remotesensing-logo

Journal Browser

Journal Browser

Remote Sensing of Greening-Browning Trends in Tree-Grass Ecosystems

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 4025

Special Issue Editor


E-Mail Website
Guest Editor
1) Mediterranean Institute for Agriculture, Environment and Development (MED), 2) Institute of Earth Sciences (ICT), University of Évora, 7000-645 Évora, Portugal
Interests: remote sensing; tree-grass ecosystem conservation; land degradation; biogeophysical effects of vegetation cover change; machine learning

Special Issue Information

Dear Colleagues,

Tree-grass ecosystems (TGE) are mixed woody-herbaceous communities that occupy approximately ~36% of the world’s land area, occurring in all continents (except Antarctica) and in different bioclimatic regions (e.g., tropical, subtropical, and temperate). TGE are widely recognized as multifunctional landscapes, due to their importance in providing several ecosystem services, environmental benefits, and economic commodities. Despite their socioeconomic and environmental relevance, TGE are highly susceptive and sensitive to climate change and human-induced land degradation. This can disrupt key ecological, biogeochemical, and biogeophysical processes, leading to huge modifications in several and crucial tree-grass ecosystems services such as water recycling, food production, biodiversity conservation, and local/regional climate regulation. Therefore, accurately quantifying and assessing TGE vegetation trends is crucial to deeply understand the effects of climate change (e.g., warming, atmospheric CO2 fertilization) and human-induced land degradation (e.g., fire, conversion to agriculture). However, detailed studies specifically focused on greening-browning trend analyses of tree-grass ecosystems at global scale are still scarce within the literature. Recognizing the challenge in using satellite-based data to assess vegetation trends in horizontally and vertically complex ecosystems such as the case of TGE, the Remote Sensing journal invites a broad range of high quality papers focused on the applications and development of remote sensing-based methodologies to assess tree-grass ecosystem condition through the use of greening-browning trend analysis. Submissions on the following topics are invited:

  • Long-term greening/browning trend analysis;
  • Assessment of greening/browning trends using different sensors (e.g., AVHRR-NDVI, MODIS, Landsat);
  • TGE vegetation trend analysis in different bioclimatic regions;
  • Comparisons between trend analysis methods and algorithms (e.g., averaging integrated annual or seasonal NDVI values; BFAST, DBEST, EEDM);
  • Climate and human drivers of greening/browning trends in TGE;
  • Comparisons between NDVI trend analysis and other remote sensing-based products (e.g., sun-induced chlorophyll fluorescence (SIF));
  • Identification of the global TGE hotspots in terms of greening/browning trends;
  • Impacts of greening/browning trends in biogeochemical and biogeophysical processes;
  • Impacts of greening/browning trends in TGE biodiversity conservation;
  • Field-based validation studies on greening/browning trends.
Dr. Sergio Godinho
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

  • Tree-grass ecosystems monitoring
  • Vegetation greening/browning
  • Long-term analysis
  • NDVI
  • Multisensor
  • Degradation

Published Papers (1 paper)

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

Research

18 pages, 5343 KiB  
Article
Contrasting Effects of Temperature and Precipitation on Vegetation Greenness along Elevation Gradients of the Tibetan Plateau
by Yan Wang, Dailiang Peng, Miaogen Shen, Xiyan Xu, Xiaohua Yang, Wenjiang Huang, Le Yu, Liangyun Liu, Cunjun Li, Xinwu Li, Shijun Zheng and Helin Zhang
Remote Sens. 2020, 12(17), 2751; https://doi.org/10.3390/rs12172751 - 25 Aug 2020
Cited by 33 | Viewed by 3529
Abstract
The Tibetan Plateau (TP) is one of the most sensitive regions to global climate warming, not only at the inter-annual time scale but also at the altitudinal scale. We aim to investigate the contrasting effects of temperature and precipitation on vegetation greenness at [...] Read more.
The Tibetan Plateau (TP) is one of the most sensitive regions to global climate warming, not only at the inter-annual time scale but also at the altitudinal scale. We aim to investigate the contrasting effects of temperature and precipitation on vegetation greenness at different altitudes across the TP. In this study, interannual and elevational characteristics of the Normalized Difference Vegetation Index (NDVI), temperature, and precipitation were examined during the growing season from 1982 to 2015. We compared the elevational movement rates of the isolines of NDVI, temperature, and precipitation, and the sensitivities of elevational NDVI changes to temperature and precipitation. The results show that from 1982 to 2015, the elevational variation rate of isolines for NDVI mismatched with that for temperature and precipitation. The elevational movements of NDVI isolines were mostly controlled by precipitation at elevations below 2400 m and by the temperature at elevations above 2400 m. Precipitation appears to plays a role similar to temperature, and even a more effective role than the temperature at low elevations, in controlling elevational vegetation greenness changes at both spatial and interannual scales in the TP. This study highlights the regulation of temperature and precipitation on vegetation ecosystems along elevation gradients over the whole TP under global warming conditions. Full article
(This article belongs to the Special Issue Remote Sensing of Greening-Browning Trends in Tree-Grass Ecosystems)
Show Figures

Figure 1

Back to TopTop