Abstract
Abstract. Serious land desertification and sandified threaten the urban ecological security and the sustainable economic and social development. In recent years, a large number of mobile sand dunes in Horqin sandy land flow into the northwest of Liaoning Province under the monsoon, make local agriculture suffer serious harm. According to the characteristics of desertification land in northwestern Liaoning, based on the First National Geographical Survey data, the Second National Land Survey data and the 1984–2014 Landsat satellite long time sequence data and other multi-source data, we constructed a remote sensing monitoring index system of desertification land in Northwest Liaoning. Through the analysis of space-time-spectral characteristics of desertification land, a method for multi-spectral remote sensing image recognition of desertification land under time-space constraints is proposed. This method was used to identify and extract the distribution and classification of desertification land of Chaoyang City (a typical citie of desertification in northwestern Liaoning) in 2008 and 2014, and monitored the changes and transfers of desertification land from 2008 to 2014. Sandification information was added to the analysis of traditional landscape changes, improved the analysis model of desertification land landscape index, and the characteristics and laws of landscape dynamics and landscape pattern change of desertification land from 2008 to 2014 were analyzed and revealed.
Highlights
1.1 General InstructionsLand desertification is mainly characterized by wind erosion, sand burial and fixed sand dune activation, which is one of the most serious resource and ecological environmental problems in the world
This paper explores an indicator system for remote sensing monitoring of desertification land in northwestern Liaoning, and proposes a desertification land identification method based on multi-spectral remote sensing images under the constraint of time and space in the extraction process for desertification land, which effectively solve the problem of low precision of remote sensing automatic monitoring of desertification land and improve the efficiency of automatic monitoring
A multi images local adaptive regression analysis model is selected to process the strip of Landsat image acquired after 2008, to remove the rule strip information loss caused by the failure of airborne scanning line corrector (SLC)
Summary
Land desertification is mainly characterized by wind erosion, sand burial and fixed sand dune activation, which is one of the most serious resource and ecological environmental problems in the world. A large number of mobile sand dunes in the Horqin Sandy Land have flowed into northwestern Liaoning under the action of monsoons, resulting in the loss of nutrients in large areas of farmland and the reduction in crop yields. The related research on remote sensing monitoring of desertification land in northwestern Liaoning has been carried out. With the large number of researches on land desertification information extraction and dynamic change monitoring, the method of extracting desertification information using remote sensing information has made great progress. The analysis of the relationship between vegetation and climate in the desertification region based on time series NDVI data is a hot topic in the research field of ecological environment at home and abroad. This paper explores an indicator system for remote sensing monitoring of desertification land in northwestern Liaoning, and proposes a desertification land identification method based on multi-spectral remote sensing images under the constraint of time and space in the extraction process for desertification land, which effectively solve the problem of low precision of remote sensing automatic monitoring of desertification land and improve the efficiency of automatic monitoring
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