摘要
随着湛江市城镇化的发展,湛江市生态用地面积减少,生态环境恶化。因此,快速、全面及准确地定量监测湛江市生态环境质量变化具有重要意义。选用2000年、2005年、2009年、2015年、2020年Landsat系列卫星影像,选取绿度、湿度、干度、热度、土地利用与人口分布6项指标,构建改进遥感生态指数(improved remote sensing ecological index,IRSEI),定量分析湛江市2000—2020年间生态环境质量变化。研究结果表明:2000年、2005年、2009年、2015年与2020年IRSEI指数均值分别为0.18,0.18,0.35,0.42和0.38,呈先升后降的变化趋势;对2000—2020年间IRSEI进行差值处理,研究区生态环境变化“明显变好”、“轻度变好”、“基本不变”、“轻度变差”、“明显变差”的面积占比分别为78.95%,8.70%,8.01%,1.35%和2.99%,以“明显变好”为主;IRSEI指数可以较好地反映出2000—2020年间海岸带城区环境较差的现象,具体表现为海岸带区域的建筑用地IRSEI指数较低,研究结果将为湛江市生态环境保护提供理论基础和科学依据。
Urbanization has decreased the area of ecological land and deteriorated ecological environment in Zhanjiang City.Therefore,it is significant to quickly,comprehensively,and accurately monitor the changes the ecological environment quality in this city.Based on the Landsat images in 2000,2005,2009,2015,and 2020,this study constructed the improved remote sensing ecological index(IRSEI)using six indicators,namely greenness(NDVI),humidity(WET),dryness(NDBSI),heatiness(LST),land use(LUI),and population distribution(POP).Using IRSEI,this study quantitatively analyzed the changes in the ecological environment quality in Zhanjiang during 2000—2020.The results are as follows:①The mean IRSEI values of 2000,2005,2009,2015,and 2020 are 0.18,0.18,0.35,0.42,and 0.38,respectively,showing a first increasing and then decreasing trend.②According to the difference processing on IRSEIs during 2000—2020,the proportions of ecological environment areas with significant improvement(dominant),improvement,no change,deterioration,and significant deterioration in the study area are 78.95%,8.70%,8.01%,1.35%,and 2.99%,respectively.③The IRSEI can effectively reflect the poor urban environment along the coastal zone during 2000—2020,specifically manifested as a low IRSEI value of building land along the coastal zone.The results of this study can provide a theoretical and scientific basis for Zhanjiang’s ecological environment protection.
作者
王静
王佳
徐江琪
黄邵东
刘东云
WANG Jing;WANG Jia;XU Jiangqi;HUANG Shaodong;LIU Dongyun(Beijing Key Laboratory of Precision Forestry,Beijing Forestry University,Beijing 100091,China;College of Forestry,Beijing Forestry University,Beijing 100091,China;School of Landscape Architecture,Beijing Forestry University,Beijing 100091,China)
出处
《自然资源遥感》
CSCD
北大核心
2023年第3期43-52,共10页
Remote Sensing for Natural Resources
基金
国家自然科学基金项目“融合多源数据的京津冀地区植被NPP对气候变化和人类活动的响应与多情景模拟”(编号:42171329)
“基于夜间灯光遥感数据的京津冀地区人口PM2.5暴露时空分异及风险评价”(编号:42071342)共同资助。
关键词
生态环境质量
海岸带
改进遥感生态指数
ecological environment quality
coastal zone
improved remote sensing ecological index