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Application of Remote Sensing to Flood and Drought Analysis, Monitoring...
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Application of Remote Sensing to Flood and Drought Analysis, Monitoring and Risk Management

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 15 April 2025 | Viewed by 5344

Special Issue Editor

Dr. Andrés Navarro

E-Mail Website
Guest Editor
Institute of Environmental Sciences (ICAM), University of Castilla-La Mancha (UCLM), 45071 Toledo, Spain
Interests: precipitation science; remote sensing of precipitation; extreme precipitation events
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Floods and droughts are two of the most devastating natural hazards affecting populations, property and infrastructure. The World Bank estimates that at least 1.65 billion people have been affected by floods and 1.43 billion by droughts in the last two decades. Economic losses and damages are also significant, averaging USD 178 billion per year. Climate change is expected to increase the frequency and intensity of these events, making it more important than ever to develop effective strategies for their monitoring and management.

Remote sensing (RS) has become an essential tool for assessing these hydro-climatic risks, providing timely and accurate information on their extent, severity, and impact over large areas and at regular intervals. This information can be used to support a variety of activities, including (1) climate monitoring; (2) early warning systems; (3) emergency response; (4) recovery efforts; and (5) risk assessment and management.

This Special Issue welcomes papers that deal primarily with RS applied to hydro-climate risks, but also use modeling and ground observations for illustrative purposes (e.g., validation). Manuscripts on applications of RS to the study of single events and regional analysis will also be welcome. Case studies and papers on early warning, monitoring, and disaster management are also welcome.

The scope of this Special Issue is very broad, and there are many other topics that could be relevant to this SI, including insurance, agriculture, infrastructure, and human health.

Dr. Andrés Navarro
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precipitation
  • floods
  • droughts
  • extreme precipitation events
  • natural hazards
  • hydrology

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Published Papers (3 papers)

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Research

29 pages, 13136 KiB  
Article
Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco
by Imane Serbouti, Jérôme Chenal, Biswajeet Pradhan, El Bachir Diop, Rida Azmi, Seyid Abdellahi Ebnou Abdem, Meriem Adraoui, Mohammed Hlal and Mariem Bounabi
Remote Sens. 2024, 16(18), 3398; https://doi.org/10.3390/rs16183398 - 12 Sep 2024
Viewed by 1473
Abstract
Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco’s Oum Er-Rbia (OER) watershed from 2002 to 2022, using the [...] Read more.
Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco’s Oum Er-Rbia (OER) watershed from 2002 to 2022, using the newly developed Watershed Integrated Multi-Drought Index (WIMDI), through Google Earth Engine (GEE). WIMDI integrates several drought indices, including SMCI, ESI, VCI, TVDI, SWI, PCI, and SVI, via a localized weighted averaging model (LOWA). Statistical validation against various drought-type indices including SPI, SDI, SEDI, and SMCI showed WIMDI’s strong correlations (r-values up to 0.805) and lower RMSE, indicating superior accuracy. Spatiotemporal validation against aggregated drought indices such as VHI, VDSI, and SDCI, along with time-series analysis, confirmed WIMDI’s robustness in capturing drought variability across the OER watershed. These results highlight WIMDI’s potential as a reliable tool for effective drought monitoring and management across diverse ecosystems and climates. Full article
(This article belongs to the Special Issue Application of Remote Sensing to Flood and Drought Analysis, Monitoring and Risk Management)
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21 pages, 10773 KiB  
Article
A Synthetic Aperture Radar-Based Robust Satellite Technique (RST) for Timely Mapping of Floods
by Meriam Lahsaini, Felice Albano, Raffaele Albano, Arianna Mazzariello and Teodosio Lacava
Remote Sens. 2024, 16(12), 2193; https://doi.org/10.3390/rs16122193 - 17 Jun 2024
Cited by 3 | Viewed by 1405
Abstract
Satellite data have been widely utilized for flood detection and mapping tasks, and in recent years, there has been a growing interest in using Synthetic Aperture Radar (SAR) data due to the increased availability of recent missions with enhanced temporal resolution. This capability, [...] Read more.
Satellite data have been widely utilized for flood detection and mapping tasks, and in recent years, there has been a growing interest in using Synthetic Aperture Radar (SAR) data due to the increased availability of recent missions with enhanced temporal resolution. This capability, when combined with the inherent advantages of SAR technology over optical sensors, such as spatial resolution and independence from weather conditions, allows for timely and accurate information on flood event dynamics. In this study, we present an innovative automated approach, SAR-RST-FLOOD, for mapping flooded areas using SAR data. Based on a multi-temporal analysis of Sentinel 1 data, such an approach would allow for robust and automatic identification of flooded areas. To assess its reliability and accuracy, we analyzed five case studies in areas where floods caused significant damage. Performance metrics, such as overall (OA), user (UA), and producer (PA) accuracy, as well as the Kappa index (K), were used to evaluate the methodology by considering several reference flood maps. The results demonstrate a user accuracy exceeding 0.78 for each test map when compared to the observed flood data. Additionally, the overall accuracy values surpassed 0.96, and the kappa index values exceeded 0.78 when compared to the mapping processes from observed data or other reference datasets from the Copernicus Emergency Management System. Considering these results and the fact that the proposed approach has been implemented within the Google Earth Engine framework, its potential for global-scale applications is evident. Full article
(This article belongs to the Special Issue Application of Remote Sensing to Flood and Drought Analysis, Monitoring and Risk Management)
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27 pages, 6482 KiB  
Article
Response of Ecosystem Carbon–Water Fluxes to Extreme Drought in West Asia
by Karam Alsafadi, Bashar Bashir, Safwan Mohammed, Hazem Ghassan Abdo, Ali Mokhtar, Abdullah Alsalman and Wenzhi Cao
Remote Sens. 2024, 16(7), 1179; https://doi.org/10.3390/rs16071179 - 28 Mar 2024
Cited by 2 | Viewed by 1762
Abstract
Global warming has resulted in increases in the intensity, frequency, and duration of drought in most land areas at the regional and global scales. Nevertheless, comprehensive understanding of how water use efficiency (WUE), gross primary production (GPP), and actual evapotranspiration (AET)-induced water losses [...] Read more.
Global warming has resulted in increases in the intensity, frequency, and duration of drought in most land areas at the regional and global scales. Nevertheless, comprehensive understanding of how water use efficiency (WUE), gross primary production (GPP), and actual evapotranspiration (AET)-induced water losses respond to exceptional drought and whether the responses are influenced by drought severity (DS) is still limited. Herein, we assess the fluctuation in the standardized precipitation evapotranspiration index (SPEI) over the Middle East from 1982 to 2017 to detect the drought events and further examine standardized anomalies of GPP, WUE, and AET responses to multiyear exceptional droughts, which are separated into five groups designed to characterize the severity of extreme drought. The intensification of the five drought events (based on its DS) increased the WUE, decreased the GPP and AET from D5 to D1, where both the positive and negative variance among the DS group was statistically significant. The results showed that the positive values of standardized WUE with the corresponding values of the negative GPP and AET were dominant (44.3% of the study area), where the AET values decreased more than the GPP, and the WUE fluctuation in this region is mostly controlled by physical processes, i.e., evaporation. Drought’s consequences on ecosystem carbon-water interactions ranged significantly among eco-system types due to the unique hydrothermal conditions of each biome. Our study indicates that forthcoming droughts, along with heightened climate variability, pose increased risks to semi-arid and sub-humid ecosystems, potentially leading to biome restructuring, starting with low-productivity, water-sensitive grasslands. Our assessment of WUE enhances understanding of water-carbon cycle linkages and aids in projecting ecosystem responses to climate change. Full article
(This article belongs to the Special Issue Application of Remote Sensing to Flood and Drought Analysis, Monitoring and Risk Management)
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