K. Mandal, Tanushree Sarkar, Snehashis Alam, K. Dharanirajan, Shivaprasad Sharma S. V.
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引用次数: 1
摘要
毫不夸张地说,洪水是最常见和最具灾难性的自然灾害之一,对生态系统和人类生活产生了广泛的影响。世界银行的结论是,印度是世界上最容易发生洪水的国家之一。本研究的重点是利用Sentinel-1A (c波段)SAR数据识别印度马尔达地区的实时洪水危险区。使用ArcGIS、Erdas-Imagine和SNAP进行分析。这些淹没层与Malda区村庄的数据库相交,以确定洪水造成的破坏的全部程度,并最终确定实时洪水影响面积(2019年9月4日为380.19 km²,9月10日为338.87 km²)。有人指出,9月4日、766和9月10日,765个村庄因淹水而遭到严重破坏。此外,在该地区的15个街区中,Harischandrapur-II(75.67%)、Manikchak(68.60%)和Kaliachak-III(68.00%)遭受的洪水最多。最后,在马尔达区受洪水影响的村庄进行分层随机抽样,以估计受洪水影响的总体人口、家庭和受灾情况。最安全的街区是Chanchal-I、Gazole、Harischandrapur-I和Kaliachak-I,而最脆弱的街区是Harischandrapur-II、Kaliachak-III和Manikchak。根据洪水对儿童的影响,最脆弱的街区是Malda Old, English Bazar, Kaliyachak-III和Harishchandrapur-II。
Application of Sentinel-1A SAR Data for Village Level Flood Inundation Mapping in Malda District, West Bengal, India
It’s no exaggeration to say that floods are among the most common and catastrophic natural disasters, with widespread impacts on ecosystems and human lives. The World Bank has concluded that India is one of the most flood-prone countries in the world. This research has been focused on identification of real-time flood hazard area in the Malda district (India) using SAR data, Sentinel-1A (C-band). ArcGIS, Erdas-Imagine, and SNAP were used for this analysis. These inundation layers were intersected with the Malda district village’s database to determine the full extent of the devastation caused by the floods and finally determined the real-time flood-impacted area (380.19 km² on 4th September and 338.87 km² on 10th September, 2019). It was noted that on 4th September, 766 and 10th September 765 villages were seriously devastated owing to water. Moreover, among the 15 blocks of this district, Harischandrapur-II (75.67%), Manikchak (68.60%) and Kaliachak-III (68.00%) have experienced the most flooding. Finally, in order to estimate the overall population, households and affected by the floods, stratified random sampling was carried out in the flood-impacted villages of the Malda district. The safest blocks are Chanchal-I, Gazole, Harischandrapur-I and Kaliachak-I and the highly vulnerable blocks are Harischandrapur-II, Kaliachak-III and Manikchak. According to the flood influences on children, the most vulnerable blocks are Malda Old, English Bazar, Kaliyachak-III, and Harishchandrapur-II.