Monitoring Post-Flood Recovery of Croplands Using the Integrated Sentinel-1/2 Imagery in the Yangtze-Huai River Basin

Miao Li,Ying Tu,Zhehao Ren,Tao Zhang,Bing Xu

doi:10.3390/rs14030690

Abstract

The increasingly frequent flooding imposes tremendous and long-lasting damages to lives and properties in impoverished rural areas. Rapid, accurate, and large-scale flood mapping is urgently needed for flood management, and to date has been successfully implemented benefiting from the advancement in remote sensing and cloud computing technology. Yet, the effects of agricultural emergency response to floods have been limitedly evaluated by satellite-based remote sensing, resulting in biased post-flood loss assessments. Addressing this challenge, this study presents a method for monitoring post-flood agricultural recovery using Sentinel-1/2 imagery, tested in three flood-affected main grain production areas, in the middle and lower Yangtze and Huai River, China. Our results indicated that 33~72% of the affected croplands were replanted and avoided total crop failures in summer 2020. Elevation, flood duration, crop rotation scheme, and flooding emergency management affect the post-flood recovery performance. The findings also demonstrate rapid intervention measures adjusted to local conditions could reduce the agricultural failure cost from flood disasters to a great extent. This study provides a new alternative for comprehensive disaster loss assessment in flood-prone agricultural regions, which will be insightful for worldwide flood control and management.

Highlights

Accepted: 28 January 2022The increasing extreme weather in the context of global climate change has posed severe threats to the function of living environments and the health of humans [1]
We proposed a method by combining synthetic aperture radar (SAR) and optical imaging to detect flood-affected cropland and monitor spontaneous agricultural recovery during and after the flooding disasters
For other flood-prone agricultural regions worldwide, annually flooding duration maps combined with natural conditions and socioeconomic backgrounds would help delineate potential areas to conduct timely agricultural recovery and schedule appropriate cropping patterns

Summary

Introduction

The increasing extreme weather in the context of global climate change has posed severe threats to the function of living environments and the health of humans [1]. Among these threats, floods have become the most common type accounting for 44% of natural disasters and affecting 1.6 billion people globally from 2000 to 2019 [2]. In addition to the increased proportion of the population exposed to floods [3], agricultural production activities tend to be another relatively vulnerable sector in response to damaging floods. The impact of flooding on crop yield varies dependent on flood characteristics (i.e., frequency, duration, depth, seasonality), crop types (tolerance of excess water and anaerobic soil conditions), and emergency activities [4].

Methods

Results

Discussion

Conclusion