Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to co...Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus （ETM＋） image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data. Principal component analysis （PCA） is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help the classification precision of a decision tree to be improved. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. According to the research, the third principal component （PC3） is an effective variable in the decision tree classification for salinized soil information extraction. The research demonstrated that the PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM＋ sensor （TM1） was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk （Tamarix chinensis Lour）; and areas comprising mixed water bodies and vegetation can be identified using the spectral indices MNDWI （modified normalized difference water index） and NDVI （normalized difference vegetation index）. Based upon this analysis, a decision tree classifier was applied to classify landcover types with different levels of soil saline. The results were checked using a statistical accuracy assessment. The overall accuracy of the classification was 94.80%, which suggested that the decision tree model is a simple and effective method with relatively high precision.展开更多
Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced tech...Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.展开更多
Information on the effects of halophyte communities on soil organic carbon(SOC)is useful for sequestrating C in arid regions.In this study,we identified four typical natural halophyte communities in the Manasi River B...Information on the effects of halophyte communities on soil organic carbon(SOC)is useful for sequestrating C in arid regions.In this study,we identified four typical natural halophyte communities in the Manasi River Basin in Xinjiang Province,Northeast China,namely,Karelinia caspia(Pall.)Less.,Bassia dasyphylla(Fisch.et C.A.Mey.)Kuntze,Haloxylon ammodendron(C.A.Mey.)Bunge,and Tamarix ramosissima Lour.We compared soil aggregation and aggregated-associated SOC under these communities.The aggregate fraction of 0.053–0.25 mm accounted for 47%–75%of the total soil mass,significantly more than the>0.25 and<0.053 mm fractions,under all the halophyte communities.Significant differences in soil aggregate size distribution were observed among the plant communities,with the H.ammodendron and B.dasyphylla communities showing the highest proportions of>0.25 mm aggregates(13.3%–43.8%)and T.ramosissima community having more<0.053 mm aggregates(14.1%–27.2%).Aggregate-associated SOC concentrations were generally the highest in the>0.25 mm fraction,followed by the<0.053 mm fraction,and were the lowest in the 0.053–0.25 mm fraction;however,because of their large mass,0.25–0.053 mm aggregates contributed significantly more to the total SOC.Total SOC concentrations(0–60 cm depth)decreased in the order of H.ammodendron(5.7 g kg^-1)>T.ramosissima(4.9 g kg^-1)>K.caspia(4.2 g kg^-1)>B.dasyphylla(3.4 g kg^-1).The H.ammodendron community had the highest total SOC and aggregate-associated SOC,which was primarily because aggregate-associated SOC content at the 0–10 and 10–20 cm depths under this community were higher than those under other plant communities.The H.ammodendron community could be beneficial for increasing SOC in saline soils in the arid region.展开更多
从土壤物理、化学、生物等方面系统地研究了油菜、豆科禾本科牧草混播人工草地土壤环境效应。干旱年型(生长季降水167.5 m m )混播草地至开花盛期土壤贮水量高于天然草地,之后呈降低趋势;丰水年型(生长季降水355.9 m m )土壤贮水量均高...从土壤物理、化学、生物等方面系统地研究了油菜、豆科禾本科牧草混播人工草地土壤环境效应。干旱年型(生长季降水167.5 m m )混播草地至开花盛期土壤贮水量高于天然草地,之后呈降低趋势;丰水年型(生长季降水355.9 m m )土壤贮水量均高于天然草地,1 m 土体贮水量增加5.7～67.6 m m 。土壤盐分表聚性特征明显,混播草地改善土壤盐分状况显著,耕层和1 m 土体含盐量分别较天然草地降低0.31～6.00g/kg和0.12～1.21 g/kg。混播草地肥力状况改善,速磷和有机质含量增加,而速氮、全氮、全磷含量则呈降低趋势,磷酸酶和H2O2 酶活性增强,脲酶活性下降;> 0.25m m 水稳性团聚体含量提高6.03% 。,结构系数、团聚度提高,改善了土壤结构状况,增大了土壤持水能力。混播草地地上部干物质和粗蛋白产量明显增大,较天然草地分别提高17.8% ～319.1% 和27.9% ～316.1% ,其生物产量和水分利用效率分别较天然草地提高477.1% 和15.2 kg/(m m ·hm 2),建植混播人工草地,显著提高生物产量和水分利用效率。展开更多
基金supported by the National Natural Science Foundation of China (40861020, 40961008)Huoyingdong Education Fund, China (121018)Natural Science Foundation of Xinjiang Uygur Autonomous Region, China (200821128)
文摘Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus （ETM＋） image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data. Principal component analysis （PCA） is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help the classification precision of a decision tree to be improved. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. According to the research, the third principal component （PC3） is an effective variable in the decision tree classification for salinized soil information extraction. The research demonstrated that the PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM＋ sensor （TM1） was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk （Tamarix chinensis Lour）; and areas comprising mixed water bodies and vegetation can be identified using the spectral indices MNDWI （modified normalized difference water index） and NDVI （normalized difference vegetation index）. Based upon this analysis, a decision tree classifier was applied to classify landcover types with different levels of soil saline. The results were checked using a statistical accuracy assessment. The overall accuracy of the classification was 94.80%, which suggested that the decision tree model is a simple and effective method with relatively high precision.
基金supported by the International Platform for Dryland Research and Education, Tottori University and the National Key R&D Program of China (2016YFC0500909)
文摘Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples(0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.
基金supported by the National Natural Science Foundation of China(No.31860360)the National Key R&D Program of China(No.2016YFC0501406)。
文摘Information on the effects of halophyte communities on soil organic carbon(SOC)is useful for sequestrating C in arid regions.In this study,we identified four typical natural halophyte communities in the Manasi River Basin in Xinjiang Province,Northeast China,namely,Karelinia caspia(Pall.)Less.,Bassia dasyphylla(Fisch.et C.A.Mey.)Kuntze,Haloxylon ammodendron(C.A.Mey.)Bunge,and Tamarix ramosissima Lour.We compared soil aggregation and aggregated-associated SOC under these communities.The aggregate fraction of 0.053–0.25 mm accounted for 47%–75%of the total soil mass,significantly more than the>0.25 and<0.053 mm fractions,under all the halophyte communities.Significant differences in soil aggregate size distribution were observed among the plant communities,with the H.ammodendron and B.dasyphylla communities showing the highest proportions of>0.25 mm aggregates(13.3%–43.8%)and T.ramosissima community having more<0.053 mm aggregates(14.1%–27.2%).Aggregate-associated SOC concentrations were generally the highest in the>0.25 mm fraction,followed by the<0.053 mm fraction,and were the lowest in the 0.053–0.25 mm fraction;however,because of their large mass,0.25–0.053 mm aggregates contributed significantly more to the total SOC.Total SOC concentrations(0–60 cm depth)decreased in the order of H.ammodendron(5.7 g kg^-1)>T.ramosissima(4.9 g kg^-1)>K.caspia(4.2 g kg^-1)>B.dasyphylla(3.4 g kg^-1).The H.ammodendron community had the highest total SOC and aggregate-associated SOC,which was primarily because aggregate-associated SOC content at the 0–10 and 10–20 cm depths under this community were higher than those under other plant communities.The H.ammodendron community could be beneficial for increasing SOC in saline soils in the arid region.
文摘从土壤物理、化学、生物等方面系统地研究了油菜、豆科禾本科牧草混播人工草地土壤环境效应。干旱年型(生长季降水167.5 m m )混播草地至开花盛期土壤贮水量高于天然草地,之后呈降低趋势;丰水年型(生长季降水355.9 m m )土壤贮水量均高于天然草地,1 m 土体贮水量增加5.7～67.6 m m 。土壤盐分表聚性特征明显,混播草地改善土壤盐分状况显著,耕层和1 m 土体含盐量分别较天然草地降低0.31～6.00g/kg和0.12～1.21 g/kg。混播草地肥力状况改善,速磷和有机质含量增加,而速氮、全氮、全磷含量则呈降低趋势,磷酸酶和H2O2 酶活性增强,脲酶活性下降;> 0.25m m 水稳性团聚体含量提高6.03% 。,结构系数、团聚度提高,改善了土壤结构状况,增大了土壤持水能力。混播草地地上部干物质和粗蛋白产量明显增大,较天然草地分别提高17.8% ～319.1% 和27.9% ～316.1% ,其生物产量和水分利用效率分别较天然草地提高477.1% 和15.2 kg/(m m ·hm 2),建植混播人工草地,显著提高生物产量和水分利用效率。
