Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR
Due to the fast deforestation rates in the tropics, multiple international efforts have been launched to reduce deforestation and develop consistent methodologies to assess forest extension and change. Since 2010 Colombia implemented the Mainstream Sustainable Cattle Ranching project with the partic...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/19053
- Acceso en línea:
- http://repository.urosario.edu.co/handle/10336/19053
- Palabra clave:
- Synthetic Aperture Radar
Alos Palsar
Carbon Cycles
Cattle Ranching
Classification Errors
Colombia
Complex Topographies
Heterogeneous Region
Payment For Environmental Services
Deforestation
Huertos, frutas, silvicultura
Deforestación
Ciclo del carbono (Biogeoquímica)
- Rights
- License
- Abierto (Texto Completo)
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dc.title.spa.fl_str_mv |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
title |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
spellingShingle |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR Synthetic Aperture Radar Alos Palsar Carbon Cycles Cattle Ranching Classification Errors Colombia Complex Topographies Heterogeneous Region Payment For Environmental Services Deforestation Huertos, frutas, silvicultura Deforestación Ciclo del carbono (Biogeoquímica) |
title_short |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
title_full |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
title_fullStr |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
title_full_unstemmed |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
title_sort |
Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR |
dc.subject.spa.fl_str_mv |
Synthetic Aperture Radar Alos Palsar Carbon Cycles Cattle Ranching Classification Errors Colombia Complex Topographies Heterogeneous Region Payment For Environmental Services Deforestation |
topic |
Synthetic Aperture Radar Alos Palsar Carbon Cycles Cattle Ranching Classification Errors Colombia Complex Topographies Heterogeneous Region Payment For Environmental Services Deforestation Huertos, frutas, silvicultura Deforestación Ciclo del carbono (Biogeoquímica) |
dc.subject.ddc.spa.fl_str_mv |
Huertos, frutas, silvicultura |
dc.subject.lemb.spa.fl_str_mv |
Deforestación Ciclo del carbono (Biogeoquímica) |
description |
Due to the fast deforestation rates in the tropics, multiple international efforts have been launched to reduce deforestation and develop consistent methodologies to assess forest extension and change. Since 2010 Colombia implemented the Mainstream Sustainable Cattle Ranching project with the participation of small farmers in a payment for environmental services (PES) scheme where zero deforestation agreements are signed. To assess the fulfillment of such agreements at farm level, ALOS-1 and ALOS-2 PALSAR fine beam dual imagery for years 2010 and 2016 was processed with ad-hoc routines to estimate stable forest, deforestation, and stable nonforest extension for 2615 participant farms in five heterogeneous regions of Colombia. Landsat VNIR imagery was integrated in the processing chain to reduce classification uncertainties due to radar limitations. Farms associated with Meta Foothills regions showed zero deforestation during the period analyzed (2010-2016), while other regions showed low deforestation rates with the exception of the Cesar River Valley (75 ha). Results, suggests that topography and dry weather conditions have an effect on radar-based mapping accuracy, i.e., deforestation and forest classes showed lower user accuracy values on mountainous and dry regions revealing overestimations in these environments. Nevertheless, overall ALOS Phased Array L-band SAR (PALSAR) data provided overall accurate, relevant, and consistent information for forest change analysis for local zero deforestation agreements assessment. Improvements to preprocessing routines and integration of high dense radar time series should be further investigated to reduce classification errors from complex topography conditions. © 2018 by the authors. |
publishDate |
2018 |
dc.date.created.none.fl_str_mv |
2018 |
dc.date.issued.none.fl_str_mv |
2018 |
dc.date.accessioned.none.fl_str_mv |
2019-02-12T20:58:57Z |
dc.date.available.none.fl_str_mv |
2019-02-12T20:58:57Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
10.3390/rs10091464 |
dc.identifier.issn.none.fl_str_mv |
2072-4292 |
dc.identifier.uri.none.fl_str_mv |
http://repository.urosario.edu.co/handle/10336/19053 |
identifier_str_mv |
10.3390/rs10091464 2072-4292 |
url |
http://repository.urosario.edu.co/handle/10336/19053 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationTitle.none.fl_str_mv |
Remote Sensing |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 10 |
dc.relation.ispartof.spa.fl_str_mv |
Remote Sensing, ISSN:2072-4292, Vol. 10 (2018) |
dc.relation.uri.spa.fl_str_mv |
https://www.mdpi.com/2072-4292/10/9/1464 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.acceso.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
institution |
Universidad del Rosario |
dc.source.bibliographicCitation.spa.fl_str_mv |
Keenan, R.J., Reams, G.A., Achard, F., de Freitas, J.V., Grainger, A., Lindquist, E., Dynamics of global forest area: Results from the FAO Global Forest Resources Assessment 2015 (2015) For. Ecol. Manag, 352, pp. 9-20 |
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instname:Universidad del Rosario |
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reponame:Repositorio Institucional EdocUR |
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37f220fb-70d1-464b-adfc-a95a5f05beef6004508116007aec6140-965e-405a-b18a-b60e4864e991600e2029fab-29ae-4624-b85b-1b9c56b15f58600823cc981-08f6-487d-aa68-7c3603201f156008c21bd9f-032e-4e31-bbd3-6a1c3eb5b799600b2f4f125-208c-4be1-b968-e4485ac3c734600a2ffff15-2cac-4d19-a896-20fd9ef62057600fda87fb6-2695-4a50-a58b-911cf31f43416004508116002019-02-12T20:58:57Z2019-02-12T20:58:57Z20182018Due to the fast deforestation rates in the tropics, multiple international efforts have been launched to reduce deforestation and develop consistent methodologies to assess forest extension and change. Since 2010 Colombia implemented the Mainstream Sustainable Cattle Ranching project with the participation of small farmers in a payment for environmental services (PES) scheme where zero deforestation agreements are signed. To assess the fulfillment of such agreements at farm level, ALOS-1 and ALOS-2 PALSAR fine beam dual imagery for years 2010 and 2016 was processed with ad-hoc routines to estimate stable forest, deforestation, and stable nonforest extension for 2615 participant farms in five heterogeneous regions of Colombia. Landsat VNIR imagery was integrated in the processing chain to reduce classification uncertainties due to radar limitations. Farms associated with Meta Foothills regions showed zero deforestation during the period analyzed (2010-2016), while other regions showed low deforestation rates with the exception of the Cesar River Valley (75 ha). Results, suggests that topography and dry weather conditions have an effect on radar-based mapping accuracy, i.e., deforestation and forest classes showed lower user accuracy values on mountainous and dry regions revealing overestimations in these environments. Nevertheless, overall ALOS Phased Array L-band SAR (PALSAR) data provided overall accurate, relevant, and consistent information for forest change analysis for local zero deforestation agreements assessment. Improvements to preprocessing routines and integration of high dense radar time series should be further investigated to reduce classification errors from complex topography conditions. © 2018 by the authors.application/pdf10.3390/rs100914642072-4292http://repository.urosario.edu.co/handle/10336/19053engRemote SensingVol. 10Remote Sensing, ISSN:2072-4292, Vol. 10 (2018)https://www.mdpi.com/2072-4292/10/9/1464Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Keenan, R.J., Reams, G.A., Achard, F., de Freitas, J.V., Grainger, A., Lindquist, E., Dynamics of global forest area: Results from the FAO Global Forest Resources Assessment 2015 (2015) For. Ecol. Manag, 352, pp. 9-20instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURSynthetic Aperture RadarAlos PalsarCarbon CyclesCattle RanchingClassification ErrorsColombiaComplex TopographiesHeterogeneous RegionPayment For Environmental ServicesDeforestationHuertos, frutas, silvicultura634600DeforestaciónCiclo del carbono (Biogeoquímica)Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSARarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Pedraza, CarlosClereci, NicolaForero, Cristian FabiánMelo, AméricaNavarrete, DiegoLizcano, DiegoZuluaga, Andrés FelipeDelgado, JulianaGalindo, GustavoPedraza, CarlosClerici, NicolaForero, Cristian FabiánMelo, AméricaNavarrete, DiegoLizcano, DiegoZuluaga, Andrés FelipeDelgado, JulianaGalindo, GustavoORIGINAL17.pdfapplication/pdf10902176https://repository.urosario.edu.co/bitstreams/c0abef9e-79d0-4599-b787-16d638854cfe/download640d1f09a537bb18819954330c731ea3MD51TEXT17.pdf.txt17.pdf.txtExtracted texttext/plain59364https://repository.urosario.edu.co/bitstreams/1d7c327b-408f-4bf0-9d99-a5eba85f106e/download8892f99cdc59ef4fd2cd4073e35bffd1MD52THUMBNAIL17.pdf.jpg17.pdf.jpgGenerated Thumbnailimage/jpeg4781https://repository.urosario.edu.co/bitstreams/2c19bde4-7397-4e08-a4ee-3fbaf999f238/download74a2a11c376bab191ef84a970f4472a4MD5310336/19053oai:repository.urosario.edu.co:10336/190532019-09-19 07:37:54.609585https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |