Asia is the largest distribution area of salt-affected soils in the world. Very few countries in Asia couldescape from hazard of salinization. This paper deals with various salt-affected soils spreading in East Asiaan...Asia is the largest distribution area of salt-affected soils in the world. Very few countries in Asia couldescape from hazard of salinization. This paper deals with various salt-affected soils spreading in East Asiaand its neighboring regions (including China, Japan, Kampuchea, Democratic People’s Republic of Korea,Republic of Korea, Laos, Mongolia, Burma, Thailand and Vietnam). Principles of occurrence of salinization,and features of salt-affected soils in these regions have been studied in the present paper. Based on studieson types, features and distribution patterns of salt-affected soils, a salt-affected soil map of East Asia andits neighboring regions has been complied. Mechanism and manifestation of the salinization hazard on theregional agriculture and ecological environment, measures of preventing salinization hazard and exploitingsalt-affected soils in these regions are also discussed.展开更多
Salt-affected soils classification using remotely sensed images is one of the most common applications in remote sensing,and many algorithms have been developed and applied for this purpose in the literature.This stud...Salt-affected soils classification using remotely sensed images is one of the most common applications in remote sensing,and many algorithms have been developed and applied for this purpose in the literature.This study takes the Delta Oasis of Weigan and Kuqa Rivers as a study area and discusses the prediction of soil salinization from ETM +Landsat data.It reports the Support Vector Machine(SVM) classification method based on Independent Component Analysis(ICA) and Texture features.Meanwhile,the letter introduces the fundamental theory of SVM algorithm and ICA,and then incorporates ICA and texture features.The classification result is compared with ICA-SVM classification,single data source SVM classification,maximum likelihood classification(MLC) and neural network classification qualitatively and quantitatively.The result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification.It has high spread ability toward higher array input.The overall accuracy is 98.64%,which increases by10.2% compared with maximum likelihood classification,even increases by 12.94% compared with neural net classification,and thus acquires good effectiveness.Therefore,the classification method based on SVM and incorporating the ICA and texture features can be adapted to RS image classification and monitoring of soil salinization.展开更多
文摘Asia is the largest distribution area of salt-affected soils in the world. Very few countries in Asia couldescape from hazard of salinization. This paper deals with various salt-affected soils spreading in East Asiaand its neighboring regions (including China, Japan, Kampuchea, Democratic People’s Republic of Korea,Republic of Korea, Laos, Mongolia, Burma, Thailand and Vietnam). Principles of occurrence of salinization,and features of salt-affected soils in these regions have been studied in the present paper. Based on studieson types, features and distribution patterns of salt-affected soils, a salt-affected soil map of East Asia andits neighboring regions has been complied. Mechanism and manifestation of the salinization hazard on theregional agriculture and ecological environment, measures of preventing salinization hazard and exploitingsalt-affected soils in these regions are also discussed.
基金Supported by the National Key Basic Research Development Pro-gram (2009CB421302 )National Natural Science Foundation ofChina (40861020,40961025,40901163)+1 种基金Natural Science Foun-dation of Xinjiang (200821128 )Open Foundation of State KeyLaboratory of Resources and Environment Information ystems(2010KF0003SA)
文摘Salt-affected soils classification using remotely sensed images is one of the most common applications in remote sensing,and many algorithms have been developed and applied for this purpose in the literature.This study takes the Delta Oasis of Weigan and Kuqa Rivers as a study area and discusses the prediction of soil salinization from ETM +Landsat data.It reports the Support Vector Machine(SVM) classification method based on Independent Component Analysis(ICA) and Texture features.Meanwhile,the letter introduces the fundamental theory of SVM algorithm and ICA,and then incorporates ICA and texture features.The classification result is compared with ICA-SVM classification,single data source SVM classification,maximum likelihood classification(MLC) and neural network classification qualitatively and quantitatively.The result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification.It has high spread ability toward higher array input.The overall accuracy is 98.64%,which increases by10.2% compared with maximum likelihood classification,even increases by 12.94% compared with neural net classification,and thus acquires good effectiveness.Therefore,the classification method based on SVM and incorporating the ICA and texture features can be adapted to RS image classification and monitoring of soil salinization.
