Remote Sensing, natural hazards and the contribution of ESA Sentinels missions

Poursanidis, Dimitris; Chrysoulakis, Nektarios

doi:10.1016/j.rsase.2017.02.001

Cited by 63 publications

(44 citation statements)

References 147 publications

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“…Moreover, it is spatially restricted over sensitive areas and the frequent updates of such datasets are very costly. SRS-based methods, such as that of the present work, can provide an automated method to extract high-resolution DSMs across the globe with a relatively low cost, high accuracy, and frequent temporal cover, whereas the spatial coverage is quite large and there are no restrictions on the spatial coverage [20]. The reference DSM has been produced by using stereo airborne cameras with a simultaneous image caption at elevations lower than that of the Pleiades 1B satellite.…”

Section: Resultsmentioning

confidence: 99%

Validation of Pleiades Tri-Stereo DSM in Urban Areas

Panagiotakis

Chrysoulakis

Charalampopoulou

et al. 2018

IJGI

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Abstract:We present an accurate digital surface model (DSM) derived from high-resolution Pleiades-1B 0.5 m panchromatic tri-stereo images, covering an area of 400 km 2 over the Athens Metropolitan Area. Remote sensing and photogrammetry tools were applied, resulting in a 1 m × 1 m posting DSM over the study area. The accuracy of the produced DSM was evaluated against measured elevations by a differential Global Positioning System (d-GPS) and a reference DSM provided by the National Cadaster and Mapping Agency S.A. Different combinations of stereo and tri-stereo images were used and tested on the quality of the produced DSM. Results revealed that the DSM produced by the tri-stereo analysis has a root mean square error (RMSE) of 1.17 m in elevation, which lies within the best reported in the literature. On the other hand, DSMs derived by standard analysis of stereo-pairs from the same sensor were found to perform worse. Line profile data showed similar patterns between the reference and produced DSM. Pleiades tri-stereo high-quality DSM products have the necessary accuracy to support applications in the domains of urban planning, including climate change mitigation and adaptation, hydrological modelling, and natural hazards, being an important input for simulation models and morphological analysis at local scales.

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Section: Resultsmentioning

confidence: 99%

Validation of Pleiades Tri-Stereo DSM in Urban Areas

Panagiotakis

Chrysoulakis

Charalampopoulou

et al. 2018

IJGI

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“…The fusion of the Copernicus Sentinel-1 (also available in GEE) and the Sentinel-2 open and free image archive for the development of 10-m topobathymetric digital elevation models (DEMs)-seamless merged elevation products of terrestrial and underwater topography [45] useful for numerous Earth science applications including mapping and modelling of inundation, sediment transport, sea-level rise, and storm surge [46].…”

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confidence: 99%

Estimating Satellite-Derived Bathymetry (SDB) with the Google Earth Engine and Sentinel-2

et al. 2018

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Bathymetry mapping forms the basis of understanding physical, economic, and ecological processes in the vastly biodiverse coastal fringes of our planet which are subjected to constant anthropogenic pressure. Here, we pair recent advances in cloud computing using the geospatial platform of the Google Earth Engine (GEE) with optical remote sensing technology using the open Sentinel-2 archive, obtaining low-cost in situ collected data to develop an empirical preprocessing workflow for estimating satellite-derived bathymetry (SDB). The workflow implements widely used and well-established algorithms, including cloud, atmospheric, and sun glint corrections, image composition and radiometric normalisation to address intra-and inter-image interferences before training, and validation of four SDB algorithms in three sites of the Aegean Sea in the Eastern Mediterranean. Best accuracy values for training and validation were R 2 = 0.79, RMSE = 1.39 m, and R 2 = 0.9, RMSE = 1.67 m, respectively. The increased accuracy highlights the importance of the radiometric normalisation given spatially independent calibration and validation datasets. Spatial error maps reveal over-prediction over low-reflectance and very shallow seabeds, and under-prediction over high-reflectance (<6 m) and optically deep bottoms (>17 m). We provide access to the developed code, allowing users to map bathymetry by customising the time range based on the field data acquisition dates and the optical conditions of their study area.

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“…A utilização de Sensoriamento Remoto surge como uma excelente ferramenta no estudo e análise de desastres ambientais, uma vez que o processo de mensuração e de observação não depende de contato direto com o objeto de estudo (POURSANIDIS; CHRYSOULAKIS, 2017). O constante desenvolvimento das pesquisas espaciais tem resultado no lançamento de uma grande variedade de satélites, os quais são capazes proporcionar imagens em diferentes resoluções espaciais, temporais, espectrais e radiométricas.…”

Section: Introductionunclassified

Análise de técnicas de detecção de mudança para mapeamento de desastres com uso de dados de sensoriamento remoto

Oliveira

Negri

Santos

2020

Rev. Bras. Cartogr.

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Nos anos recentes, o Brasil tem sofrido uma série de desastres ambientais, que por sua vez afetam a sociedade, economia e biodiversidade em níveis imensuráveis. O uso de dados obtidos por sensoriamento remoto surge como fonte de informação indispensável na realização de análises sobre os impactos causados pelos desastres ambientais. Dentre diferentes métodos propostos na literatura para o processamento e extração de informação das imagens de sensoriamento remoto, encontram-se as técnicas de detecção de mudança. De modo geral, tais técnicas permitem a obtenção de mapas capazes de expressar as alterações ocorridas na cobertura do solo de uma dada região e período. O uso destas técnicas aponta potencial quanto a geração de insumos para análises relacionadas aos impactos causados por desastres ambientais. Neste contexto, este estudo apresenta a aplicação e comparação entre diferentes métodos de detecção de mudança sobre áreas afetadas por recentes desastres ambientais no Brasil. Os métodos abordados neste trabalho são restritos ao conceito não supervisionado, os quais não exigem informações a priori sobre os dados. Foram realizadas três aplicações, relacionadas aos colapsos ocorridos nas barragens de Mariana e Brumadinho, no estado de Minas Gerais, e queimadas no estado do Mato Grosso, com uso de dados obtidos pelos satélites Landsat-8 e Sentinel-1 e 2. Os resultados obtidos evidenciam que tais técnicas, desde que parametrizadas adequadamente e fazendo uso de atributos favoráveis, são capazes de realizar mapeamentos sobre alterações derivadas dos eventos de desastres.

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Remote Sensing, natural hazards and the contribution of ESA Sentinels missions

Cited by 63 publications

References 147 publications

Validation of Pleiades Tri-Stereo DSM in Urban Areas

Validation of Pleiades Tri-Stereo DSM in Urban Areas

Estimating Satellite-Derived Bathymetry (SDB) with the Google Earth Engine and Sentinel-2

Análise de técnicas de detecção de mudança para mapeamento de desastres com uso de dados de sensoriamento remoto

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