Paper
18 November 2014 Dynamic monitoring of vegetation coverage change in Lu County based on TM/OLI-NDVI
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Abstract
TM data of 1998, 2002 and OLI data of 2013 were chosen in Lu County. Fractional Vegetation Cover of study area was obtained based on the basic processing of data measurement ascertaining atmospheric correction, the retrieval of surface albedo and the calculation of Normalized Difference Vegetation Index (NDVI) in this research. Spatial differences and influencing factors of Fractional Vegetation Cover in Lu County over past twenty five years were obtained through statistical and analysis. Studies have shown that vegetation cover changed for the better in the 35.62 percent areas of Lu County from 1988 to 2002 and 15.54 percent areas changed for the worse. The main factor that vegetation cover changed for the better is the change of imaging time. Significant increase could be found in vegetation cover because rice was not harvested on August 5 in 2002, but the opposite of September 5 in 1988. Meanwhile, scattered residential building construction in the southeast, agricultural land and mall-scale urban construction in the southwest could be main factors that had made vegetation cover changed for the worse. From 2002 to 2013, vegetation cover changed for the better in the 12.29 percent areas where located in the southeast of Lu County mainly because regional vegetation change. Meanwhile, vegetation cover changed for the worse in the 39.28 percent areas mainly because a large number of urban construction and mining development area in the middle and west and a large number of new scattered residential and agricultural land in the west and east.
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Sen Zeng, Hanhu Liu, and Tao Chen "Dynamic monitoring of vegetation coverage change in Lu County based on TM/OLI-NDVI", Proc. SPIE 9299, International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications, 929912 (18 November 2014); https://doi.org/10.1117/12.2073018
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KEYWORDS
Vegetation

Lutetium

Agriculture

Remote sensing

Mining

Atmospheric corrections

Earth observing sensors

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