城市化地区Landsat水体指数适用性分析

杨振华; 赵铜铁钢; 林鸿章; 陈晓宏

doi:10.16058/j.issn.1005-0930.2023.03.002

城市化地区Landsat水体指数适用性分析

杨振华^1,2,3,
赵铜铁钢^1,2,3, ,,
林鸿章^1,2,
陈晓宏^1,2

1. 南方海洋科学与工程广东省实验室(珠海), 广东珠海 519000;
2. 中山大学土木工程学院, 广东广州 510275;
3. 广东省华南地区水安全调控工程技术研究中心, 广东广州 510275

基金项目:

国家自然科学基金项目(51979295,51861125203,U1911204)

国家重点研发计划项目(2017YFC0405900)

广东省科技厅项目(2019ZT08G090)

详细信息

作者简介:
杨振华(1991-),男,博士研究生.E-mail:yangzhh63@mail2.sysu.edu.cn

通讯作者:
赵铜铁钢(1986-),男,教授.E-mail:zhaottg@mail.sysu.edu.cn

中图分类号: P237
计量
- 文章访问数: 232
- HTML全文浏览量: 27
- PDF下载量: 63
出版历程
- 收稿日期: 2022-01-13
- 修回日期: 2022-08-04
- 网络出版日期: 2023-05-03

Interpretation and Applicability Analysis of Landsat Water Index in Urbanized Areas

1. Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Zhuhai 519000, China;
2. School of Civil Engineering, SunYat-sen University, Guangzhou 510275, China;
3. Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Guangzhou 510275, China

摘要

摘要: 遥感水体指数是地表生态环境分析的重要基础,在大规模水体提取与水文监测中起关键作用.多种水体指数研究集中于大尺度、短历时、非城市化为主的区域,而对于城市化地区的水体指数适用性问题却一直困扰着城市水体的提取.针对常用水体指数(TCW、NDWI、MNDWI)和改进的新型水体指数(WI2015、AWEInsh、ANDWI、MBWI、WI2020),搜集深圳市1986~2020年逐月Landsat影像,以建筑阴影、亮建筑、暗建筑、滩涂噪声和山体阴影5种案例区为例,分析不同水体指数在城市地表覆被噪声区的解译能力.结果表明:(1)水体指数的生产者精度与用户精度呈负相关(Otsu阈值),TCW、NDWI、ANDWI、AWEInsh可有效过滤建筑类噪声和山体阴影,但无法识别细小河流水体,MNDWI、WI2015、MBWI、WI2020则相反;(2)光谱变换型和差值型水体指数考虑多波段的绝对值,可分离度较低,适用于高质量影像制图,比值型和逻辑运算型水体指数计算多波段的相对值,更适用于长序列监测;(3)多案例、多时相的案例区抽样验证方法有效突显出水体指数的解译能力和阈值适用性,城市地区NDWI适用性最强,非城市地区WI2020提取精度最高.上述研究为城市水文监测过程的水体指数选取、精度验证提供了一定的理论参考和实践依据.
- 水体指数 /
- 适用性分析 /
- Landsat影像 /
- 城市化 /
- 水文监测 /
- 可分离度 /
- 阈值
Abstract: Remote sensing water indices are important basis for surface eco-environment analysis,and are critical to large-scale waterbody interpretation and hydrological monitoring.A variety of water indices focus on large-scale,short-term,non-urbanized regions,while the extraction of urban water bodies has been plagued by the applicability of these indices.The study collected Landsat images from 1986 to 2020 in Shenzhen city,and adopted three commonly used water indices(TCW,NDWI,MNDWI) and five improved water indices(WI2015,AWEInsh,ANDWI,MBWI,WI2020).The interpretation ability of these water indices in the urban noise area were analyzed by taking five regions of building shadow,high albedo building,low albedo building,tidal-flat and mountain shadow as examples.The results show that:(1)Producer accuracy of water indices are negatively correlated with user accuracy(Otsu threshold),and TCW,NDWI,ANDWI,AWEInsh can effectively filter architectural noise and mountain shadow,but unrecognize small river water bodies,MNDWI,WI2015,MBWI,WI2020 are the opposite;(2)The spectral transformation type and difference type water indices consider the absolute value of multiple bands with low separability,and they are suitable for high-quality image mapping.The ratio type and logical operation type water indices calculate the relative value of multiple bands,and suitable for long-term monitoring;(3)The method of multi-temporal sampling verification in typical cases highlights the interpretation ability and threshold applicability of water indices,and the NDWI is most applicable in urbanized areas,while the WI2020 achieves the highest interpretation accuracy in non-urbanized areas.The above research provides a certain theoretical reference and practical basis for the selection of water index and accuracy verification for urban hydrological monitoring.
- water index /
- applicability analysis /
- Landsat image /
- urbanization /
- hydrological monitoring /
- separability /
- threshold

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参考文献(36)

[1]	刘荣娟,濮励杰,朱明,等.2000~2020年江苏省如东海岸线与滩涂围垦时空演变及影响机制[J].地理研究,2021,40(8):2367-2379 Liu Rongjuan,Pu Lijie,Zhu Ming,et al.Spatio-temporal evolution and influence mechanism of shorelines and tidal flat reclamation during 2000~2020 in Rudong,Jiangsu province[J].Geographical Research,2021,40(8),2367-2379
[2]	陈超,傅姣琪,随欣欣,等.面向灾后水体遥感信息提取的知识决策树构建及应用[J].遥感学报,2018,22(5):792-801 Chen Chao,Fu Jiaoqi,Sui Xinxin,et al.Construction and application of knowledge decision tree after a disaster for water body information extraction from remote sensing images[J].Journal of Remote Sensing,2018,22(5):792-801
[3]	Wang X, Xiao X,Zou Z,et al.Gainers and losers of surface and terrestrial water resources in China during 1989-2016[J].Nat Commun,2020,11(1):3471
[4]	高吉喜,王永财,侯鹏,等.近20年黄河流域陆表水域面积时空变化特征研究[J].水利学报,2020,51(9):1157-1164 Gao Jixi,Wang Yongcai,Hou Peng,et al.Temporal and spatial variation characteristics of land surface water area in the Yellow River basin in recent 20 years[J].Journal of Hydraulic Engineering,2020,51(9):1157-1164
[5]	张晓瑶,张潇,李冬花,等.城市土地利用变化对生态系统服务价值影响的多情景模拟——以深圳市为例[J].生态学报,42(6):2086-2097 Zhang Xiaoyao,Zhang Xiao,Li Donghua,et al.Multi-scenario simulation of the impact of urban land use change on ecosystem service value in Shenzhen[J].Acta Ecologica Sinica,2022,42(6):2086-2097
[6]	Mcfeeters S K.The use of the normalized difference water index(NDWI) in the delineation of open water features[J].International Journal of Remote Sensing,1996,17(7):1425-1432
[7]	陈文倩,丁建丽,李艳华,等.基于国产GF-1遥感影像的水体提取方法[J].资源科学,2015,37(6):1166-1172 Chen Wenqian,Ding Jianli,Li Yanhua,et al.Extraction of water information based on China-made GF-1 remote sense image[J].Resources Science,2015,37(6):1166-1172
[8]	汪金花,张永彬,孔改红.谱间关系法在水体特征提取中的应用[J].矿山测量,2004,(4):30-32 Wang Jinhua,Zhang Yongbin,Kong Gaihong,Application of spectral relationship method in water feature extraction[J].Mine Survey,2004,(4):30-32
[9]	王小标,谢顺平,都金康.水体指数构建及其在复杂环境下有效性研究[J].遥感学报,2018,22(2):360-372 Wang Xiaobiao,Xie Shunping,Du Jinkang.Water index formulation and its effectiveness research on the complicated surface water surroundings[J].Journal of Remote Sensing,2018,22(2):360-372
[10]	Feyisa G L,Meilby H,Fensholt R,et al.Automated water extraction index:A new technique for surface water mapping using Landsat imagery[J].Remote Sensing of Environment,2014,140:23-35
[11]	Xu Hanqiu.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
[12]	毕海芸,王思远,曾江源,等.基于TM影像的几种常用水体提取方法的比较和分析[J].遥感信息,2012,27(5):77-82 Bi Haiyun,Wang Siyuan,Zeng Jiangyuan,et al.Comparison and analysis of several common water extraction methods based on TM image[J].Remote Sensing Information,2012,27(5):77-82
[13]	翟涌光,张鑫,冀鸿兰,等.基于遥感影像的黄河内蒙古段冰-水分类研究[J].干旱区地理,2022,45(3):763-773 Zhai Yongguang,Zhang Xin,Ji Honglan,et al.Ice-water classification in Inner Mongolia reach of the Yellow River based on remote sensing images[J].Arid Land Geography,2022,45(3):763-773
[14]	杨存建,周成虎.TM影像的居民地信息提取方法研究[J].遥感学报,2000,4(2):146-150 Yang Cunjian,Zhou Chenghu.Extracting residential areas on the TM imagery[J].Journal of Remote Sensing,2000,4(2):146-150
[15]	杨树文,薛重生,刘涛,等.一种利用TM影像自动提取细小水体的方法[J].测绘学报,2010,39(6):611-617 Yang Shuwen,Xue Chongsheng,Liu Tao,et al.A method of small water information automatic extraction from TM remote sensing images[J].Acta Geodaetica et Cartographica Sinica,2010,39(6):611-617
[16]	徐涵秋.水体遥感指数研究进展[J].福州大学学报(自然科学版),2021,49(5):613-625 Xu Hanqiu.Development of remote sensing water indices:A review[J].Journal of Fuzhou University(Natural Science Edition),2021,49(5):613-625
[17]	Zou Z,Xiao X,Dong J,et al.Divergent trends of open-surface water body area in the contiguous United States from 1984 to 2016[J].Proc Natl Acad Sci USA,2018,115(15):3810-3815
[18]	Yang X C,Qin Q M,Yesou H,et al.Monthly estimation of the surface water extent in France at a 10-m resolution using Sentinel-2 data[J].Remote Sensing of Environment,2020,244
[19]	Crist E P.A TM tasseled cap equivalent transformation for reflectance factor data[J].Remote Sensing of Environment,1985,17(3):301-306
[20]	丁凤.基于新型水体指数(NWI)进行水体信息提取的实验研究[J].测绘科学,2009,34(4):155-157 Ding Feng.Study on information extraction of waterbody with a new water index(NWI)[J].Science of Surveying and Mapping,2009,34(4):155-157
[21]	沈占锋,夏列钢,李均力,等.采用高斯归一化水体指数实现遥感影像河流的精确提取[J].中国图象图形学报,2013,18(4):421-428 Shen Zhanfeng,Xia Liegang,Li Junli,et al.Automatic and high-precision extraction of rivers from remotely sensed images with Gaussian normalized water index[J].Journal of Image and Graphics,2013,18(4):421-428
[22]	Wang Shudong,Muhammad Hasan Ali Baig,Zhang Lifu,et al.A simple enhanced water index(EWI) for percent surface water estimation using Landsat data[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2015,8(1):90-97
[23]	Rad A M,Kreitler J,Sadegh M.Augmented normalized difference water index for improved surface water monitoring[J].Environmental Modelling & Software,2021,140
[24]	Fisher A,Flood N,Danaher T.Comparing Landsat water index methods for automated water classification in eastern Australia[J].Remote Sensing of Environment,2016,175:167-182
[25]	洪亮,黄雅君,杨昆,等.复杂环境下高分二号遥感影像的城市地表水体提取[J].遥感学报,2019,23(5):871-882 Hong Liang,Huang Yajun,Yang Kun,et al.Study on urban surface water extraction from heterogeneous environments using GF-2 remotely sensed images[J].Journal of Remote Sensing,2019,23(5):871-882
[26]	Nguyen U N T,Pham L T H,Dang T D.An automatic water detection approach using Landsat 8 OLI and Google Earth Engine cloud computing to map lakes and reservoirs in New Zealand[J].Environ Monit Assess,2019,191(4):235
[27]	张戈,夏建新,杜蕾,等.Landsat8和Sentinel-2A的水体指数比较与协同应用——以黑河流域典型区为例[J].应用基础与工程科学学报,2020,28(6):1361-1368 Zhang Ge,Xia Jianxin,Du Lei,et al.Comparison and collaborative application of water index based on Landsat8 and Sentinel-2A data:A case study in Heihe River Basin,Northwest China[J].Journal of Basic Science and Engineering,2020,28(6):1361-1368
[28]	李丹,吴保生,陈博伟,等.基于卫星遥感的水体信息提取研究进展与展望[J].清华大学学报(自然科学版),2020,60(2):147-161 Li Dan,Wu Baosheng,Chen Bowei,et al.Review of water body information extraction based on satellite remote sensing[J].Journal of Tsinghua University(Science and Technology),2020,60(2):147-161
[29]	Yang X C,Qin Q M,Grussenmeyer P,et al.Urban surface water body detection with suppressed built-up noise based on water indices from Sentinel-2 MSI imagery[J].Remote Sensing of Environment,2018,219:259-270
[30]	Otsu N.A threshold selection method from gray-level histograms[J].IEEE Transactions on Systems Man & Cybernetics,1979,9(1):62-66
[31]	Wang Jida,Blake A Walter,Yao Fangfang,et al.GeoDAR:Georeferenced global dam and reservoir dataset for bridging attributes and geolocations[J].Earth System Science Data,2021
[32]	Zhu Z,Woodcock C E.Object-based cloud and cloud shadow detection in Landsat imagery[J].Remote Sensing of Environment,2012,118:83-94
[33]	许晓聪,李冰洁,刘小平,等.全球2000年~2015年30m分辨率逐年土地覆盖制图[J].遥感学报,2021,25(9):1896-1916 Xu Xiaocong,Li Bingjie,Liu Xiaoping,et al.Mapping annual global land cover changes at a 30m resolution from 2000 to 2015[J].National Remote Sensing Bulletin,2021,25(9):1896-1916
[34]	郭兴杰,王寒梅,史玉金,等.近期长江口南槽河道滩槽冲刷及驱动因素分析[J].应用基础与工程科学学报,2021,29(4):785-796 Guo Xingjie,Wang Hanmei,Shi Yujin,et al.Analysis of the bottom evolution and the drive mechanisms in the south passage of yangtze estuary over the recent years[J].Journal of Basic Science and Engineering,2021,29(4):785-796
[35]	Cao Ruyin,Chen Yang,Chen Jin,et al.Thick cloud removal in Landsat images based on autoregression of Landsat time-series data[J].Remote Sensing of Environment,2020,249:112001
[36]	Sekertekin A.A survey on global thresholding methods for mapping open water body using Sentinel-2 satellite imagery and normalized difference water index[J].Archives of Computational Methods in Engineering,2020

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