大田县近22 a环境变化遥感监测研究
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摘要
利用1992、2004、2014年3期Landsat遥感影像反演得到绿度、湿度、干度和热度因子后,基于主成分分析法生成遥感生态指数(RSEI),对大田县生态环境质量时空变化情况进行分析.结果表明:大田县三时期RSEI平均值分别为0. 673,0. 663,0. 735,表明近22 a以来,整体生态环境呈现先略有下降后小幅增加的变化趋势,以2004年为中间年份,前后变化幅度分别为-1. 49%与10. 86%.大田县近22 a生态环境改善总面积为955. 12 km2,占比42. 43%;生态环境退化总面积为173. 01 km2,占比7. 69%,改善面积显著大于退化面积,表明大田县政府一系列整治环境的政策对改善境内生态起到关键作用.
This paper used 1992,2004 and 2014 Landsat remote sensing images to retrieve four indexes which were greenness,wetness,dryness and heat. Then,based on principal component analysis method,remote sensing based ecological index( RSEI) was obtained to analyse the temporal and spatial variation characteristics of Datian county' s ecological environmental quality.The results shows: The Datian county' s mean RSEI value of three period is 0. 673,0. 663 and0. 735 respectively. It notes that overall ecological environment in recent 22 years shows first slightly decreased and then minor increased trend. Set 2004 as the middle period,the range of variation was-1. 49% and 10. 86% respectively. In recent 22 years,the total ecological environment improved area of Datian county was 955. 12 km2,accounting for 42. 43%; Opposite,the total ecological environment degraded area of Datian county was 173. 01 km2,which accounted for 7. 69%. The improved area was significantly greater than the degraded area,which shows that the a series of Datian county government policies play a key role in improving the ecological environment.
This paper used 1992,2004 and 2014 Landsat remote sensing images to retrieve four indexes which were greenness,wetness,dryness and heat. Then,based on principal component analysis method,remote sensing based ecological index( RSEI) was obtained to analyse the temporal and spatial variation characteristics of Datian county' s ecological environmental quality.The results shows: The Datian county' s mean RSEI value of three period is 0. 673,0. 663 and0. 735 respectively. It notes that overall ecological environment in recent 22 years shows first slightly decreased and then minor increased trend. Set 2004 as the middle period,the range of variation was-1. 49% and 10. 86% respectively. In recent 22 years,the total ecological environment improved area of Datian county was 955. 12 km2,accounting for 42. 43%; Opposite,the total ecological environment degraded area of Datian county was 173. 01 km2,which accounted for 7. 69%. The improved area was significantly greater than the degraded area,which shows that the a series of Datian county government policies play a key role in improving the ecological environment.
引文
[1]赵其国,黄国勤,马艳芹.中国生态环境状况与生态文明建设[J].生态学,2016,36(19):6328-6335.
[2]朱嘉伟.生态环境承载力评价研究——以河南省为例[J].生态学报,2017,37(21):1-9.
[3]李苗,臧淑英,吴长山,等.哈尔滨市城乡结合部不透水面时空变化及驱动力分析[J].地理学报,2017,72(1):105-115.
[4]殷刚,孟现勇,王浩,等. 1982-2012年中亚地区植被时空变化特征及其与气候变化的相关分析[J].生态学报,2017,37(9):3149-3163.
[5]周榕,徐涵秋,林云彬.城市建成区地表温度热通量的遥感研究——以泉州市区为例[J].遥感信息,2006(6):50-54.
[6]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):7853-7861.
[7]吴志杰,王猛猛,陈绍杰,等.基于遥感生态指数的永定矿区生态变化监测与评价[J].生态科学,2016,35(5):200-207.
[8]罗春,刘辉,戚陆越.基于遥感指数的生态变化评估——以常宁市为例[J].国土资源遥感,2014,26(4):145-150.
[9]张浩,杜培军,罗洁琼,等.基于遥感生态指数的南京市生态变化分析[J].地理空间信息,2017,15(2):58-63.
[10]严志垕.福建省大田县矿山水土流失现状及防治措施[J].亚热带水土保持,2014,26(3):54-57.
[11]王春菊,陈志强,汤小华.基于GIS技术的大田县水土流失成因分析[J].中国水土保持,2004(1):35-37.
[12]柯双根.大田县矿山水土流失综合治理的探索与实践[J].能源与环境,2016(3):60-61.
[13]徐涵秋.基于影像的Landsat TM/ETM+数据正规化技术[J].武汉大学学报(信息科学版),2007,32(1):62-66.
[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] BAIG M H A,ZHANG L,TONG S,et al. Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance[J]. Remote Sensing Letters,2014,5(5):423-431.
[16] XU H Q. A new index for delineating built-up land features in satellite imagery[J]. International Journal of Remote Sensing,2008,29(14):4276-4296.
[17] RIKIMARU A,ROY P S,MIYATAKE S. Tropical forest cover density mapping[J]. Tropical Ecology,2002,43(1):39-47.
[18] NASA. Landsat 7 Science Data Users Handbook[EB/OL].(2012-09-05). http:∥landsathandbook. gsfc. nasa. gov.
[19]徐涵秋.新型Landsat8卫星影像的反射率和地表温度反演[J].地球物理学报,2015,58(3):741-747.
[20] NICHOL J. Remote sensing of urban heat islands by day and night[J]. Photogrammetric Engineering and Remote Sensing,2005,71(5):613-621.
[2]朱嘉伟.生态环境承载力评价研究——以河南省为例[J].生态学报,2017,37(21):1-9.
[3]李苗,臧淑英,吴长山,等.哈尔滨市城乡结合部不透水面时空变化及驱动力分析[J].地理学报,2017,72(1):105-115.
[4]殷刚,孟现勇,王浩,等. 1982-2012年中亚地区植被时空变化特征及其与气候变化的相关分析[J].生态学报,2017,37(9):3149-3163.
[5]周榕,徐涵秋,林云彬.城市建成区地表温度热通量的遥感研究——以泉州市区为例[J].遥感信息,2006(6):50-54.
[6]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):7853-7861.
[7]吴志杰,王猛猛,陈绍杰,等.基于遥感生态指数的永定矿区生态变化监测与评价[J].生态科学,2016,35(5):200-207.
[8]罗春,刘辉,戚陆越.基于遥感指数的生态变化评估——以常宁市为例[J].国土资源遥感,2014,26(4):145-150.
[9]张浩,杜培军,罗洁琼,等.基于遥感生态指数的南京市生态变化分析[J].地理空间信息,2017,15(2):58-63.
[10]严志垕.福建省大田县矿山水土流失现状及防治措施[J].亚热带水土保持,2014,26(3):54-57.
[11]王春菊,陈志强,汤小华.基于GIS技术的大田县水土流失成因分析[J].中国水土保持,2004(1):35-37.
[12]柯双根.大田县矿山水土流失综合治理的探索与实践[J].能源与环境,2016(3):60-61.
[13]徐涵秋.基于影像的Landsat TM/ETM+数据正规化技术[J].武汉大学学报(信息科学版),2007,32(1):62-66.
[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] BAIG M H A,ZHANG L,TONG S,et al. Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance[J]. Remote Sensing Letters,2014,5(5):423-431.
[16] XU H Q. A new index for delineating built-up land features in satellite imagery[J]. International Journal of Remote Sensing,2008,29(14):4276-4296.
[17] RIKIMARU A,ROY P S,MIYATAKE S. Tropical forest cover density mapping[J]. Tropical Ecology,2002,43(1):39-47.
[18] NASA. Landsat 7 Science Data Users Handbook[EB/OL].(2012-09-05). http:∥landsathandbook. gsfc. nasa. gov.
[19]徐涵秋.新型Landsat8卫星影像的反射率和地表温度反演[J].地球物理学报,2015,58(3):741-747.
[20] NICHOL J. Remote sensing of urban heat islands by day and night[J]. Photogrammetric Engineering and Remote Sensing,2005,71(5):613-621.