Research Of Vegetation Change Trend With Remote Sensing Technology In Coal Mine Surface Subsidence Area Of Binchang

In recently years, with the exploitation of coal mine continues to increase, mining groundsubsidence caused great influence to the economic development and ecological environment.Coal mining to promote regional economic development, due to the coal resources belong tothe primary energy, do not have the ability to regenerate, although in a certain period of time topromote regional economic development, but the damage is immeasurable. Mainly on waterresources in mining area, the destruction caused by surface subsidence, cracks etc.. So the coalmining and the destruction caused by the exploitation of the industrial development is notsustainable, must surface to mining subsidence hazard monitoring and prevention, and providethe necessary data and decision basis for governance follow-up mining area.Method combining InSAR technique and conventional remote sensing technology formonitoring surface subsidence of Binchang mining area of Shaanxi province. This paper usesthe data mainly includes Landsat data from2006to2007two SAR data in2005and2009to5years. Area are determined by SAR image processing to get the surface subsidence Binchangmining area, the methods of obtaining mainly differential interferometry and DEM inversionby two images obtained before and after the settlement, differential interferometric imaging,and interference from difference image is extracted mining surface subsidence area.Vegetation is all land plants in general, vegetation changes for the whole of the earth’secological environment is very sensitive, so it is the most valuable imaging factor. Based onthe research of mining subsidence images to extract vegetation index as the main influencefactors, to study the relationship between mining subsidence and surface ecologicalenvironment and influence each other. Methods using pixel two model to achieve theextraction of vegetation index from Landsat images, change of subsidence area vegetationindex from time and space.In accordance with the basic research ideas and test on the above, this paper uses D-InSAR technology and remote sensing technology the perfect combination of miningsubsidence area was extracted and NDVI value. According to the research and test resultsobtained the following results:(1) through the two scenes of ALOS PALSA images differential interferometryprocessing, the subsidence distribution corresponding, accurately determined experimentalarea land surface subsidence distribution.(2) TM images of2005to2009period of interest extraction subsidence area (A, B, C)NDVI value of surface mining subsidence area, find experimentation area surface NDVIchange and mining activities with temporal correlation, with the passage of time and itsincreased after the first drop phenomenon.(3) For the spatial correlation analysis of images, TM images of three found that changesin the region of interest respectively5.20%,-9.18%and-15.51%. The non vegetation NDVIsubsidence area values showed an increasing trend year by year; surface subsidence areaNDVI value with the passage of time gradually decreased, and the value of NDVI andsubsidence range and degree is certain correlation.