Postflood damage evaluation using Landsat TM and ETM+ data integrated with DEM

Gianinetto, Marco; Villa, Paolo; Lechi, G. M.

doi:10.1109/tgrs.2005.859952

Cited by 65 publications

(36 citation statements)

References 17 publications

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“…Terrain information is thus useful in assisting water detection. There are many studies that have employed Digital Elevation Models (DEMs), digital representations of ground surface topography or relief, in detecting water bodies from remote sensing imagery [15][16][17]. More and more DEM data sources are becoming accessible, including Shuttle Radar Topographic Mission (SRTM) DEM with up to 1 arc-second resolution and TanDEM-X with 12 m resolution.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Huang

Nguyen

Zhang

et al. 2017

IJGI

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Abstract:The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from terrain effects when being used for mapping surface water, just as other SAR data do. Terrain indices derived from Digital Elevation Models (DEMs) are easy but effective approaches to reduce this kind of interference, considering the close relationship between surface water movement and topography. This study compares two popular terrain indices, namely the Multi-resolution Valley Bottom Flatness (MrVBF) and the Height Above Nearest Drainage (HAND), toward their performance on assisting surface water mapping using Sentinel-1 SAR data. Four study sites with different terrain characteristics were selected to cover a very wide range of topographic conditions. For two of these sites that are floodplain dominated, both normal and flooded scenarios were examined. MrVBF and HAND values for the whole study areas, as well as statistics of these values within water areas were compared. The sensitivity of applying different thresholds for MrVBF and HAND to mask out terrain effect was investigated by adopting quantity disagreement and allocation disagreement as the accuracy indicators. It was found that both indices help improve water mapping, reducing the total disagreement by as much as 1.6%. The HAND index performs slightly better in most of the study cases, with less sensitivity to thresholding. MrVBF classifies low-lying areas with more details, which sometimes makes it more effective in eliminating false water bodies in rugged terrain. It is therefore recommended to use HAND for large scale or global scale water mapping. However, for water detection in complex terrain areas, MrVBF also performs very well.

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Section: Introductionmentioning

confidence: 99%

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Huang

Nguyen

Zhang

et al. 2017

IJGI

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“…Under the effects of the tropical climate, there are many typhoons occurring in rainy seasons, resulting in a variety of long-lasting flood events along the Mekong river basin in history. The downside of flood disasters is that it resulted in serious negative effects on the psychology of local residents, food security, the environment, and the regional economy [2][3][4][5][6][7][8]. Flood events, on the contrary, play a vital role in agriculture by transporting and providing a huge amount of silt and fertilized sediment to feed the agricultural land in inundated areas [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Object-Based Flood Mapping and Affected Rice Field Estimation with Landsat 8 OLI and MODIS Data

Dao

Liou

2015

Remote Sensing

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Cambodia is one of the most flood-prone countries in Southeast Asia. It is geographically situated in the downstream region of the Mekong River with a lowland floodplain in the middle, surrounded by plateaus and high mountains. It usually experiences devastating floods induced by an overwhelming concentration of rainfall water over the Tonle Sap Lake's and Mekong River's banks during monsoon seasons. Flood damage assessment in the rice ecosystem plays an important role in this region as local residents rely heavily on agricultural production. This study introduced an object-based approach to flood mapping and affected rice field estimation in central Cambodia. In this approach, image segmentation processing was conducted with optimal scale parameter estimation based on the variation of objects' local variances. The inundated area was identified by using Landsat 8 images with an overall accuracy of higher than 95% compared to those derived from finer spatial resolution images. Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products were utilized to identify the paddy rice field based on seasonal inter-variation between vegetation and water index during the transplanting stage. The rice classification result was well correlated with the statistical data at a commune level (R 2 = 0.675). The flood mapping and affected rice estimation results are useful to provide local governments with valuable information for flooding mitigation and post-flooding compensation and restoration.

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“…Although remotely sensed data have been used to assess the damage from local to regional extents (e.g., [2,14,15,[17][18][19]), estimates of possible structure damage and monetary loss, which are two key components in the flood risk analysis, are still a challenge. Using high resolution optical satellite data and airborne LiDAR data, Gerl et al [20] derived a land cover classification and map of urban structure types, and then input them into their multi-parameter flood damage models including regression tree models.…”

Section: Risk Analysis and Information Disseminationmentioning

confidence: 99%

Advances in Remote Sensing of Flooding

Wang¹

2015

Water

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Abstract:With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR) coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS) can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS)-based urban flood vulnerability and risk maps.Keywords: flood; flood risk analyses and mitigation; geographic information system (GIS); mapping flood extent and assessing flood damage; remote sensing and geospatial technologies and datasets

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Postflood damage evaluation using Landsat TM and ETM+ data integrated with DEM

Cited by 65 publications

References 17 publications

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Object-Based Flood Mapping and Affected Rice Field Estimation with Landsat 8 OLI and MODIS Data

Advances in Remote Sensing of Flooding

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