Near real-time SAR-based processing to support flood monitoring

被引:0
作者
Roberto Cossu
Elisabeth Schoepfer
Philippe Bally
Luigi Fusco
机构
[1] ESA-ESRIN,
[2] Directorate of Earth Observation Programmes,undefined
来源
Journal of Real-Time Image Processing | 2009年 / 4卷
关键词
Near real-time processing; Fast data access; Grid; SAR; Earth Observation for disaster management;
D O I
暂无
中图分类号
学科分类号
摘要
Earth Observation has proven to be a synoptic and objective source of information to derive crisis and damage maps. In case of flood events, often characterized by weather conditions which prevent the possibility of exploiting data acquired by optical sensors, synthetic aperture radar (SAR) sensors become the only space-born source of information due to their all-weather capability. In order to assure the delivery of damage maps as soon as possible after a disaster, the access and the exploitation of SAR data must be accelerated and simplified with respect to the current procedures. In this context, two issues needed to be addressed: fast access to large data archives, and provision of near real-time on demand processing services. This paper presents a near real-time SAR processing service to support the mapping of flooded areas. The service exploits Grid technology to manage large volumes of data and to provide the computational resources to cope with SAR processing demanding tasks. The algorithm for the implemented orthorectification of the final products is presented. The validation of the derived products shows a reliable accuracy for co-registration of half a pixel. The geolocation accuracy resulted below 100 m. The service makes a significant contribution to accelerating the access and exploitation of ESA SAR data.
引用
收藏
页码:205 / 218
页数:13
相关论文
共 50 条
  • [1] Near real-time SAR-based processing to support flood monitoring
    Cossu, Roberto
    Schoepfer, Elisabeth
    Bally, Philippe
    Fusco, Luigi
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2009, 4 (03) : 205 - 218
  • [2] FLOOD INUNDATION DEPTH ESTIMATION FROM SAR-BASED FLOOD EXTENT AND DEM
    Moya, Luis
    Mas, Erick
    Koshimura, Shunichi
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 337 - 340
  • [3] Near real-time monitoring of river ice in support of flood forecasting in eastern Canada: Towards the integration of earth observation technology in flood hazard mitigation
    Puestow, TM
    Randell, CJ
    Rollings, KW
    Khan, AA
    Picco, R
    IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET, 2004, : 2268 - 2271
  • [4] NEAR REAL-TIME SAR IMAGE FOCUSING ONBOARD SPACECRAFT
    Sugimoto, Yohei
    Ozawa, Satoru
    Inaba, Noriyasu
    IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 8038 - 8041
  • [5] Improving SAR-based flood detection in arid regions using texture features
    Ritushree, D. K.
    Garg, Shagun
    Dasgupta, Antara
    Martinis, Sandro
    Selvakumaran, Sivasakthy
    Motagh, Mahdi
    2023 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE FOR GEOANALYTICS AND REMOTE SENSING, MIGARS, 2023, : 175 - 178
  • [6] OPTIMIZED GLCM-BASED TEXTURE FEATURES FOR IMPROVED SAR-BASED FLOOD MAPPING
    Dasgupta, A.
    Grimaldi, S.
    Ramsankaran, R.
    Walker, J. P.
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 3258 - 3261
  • [7] An assessment of the 'Height Above Nearest Drainage' terrain descriptor for the thematic enhancement of automatic SAR-based flood monitoring services
    Chow, Candace
    Twele, Andre
    Martinis, Sandro
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XVIII, 2016, 9998
  • [8] Real-Time Processing of Multi-Channel SAR Data with GPUs
    Often, Matern
    Vlothuizen, Wouter
    Spreeuw, Hanno
    Varbanescu, Ana
    2016 13TH EUROPEAN RADAR CONFERENCE (EURAD), 2016, : 65 - 68
  • [9] Multi-DSPs SAR real-time signal processing system based on cPCI bus
    Yue-sheng, Tang
    Chang-yao, Zhang
    2007 1ST ASIAN AND PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR PROCEEDINGS, 2007, : 661 - 663
  • [10] Learning U-Net without forgetting for near real-time wildfire monitoring by the fusion of SAR and optical time series
    Zhang, Puzhao
    Ban, Yifang
    Nascetti, Andrea
    REMOTE SENSING OF ENVIRONMENT, 2021, 261