Special Issue "Environmental Stress and Natural Vegetation Growth"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Prof. Jarosław Chormański
E-Mail Website
Guest Editor
Department of Remote Sensing and Environmental Assessment; Institute of Environmental Engineering, Warsaw University of Life Sciences—SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland
Interests: urban and eco-hydrology; ecosystem services; imaging spectroscopy; remote sensing, UAS
Special Issues and Collections in MDPI journals
Prof. Dr. Tim Van de Voorde
E-Mail Website
Guest Editor
Department of Geography, Ghent University, Krijgslaan 281 S8, 9000 Gent, Belgium
Interests: urban remote sensing, urban green and ecosystem services, deep learning in remote sensing, LULC change, monitoring cultural heritage with remote sensing

Special Issue Information

Dear Colleagues,

Vegetation in optimal conditions provides many ecosystem services in natural, agricultural, as well as urban environments. As vegetation condition depends on a broad range of environmental factors, innovative and robust tools are crucial for generating the data flows needed to produce essential variables and state indicators required by monitoring approaches that aim to inform policy makers and ensure environmental protection and improvement. Notwithstanding the importance of in situ data to monitor ecosystem functioning and biodiversity change, remote sensing provides the opportunity to assess vegetation conditions at different scales (form local to global) more efficiently than traditional field surveys. Pressures and impact on vegetation or ecosystems in general, however, depend on vegetation type, climate zone, and human activities. Hence, tools for assessing stress factors require customized development or parametrization.

This proposed Special Issue addresses research on assessing vegetation stress and/or its impact on ecosystem service provisioning using different remote sensing techniques. We welcome original contributions on vegetation conditions and pressure in all kinds of biomes, in natural as well as in environments strongly influenced by humans (e.g., urban and agricultural areas) relying on all possible types of remotely sensed data: local applications with UAV or airborne flights as well as regional or global studies using active or passive satellite sensors. Research on environmental indicators or essential variables using widely known remote sensing indices (e.g., crop water stress index—CWSI, normalized difference vegetation index—NDVI) as well as newly created ones is welcome in this Special Issue.

Prof. Jarosław Chormański
Prof. Dr. Tim Van de Voorde
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 papers will be 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 2000 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.


  • Environmental stress monitoring and modeling
  • Ecosystem services
  • Essential variables
  • Environmental indicators
  • Thermal indices
  • Optical indices

Published Papers (1 paper)

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Open AccessArticle
Remotely Sensed Land Surface Temperature-Based Water Stress Index for Wetland Habitats
Remote Sens. 2020, 12(4), 631; https://doi.org/10.3390/rs12040631 - 14 Feb 2020
Despite covering only 2–6% of land, wetland ecosystems play an important role at the local and global scale. They provide various ecosystem services (carbon dioxide sequestration, pollution removal, water retention, climate regulation, etc.) as long as they are in good condition. By definition, [...] Read more.
Despite covering only 2–6% of land, wetland ecosystems play an important role at the local and global scale. They provide various ecosystem services (carbon dioxide sequestration, pollution removal, water retention, climate regulation, etc.) as long as they are in good condition. By definition, wetlands are rich in water ecosystems. However, ongoing climate change with an ambiguous balance of rain in a temperate climate zone leads to drought conditions. Such periods interfere with the natural processes occurring on wetlands and restrain the normal functioning of wetland ecosystems. Persisting unfavorable water conditions lead to irreversible changes in wetland habitats. Hence, the monitoring of habitat changes caused by an insufficient amount of water (plant water stress) is necessary. Unfortunately, due to the specific conditions of wetlands, monitoring them by both traditional and remote sensing techniques is challenging, and research on wetland water stress has been insufficient. This paper describes the adaptation of the thermal water stress index, also known as the crop water stress index (CWSI), for wetlands. This index is calculated based on land surface temperature and meteorological parameters (temperature and vapor pressure deficit—VPD). In this study, an unmanned aerial system (UAS) was used to measure land surface temperature. Performance of the CWSI was confirmed by the high correlation with field measurements of a fraction of absorbed photosynthetically active radiation (R = −0.70) and soil moisture (R = −0.62). Comparison of the crop water stress index with meteorological drought indices showed that the first phase of drought (meteorological drought) cannot be detected with this index. This study confirms the potential of using the CWSI as a water stress indicator in wetland ecosystems. Full article
(This article belongs to the Special Issue Environmental Stress and Natural Vegetation Growth)
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