Exposure, hazard and risk mapping during a flood event using open source geospatial technology

被引:12
作者
Aggarwal, Arpit [1 ]
机构
[1] Risk Management Solut, Spatial Modeling Grp, Noida 201301, India
关键词
LANDSAT TM DATA; TIME-SERIES; FOREST; EXTENT; AREAS; INDEX; DELINEATION; DYNAMICS; IMAGERY;
D O I
10.1080/19475705.2015.1069408
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
After a flood event there is a need to delineate the hazard footprint as quickly as possible in order to assess the magnitude of losses and to plan for the relief operations. Delineation of such hazard footprint is generally hindered by the lack of geospatial data, technology and related software packages. This paper demonstrates the use of open source data and software packages which can be used to implement most recent technology available for flood hazard footprint delineation. This study utilizes open source software packages and web applications like Geographic Resource Analysis Support System, Quantum geographic information system and Google Earth to implement a complete process of hazard mapping using remotely sensed data which include pre-processing, mapping (both hazard and exposure) and accuracy assessment. In this study, Brisbane flood event of 2011 has been taken as a case study. For built-up extraction, the Landsat 7-band image has been transformed to a stack of 3-band image using vegetation, water and built-up indices. It has been observed by scattergram analysis that these transformations make vegetation, water and built-up classes more separable. Built-up area has been delineated using supervised maximum likelihood classification on the new 3-band image. For flood hazard mapping, thresholding of near-infrared band has been utilized along with the assistance of mid-infrared band to discriminate water from built-up classes. After delineating both exposure and hazard map, final risk map due to flood event has been generated to assess the urban exposure under the flood hazard impact.
引用
收藏
页码:1426 / 1441
页数:16
相关论文
共 31 条
[1]   Digital processing of a Landsat-TM time series for mapping and monitoring degraded areas caused by independent gold miners, Roraima State, Brazilian Amazon [J].
Almeida, R ;
Shimabukuro, YE .
REMOTE SENSING OF ENVIRONMENT, 2002, 79 (01) :42-50
[2]  
[Anonymous], 2005, J REMOTE SENSING
[3]  
Arino O., 1997, EARTH OBS Q, V56, P32
[4]  
Banumann PR, 1996, REMOTE SENSING CORE, V4
[5]   Characterizing 23 years (1972-95) of stand replacement disturbance in western Oregon forests with Landsat imagery [J].
Cohen, WB ;
Spies, TA ;
Alig, RJ ;
Oetter, DR ;
Maiersperger, TK ;
Fiorella, M .
ECOSYSTEMS, 2002, 5 (02) :122-137
[6]   A REVIEW OF ASSESSING THE ACCURACY OF CLASSIFICATIONS OF REMOTELY SENSED DATA [J].
CONGALTON, RG .
REMOTE SENSING OF ENVIRONMENT, 1991, 37 (01) :35-46
[7]  
Crichton D., 2001, IMPLICATIONS CLIMATE
[8]   Urban sustainability in the presence of flood and geological hazards: The development of a GIS-based vulnerability and risk assessment methodology [J].
Fedeski, Michael ;
Gwilliam, Julie .
LANDSCAPE AND URBAN PLANNING, 2007, 83 (01) :50-61
[9]  
Frazier PS, 2000, PHOTOGRAMM ENG REM S, V66, P1461
[10]   A generalized soil-adjusted vegetation index [J].
Gilabert, MA ;
González-Piqueras, J ;
García-Haro, FJ ;
Meliá, J .
REMOTE SENSING OF ENVIRONMENT, 2002, 82 (2-3) :303-310