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利用多源 Sentinel-1 和 Sentinel-2 数据评估印度西孟加拉邦部分地区超级气旋 Amphan 对黄麻作物的附着物损害。

Assessing lodging damage of jute crop due to super cyclone Amphan using multi-temporal Sentinel-1 and Sentinel-2 data over parts of West Bengal, India.

机构信息

Agro-Ecosystem and Modeling Division, Agricultural Sciences and Applications Group, National Remote Sensing Centre, Indian Space Research Organization, Hyderabad, India.

出版信息

Environ Monit Assess. 2021 Jul 4;193(8):464. doi: 10.1007/s10661-021-09220-w.

Abstract

The present study is a maiden attempt to assess jute crop lodging due to super cyclone Amphan (20 May 2020) by synergistic use of Sentinel-2 (optical) and Sentinel-1 (SAR) data over part of West Bengal, India. Pre-event Sentinel-2 data (9 April, 14 May) along with the ground information were used to map the jute crop of the affected districts with accuracy of 85%. The cross-polarized backscatter (σ) of Sentinel-1 was found to be sensitive to the sudden change in the canopy structure due to lodging and partial flooding. [Formula: see text](σ - σ) indicating post-event damage was > 2.5 dB over the affected jute crop and [Formula: see text] (σ - σ) representing post-event recovery showed > 1.5 dB for recovered crop, depending on the crop vigor/height. Decision matrix was prepared combining [Formula: see text] and [Formula: see text] for NDVI-based crop vigor strata (low, medium, and high) to classify the area into affected, marginally affected and normal. Overall accuracy of the classified map was found to be 84.12% with kappa coefficient of 0.74. Nearly, 12.5% of the jute area, i.e., 38,119 ha was found to be either affected or marginally affected due to Amphan and distributed in the southern part of Murshidabad, north-eastern Nadia, northern 24 Paraganas (N), and middle region of Hooghli district. Geospatial map of block-wise affected jute area was prepared to facilitate informed decision making. The study demonstrated an operational methodology for assessing crop lodging due to natural calamities to support relief management and crop insurance.

摘要

本研究首次尝试利用 Sentinel-2(光学)和 Sentinel-1(SAR)数据协同评估 2020 年 5 月 20 日超级气旋“安攀”对黄麻作物倒伏的影响,研究区域位于印度西孟加拉邦的部分地区。利用灾前 Sentinel-2 数据(4 月 9 日、5 月 14 日)和地面信息,对受灾地区的黄麻作物进行了制图,其精度达到了 85%。Sentinel-1 的交叉极化后向散射(σ)被发现对因倒伏和部分淹没导致的冠层结构的突然变化敏感。(σ-σ)表示灾后的损伤,受灾黄麻作物的(σ-σ)值>2.5dB,而(σ-σ)表示灾后的恢复,对于恢复的作物,(σ-σ)值>1.5dB,这取决于作物的活力/高度。根据归一化植被指数(NDVI)为基础的作物活力分层(低、中、高),通过决策矩阵将(σ-σ)和(σ-σ)结合起来,对受灾、轻度受灾和正常区域进行分类。分类图的总精度为 84.12%,kappa 系数为 0.74。研究发现,由于“安攀”的影响,约 12.5%的黄麻作物(38119 公顷)受到了影响或轻度受灾,分布在默尔希达巴德南部、纳迪亚东北部、北 24 帕拉加纳(N)北部和豪利区中部。制作了受灾黄麻作物的区块空间地图,以便为决策提供信息。该研究展示了一种用于评估自然灾害导致的作物倒伏的操作方法,以支持救灾管理和作物保险。

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