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Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system

BACKGROUND: The reliable monitoring, reporting and verification (MRV) of carbon emissions and removals from the forest sector is an important part of the efforts on reducing emissions from deforestation and forest degradation (REDD+). Forest-dependent local communities are engaged to contribute to M...

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Autores principales: Murthy, M. S. R., Gilani, Hammad, Karky, Bhaskar Singh, Sharma, Eklabya, Sandker, Marieke, Koju, Upama Ashish, Khanal, Shiva, Poudel, Mohan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711765/
https://www.ncbi.nlm.nih.gov/pubmed/29196960
http://dx.doi.org/10.1186/s13021-017-0087-8
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author Murthy, M. S. R.
Gilani, Hammad
Karky, Bhaskar Singh
Sharma, Eklabya
Sandker, Marieke
Koju, Upama Ashish
Khanal, Shiva
Poudel, Mohan
author_facet Murthy, M. S. R.
Gilani, Hammad
Karky, Bhaskar Singh
Sharma, Eklabya
Sandker, Marieke
Koju, Upama Ashish
Khanal, Shiva
Poudel, Mohan
author_sort Murthy, M. S. R.
collection PubMed
description BACKGROUND: The reliable monitoring, reporting and verification (MRV) of carbon emissions and removals from the forest sector is an important part of the efforts on reducing emissions from deforestation and forest degradation (REDD+). Forest-dependent local communities are engaged to contribute to MRV through community-based monitoring systems. The efficiency of such monitoring systems could be improved through the rational integration of the studies at permanent plots with the geospatial technologies. This article presents a case study of integrating community-based measurements at permanent plots at the foothills of central Nepal and biomass maps that were developed using GeoEye-1 and IKONS satellite images. RESULTS: The use of very-high-resolution satellite-based tree cover parameters, including crown projected area (CPA), crown density and crown size classes improves salience, reliability and legitimacy of the community-based survey of 0.04% intensity at the lower cost than increasing intensity of the community-based survey to 0.14% level (2.5 USD/ha vs. 7.5 USD/ha). CONCLUSION: The proposed REDD+ MRV complementary system is the first of its kind and demonstrates the enhancement of information content, accuracy of reporting and reduction in cost. It also allows assessment of the efficacy of community-based forest management and extension to national scale. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13021-017-0087-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-57117652017-12-07 Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system Murthy, M. S. R. Gilani, Hammad Karky, Bhaskar Singh Sharma, Eklabya Sandker, Marieke Koju, Upama Ashish Khanal, Shiva Poudel, Mohan Carbon Balance Manag Research BACKGROUND: The reliable monitoring, reporting and verification (MRV) of carbon emissions and removals from the forest sector is an important part of the efforts on reducing emissions from deforestation and forest degradation (REDD+). Forest-dependent local communities are engaged to contribute to MRV through community-based monitoring systems. The efficiency of such monitoring systems could be improved through the rational integration of the studies at permanent plots with the geospatial technologies. This article presents a case study of integrating community-based measurements at permanent plots at the foothills of central Nepal and biomass maps that were developed using GeoEye-1 and IKONS satellite images. RESULTS: The use of very-high-resolution satellite-based tree cover parameters, including crown projected area (CPA), crown density and crown size classes improves salience, reliability and legitimacy of the community-based survey of 0.04% intensity at the lower cost than increasing intensity of the community-based survey to 0.14% level (2.5 USD/ha vs. 7.5 USD/ha). CONCLUSION: The proposed REDD+ MRV complementary system is the first of its kind and demonstrates the enhancement of information content, accuracy of reporting and reduction in cost. It also allows assessment of the efficacy of community-based forest management and extension to national scale. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13021-017-0087-8) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-12-01 /pmc/articles/PMC5711765/ /pubmed/29196960 http://dx.doi.org/10.1186/s13021-017-0087-8 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Murthy, M. S. R.
Gilani, Hammad
Karky, Bhaskar Singh
Sharma, Eklabya
Sandker, Marieke
Koju, Upama Ashish
Khanal, Shiva
Poudel, Mohan
Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system
title Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system
title_full Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system
title_fullStr Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system
title_full_unstemmed Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system
title_short Synergizing community-based forest monitoring with remote sensing: a path to an effective REDD+ MRV system
title_sort synergizing community-based forest monitoring with remote sensing: a path to an effective redd+ mrv system
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711765/
https://www.ncbi.nlm.nih.gov/pubmed/29196960
http://dx.doi.org/10.1186/s13021-017-0087-8
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