental characteristics in a semi-arid region of Iran. To achieve this goal, we digitized parent materials and landforms by recent orthophotography. Also, we extracted ten topographical attributes and five remote sensing variables from a digital elevation model(DEM) and the Landsat Enhanced Thematic Mapper(ETM), respectively. These factors were contrasted for 334 soil samples(depth of 0–30 cm). Cluster analysis and soil maps reveal that Cluster 1 comprises of limestones, massive limestones and mixed deposits of conglomerates with low soil organic carbon(SOC) and clay contents, and Cluster 2 is composed of soils that originated from quaternary and early quaternary parent materials such as terraces, alluvial fans, lake deposits, and marls or conglomerates that register the highest SOC content and the lowest sand and silt contents. Further, it is confirmed that soils with the highest SOC and clay contents are located in wetlands, lagoons, alluvial fans and piedmonts, while soils with the lowest SOC and clay contents are located in dissected alluvial fans, eroded hills, rock outcrops and steep hills. The results of principal component analysis using the remote sensing data and topographical attributes identify five main components, which explain 73.3% of the total variability of soil properties. Environmental factors such as hillslope morphology and all of the remote sensing variables can largely explain SOC variability, but no significant correlation is found for soil texture and calcium carbonate equivalent contents. Therefore, we conclude that SOC can be considered as the best-predicted soil property in semi-arid regions.
基金the German Research Foundation (DFG) (No.LE 945/10-1).
文摘In the light of an increasing demand for staple food, especially rice, in southeast China, investigations on the specific site potential expressed as the relationship between soil and crop yield parameters gain increasing importance. Soil texture and several soil chemical parameters as well as plant properties such as crop height, biomass and grain yield were investigated along two terraced catenas with contrasting soil textures cropped with wet rice. We were aiming at identifying correlative relationships between soil and crop properties. Data were analyzed both statistically and geostatistically on the basis of semivariograms. Statistical analysis indicated a significant influence of the relief position on the spatial distribution of soil texture, total carbon and total nitrogen contents. Significant correlations were found for the catena located in a sandstone area (Catena A) between rice yield and silt as well as total nitrogen content. Corresponding relationships were not detectable for paddy fields that developed from Quaternary clays (Catena B). As suggested by the nugget to sill ratio, spatial variability of soil texture, total carbon and nitrogen was mainly controlled by intrinsic factors, which might be attributed to the erosional transport of fine soil constituents, indicating the importance of the relief position and slope in soil development even in landscapes that are terraced. The crop parameters exhibited short ranges of influence and about one third of their variability was unexplained. Comparable ranges of selected crop and soil parameters, found only for Catena A, are indicative of close spatial interactions between rice yield and soil features. Our findings show that especially in sandstone-dominated areas, a site-specific management can contribute to an environmentally safe rice production increase.
文摘The role of soil moisture in the survival and growth of trees cannot be over-emphasized and it contributes to the net productivity of the forest. However, information on the spatial distribution of the soil moisture content regarding the tree volume in forest ecosystems especially in Nigeria is limited. Therefore, this study combined spatial and ground data to determine soil moisture distribution and tree volume in the International Institute of Tropical Agriculture (IITA) forest, Ibadan. Satellite images of 1989, 1999, 2009 and 2019 were obtained and processed using topographic and vegetation-based models to examine the soil moisture status of the forest. Satellite-based soil moisture obtained was validated with ground soil moisture data collected in 2019. Tree growth variables were obtained for tree volume computation using Newton’s formular. Forest soil moisture models employed in this study include Topographic Wetness Index (TWI), Temperature Dryness Vegetation Index (TDVI) and Modified Normalized Difference Wetness Index (MNDWI). Relationships between index-based and ground base Soil Moisture Content (SMC), as well as the correlation between soil moisture and tree volume, were examined. The study revealed strong relationships between tree volume and TDVI, SMC, TWI with R<sup>2</sup> values of 0.91, 0.85, and 0.75, respectively. The regression values of 0.89 between in-situ soil data and TWI and 0.83 with TDVI ascertain the reliability of satellite data in soil moisture mapping. The decision of which index to apply between TWI and TDVI, therefore, depends on available data since both proved to be reliable. The TWI surface is considered to be a more suitable soil moisture prediction index, while MNDWI exhibited a weak relationship (R<sup>2</sup> = 0.03) with ground data. The strong relationships between soil moisture and tree volume suggest tree volume can be predicted based on available soil moisture content. Any slight undesirable change in soil moisture could lead to severe forest conditions.
基金supported by the National Natural Science Foundation of China (41130530,91325301,41431177,41571212,41401237)the Project of "One-Three-Five" Strategic Planning & Frontier Sciences of the Institute of Soil Science,Chinese Academy of Sciences (ISSASIP1622)+1 种基金the Government Interest Related Program between Canadian Space Agency and Agriculture and Agri-Food,Canada (13MOA01002)the Natural Science Research Program of Jiangsu Province (14KJA170001)
文摘Conventional soil maps generally contain one or more soil types within a single soil polygon.But their geographic locations within the polygon are not specified.This restricts current applications of the maps in site-specific agricultural management and environmental modelling.We examined the utility of legacy pedon data for disaggregating soil polygons and the effectiveness of similarity-based prediction for making use of the under-or over-sampled legacy pedon data for the disaggregation.The method consisted of three steps.First,environmental similarities between the pedon sites and each location were computed based on soil formative environmental factors.Second,according to soil types of the pedon sites,the similarities were aggregated to derive similarity distribution for each soil type.Third,a hardening process was performed on the maps to allocate candidate soil types within the polygons.The study was conducted at the soil subgroup level in a semi-arid area situated in Manitoba,Canada.Based on 186 independent pedon sites,the evaluation of the disaggregated map of soil subgroups showed an overall accuracy of 67% and a Kappa statistic of 0.62.The map represented a better spatial pattern of soil subgroups in both detail and accuracy compared to a dominant soil subgroup map,which was commonly used in practice.Incorrect predictions mainly occurred in the agricultural plain area and the soil subgroups that are very similar in taxonomy,indicating that new environmental covariates need to be developed.We concluded that the combination of legacy pedon data with similarity-based prediction is an effective solution for soil polygon disaggregation.
基金funded by a pilot project entitled“Deep Geological Survey of Benxi-Linjiang Area”(1212011220247)of the 3D Geological Mapping and Deep Geological Survey of China Geological Survey。
文摘A method is proposed for the prospecting prediction of subsurface mineral deposits based on soil geochemistry data and a deep convolutional neural network model.This method uses three techniques(window offset,scaling,and rotation)to enhance the number of training data for the model.A window area is used to extract the spatial distribution characteristics of soil geochemistry and measure their correspondence with the occurrence of known subsurface deposits.Prospecting prediction is achieved by matching the characteristics of the window area of an unknown area with the relationships established in the known area.This method can efficiently predict mineral prospective areas where there are few ore deposits used for generating the training dataset,meaning that the deep-learning method can be effectively used for deposit prospecting prediction.Using soil active geochemical measurement data,this method was applied in the Daqiao area,Gansu Province,for which seven favorable gold prospecting target areas were predicted.The Daqiao orogenic gold deposit of latest Jurassic and Early Jurassic age in the southern domain has more than 105 t of gold resources at an average grade of 3-4 g/t.In 2020,the project team drilled and verified the K prediction area,and found 66 m gold mineralized bodies.The new method should be applicable to prospecting prediction using conventional geochemical data in other areas.
文摘土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获取、三维空间推测、三维数据模型、三维模型构建和可视化方法等方面的研究。本文对三维空间土壤推测与土壤模型构建的已有方法进行梳理和评述,以期为三维数字土壤制图的应用和发展提供建议。以三维土壤制图、三维GIS、三维数据模型、三维地质建模、三维可视化、土壤空间变异、空间推测、克里格插值、土壤-景观分析、深度函数、机器学习、地统计学、随机模拟等为关键词检索Web of Science数据库,基于相关度、引用率和文献来源等因素进一步筛选出重点文献进行分析。归纳整理了土壤空间变异性、三维空间土壤推测、三维空间数据模型和三维模型构建等关键技术的现有研究体系,对各种三维推测和建模方法的优缺点和适用场景作出评价。针对目前研究中存在的垂直方向土壤数据稀少、土壤三维推测精度低、三维模型质量待提高等问题,提出一些可行的研究思路。
基金study funded by the Wetland Monitoring and Assessment Services for Transboundary Basins of Southern Africa(WeMAST)Project,which receives funding through the GMES and Africa programme.
文摘This review article presents a comprehensive overview of the current status of the Landsat program and its applications in soil erosion modelling and assessment within arid environments.Literature for the period between 1972 and 2022 was retrieved using directed search strategies and keywords.A total of 170 journal articles were gathered and analyzed.The literature analysis reveals that 27(16%)of the publications fall within the period from 2007 to 2011,marking the highest occurrence within a five-year interval.The scrutinized literature was classified into ten distinct periods,or“pentades,”to accommodate the evolving applications of the Landsat program in response to advancements in remotely sensed data quality.This review article underscores the substantial contribution of Landsat data to the monitoring and assessment of soil erosion attributed to the action of water.Numerous studies have been conducted to model soil erosion using the Revised Universal Soil Loss Equation(RUSLE)model,facilitated by Geographic Information Systems(GIS)and remote sensing technologies.Nonetheless,the integration of Landsat data does present some challenges.Notably,the limitations of coarse resolution and data loss,particularly the scan line issues affecting Landsat 7,have hindered the full potential of the affected satellite datasets.As a solution,a multi-source approach that amalgamates diverse datasets is advocated to bridge data gaps and address disparities in spatial and temporal resolutions.To conclude,the Landsat mission has indisputably emerged as an indispensable instrument for facilitating the assessment and monitoring of soil erosion in resource-constrained communities.To advance this field,there is need to bolster storage infrastructure to manage large datasets,ensuring continuity for these sensor outputs,presenting a promising path for future research.
文摘土壤盐渍化是干旱半干旱区土地退化的主要形式之一,其发生发展是一个复杂的非线性动力学过程。该文通过对吉林省长岭县土壤盐渍化成因及特征分析,确定土壤盐渍化影响因子及动态机制,并利用地理元胞自动机对复杂系统时空动态演化过程具有较强的计算及模拟能力特点,在G IS与RS支持下,建立土壤盐渍化CA动态模型,即土壤盐渍化地理元胞自动机模型(G eoCA-Sa lin ization),并结合相关属性数据和空间数据,模拟长岭县土壤盐渍化发生发展的时空动态规律,并对今后的可能发展做出预测。结果表明:基于G eoCA-Sa lin ization模型对长岭县土壤盐渍化时空演变进行的模拟与实际情况基本吻合,同时基于该模型的土壤盐渍化时空演变预测符合当前的发展态势。与其他方法相比,该方法能更好地实现任意有效离散时间距与瞬时动态可视化表达的结合,是土壤盐渍化时空演变模拟与预测较为有效的方法。
