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Forest Dynamics and Degradation Monitoring in the Brazilian Amazon

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

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 2600

Special Issue Editors


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Guest Editor
National Institute for Space Research, Brazil.
Interests: land use and land cover change; forest degradation; selective logging; time series analysis; sampling

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Guest Editor
School of Geography, University of Leeds, Leeds, UK
Interests: land use and land cover change; climate sensitivity of tropical forests; tropical ecology; carbon cycling

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Guest Editor
School of GeoSciences, University of Edinburgh, Crew Building, Edinburgh EH9 3JN, UK
Interests: remote sensing; climate change; deforestation; forest degradation; terrestrial carbon

Special Issue Information

Dear Colleagues,

The Amazon is the largest and most biodiverse continuous rainforest on the planet and provides substantial ecosystem services to the entire world. Thus, Amazon deforestation is a major environmental matter. About two-thirds of the Amazon are in Brazil, where the majority of Amazon deforestation has been happening. Despite this, 80% of Brazil’s Amazon area remains forested, although the extent to which this remaining forest has been degraded remains an open question.

Thus, this Special Issue focuses on state-of-the-art remote sensing applied to Forest Dynamics and Degradation Monitoring in the Brazilian Amazon. Also, we are glad to receive works in Cerrado or Atlantic Forest in this subject.  Therefore, papers covering the following topics are welcome:

  1. Near real-time forest monitoring;
  2. Biodiversity loss;
  3. Selective logging;
  4. REDD+ and other forest protection mechanisms;
  5. Fire;
  6. Forest regrowth;
  7. Forest climate sensitivity.

Other papers of relevance to understanding the dynamics and degradation status of Brazilian Amazon forests but which do not directly fit into the above categories are also welcome.

Dr. Marcos Adami
Dr. David Galbraith
Dr. Edward Mitchard
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

  • Land use and land cover change
  • REDD+
  • Fire
  • Selective logging
  • Forest monitoring
  • Forest regrowth

Published Papers (1 paper)

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Research

19 pages, 40415 KiB  
Article
The Novel Microwave Temperature Vegetation Drought Index (MTVDI) Captures Canopy Seasonality across Amazonian Tropical Evergreen Forests
by Liyang Liu, Xueqin Yang, Fanxi Gong, Yongxian Su, Guangqing Huang and Xiuzhi Chen
Remote Sens. 2021, 13(3), 339; https://doi.org/10.3390/rs13030339 - 20 Jan 2021
Cited by 8 | Viewed by 2127
Abstract
Despite its perennial canopy, the Amazonian tropical evergreen forest shows significant canopy growth seasonality, which has been represented by optical satellite-based observations. In this paper, a new Microwave Temperature–Vegetation Drought Index (MTVDI) based on Advanced Microwave Scanning Radiometer for the Earth Observing System [...] Read more.
Despite its perennial canopy, the Amazonian tropical evergreen forest shows significant canopy growth seasonality, which has been represented by optical satellite-based observations. In this paper, a new Microwave Temperature–Vegetation Drought Index (MTVDI) based on Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) sensors was used to capture the canopy seasonality from 2003 to 2010 in comparison with four climatic dryness indicators (Palmer Drought Severity Index (PDSI), Climatological Water Deficit (CWD), Terrestrial Water Storage (TWS), Vapor Pressure Deficit (VPD)) and two photosynthesis proxies (Enhanced Vegetation Index (EVI) and Solar-Induced chlorophyll Fluorescence (SIF)), respectively. Our results suggest that the MTVDI shows opposite seasonal variability with two photosynthesis proxies and performs better than the four climatic dryness indicators in reflecting the canopy photosynthesis seasonality of tropical forests in the Amazon. Besides, the MTVDI captures wet regions that show green-up during the dry season with mean annual precipitation higher than 2000 mm per year. The MTVDI provides a new way for monitoring the canopy seasonality of tropical forests from microwave signals. Full article
(This article belongs to the Special Issue Forest Dynamics and Degradation Monitoring in the Brazilian Amazon)
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