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Remote Sensing
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Remote Sensing in Assessing Responses of Vegetation to Drought
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Remote Sensing in Assessing Responses of Vegetation to Drought

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 11409

Special Issue Editors

Dr. Rajen Bajgain

E-Mail Website
Guest Editor
USDA-ARS, Sustainable Water Management Research Unit (SWMRU), 141 Experiment Station Rd, Stoneville, MS 38776, USA
Interests: carbon and water flux; land-vegetation-atmosphere interaction; remote sensing applications for drought monitoring; GHGs modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Yuting Zhou

E-Mail Website
Guest Editor
Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA
Interests: drought; land use land cover change; carbon and water cycle; food water energy nexus; sustainability

Special Issue Information

Dear Colleagues,

Vegetation drought is one of the costliest natural disasters due to its spatial coverage, frequency, intensity, and duration. Drought has devastating impacts on agriculture and other ecosystems and its occurrence is expected to be more frequent in the face of increasing climatic variability. Drought is one of the main drivers in constraining several aspects of vegetation including productivity. Understanding and assessing drought is a crucial challenge but extremely important. To understand vegetation response to drought (soil moisture deficiency) in a broader perspective and larger spatial extent, assessing drought quantitively using remote sensing indices is required. Studies on drought assessment are necessary to make drought less harmful to society.

Here, we invite manuscripts on the use of remote sensing concepts, methods, models, and data products to assess vegetation drought in terms of drought duration, intensity, frequency, and any other aspects related to ecosystem structure, function, and services. Preference will be given to studies that consider the responses/feedback of vegetation to drought ranging from field to landscape level. The direct quantification of drought is a difficult task, so studies that identify/assess drought by its effects on different aspects of vegetation would be primarily covered in this special issue. Therefore, the scope of this Special Issue “Remote Sensing in Assessing Responses of Vegetation to Drought" covers phenological, physiological, biophysical, and other physical and functional responses of vegetation to drought.

Potential topics for this Special Issue include but are not limited to the following:

  • Ecosystem responses to water stress-phenological, biophysical, structural, functional, physiological
  • Rainfall variability and soil moisture deficit and plant water stress
  • Vegetation phenology and drought
  • Flash drought
  • Vegetation mortality
  • Leaf area index, aboveground biomass assessment due to drought
  • Vegetation recovery
  • Carbon and water cycle gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET)

Dr. Rajen Bajgain
Dr. Yuting Zhou
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 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

  • Drought impacts
  • Drought index
  • Ecosystem functions
  • Drought duration
  • Drought intensity Phenological response
  • Biophysical response
  • Soil moisture
  • Vegetation water content
  • Gross primary productivity
  • Evapotranspiration
  • Leaf area index
  • Drought indicator
  • Flash drought
  • Vegetation mortality

Published Papers (3 papers)

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Research

17 pages, 5166 KiB  
Article
Assessment of Drought Impact on Net Primary Productivity in the Terrestrial Ecosystems of Mongolia from 2003 to 2018
by Lkhagvadorj Nanzad, Jiahua Zhang, Battsetseg Tuvdendorj, Shanshan Yang, Sonam Rinzin, Foyez Ahmed Prodhan and Til Prasad Pangali Sharma
Remote Sens. 2021, 13(13), 2522; https://doi.org/10.3390/rs13132522 - 29 Jun 2021
Cited by 21 | Viewed by 3271
Abstract
Drought has devastating impacts on agriculture and other ecosystems, and its occurrence is expected to increase in the future. However, its spatiotemporal impacts on net primary productivity (NPP) in Mongolia have remained uncertain. Hence, this paper focuses on the impact of drought on [...] Read more.
Drought has devastating impacts on agriculture and other ecosystems, and its occurrence is expected to increase in the future. However, its spatiotemporal impacts on net primary productivity (NPP) in Mongolia have remained uncertain. Hence, this paper focuses on the impact of drought on NPP in Mongolia. The drought events in Mongolia during 2003–2018 were identified using the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The Boreal Ecosystem Productivity Simulator (BEPS)-derived NPP was computed to assess changes in NPP during the 16 years, and the impacts of drought on the NPP of Mongolian terrestrial ecosystems was quantitatively analyzed. The results showed a slightly increasing trend of the growing season NPP during 2003–2018. However, a decreasing trend of NPP was observed during the six major drought events. A total of 60.55–87.75% of land in the entire country experienced drought, leading to a 75% drop in NPP. More specifically, NPP decline was prominent in severe drought areas than in mild and moderate drought areas. Moreover, this study revealed that drought had mostly affected the sparse vegetation NPP. In contrast, forest and shrubland were the least affected vegetation types. Full article
(This article belongs to the Special Issue Remote Sensing in Assessing Responses of Vegetation to Drought)
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16 pages, 1228 KiB  
Article
Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe
by Mehdi H. Afshar, Amen Al-Yaari and M. Tugrul Yilmaz
Remote Sens. 2021, 13(7), 1251; https://doi.org/10.3390/rs13071251 - 25 Mar 2021
Cited by 14 | Viewed by 3242
Abstract
Agricultural droughts impose many economic and social losses on various communities. Most of the effective tools developed for agricultural drought assessment are based on vegetation indices (VIs). The aim of this study is to compare the response of two commonly used VIs to [...] Read more.
Agricultural droughts impose many economic and social losses on various communities. Most of the effective tools developed for agricultural drought assessment are based on vegetation indices (VIs). The aim of this study is to compare the response of two commonly used VIs to meteorological droughts—Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and Soil Moisture and Ocean Salinity (SMOS) vegetation optical depth (VOD). For this purpose, meteorological droughts are calculated by using a standardized precipitation index over more than 24,000 pixels at 0.25° × 0.25° spatial resolution located in central Europe. Then, to evaluate the capability of VIs in the detection of agricultural droughts, the average values of VIs anomalies during dry and wet periods obtained from meteorological droughts are statistically compared to each other. Additionally, to assess the response time of VIs to meteorological droughts, a time lag of one to six months is applied to the anomaly time series of VIs during their comparison. Results show that over 35% of the considered pixels NDVI, over 22% of VOD, and over 8% of both VIs anomalies have a significant response to drought events, while the significance level of these differences and the response time of VIs vary with different land use and climate conditions. Full article
(This article belongs to the Special Issue Remote Sensing in Assessing Responses of Vegetation to Drought)
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20 pages, 6860 KiB  
Article
Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping
by Mahendra Bhandari, Shannon Baker, Jackie C. Rudd, Amir M. H. Ibrahim, Anjin Chang, Qingwu Xue, Jinha Jung, Juan Landivar and Brent Auvermann
Remote Sens. 2021, 13(6), 1144; https://doi.org/10.3390/rs13061144 - 17 Mar 2021
Cited by 19 | Viewed by 4001
Abstract
Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the [...] Read more.
Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the temporal effects of drought on canopy growth of winter wheat. Weekly UAS data were collected using red, green, and blue (RGB) and multispectral (MS) sensors over a yield trial consisting of 22 winter wheat cultivars in both irrigated and dryland environments. Raw-images were processed to compute canopy features such as canopy cover (CC) and canopy height (CH), and vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Excess Green Index (ExG), and Normalized Difference Red-edge Index (NDRE). The drought was more severe in 2018 than in 2019 and the effects of growth differences across years and irrigation levels were visible in the UAS measurements. CC, CH, and VIs, measured during grain filling, were positively correlated with grain yield (r = 0.4–0.7, p < 0.05) in the dryland in both years. Yield was positively correlated with VIs in 2018 (r = 0.45–0.55, p < 0.05) in the irrigated environment, but the correlations were non-significant in 2019 (r = 0.1 to −0.4), except for CH. The study shows that high-throughput UAS data can be used to monitor the drought effects on wheat growth and productivity across the temporal and spatial domains. Full article
(This article belongs to the Special Issue Remote Sensing in Assessing Responses of Vegetation to Drought)
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