Global land degradation and urbanization are rapidly progressing during the 21st century. Here in, we assessed spatio-temporal changes in global land cover using categorical intensity analyses from 1992 to 2018 to evaluate global land degradation and urbanization. Specifically, we evaluated the decrease, increase, and expansion processes and observed temporal differences. These evaluations were performed on a global scale across continents and climates at a category level for five-time intervals. In this study, inputs were gridded into land cover from 1992, 1997, 2002, 2007, 2012, and 2018. We analyzed five land categories: Cropland, Forest, Shrubland, Grassland, Other (SGO), Urban, and Bare areas. The analysis of change for the last 26 years shows that the loss intensities for Cropland are dormant during the first- and second-time intervals but active during the third, fourth, and last time intervals. Forest experiences loss intensities during all time intervals. SGO experiences only active loss during the second time interval and dormant loss intensities during all other time intervals. Urban Is the only category that experiences active gain intensities during all time intervals. Our study also indicates that for the last 26 years, urbanization has degraded and converted land in the temperate regions. Additionally, in South America and tropical regions, the expansion of Cropland is the biggest contributor to the decline in Forests and SGO. The findings can assist policymakers in managing future land use change sustainably.
Munkhnasan Lamchin, Graduated B.A and MS from the National University of Mongolia (Department of Geography) (2007). Ph.D. graduated in Division of Environmental Science & Ecological Engineering, Korea University in Seoul, Korea. She was trying to study assessment of land degradation, vegetation and land cover their correlation analysis in the local, national, regional and global level. Local level: She normalized the indicators, determined their weights, and defined five levels of desertification; non, low, medium, high, and severe in local level. Sets of rules were constructed, and a Multi-Criteria Evaluation (MCE) approach was used to assess desertification and test the correlations between the seven variables in comparison to the different levels of desertification, with field and reference data used for accuracy. They provide a review of the literature on MCE applied to desertification assessment issues based on satellite data. National level: She explored the spatio-temporal trends of changing vegetation cover in Mongolia, national level from 2002 to 2010 by investigating changes in the normalized difference vegetation index (NDVI) with rainfall. Residuals of NDVI (differences between the observed and predicted NDVI) for each pixel were calculated, and the trends in these residuals was analyzed by linear regression. From the 12 months NDVI and rainfall values they determine a linear regression line for each pixel. The positive or negative slope of this line is considered to reflect an increase or decrease in green biomass. Regional level: She estimated the overall trends for vegetation greenness, climate variables and analyzed trends during summer (April to October), winter (November to March), and the entire year. Second, we carried out correlation and regression analyses to detect correlations between vegetation greenness and climate variables in the Asia. Global level: Her on of research is estimated the overall trends for vegetation greenness and climate variables over five time periods and analysed four-season trends. Second, we performed correlation and regression analyses to detect correlations between vegetation greenness and climate variables. Next, we extracted trends and correlation results by mainland cover type (forest, cropland, and grassland). And she is calculating land cover change trend and prediction of global scale.
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