remotesensing-logo

Journal Browser

Journal Browser

Special Issue "Remote Sensing for Drought Monitoring and Forecasting"

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

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 4796

Special Issue Editors

Dr. Massimiliano Pasqui
E-Mail Website
Guest Editor
Institute for the Bioeconomy, National Research Council, Italy
Interests: atmospheric modelling; seasonal forecast; drought monitoring and early warning systems; climate change/variability at national and international levels; food security
Dr. Ramona Magno
E-Mail Website
Guest Editor
Institute for the Bioeconomy, National Research Council, Italy
Interests: drought monitoring and early warning systems; climate change/variability at national and international levels; forest management; land use/land cover characterization; desertification
Dr. Luca Brocca
grade E-Mail Website
Guest Editor
National Research Council, Research Institute for Geo-Hydrological Protection, via Madonna Alta 126, 06128 Perugia, Italy
Interests: soil moisture; rainfall; river discharge; flood; landslide; drought; water resources management; agriculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The drought is a creeping and complex phenomenon with different types of impacts. Drought dynamic reveals a time gap between the onset phase of an event and the management phase of the consequent emergency, but often, this gap is too wide to reduce negative impacts effectively. Furthermore, drought information is frequently scattered and not integrated enough to support diverse users’ real needs. 

The reliable early identification of drought episodes, along with their evolution scenarios, would significantly increase the ability to deal with and manage periods of agro-ecosystem stress or water scarcity. The nexus among local knowledge elements, scientific data, and the use of indicators related to them could significantly improve the identification of the human societal negative consequences of drought. Furthermore, climate change places our society under increasing pressure by forcing humans to adapt. Thus, there is an urgent need to increase preparedness through proactive solutions providing timely and simple information to a broader audience. Such a growing demand for knowledge of drought monitoring and prediction will contribute to mitigating and managing emerging social negative impacts and conflicts during periods of rainfall deficits by increasing preparedness, stimulating resilience, and improving adaptation options. 

The recent development of satellite-based remote sensing techniques and in situ sensors has increased our ability to observe the state of agro-ecosystems on Earth. Thus, by increasing our level of understanding the evolution of drought and by identifying risks and negative impacts earlier, we could now better contribute to improving risk mitigation processes in agro-ecosystems, food production, and food security systems worldwide.

This Special Issue of Remote Sensing addresses papers that propose innovative strategies for monitoring and forecasting drought triggering and development mechanisms that will break down barriers for users with different levels of backgrounds in managing water resources during prolonged periods of rainfall shortage. Cross-cutting approaches that bridge environmental/geophysical drought features with socioeconomic impacts and options are also welcome. Areas of special interest include but not are limited to:

  • Use of numerical and empirical modeling for the seasonal and climatic prediction of drought;
  • Innovative numerical techniques to integrate in-situ and satellite-based remote sensed data to improve social resilience to drought;
  • Innovative methods to analyze the spatiotemporal structures of drought and to identify internal and external forcing in drought onset and development;
  • Effective and authoritative approaches to communicate and visualize drought conditions;
  • Data mining and GIS applications for drought monitoring, forecasting, and visualizing;
  • Regional, continental, and global scale case studies of early warning systems developed in recent years as integrated drought climate services;
  • Approaches for measuring uncertainty in drought monitoring and prediction.

Dr. Massimiliano Pasqui
Dr. Ramona Magno
Dr. Luca Brocca
Guest Editors

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 2500 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

  • Vegetation monitoring
  • Drought management
  • Agriculture and Food security
  • Climate change adaptation options
  • Socio-economic impacts
  • Meteorological, agricultural and hydrological drought indices
  • Prediction uncertainty
  • Predictability
  • Soil moisture
  • Evapotranspiration
  • Water scarcity

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Drought Assessment on Vegetation in the Loess Plateau Using a Phenology-Based Vegetation Condition Index
Remote Sens. 2022, 14(13), 3043; https://doi.org/10.3390/rs14133043 - 24 Jun 2022
Viewed by 272
Abstract
Frequent droughts induced by climate warming have caused increasing impacts on the vegetation of the Loess Plateau (LP). However, the effects of drought on vegetation are highly dependent on when the drought occurs and how long it lasts during the growing season. Unfortunately, [...] Read more.
Frequent droughts induced by climate warming have caused increasing impacts on the vegetation of the Loess Plateau (LP). However, the effects of drought on vegetation are highly dependent on when the drought occurs and how long it lasts during the growing season. Unfortunately, most of the existing drought indices ignore the differences in the drought effects on different vegetation growth stages. In this study, we first established a phenology-based vegetation condition index, namely weighted vegetation condition index (WVCI), which accounts for the differences in vegetation sensitivity to drought by assigning specific weights to different phenological stages of vegetation. Then, we used the WVCI to reveal the temporal and spatial variations in vegetative drought from 2001 to 2019 over the LP from the aspects of drought frequency, trend and relative deviation. The results showed that (1) the LP experienced frequent droughts during the study period, but mainly mild and moderate droughts. The drought frequencies decreased from southeast to northwest, and extreme droughts rarely occurred in mountainous areas and plains. (2) The droughts in most areas of the LP tended to ease, and only a few areas in the Hetao Plain, Ningxia Plain and Fenwei Plain showed an increasing trend of drought. (3) After 2012, the departure percentage of WVCI in most areas of the LP was positive, indicating above-average vegetation conditions. (4) Compared with the well-established vegetation condition index, the WVCI proved to have the ability to monitor and assess vegetative drought on an annual scale in the LP. As a result, our research could help develop and implement drought-resistance and disaster-prevention measures on the LP. Full article
(This article belongs to the Special Issue Remote Sensing for Drought Monitoring and Forecasting)
Show Figures

Graphical abstract

Article
Sentinel-1 SAR Backscatter Response to Agricultural Drought in The Netherlands
Remote Sens. 2022, 14(10), 2435; https://doi.org/10.3390/rs14102435 - 19 May 2022
Viewed by 570
Abstract
Drought is a major natural hazard that impacts agriculture, the environment, and socio-economic conditions. In 2018 and 2019, Europe experienced a severe drought due to below average precipitation and high temperatures. Drought stress affects the moisture content and structure of agricultural crops and [...] Read more.
Drought is a major natural hazard that impacts agriculture, the environment, and socio-economic conditions. In 2018 and 2019, Europe experienced a severe drought due to below average precipitation and high temperatures. Drought stress affects the moisture content and structure of agricultural crops and can result in lower yields. Synthetic Aperture Radar (SAR) observations are sensitive to the dielectric and geometric characteristics of crops and underlying soils. This study uses data from ESA’s Sentinel-1 SAR satellite to investigate the influence of drought stress on major arable crops of the Netherlands, its regional variability and the impact of water management decisions on crop development. Sentinel-1 VV, VH and VH/VV backscatter data are used to quantify the variability in the spatio-temporal dynamics of agricultural crop parcels in response to drought. Results show that VV and VH backscatter values are 1 to 2 dB lower for crop parcels during the 2018 drought compared to values in 2017. In addition, the growth season indicated by the cross-ratio (CR, VH/VV) for maize and onion is shorter during the drought year. Differences due to irrigation restrictions are observed in backscatter response from maize parcels. Lower CR values in 2019 indicate the impact of drought on the start of the growing season. Results demonstrate that Sentinel-1 can detect changes in the seasonal cycle of arable crops in response to agricultural drought. Full article
(This article belongs to the Special Issue Remote Sensing for Drought Monitoring and Forecasting)
Show Figures

Figure 1

Article
Spatial Multi-Criterion Decision Making (SMDM) Drought Assessment and Sustainability over East Africa from 1982 to 2015
Remote Sens. 2021, 13(24), 5067; https://doi.org/10.3390/rs13245067 - 14 Dec 2021
Viewed by 697
Abstract
Droughts are ranked among the most devastating agricultural disasters that occur naturally in the world. East Africa is the most vulnerable and drought-prone region worldwide. In this study, four drought indices were used as input variables for drought assessment from 1982 to 2015. [...] Read more.
Droughts are ranked among the most devastating agricultural disasters that occur naturally in the world. East Africa is the most vulnerable and drought-prone region worldwide. In this study, four drought indices were used as input variables for drought assessment from 1982 to 2015. This work applied the SMDM algorithm to the integrated approach of OLR and Hurst exponent. The Detrended Fluctuation Analysis (DFA) and Ordinary Least Square (OLR) were merged to compute the trend and persistence (Hurst exponent) of the drought indices. Result indicates that the OLR at time scale 1, 6, and 12 shows a similar distribution with positive (negative) trends scattered in the Northwest (Northeast and Southern) parts of the study area which differs with the OLR aggregated at a 3-month time scale. The percentage pixel distribution for OLR-1, OLR-3, OLR-6, and OLR-12 is 18.2 (81.8), 72.5 (27.5), 32.9 (67.1), and 36.9 (63.1) for increasing (decreasing) trends respectively. Additionally, results indicate that DFA-1 is highly persistent with few random pixels scattered around Ethiopia, South Sudan and Tanzania, with percentage pixels as 88.7, 11.3 and 0.1 representing h > 0.5, h = 0.5, and h < 0.5, respectively. DFA-6 shows high (low) pixels representing h > 0.5 (h > 1), respectively. Meanwhile, for DFA-3 and DFA-12, the distribution shows persistence and a random walk, respectively. Drought conditions may eventually persist, reverse or vary drastically in an unpredictable manner depending on the driving forces. Overall, the drought risk map at 1-, 3-, and 6-month aggregates has shown severe degradation in Southern Kenya and Tanzania while noticeable improvements are seen in western Ethiopia and South Sudan. Full article
(This article belongs to the Special Issue Remote Sensing for Drought Monitoring and Forecasting)
Show Figures

Figure 1

Article
Drought Assessment in the São Francisco River Basin Using Satellite-Based and Ground-Based Indices
Remote Sens. 2021, 13(19), 3921; https://doi.org/10.3390/rs13193921 - 30 Sep 2021
Cited by 4 | Viewed by 944
Abstract
The São Francisco River Basin (SFRB) plays a key role for the agricultural and hydropower sectors in Northeast Brazil (NEB). Historically, in the low part of the SFRB, people have to cope with strong periods of drought. However, there are incipient signs of [...] Read more.
The São Francisco River Basin (SFRB) plays a key role for the agricultural and hydropower sectors in Northeast Brazil (NEB). Historically, in the low part of the SFRB, people have to cope with strong periods of drought. However, there are incipient signs of increasing drought conditions in the upper and middle parts of the SFRB, where its main reservoirs (i.e., Três Marias, Sobradinho, and Luiz Gonzaga) and croplands are located. Therefore, the assessment of the impacts of extreme drought events in the SFRB is of vital importance to develop appropriate drought mitigation strategies. These events are characterized by widespread and persistent dry conditions with long-term impacts on water resources and rain-fed agriculture. The purpose of this study is to provide a comprehensive evaluation of extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and soil moisture over different time windows between 1980 and 2020. The Standardized Precipitation-Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) at 3- and 12-month time scales derived from ground data were used as benchmark drought indices. The self-calibrating Palmer Drought Severity Index (scPDSI) and the Soil Moisture and Ocean Salinity-based Soil Water Deficit Index (SWDIS) were used to assess the agricultural drought. The Water Storage Deficit Index (WSDI) and the Groundwater Drought Index (GGDI) both derived from the Gravity Recovery and Climate Experiment (GRACE) were used to assess the hydrological drought. The SWDISa and WSDI showed the best performance in assessing agricultural and hydrological droughts across the whole SFRB. A drying trend at an annual time scale in the middle and south regions of the SFRB was evidenced. An expansion of the area under drought conditions was observed only during the southern hemisphere winter months (i.e., JJA). A marked depletion of groundwater levels concurrent with an increase in soil moisture content was observed during the most severe drought conditions, indicating an intensification of groundwater abstraction for irrigation. These results could be useful to guide social, economic, and water resource policy decision-making processes. Full article
(This article belongs to the Special Issue Remote Sensing for Drought Monitoring and Forecasting)
Show Figures

Graphical abstract

Article
Drought Monitoring over Yellow River Basin from 2003–2019 Using Reconstructed MODIS Land Surface Temperature in Google Earth Engine
Remote Sens. 2021, 13(18), 3748; https://doi.org/10.3390/rs13183748 - 18 Sep 2021
Cited by 21 | Viewed by 1310
Abstract
Drought is one of the most complex and least-understood environmental disasters that can trigger environmental, societal, and economic problems. To accurately assess the drought conditions in the Yellow River Basin, this study reconstructed the Land Surface Temperature (LST) using the Annual Temperature Cycle [...] Read more.
Drought is one of the most complex and least-understood environmental disasters that can trigger environmental, societal, and economic problems. To accurately assess the drought conditions in the Yellow River Basin, this study reconstructed the Land Surface Temperature (LST) using the Annual Temperature Cycle (ATC) model and the Normalized Difference Vegetation Index (NDVI). The Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature-Vegetation Drought Index (TVDI), which are four typical remote sensing drought indices, were calculated. Then, the air temperature, precipitation, and soil moisture data were used to evaluate the applicability of each drought index to different land types. Finally, this study characterized the spatial and temporal patterns of drought in the Yellow River Basin from 2003 to 2019. The results show that: (1) Using the LST reconstructed by the ATC model to calculate the drought index can effectively improve the accuracy of drought monitoring. In most areas, the reconstructed TCI, VHI, and TVDI are more reliable for monitoring drought conditions than the unreconstructed VCI. (2) The four drought indices (TCI, VCI, VH, TVDI) represent the same temporal and spatial patterns throughout the study area. However, in some small areas, the temporal and spatial patterns represented by different drought indices are different. (3) In the Yellow River Basin, the drought level is highest in the northwest and lowest in the southwest and southeast. The dry conditions in the Yellow River Basin were stable from 2003 to 2019. The results in this paper provide a basis for better understanding and evaluating the drought conditions in the Yellow River Basin and can guide water resources management, agricultural production, and ecological protection of this area. Full article
(This article belongs to the Special Issue Remote Sensing for Drought Monitoring and Forecasting)
Show Figures

Graphical abstract

Back to TopTop