ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 25–32, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-25-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 25–32, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-25-2020

  03 Aug 2020

03 Aug 2020

LAND SALINIZATION DYNAMICS BASED ON FEATURE SPACE COMBINATIONS FROM LANDSAT IMAGE IN TONGYU COUNTY, NORTHEAST CHINA

F. Huang, P. Wang, Y. Liu, and H. Y. Li F. Huang et al.
  • Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Renmin Street, Changchun, China

Keywords: Salinization, Feature Space, Albedo, Modified Soil Adjusted Vegetation Index, Salinity Index, Landsat Image

Abstract. Land salinization is one of the most common land degradation processes. Tongyu county exemplifies all the forms of land degradation in Northeast China and is prone to land salinization due to its fragile physical conditions. In this study, Landsat remote sensing images are adopted to invert surface albedo, MSAVI (modified soil adjusted vegetation index), and salinity index (SI) data. The feature space models of albedo-SI and MSAVI-SI, considering the bare soil and vegetation information respectively, are constructed and compared. Land salinization changes for the period of 1998–2017 are investigated using the salinization monitoring index (SMI) and salinization detection index (SDI) extracted from the feature space models. Our results show that the land salinization situation in Tongyu county have tended to improve, associated with the biological, ecological and engineering means for the degraded land rehabilitation. The feature space models is applicable for the extraction of salinization information, and albedo-SI may evaluate land salinization levels with higher accuracy.