How Can Remote Sensing Help Monitor Tropical Moist Forest Degradation?—A Systematic Review

Round 1

Reviewer 1 Report

General comments:

The paper presents an extensive interesting review of the EO-based approached to monitor forest degradation.

However I recommend taking into account the following main comments before publication:

• Bibliographic references to be completed on international standards (from FAO), changes in forest cover and approaches to map degraded forests (see minimum suggested list in detailed comments)
• Link to the UNFCCC decision and in particular to REDD+ activities (where the second D stands for Degradation) and to related MRV approaches (IPCC Guidelines, GOFC, GFOI) needs to appear somewhere
• I have a problem in mixing in the introduction the issue of degradation (with structure and composition indicators) with the issue of resilience (with regeneration indicators). The paper should either focus on forest degradation only (it would make the paper more targeted) or indicate more clearly that it covers both items (with risk of dispersion)
• The introduction should present the key drivers of forest degradation in tropical moist forests: logging activities, fragmentation of landscapes, mining and human-made fires

Detailed comments

“Here, we performed a systematic review of studies on moist tropical forest degradation using remote sensing and fitting indicators of forest resilience to perturbations”

To my understanding these are 2 different topics (1. systematic review of studies on moist tropical forest degradation using remote sensing and 2. fitting indicators of forest resilience to perturbations).

A tropical forest can be assessed as degraded, independently of its resilience. The resilience and related-regeneration issue is a second-level issue (after degradation as first level).

The paper should focus on forest degradation only (it would make the paper more targeted) – otherwise it needs to be clarified in the introduction.

“Indicators of compositional, structural and regeneration criteria were noted” Regeneration is related to resilience not to degradation

“(3) the study is localized in a tropical moist forest”

• ‘Moist’ should appear in the title.

The introduction should also mention that all scales (extent / coverage) are considered in the review. (from local scale with UAV to pan tropical scale with EO data).

Bibliographic references needs to be completed

The paper is lacking a few key references on the concept of forest degradation used by international bodies such as FAO (in addition to FA 2011) or under UNFCCC REDD+ (GOFC-GOLD or GFOI), e.g. at least those ones (it should be up to the authors to make such review):

• FAO, 2018. Global forest resources assessment 2020: terms and definitions. FAO working paper 188. FAO, Rome.
• GFOI, 2016, Integration of remote-sensing and ground-based observations for estimation of emissions and removals of greenhouse gases in forests: Methods and Guidance from the Global Forest Observations Initiative, Edition 2.0, FAO, Rome.
• GOFC-GOLD, 2015, A Sourcebook of Methods and Procedures for Monitoring and Reporting Anthropogenic Greenhouse Gas Emissions and Removals Associated with Deforestation, Gains and Losses of Carbon Stocks in Forests Remaining Forests, and Forestation GOFC-GOLD Report version COP21-1. (GOFC-GOLD Land Cover Project Office, Wageningen University, The Netherlands).

The paper is also lacking a few important references in introduction on (i) changes of tropical forest cover or primary / intact forests cover

• Keenan, R et al Dynamics of global forest area: results from the 2015 Global Forest Resources Assessment. Forest Ecol. Manage. 352, 9–20.
• Morales-Hidalgo D et al 2015 Status and trends in global primary forest, protected areas, and areas designated for conservation of biodiversity from the Global Forest Resources Assessment 2015 Forest Ecol. Manage. 352 (2015) 68–77
• Potapov P et al 2017. The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013 Science Advances 3, no. 1, e1600821

(ii)  C emissions from tropical deforestation / degradation

• Achard F et al 2014 Determination of tropical deforestation rates and related carbon losses from 1990 to 2010 Glob. Change Biol. 20 2540–54
• Tyukavina A, et al 2015 Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012 Environ. Res. Lett. 10 074002

The paper is also lacking important and updated references on the use of methods to monitor forest degradation from EO data, in particular:

• Almeida Lima T, et al (2019) Comparing Sentinel-2 MSI and Landsat 8 OLI Imagery for Monitoring Selective Logging in the Brazilian  Amazon Remote Sens. 2019, 11(8) : 961;
• Baccini et al 2017, Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science 358, 230–234 (2017)
• Bourgoin et al 2020 Assessing the ecological vulnerability of forest landscape to agricultural frontier expansion in the Central Highlands of Vietnam Int J Appl Earth Obs Geoinformation 84 (2020) 101958
• Bullock et al 2020, Satellite-based estimates reveal widespread forest degradation in the Amazon. Glob Change Biol. 2020;00:1–14
• Langner et al 2018 Towards Operational Monitoring of Forest Canopy Disturbance in Evergreen Rain Forests: A Test Case in Continental Southeast Asia. Remote Sens. 2018, 10, 544;

Author Response

Dear Reviewer 1,

Thank you for your review and for all the suggestions you made. Please find attached our response to your comments.

Best regards,

Chloé Dupuis

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript with the title “How can remote sensing help monitoring tropical forest degradation? – A systematic review” presents a systematic review of studies on moist tropical forest degradation using remote sensing data and fitting indicators of forest resilience to perturbations.  The manuscripts made a review on a worthy topic and the structure is strong. The paper reads well and provide a comprehensive revision about forest degradation monitoring on the moist tropical forest, and therefore I suggest changing the title to “How can remote sensing help monitoring moist tropical forest degradation? – A systematic review” to avoid wrong expectations. The forest degradation dynamic, as the authors have been pointed out, is very complex and depends on many factors according to the specific type of vegetation. Tropical Forest includes besides moist; dry, deciduous and sub deciduous forest that is not the scope of the paper.

Aside from that, this reviewer believes that the systematic review would make a nice contribution to the scientific community.

Nitpicky:

Table 3. please define “GV” from Forests Degradation Index Equation.

Author Response

Dear Reviewer 2,

Thank you for your review and for your positive comments.

As you recommended, we changed the title into “How can remote sensing help monitoring tropical moist forest degradation? – A systematic review”.

We also defined the "GV: pixel green fraction" from the Forest Degradation Index.

Best regards,

Chloé Dupuis

Reviewer 3 Report

Thanks for the opportunity to read this paper.

This article is a very complete review of studies on the degradation of tropical rainforests using Remote Sensing: Using very high (UAV), medium and high resolution images. Sensors: Optical, RADAR and LiDAR. It analyses in an exhaustive way the most used indexes and the conditions in which they are used. From my point of view, it describes the current situation worldwide of the state of knowledge in these disciplines.

The article, in my assessment, is ready for publication.

Author Response

Dear Reviewer 3,

Thank you for your review and for your positive comments.

Best regards,

Chloé Dupuis