Tracking desertification on the Mongolian steppe through NDVI and field-survey data

Abstract

Changing environmental and socio-economic conditions make land degradation, a major concern in Central and East Asia. Globally satellite imagery, particularly Normalized Difference Vegetation Index (NDVI) data, has proved an effective tool for monitoring land cover change. This study examines 33 grassland water points using vegetation field studies and remote sensing techniques to track desertification on the Mongolian plateau. Findings established a significant correlation between same-year field observation (line transects) and NDVI data, enabling an historical land cover perspective to be developed from 1998 to 2006. Results show variable land cover patterns in Mongolia with a 16% decrease in plant density over the time period. Decline in cover identified by NDVI suggests degradation; however, continued annual fluctuation indicates desertification Á irreversible land cover change Á has not occurred. Further, in situ data documenting greater cover near water points implies livestock overgrazing is not causing degradation at water sources. In combination of the two research methods Á remote sensing and field surveys Á strengthen findings and provide an effective way to track desertification in dryland regions.

Contraction of the Gobi Desert, 2000–2012

“…Ground-truthing has shown the effectiveness of satellite assessment as an indicator of pasture conditions in the Gobi [36,42]. Prior fieldwork by the authors found NDVI results significantly correlated (p ≤ 0.01) with area vegetation line-transect data (basal coverage assessment, to 1-km) in the Gobi [43]. There are limitations in assessing a compact timespan in an arid landscape; however, this paper uses a longer temporal data set than employed in Tucker et al's [5] seminal work on desert areal extent.…”

Change of surface cover greenness in China between 2000 and 2010

“…It is difficult to set a standard threshold of vegetation coverage for different geographic landscapes and ecological characteristics, which is why we selected a series of thresholds in greenness in this research. In fact, regions of low greenness in this study are not limited to areas defined by desert in the "convention", but it can reflect the vegetation change of desert areas well [17][18][19][20]31]. In comparison with the fourth desertification survey of China, an NDVI value of less than 1500 can be used as an evaluation standard of desert.…”

“…Hot spots such as Inner Mongolia, Horqin grassland, Hulunbuir, Ordos, Qinghai-Tibet Plateau, Minqin, and the three north shelter forests, are major focal areas of previous remote sensing research [9][10][11][12][13][14][15][16][17][18][19][20][21][22], and there is no desertification analysis about the whole territory of China. Time series data used in existing research are mostly before 2000, incomplete since 2000 to nowadays [9][10][11][12][13][14][15][16][17][18][19][20][21][22], and there is still no report for the time period of 2000 and 2010. Therefore, in this paper we aim to map China's desertification between 2000 and 2010 based on international standard and definition of desertification, and the capability of remote sensing technology, in order to lay a foundation for China's long-term remote sensing monitoring of desertification.…”

Landscape conservation and valorization by satellite imagery and historic maps. The case of Italian transhumance routes

“…The conservation analysis was made according to the method proposed by Meini et al [2013a,b] in using a vegetation index into a sample area of the sheep track. Since its wide use with very good results in remote sensing researches [see e.g., Iamonico, 2008;Sternberg et al, 2010;Duringon et al 2012;Alphan and Derse, 2013;Schucknecht et al, 2013] the Normalized Difference Vegetation Index (NDVI) was chosen. It is a standardized index which generates an image displaying greenness (relative biomass).…”