Special Issue "Remote Sensing of Environmental Health Resilience"

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

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Igor Ogashawara
Guest Editor
Department of Experimental Limnology, Leibniz-Institute for Freshwater Ecology and Inland Fisheries, D-16775 Stechlin, Germany
Interests: bio-optical modeling; water quality; optical remote sensing; water quality sensors; fluorescence, climatology
Dr. Max Jacobo Moreno-Madriñán
Guest Editor
Department of Environmental Health Science, Fairbanks School of Public Health, Indiana University, 1050 Wishard Blvd. Suite 6092, IN 46202, USA
Interests: Environmental Health Science; Vector Borne Diseases; Water Quality; Limnology; Climatology

Special Issue Information

Dear Colleagues,

While resilience is the ability of a system to survive natural catastrophes, environmental resilience is the ability of a system to undertake, absorb, and react to global or regional changes whilst maintaining its functions and controls. However, the anthropogenic demands on environmental resources are reducing the natural “buffer” of resilience of the ecosystems. To increase environmental health resilience, planning for wider ranges of both natural and anthropogenic changes is needed. In this context, remote sensing plays an important role in mitigation and adaptation strategies to contest future environmental health challenges.

We would like to invite you to submit articles about your recent research on environmental health resilience regarding the following and other related topics:

  • Environmental Health Resilience of Coral Reefs
  • Environmental Health Resilience of Oceans
  • Environmental Health Resilience of Water Quality
  • Environmental Health Resilience of Hydrology
  • Environmental Health Resilience of Urban Areas
  • Environmental Health Resilience of Tropical Forests
  • Remote Sensing Applications for Food Security in the Changing World
  • Remote Sensing Applications for Human Health in the Changing World

Dr. Igor Ogashawara
Dr. Max Jacobo Moreno-Madriñán
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 2200 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.


  • Sustainability
  • Environmental Vulnerability
  • Environmental Health
  • Environmental Resilience
  • Environmental Risk Assessment
  • Climate Variability
  • Resilience, adaptation, and mitigation

Published Papers (1 paper)

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Open AccessArticle
Assessing Terrestrial Ecosystem Resilience using Satellite Leaf Area Index
Remote Sens. 2020, 12(4), 595; https://doi.org/10.3390/rs12040595 - 11 Feb 2020
Cited by 1
Quantitative approaches to measuring and assessing terrestrial ecosystem resilience, which expresses the ability of an ecosystem to recover from disturbances without shifting to an alternative state or losing function and services, is critical and essential to forecasting how terrestrial ecosystems will respond to [...] Read more.
Quantitative approaches to measuring and assessing terrestrial ecosystem resilience, which expresses the ability of an ecosystem to recover from disturbances without shifting to an alternative state or losing function and services, is critical and essential to forecasting how terrestrial ecosystems will respond to global change. However, global and continuous terrestrial resilience measurement is fraught with difficulty, and the corresponding attribution of resilience dynamics is lacking in the literature. In this study, we assessed global terrestrial ecosystem resilience based on the long time-series GLASS LAI product and GIMMS AVHRR LAI 3g product, and validated the results using drought and fire events as the main disturbance indicators. We also analyzed the spatial and temporal variations of global terrestrial ecosystem resilience and attributed their dynamics to climate change and environmental factors. The results showed that arid and semiarid areas exhibited low resilience. We found that evergreen broadleaf forest exhibited the highest resilience (mean resilience value (from GLASS LAI): 0.6). On a global scale, the increase of mean annual precipitation had a positive impact on terrestrial resilience enhancement, while we found no consistent relationships between mean annual temperature and terrestrial resilience. For terrestrial resilience dynamics, we observed three dramatic raises of disturbance frequency in 1989, 1995, and 2001, respectively, along with three significant drops in resilience correspondingly. Our study mapped continuous spatiotemporal variation and captured interannual variations in terrestrial ecosystem resilience. This study demonstrates that remote sensing data are effective for monitoring terrestrial resilience for global ecosystem assessment. Full article
(This article belongs to the Special Issue Remote Sensing of Environmental Health Resilience)
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