关键词: 遥感, 植被净初级生产力, 光能利用率模型, 矿区生态

Abstract:

The government has paid much attention to impacts of mining on the ecological environment of the mine, and a number of studies have been done on damages mining has brought about to vegetation in mining areas. Based on domestic high resolution remote sensing image data in combination with the observation data of the meteorological stations in the region, estimation was performed of net primary productivity (NPP) of the vegetation in the mining area of Yuxian County from 2013 to 2015 with the carnegie ames stanford approach (CASA). Seasonal variation of NPP of the region and changes in land use in July of each of the past three years were analyzed, and correlations between NPP and various climate factors were also analyzed to explore formain factors affecting seasonal variation of the NPP relative to type of the vegetation. Main factors affecting NPP varied with the type of vegetation, and the type of mining activities as well. Analysis of dependence relativity between NPP and climate variables in July of 2013, 2014 and 2015 reveals that precipitation is the main factor affecting NPP in the center and south of the county, where is mining and residential quarters are concentrated, while solar radiation and temperature is the major one in the north of the county, where mountains dominate and are less disturbed by human activities.

Key words: remote sensing, net primary productivity, carnegie ames stanford approach model, ecology of mining areas