Landsat8不透水面遥感信息提取方法对比
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摘要
不透水面是重要的地表覆盖类型,利用卫星遥感影像准确提取不透水面信息对于掌握地表覆盖变化具有重要意义。现有研究已提出了多种不透水面遥感信息提取指数,但目前尚缺乏对这些不透水面指数的系统对比分析。利用Landsat8卫星遥感影像,测试了目前8种主要不透水面指数的提取精度。结果表明,在现有不透水面指数中,垂直不透水层指数能够有效增强不透水面信息,不透水面提取精度最高(89. 6%),其次是比值居民地指数和生物物理组分指数(87. 5%和87. 4%),城市指数与新建筑指数提取精度再次之(82. 9%和80. 0%),归一化差值不透水面指数、归一化建筑指数和基于指数的建筑指数未能有效增强不透水面信息,提取精度较低(<75. 0%)。此外,这8种不透水面指数都未能有效解决不透水面与大片裸地光谱混淆的问题,在裸地广泛分布的区域难以准确提取不透水面,平均提取精度仅为71. 0%,影响了不透水面指数的大区域应用。
Impervious surface is an important land cover type. Extracting impervious surface from satellite images is crucial for land use and land cover change( LUCC) studies. Although several indexes have been proposed to detect impervious surface,there is a lack of systematic comparative analysis of these indexes. To address this problem,the authors estimated the performance of eight state-of-the-art impervious surface indexes using Landsat8 satellite images. The experimental results show that perpendicular impervious index( PII) performs best,yielding the highest detection accuracy of 89. 6%. The accuracies of ratio resident-area index( RRI) and biophysical composition index( BCI) are slightly lower than the accuracy of PII,which are 87. 5% and 87. 4%,respectively.The accuracies of urban index( UI) and new built-up index( NBI) are 82. 9% and 80. 0%,respectively.Normalized difference impervious surface index( NDISI),normalized difference built-up index( NDBI),and index-based built-up index( IBI) fail to enhance the spectral characteristics of impervious surface from complex image background,thereby yielding the lowest accuracy( < 75. 0%). Importantly,the eight impervious surface indexes fail to distinguish the spectral characteristics of impervious surface from large bare land areas and the average detection accuracy is only 71. 0%,hindering their applications in bare-land-rich areas.
Impervious surface is an important land cover type. Extracting impervious surface from satellite images is crucial for land use and land cover change( LUCC) studies. Although several indexes have been proposed to detect impervious surface,there is a lack of systematic comparative analysis of these indexes. To address this problem,the authors estimated the performance of eight state-of-the-art impervious surface indexes using Landsat8 satellite images. The experimental results show that perpendicular impervious index( PII) performs best,yielding the highest detection accuracy of 89. 6%. The accuracies of ratio resident-area index( RRI) and biophysical composition index( BCI) are slightly lower than the accuracy of PII,which are 87. 5% and 87. 4%,respectively.The accuracies of urban index( UI) and new built-up index( NBI) are 82. 9% and 80. 0%,respectively.Normalized difference impervious surface index( NDISI),normalized difference built-up index( NDBI),and index-based built-up index( IBI) fail to enhance the spectral characteristics of impervious surface from complex image background,thereby yielding the lowest accuracy( < 75. 0%). Importantly,the eight impervious surface indexes fail to distinguish the spectral characteristics of impervious surface from large bare land areas and the average detection accuracy is only 71. 0%,hindering their applications in bare-land-rich areas.
引文
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[4] Song X P,Sexton J O,Huang C,et al. Characterizing the magnitude,timing and duration of urban growth from time series of Landsat-based estimates of impervious cover[J]. Remote Sensing of Environment,2016,175:1-13.
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[9] Xiao R,Ouyang Z,Zheng H,et al. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing,China[J]. Journal of Environmental Sciences,2007,19(2):250-256.
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[11] Liu C,Shao Z,Chen M,et al. MNDISI:A multi-source composition index for impervious surface area estimation at the individual city scale[J]. Remote Sensing Letters,2013,4(8):803-812.
[12]徐涵秋．一种快速提取不透水面的新型遥感指数[J]．武汉大学学报(信息科学版)，2008,33(11):1150-1153.Xu H Q. A new remote sensing index for fastly extracting impervious surface information[J]. Geomatics and Information Science of Wuhan University,2008,33(11):1150-1153.
[13] Yang L,Huang C,Homer C G,et al. An approach for mapping large-area impervious surfaces:Synergistic use of Landsat-7ETM+and high spatial resolution imagery[J]. Canadian Journal of Remote Sensing,2003,29(2):230-240.
[14] Cao X,Chen J,Imura H,et al. A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data[J]. Remote Sensing of Environment,2009,113(10):2205-2209.
[15] Pandey B,Joshi P K,Seto K C. Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data[J]. International Journal of Applied Earth Observation and Geoinformation,2013,23:49-61.
[16] Wu C S,Murray A T. Estimating impervious surface distribution by spectral mixture analysis[J]. Remote Sensing of Environment,2003,84(4):493-505.
[17] Yang J,He Y. Automated mapping of impervious surfaces in urban and suburban areas:Linear spectral unmixing of high spatial resolution imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2017,54:53-64.
[18] Deng C,Wu C. BCI:A biophysical composition index for remote sensing of urban environments[J]. Remote Sensing of Environment,2012,127:247-259.
[19] Kawamura M,Jayamana S,Tsujiko Y. Relation between social and environmental conditions in Colombo Sri Lanka and the urban index estimated by satellite remote sensing data[J]. The International Archives of Photogrammetry and Remote Sensing,1996,31:321-326.
[20] 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.
[21]查勇，倪绍祥，杨山．一种利用TM图像自动提取城镇用地信息的有效方法[J]．遥感学报，2003,7(1):37-40.Zha Y,Ni S X,Yang S. An effective approach to automatically extract urban land-use from TM imagery[J]. Journal of Remote Sensing,2003,7(1):37-40.
[22]陈洁丽，刘永学，李满春，等．基于归一化指数分析的居民地遥感信息提取[J]．测绘科学，2010,35(2):204-206.Chen J L,Liu Y X,Li M C,et al. Extracting remote sensing information of residential areas based on the analysis of normalized difference index[J]. Science of Surveying and Mapping,2010,35(2):204-206.
[23]田玉刚，徐韵，杨晓楠．一种提取城市多种不透水层的垂直不透水层指数[J]．测绘学报，2017,46(4):468-477.Tian Y G,Xu Y,Yang X N. Perpendicular impervious index for remote sensing of multiple impervious surface extraction in cities[J]. Acta Geodaetica et Cartographica Sinica,2017,46(4):468-477.
[24]吴宏安，蒋建军，张海龙，等．比值居民地指数在城镇信息提取中的应用[J]．南京师大学报(自然科学版)，2006,29(3):118-121.Wu H A,Jiang J J,Zhang H L,et al. Application of ratio residentarea index to retrieve urban residential areas based on Landsat TM data[J]. Journal of Nanjing Normal University(Natural Science Edition),2006,29(3):118-121.
[25] Ma Y,Kuang Y,Huang N. Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2010,12(2):110-118.
[26] Xu H. Modification of normalised difference water index(NDWI)to enhance open water features in remotely sensed imagery[J]. International Journal of Remote Sensing,2006,27(14):3025-3033.
[27] Huete A R. A soil-adjusted vegetation index(SAVI)[J]. Remote Sensing of Environment,1988,25(3):295-309.
[28] Loveland T R,Irons J R. Landsat 8:The plans,the reality,and the legacy[J]. Remote Sensing of Environment,2016,185:1-6.
[29] Song C,Woodcock C E,Seto K C,et al. Classification and change detection using Landsat TM data:When and how to correct atmospheric effects?[J]Remote Sensing of Environment,2001,75(2):230-244.
[30] He C,Shi P,Xie D,et al. Improving the normalized difference builtup index to map urban built-up areas using a semiautomatic segmentation approach[J]. Remote Sensing Letters,2010,1(4):213-221.
[31] Li H,Wang C,Zhong C,et al. Mapping urban bare land automatically from Landsat imagery with a simple index[J]. Remote Sensing,2017,9(3):249.
[32] Fawcett T. An introduction to ROC analysis[J]. Pattern Recognition Letters,2006,27(8):861-874.
[33] Schisterman E F,Perkins N J,Liu A,et al. Optimal cut-point and its corresponding Youden index to discriminate individuals using pooled blood samples[J]. Epidemiology,2005,16(1):73-81.
[34] Youden W J. Index for rating diagnostic tests[J]. Cancer,1950,3(1):32-35.
[35] Baig M H A,Zhang L,Shuai T,et al. Derivation of a tasseled cap transformation based on Landsat8 at-satellite reflectance[J]. Remote Sensing Letters,2014,5(5):423-431.
[36] Small C. Estimation of urban vegetation abundance by spectral mixture analysis[J]. International Journal of Remote Sensing,2001,22(7):1305-1334.
[37]杨晓楠，徐韵，田玉刚．一种用于城市信息提取的改进居民地指数[J]．国土资源遥感，2016,28(4):127-134. doi:10. 6046/gtzyyg. 2016. 04. 20.Yang X N,Xu Y,Tian Y G. A study of urban area extraction with the modified human settlement index[J]. Remote Sensing for Land and Resources,2016,28(4):127-134. doi:10. 6046/gtzyyg.2016. 04. 20.
[38]徐涵秋，王美雅．地表不透水面信息遥感的主要方法分析[J]．遥感学报，2016,20(5):1270-1289.Xu H Q,Wang M Y. Remote sensing-based retrieval of ground impervious surfaces[J]. Journal of Remote Sensing,2016,20(5):1270-1289.
[39] Herold M,Gardner M E,Roberts D A. Spectral resolution requirements for mapping urban areas[J]. IEEE Transactions on Geoscience and Remote Sensing,2003,41(9):1907-1919.
[40] Okujeni A,van der Linden S,Hostert P. Extending the vegetationimpervious-soil model using simulated EnMAP data and machine learning[J]. Remote Sensing of Environment,2015,158:69-80.
[2] Zhang L,Weng Q,Shao Z. An evaluation of monthly impervious surface dyna-mics by fusing Landsat and MODIS time series in the Pearl River Delta,China,from 2000 to 2015[J]. Remote Sensing of Environment,2017,201:99-114.
[3] Slonecker E T,Jennings D B,Garofalo D. Remote sensing of impervious surfaces:A review[J]. Remote Sensing Reviews,2001,20(3):227-255.
[4] Song X P,Sexton J O,Huang C,et al. Characterizing the magnitude,timing and duration of urban growth from time series of Landsat-based estimates of impervious cover[J]. Remote Sensing of Environment,2016,175:1-13.
[5] Weng Q. Remote sensing of impervious surfaces in the urban areas:Requirements,methods,and trends[J]. Remote Sensing of Environment,2012,117:34-49.
[6] Dams J,Dujardin J,Reggers R,et al. Mapping impervious surface change from remote sensing for hydrological modeling[J]. Journal of Hydrology,2013,485:84-95.
[7] Sofia G,Roder G,Dalla F,et al. Flood dynamics in urbanised landscapes:100 years of climate and humans’interaction[J]. Scientific Reports,2017,7:40527.
[8] Mathew A,Khandelwal S,Kaul N. Spatial and temporal variations of urban heat island effect and the effect of percentage impervious surface area and elevation on land surface temperature:Study of Chandigarh City,India[J]. Sustainable Cities and Society,2016,26:264-277.
[9] Xiao R,Ouyang Z,Zheng H,et al. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing,China[J]. Journal of Environmental Sciences,2007,19(2):250-256.
[10]徐涵秋．城市不透水面与相关城市生态要素关系的定量分析[J]．生态学报，2009,29(5):2456-2462.Xu H Q. Quantitative analysis on the relationship of urban impervious surface with other components of the urban ecosystem[J]. Acta Ecologica Sinica,2009,29(5):2456-2462.
[11] Liu C,Shao Z,Chen M,et al. MNDISI:A multi-source composition index for impervious surface area estimation at the individual city scale[J]. Remote Sensing Letters,2013,4(8):803-812.
[12]徐涵秋．一种快速提取不透水面的新型遥感指数[J]．武汉大学学报(信息科学版)，2008,33(11):1150-1153.Xu H Q. A new remote sensing index for fastly extracting impervious surface information[J]. Geomatics and Information Science of Wuhan University,2008,33(11):1150-1153.
[13] Yang L,Huang C,Homer C G,et al. An approach for mapping large-area impervious surfaces:Synergistic use of Landsat-7ETM+and high spatial resolution imagery[J]. Canadian Journal of Remote Sensing,2003,29(2):230-240.
[14] Cao X,Chen J,Imura H,et al. A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data[J]. Remote Sensing of Environment,2009,113(10):2205-2209.
[15] Pandey B,Joshi P K,Seto K C. Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data[J]. International Journal of Applied Earth Observation and Geoinformation,2013,23:49-61.
[16] Wu C S,Murray A T. Estimating impervious surface distribution by spectral mixture analysis[J]. Remote Sensing of Environment,2003,84(4):493-505.
[17] Yang J,He Y. Automated mapping of impervious surfaces in urban and suburban areas:Linear spectral unmixing of high spatial resolution imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2017,54:53-64.
[18] Deng C,Wu C. BCI:A biophysical composition index for remote sensing of urban environments[J]. Remote Sensing of Environment,2012,127:247-259.
[19] Kawamura M,Jayamana S,Tsujiko Y. Relation between social and environmental conditions in Colombo Sri Lanka and the urban index estimated by satellite remote sensing data[J]. The International Archives of Photogrammetry and Remote Sensing,1996,31:321-326.
[20] 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.
[21]查勇，倪绍祥，杨山．一种利用TM图像自动提取城镇用地信息的有效方法[J]．遥感学报，2003,7(1):37-40.Zha Y,Ni S X,Yang S. An effective approach to automatically extract urban land-use from TM imagery[J]. Journal of Remote Sensing,2003,7(1):37-40.
[22]陈洁丽，刘永学，李满春，等．基于归一化指数分析的居民地遥感信息提取[J]．测绘科学，2010,35(2):204-206.Chen J L,Liu Y X,Li M C,et al. Extracting remote sensing information of residential areas based on the analysis of normalized difference index[J]. Science of Surveying and Mapping,2010,35(2):204-206.
[23]田玉刚，徐韵，杨晓楠．一种提取城市多种不透水层的垂直不透水层指数[J]．测绘学报，2017,46(4):468-477.Tian Y G,Xu Y,Yang X N. Perpendicular impervious index for remote sensing of multiple impervious surface extraction in cities[J]. Acta Geodaetica et Cartographica Sinica,2017,46(4):468-477.
[24]吴宏安，蒋建军，张海龙，等．比值居民地指数在城镇信息提取中的应用[J]．南京师大学报(自然科学版)，2006,29(3):118-121.Wu H A,Jiang J J,Zhang H L,et al. Application of ratio residentarea index to retrieve urban residential areas based on Landsat TM data[J]. Journal of Nanjing Normal University(Natural Science Edition),2006,29(3):118-121.
[25] Ma Y,Kuang Y,Huang N. Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2010,12(2):110-118.
[26] Xu H. Modification of normalised difference water index(NDWI)to enhance open water features in remotely sensed imagery[J]. International Journal of Remote Sensing,2006,27(14):3025-3033.
[27] Huete A R. A soil-adjusted vegetation index(SAVI)[J]. Remote Sensing of Environment,1988,25(3):295-309.
[28] Loveland T R,Irons J R. Landsat 8:The plans,the reality,and the legacy[J]. Remote Sensing of Environment,2016,185:1-6.
[29] Song C,Woodcock C E,Seto K C,et al. Classification and change detection using Landsat TM data:When and how to correct atmospheric effects?[J]Remote Sensing of Environment,2001,75(2):230-244.
[30] He C,Shi P,Xie D,et al. Improving the normalized difference builtup index to map urban built-up areas using a semiautomatic segmentation approach[J]. Remote Sensing Letters,2010,1(4):213-221.
[31] Li H,Wang C,Zhong C,et al. Mapping urban bare land automatically from Landsat imagery with a simple index[J]. Remote Sensing,2017,9(3):249.
[32] Fawcett T. An introduction to ROC analysis[J]. Pattern Recognition Letters,2006,27(8):861-874.
[33] Schisterman E F,Perkins N J,Liu A,et al. Optimal cut-point and its corresponding Youden index to discriminate individuals using pooled blood samples[J]. Epidemiology,2005,16(1):73-81.
[34] Youden W J. Index for rating diagnostic tests[J]. Cancer,1950,3(1):32-35.
[35] Baig M H A,Zhang L,Shuai T,et al. Derivation of a tasseled cap transformation based on Landsat8 at-satellite reflectance[J]. Remote Sensing Letters,2014,5(5):423-431.
[36] Small C. Estimation of urban vegetation abundance by spectral mixture analysis[J]. International Journal of Remote Sensing,2001,22(7):1305-1334.
[37]杨晓楠，徐韵，田玉刚．一种用于城市信息提取的改进居民地指数[J]．国土资源遥感，2016,28(4):127-134. doi:10. 6046/gtzyyg. 2016. 04. 20.Yang X N,Xu Y,Tian Y G. A study of urban area extraction with the modified human settlement index[J]. Remote Sensing for Land and Resources,2016,28(4):127-134. doi:10. 6046/gtzyyg.2016. 04. 20.
[38]徐涵秋，王美雅．地表不透水面信息遥感的主要方法分析[J]．遥感学报，2016,20(5):1270-1289.Xu H Q,Wang M Y. Remote sensing-based retrieval of ground impervious surfaces[J]. Journal of Remote Sensing,2016,20(5):1270-1289.
[39] Herold M,Gardner M E,Roberts D A. Spectral resolution requirements for mapping urban areas[J]. IEEE Transactions on Geoscience and Remote Sensing,2003,41(9):1907-1919.
[40] Okujeni A,van der Linden S,Hostert P. Extending the vegetationimpervious-soil model using simulated EnMAP data and machine learning[J]. Remote Sensing of Environment,2015,158:69-80.
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