国产高分数据在草原露天煤矿植被监测中的应用

摘要

The CASA model using Chinese GF-1 satellite was applied at the regional scale to determine and monitor the spatial distri-bution of NPP around mining area and rehabilitation area in this study.The CASA model was improved with GF-1 Chinese satellite series by providing the FPAR and moisture stress coefficient input parameters from NDVI and NDWI.The modeling NPP produced the high accuracy validating with 0.94 using the field sampling data acquired at August 2014.As the good correlation between the observed NPP and the estimated NPP, the CASA model has the potential to be used in the regional scale using high resolution imager.The actu-al grassland NPP from CASA model showed an obvious geographical heterogeneity.The results indicated that the grazing and water lim-itation was important variable controlling regional patterns of productivity at natural site around mining area.There was obvious bounda-ry between grazing area with the NPP ranging from 200 gC/m2 .yr-300 gC/m2 .yr and un-grazing area with the NPP ranging from 300 gC/m2 .yr-400 gC/m2 .yr as the fence was used to block the cattle and sheep.The region of NPP value less than 50 gC/m2 .yr was found in mining area, characterized by bare soil, open pit and dump.Overall, the Chinese GF series data performed well in moni-toring NPP based on CASA model.As the primary of rehabilitation project is to recover the mining area as well as the natural site, NPP would be a key indicator to assess and compare the condition of natural and rehabilitated vegetation in this region.%利用高分一号卫星数据建立小尺度CASA－NPP估算模型，反演及监测草原露天煤矿区草地NPP空间分布格局，以及煤矿区内部复垦植被的NPP与表层土壤之间的关系。利用归一化植被指数、归一化水体指数等获取CASA模型有效光辐射参数、水分胁迫系数等，从而简化并改进小尺度CASA模型，遥感反演数据与实测样点数据拟合度达到0．94。结果表明，该模型能够高精度地完成小区域NPP估测。从利用CASA模型反演得到的NPP空间格局可以看出，这一地区的植被退化以采矿、放牧等人类活动为主导，原地貌区域围栏的典型草甸草原NPP在300～400 gC／m2· yr 之间，高于放牧区域 NPP，矿区内 NPP 空间变化显著，矿区内部 NPP 低于100 gC／m2· yr，明显低于周边原地貌地区。对于矿区复垦排土场区域，复垦年限和表土的养分是决定植被生长和NPP的主要因素。研究得出国产高分卫星数据可以高精度地完成小尺度NPP的估测，从而为其在草原地区以及矿山环境中监测提供了研究基础。