Analysis of Vegetation Coverage Dynamics of YongDeng County Using Normalized Difference Vegetation Index (NDVI) and Pixel Binary Model

Samuel Adingo, Liu Xue-Lu, Xiaodan Li, Jie-Ru Yu


The research is supported by the fundamental research funds of Gansu provincial natural science fund of “Research on Land use and Ecological Security in Ecologically Vulnerable Areas” (project No. GSAN-ZL-2015-045) and “Research on the Coordination Relationship between Land Urbanization and Population Urbanization” (project No. GSAU-ZL-2015-046)


Under the current background of global climate change, it is very important to study the temporal and spatial characteristics of vegetation cover which will provide a scientific basis for ecosystem management decisions that will protect the integrity of biodiversity and ensure a continuous supply of valuable ecological services. The objective of this study was to use the normalized difference vegetation index and the pixel binary model in ENVI to analyze the vegetation cover dynamics of YongDeng County using 1993, 2001, 2009, and 2017 satellite images. Satellite images were obtained from the Geospatial Data Cloud (Http/ Combined with the vegetation coverage information and unique ecological characteristics of the study area, the vegetation coverage types were classified into four grades as Grade I (Bare land, water, and built-up environment), grade II (Low yield grassland and sparse vegetation classified), grade III (Middle grassland and vegetation of cultivated land) and grade IV (Dense woodland and shrubs). The results showed a dynamic trend in the different grades of vegetation cover in the study area from 1993 to 2017. Grade I vegetation-covered an area of 1208.72 km² and 1098.09 km² in 1993 and 2001 respectively but decreased to 375.99 km² in 2009 and finally increased slightly to 398.88 km² in 2017. Grade II vegetation cover did not show significant changes over the years considered for this study. It covered an area of 3821.2 km² and 3803.1 km² in 1993 and 2001 respectively. In 2009 and 2017 it covered approximately 3769.2 km² and 3787.82 km² respectively. Grade III vegetation cover showed an increasing trend from 1993 to 2017. From 334.76 km² in 1993, it increased to 468.28 km² and 980.39 km² in 2001 and 2009 respectively, and finally increased further to 1008.5 km² in 2017. Grade IV vegetation-covered an area of 4552.62 km², 442.6 km², and 667.52 km² in 1993, 2001, and 2009 respectively and finally reduced slightly to 596.64 km² in 2017. Economic development in areas such as mining, construction, and urbanization played a major role in reducing Grade I vegetation cover. Grade II did not show any significant change because of fewer disturbances as a result of their inaccessible nature to humans. Expansion and Continues farming throughout the year as a result of the presence of an irrigation system in the area accounted for the increasing trend of Grade III vegetation cover. This study reveals there is an urgent need for measures to be put in place to mitigate activities that lead to the removal of vegetation cover as this may have serious implications on the supply of important ecological services.

Keywords: Vegetation coverage, YongDeng, NDVI, Pixel Binary model, dynamic analysis

DOI: 10.7176/JEES/10-9-09

Publication date:September 30th 2020

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ISSN (Paper)2224-3216 ISSN (Online)2225-0948

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