基于RSEI的苏锡常城市群生态环境遥感评价
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摘要
快速准确掌握地区生态环境质量及其变化分布对于区域生态环境监测与治理、城市建设规划等问题具有重要的参考价值。基于此,以苏锡常城市群为研究区,选取多时相Landsat影像,分别提取湿度、绿度、热度和干度4项指标并通过主成分分析计算遥感生态指数RSEI(Remote Sensing Ecological Index),定量评价2001～2018年间区域生态质量变化情况。结果表明:①2001～2018年间苏锡常地区生态质量呈先下降后回升的趋势。2008年前后先下降17.69%后回升7.69%,其中苏州、无锡回升幅度大于常州;②2008年之后10 a区域生态恶化趋势得到明显遏制,生态恶化区从年均增长5.85%减至2.06%,其中老城区生态质量得到明显改善。③建筑类地物占比上升是生态质量下降的重要原因之一,而逐步回归分析中绿度在4个指标中所占权重最大且与干度权重呈负相关,表明恢复植被覆盖是改善区域生态质量的关键。
Obtain regional ecological environment quality and its change distribution rapidly and accurately is of great reference value for regional ecological environment monitoring and governance,urban construction planning and other issues.Based on this,taking the Su-Xi-Chang city group as the research area,the multi-temporal Landsat images were selected to extract the four indexes of humidity,greenness,heat and dryness,respectively,and calculate the RSEI(Remote Sensing Ecological Index) through principal component analysis to quantitatively evaluate the regional Ecological quality changes from 2001 to 2018.The results show that:(1) The ecological quality of the Su-Xi-Chang Region descend first and then pick up from 2001 to 2018.After falling 17.69% in 2008,it recovered 7.69%.Among them,Suzhou and Wuxi have rebounded more than Changzhou.(2) The trend of regional ecological deterioration has been significantly curbed in the decade after 2008.The growth rate of ecological deterioration area has decreased from 5.85% to 2.06% annually,and the ecological quality of the old urban area has been significantly improved.(3) The raise of the proportion of building objects is one of the most important reasons of ecological deterioration,while the greenness has the maximum weight of the four indexes in stepwise regression analysis and the dryness weight were negatively correlated,indicating that the recovery of vegetation coverage is the key to improve the regional ecological quality.
Obtain regional ecological environment quality and its change distribution rapidly and accurately is of great reference value for regional ecological environment monitoring and governance,urban construction planning and other issues.Based on this,taking the Su-Xi-Chang city group as the research area,the multi-temporal Landsat images were selected to extract the four indexes of humidity,greenness,heat and dryness,respectively,and calculate the RSEI(Remote Sensing Ecological Index) through principal component analysis to quantitatively evaluate the regional Ecological quality changes from 2001 to 2018.The results show that:(1) The ecological quality of the Su-Xi-Chang Region descend first and then pick up from 2001 to 2018.After falling 17.69% in 2008,it recovered 7.69%.Among them,Suzhou and Wuxi have rebounded more than Changzhou.(2) The trend of regional ecological deterioration has been significantly curbed in the decade after 2008.The growth rate of ecological deterioration area has decreased from 5.85% to 2.06% annually,and the ecological quality of the old urban area has been significantly improved.(3) The raise of the proportion of building objects is one of the most important reasons of ecological deterioration,while the greenness has the maximum weight of the four indexes in stepwise regression analysis and the dryness weight were negatively correlated,indicating that the recovery of vegetation coverage is the key to improve the regional ecological quality.
引文
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[12] Wang Shiyuan,Zhang Xuexia,Zhu Tong,et al.Assessment of Ecological Environment Quality in the Changbai Mountain Nature Reserve based on Remote Sensing Technology[J].Progress in Geography,35(10):1269-1278.[王士远,张学霞,朱彤,等.长白山自然保护区生态环境质量的遥感评价[J].地理科学进展,2016,35(10):1269-1278.]
[13] Xu Hanqiu.A Remote Sensing Urban Ecological Index and Its Application[J].Acta Ecologica Sinica,2013,33(24):7853-7862.[徐涵秋.城市遥感生态指数的创建及其应用[J].生态学报,2013,33(24):7853-7862.]
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[20] Valor E,Caselles V.Mapping Land Surface Emissivity from NDVI:Application To European,African,and South American Areas[J].Remote Sensing of Environment,1996,57:167-184.
[21] Sobrino J A,Jiménez-Muňoz J C,Paolini L.Land Surface Temperature Retrieval from Landsat TM 5[J].Remote Sensing of Environment,2004,90:434-440.
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[23] Li Shanshan,Jiang Gengming.Land Surface Temperature Retrieval from Landsat-8 Data with the Generalized Split Window Alorithm[J].Remote Sensing Technology and Application,2018,33(2):284-295.[李珊珊,蒋耿明.其于通用分裂窗算法和Landsat-8数据的地表温度反演研究[J].遥感技术与应用,2018,33(2):284-295.]
[24] Liu Fei,Li Ping.Comparative Analysis of Land Surface Emissivity Retrieval Methods based on Normalized Differential Vegetation Index[J].Urban Geotechnical Investigation & Surveying,2016(2):64-68,73.[柳菲,李平.基于归一化植被指数反演地表比辐射率方法的对比研究[J].城市勘测,2016(2):64-68,73.]
[25] Rikimaru A,Roy P S,Miyatake S.Tropical Forest Cover Density Mapping[J].Tropical Ecology,2002,43(1):39-47.
[26] Xu H.A New Index for Delineating Built-Up Land Features in Satellite Imagery[J].International Journal of Remote Sensing,2008,29(14):4269-4276.
[27] Xu Hanqiu.A Study on Information Extraction of Water Body with the Modified Normalized Difference Water Index (MNDWI)[J].Journal of Remote Sensing,2005,9(5):589-595.[徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,9(5):589-595.]
[28] Zha Y,Gao J,Ni S.Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery[J].International Journal of Remote Sensing,2003,24(3):583-594.
[29] Wu Zhijie,Zhao Shuhe.A Study of Enhanced Index-based Built-Up Index based on Landsat TM Imagery[J].Remote Sensing of Land & Resources,2012,24(2):50-55.[吴志杰,赵书河.基于TM图像的“增强的指数型建筑用地指数”研究[J].国土资源遥感,2012,24(2):50-55.]
[30] Dai Yingyi,Liu Hui,Li Qiran,et al.Extraction of Built-Up Land Information from from Medium Spatial Resolution Satellite Image[J].Journal of Subtropical Resources and Environment,2013,8(4):68-74.[代颖懿,刘辉,黎启燃,等.基于中等空间分辨率遥感影像的建筑用地信息提取[J].亚热带资源与环境学报,2013,8(4):68-74.]
[31] Peng Yidong,Hao Yingying,Luo Xiaobo.Study on Extraction Precision of Building Area based on Index[J].Information Systems Engineering,2014 (11):136-137,60.[彭义东,郝莹莹,罗小波.基于指数的建筑区域提取精度研究[J].信息系统工程,2014(11):136-137,60.]
[2] Ni Minli,Shen Shuanghe,Zhang Jiahua.A Study on Thermal Environment of Urban Group in Yangtze River Delta[J].Transactions of Atmospheric Sciences,2009,32(5):711-715.[倪敏莉,申双和,张佳华.长江三角洲城市群热环境研究[J].大气科学学报,2009,32(5):711-715.]
[3] Dong Liangpeng,Jiang Zhihong,Shen Suhong.Urban Heat Island Change and Its Relationship with Urbanization of Urban Agglomerations in Yangtze River Delta in Past Decade[J].Transactions of Atmospheric Sciences,2014,37(2):146-154.[董良鹏,江志红,沈素红.近十年长江三角洲城市热岛变化及其与城市群发展的关系[J].大气科学学报,2014,37(2):146-154.]
[4] Xiao Rongbo,Ouyang Zhiyun,Li Weifeng,et al.A Review of the Eco-Environmental Consequences of Urban Heat Islands[J].Acta Ecologica Sinica,2005,25(8):2055-2060.[肖荣波,欧阳志云,李伟峰,等.城市热岛的生态环境效应[J].生态学报,2005,25(8):2055-2060.]
[5] Yue Wenze,Xu Jianhua,Xu Lihua.An Analysis on Eco-Environmental Effect of Urban Land Use based on Remote Sensing Images:A Case Study of Urban Thermal Environment and NDVI[J].Acta Ecologica Sinica,2006,26(5):1450-1460.[岳文泽,徐建华,徐丽华.基于遥感影像的城市土地利用生态环境效应研究——以城市热环境和植被指数为例[J].生态学报,2006,26(5):1450-1460.]
[6] The Central People’s Government of Republic of China.HJ/T 192-2015 Technical Criterion for Ecosystem Status Evalution[S].Beijing:China Standard Press,2015.[国家环境保护总局.HJ/T 192-2015生态环境状况评价技术规范(试行)[S].北京:中国标准出版社,2015.]
[7] Yang Hui,Han Ling,Zhang Shuo,et al.Ecological Environmental Quality Assessment based on Landsat8 Satellite Images by Taking Yichang City of Three Gorges Reservoir Area as an Example[J].Henan Science,2019,37(1):93-97.[杨辉,韩玲,张硕,等.基于Landsat8卫星影像的生态环境质量评价——以三峡库区的宜昌市为例[J].河南科学,2019,37(1):93-97.]
[8] Zhen Jianghong,Wang Yafeng,Tian Yuanyuan,et al.Study on Ecological Environment Effects of Urban Spatial Expansion:Taking Inner Mongolia Hohhot City as an Example[J].Geographic Science,2019,38(5):1080-1091.[甄江红,王亚丰,田圆圆,等.城市空间扩展的生态环境效应研究——以内蒙古呼和浩特市为例[J].地理研究,2019,38(5):1080-1091.]
[9] Zhang Yuan,Wang Zhifang,Chen Nan,et al.Spatiotemporal Variation Characteristics and Related Affecting Factors of Hubei Province Eco-Environmental Status[J].Environmental Science & Technology,2017,40(Sup.2):300-305.[张媛,望志方,陈楠,等.湖北省生态环境状况时空变化特征及影响因素分析[J].环境科学与技术,2017,40(增刊2):300-305.]
[10] Xu Hanqiu.A Remote Sensing Index for Assessment of Regional Ecological Changes[J].China Environmental Science,2013,33(5):889-897.[徐涵秋.区域生态环境变化的遥感评价指数[J].中国环境科学,2013,33(5):889-897.]
[11] Zhang Can,Xu Hanqiu,Zhang Hao,et al.Fractional Vegetation Cover Change and Its Ecological Effect Assessment in a Typical Reddish Soil Region of Southeastern China:Changting County,Fujian Province[J].Journal of Natural Resources,2015,30(6):917-928.[张灿,徐涵秋,张好,等.南方红壤典型水土流失区植被覆盖度变化及其生态效应评估——以福建省长汀县为例[J].自然资源学报,2015,30(6):917-928.]
[12] Wang Shiyuan,Zhang Xuexia,Zhu Tong,et al.Assessment of Ecological Environment Quality in the Changbai Mountain Nature Reserve based on Remote Sensing Technology[J].Progress in Geography,35(10):1269-1278.[王士远,张学霞,朱彤,等.长白山自然保护区生态环境质量的遥感评价[J].地理科学进展,2016,35(10):1269-1278.]
[13] Xu Hanqiu.A Remote Sensing Urban Ecological Index and Its Application[J].Acta Ecologica Sinica,2013,33(24):7853-7862.[徐涵秋.城市遥感生态指数的创建及其应用[J].生态学报,2013,33(24):7853-7862.]
[14] Crist E P.A TM Tasseled Cap Equivalent Transformation for Reflectance Factor Data[J].Remote Sensing of Environment,1985,17(3):301-306.
[15] Huang C,Wylie B,Yang L,et al.Derivation of a Tasselled Cap Transformation based on Landsat 7 At-Satellite Reflectance[J].International Journal of Remote Sensing,2002,23(8):1741-1748.
[16] Huang C,Wylie B,Yang L,et al.Derivation of a Tasselled Cap Transformation based on Landsat 8 At-Satellite Reflectance[J].Remote Sensing Letters,2014,5(5):423-431.
[17] NASA.Landsat 8 Data Users Handbook[EB/OL].2015.Https://Www.Usgs.Gov/Land-Resources/Nli/Landsat/Landsat-8-Data-Users-Handbook.
[18] Chander G,Markham B L,Helder D L.Summary of Current Radiometric Calibration Coefficients for Landsat MSS,TM,ETM+,and EO-1 ALI Sensors[J].Remote Sensing of Environment,2009,113:893-903.
[19] Van A A,Owe M.On the Relationship between Thermal Emissivity and the Normalized Difference Vegetation Index for Natural Surfaces[J].International Journal of Remote Sensing,1993,14(6):1119-1131.
[20] Valor E,Caselles V.Mapping Land Surface Emissivity from NDVI:Application To European,African,and South American Areas[J].Remote Sensing of Environment,1996,57:167-184.
[21] Sobrino J A,Jiménez-Muňoz J C,Paolini L.Land Surface Temperature Retrieval from Landsat TM 5[J].Remote Sensing of Environment,2004,90:434-440.
[22] Qin Zhihao,Li Wenjuan,Xu Bin,et al.The Estimation of Land Surface Emissivity for Landsat TM6[J].Remote Sensing of Land & Resources,2004,16(3):28-32,36-41,74.[覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004,16(3):28-32,36-41,74.]
[23] Li Shanshan,Jiang Gengming.Land Surface Temperature Retrieval from Landsat-8 Data with the Generalized Split Window Alorithm[J].Remote Sensing Technology and Application,2018,33(2):284-295.[李珊珊,蒋耿明.其于通用分裂窗算法和Landsat-8数据的地表温度反演研究[J].遥感技术与应用,2018,33(2):284-295.]
[24] Liu Fei,Li Ping.Comparative Analysis of Land Surface Emissivity Retrieval Methods based on Normalized Differential Vegetation Index[J].Urban Geotechnical Investigation & Surveying,2016(2):64-68,73.[柳菲,李平.基于归一化植被指数反演地表比辐射率方法的对比研究[J].城市勘测,2016(2):64-68,73.]
[25] Rikimaru A,Roy P S,Miyatake S.Tropical Forest Cover Density Mapping[J].Tropical Ecology,2002,43(1):39-47.
[26] Xu H.A New Index for Delineating Built-Up Land Features in Satellite Imagery[J].International Journal of Remote Sensing,2008,29(14):4269-4276.
[27] Xu Hanqiu.A Study on Information Extraction of Water Body with the Modified Normalized Difference Water Index (MNDWI)[J].Journal of Remote Sensing,2005,9(5):589-595.[徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,9(5):589-595.]
[28] Zha Y,Gao J,Ni S.Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery[J].International Journal of Remote Sensing,2003,24(3):583-594.
[29] Wu Zhijie,Zhao Shuhe.A Study of Enhanced Index-based Built-Up Index based on Landsat TM Imagery[J].Remote Sensing of Land & Resources,2012,24(2):50-55.[吴志杰,赵书河.基于TM图像的“增强的指数型建筑用地指数”研究[J].国土资源遥感,2012,24(2):50-55.]
[30] Dai Yingyi,Liu Hui,Li Qiran,et al.Extraction of Built-Up Land Information from from Medium Spatial Resolution Satellite Image[J].Journal of Subtropical Resources and Environment,2013,8(4):68-74.[代颖懿,刘辉,黎启燃,等.基于中等空间分辨率遥感影像的建筑用地信息提取[J].亚热带资源与环境学报,2013,8(4):68-74.]
[31] Peng Yidong,Hao Yingying,Luo Xiaobo.Study on Extraction Precision of Building Area based on Index[J].Information Systems Engineering,2014 (11):136-137,60.[彭义东,郝莹莹,罗小波.基于指数的建筑区域提取精度研究[J].信息系统工程,2014(11):136-137,60.]