基于多源遥感数据的环境质量背景重构及变化模拟  

Environmental Quality Background Reconstruction and Its Change Simulation Using Multi-Source Remote Sensing Data

作　　者：胡文敏[1] 周卫军[1] 余德[1] 王彬武[2] 刘沛[1] 杨威[1] 

机构地区：[1]湖南农业大学资源环境学院/遥感与地理信息实验室,中国湖南长沙410128 [2]中国农业大学资源与环境学院,中国北京100193

出　　处：《经济地理》2014年第4期171-178,共8页Economic Geography

基　　金：国家自然科学基金项目(41001071)

摘　　要：利用多源遥感数据反演算法获取环境指标,结合生态环境质量数字模型和灰色多元回归模型,以洞庭湖为例,对环境质量背景进行了重构和预测,结果表明:7年间湖区生态环境质量总体下滑,城市郊区和湿地尤为明显。大气可降雨量降低,植被覆盖度减少,地表温度升高,土地利用强度增加为主要驱动因素,土地利用强度和降雨条件与湖区生态环境质量有较强相关性;未来短期内湖区土地生态环境质量具有退化趋势,预测2021年环境质量相比2007年将退化18.5%;环境变化并不完全是单一要素驱动或多要素叠加干扰,还存在环境因子的集聚作用,包括正向集聚—提升环境质量和负向集聚—降低环境质量,重视正向聚集(促进降雨、增加植被覆盖度、降低土地利用强度等)带来的环境效应将有利于改善湖区生态环境。The environmental factors were calculated with an inversion algorithm of multi-source remote sensing data. The envriomental quality background was reconstructed and predicted with a digital environmental model and grey multiple regression model in Dongting Lake area. The results showed a degenerative tendency in the lake area from the quality changes between 2001 and 2007, primarily in the suburbs and wetlands. Atmospheric water vapour, land use intensity, surface temperature, vegetation coverage, and soil water content were the main driving factors. The prediction showed the environmental quality degraded 18.5% in next 14 years （2008--2021）. Environment changes were not exactly the single factor driving or interference of multi-factor combinations, but the environmental agglomeration effect including positive and negative side, respectively mean increase and decrease of environmental quality. Paying more attention to the positive agglomeration effect to the environment （increase rainfall and vegetation coverage, reduce the land use intensity, etc） will improve the environment quality.

关 键 词：环境质量 土地利用 多源遥感 聚集效应 灰色多元回归 

分 类 号：F062.9[经济管理—政治经济学]