Opis

• Tytuł:
  Flood Mapping Using the Sentinel-1 SAR Dataset and Application of the Change Detection Approach Technique (CDAT) to the Google Earth Engine In Sindh Province, Pakistan
• Twórca:
  ahmedyaseen_004, ahmed_004;
  Ateeq ur Rehman;
  Rasheed, Fahad;
  Miandad, Muhammad;
  Rehman, Ghani
• Opis:
  Flooding is a natural disaster characterised by overflowing water onto normally dry land, resulting in widespread damage and disruption to communities. Using Geographic Information Systems (GIS) and Remote Sensing (RS) technologies, accurate flood maps can be created. The Change Detection approach was employed using pre-processed Sentinel-1 SAR data. Pre-processing steps, including Thermal-Noise Removal, Radiometric Calibration, and Terrain Correction, were carried out using the Google Earth Engine (GEE) platform. This methodology allows for accurate and reliable analysis of land cover changes and provides valuable information for land management and decision-making processes in the region. The purpose of this study was to estimate the damage caused by flooding. The flood status between 18 August 2022 and 28 August 2022 was analysed. The estimated flood extent based on Sentinel-1 SAR data is almost 759,642 ha. The estimated number of people exposed is almost 663,797, estimated using the Global Human Settlement Layer (2015), with a resolution of about 250 m. Based on a MODIS land cover dataset with a resolution of 500 m, the estimated area of crops damaged is almost 415,450 ha and estimated urban area affected is almost 8435 ha.  
• Dostępność obiektu:
  Dostęp otwarty
• Prawa: https://creativecommons.org/licenses/by-nd/4.0 ;
  Prawa autorskie (c) 2023 Ahmed Yaseen Ghouri, Aleeza Khan, Haseeb Raoof, Dr.Muhammad Miandad, Dr. Ghani Rehman
• Data:
  2023.12.15
• Typ:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Język:
  angielski
• Źródło:
  Ecological Questions; Vol. 35 No. 2 (2024); 149-159;
  Ecological Questions; Tom 35 Nr 2 (2024); 149-159;
  1644-7298
• Format:
  application/pdf
• Wydawca:
  Uniwersytet Mikołaja Kopernika w Toruniu
• Relacja: https://apcz.umk.pl/EQ/article/view/44175/37123
• Temat i słowa kluczowe:
  Remote Sensing;
  Flood Risk;
  Indus River Valley;
  CDAT Algorithms;
  Flood Inundation Mapping;
  damage to local communities;
  endangered cultural heritage
• Identyfikator: https://apcz.umk.pl/EQ/article/view/44175
• Dostawca danych:
  Akademicka Platforma Czasopism
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