Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia

El objetivo general de este proyecto es desarrollar y aplicar enfoques innovadores relacionados con sensores de Observación Terrestre por satélite, desarrollar métodos analíticos y tecnologías para gestionar y procesar Big Data, proporcionando sistemas de monitoreo consistentes, transparentes, robus...

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Fecha de publicación:
2023
Institución:
Universidad del Rosario
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Repositorio EdocUR - U. Rosario
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spa
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oai:repository.urosario.edu.co:10336/43363
Acceso en línea:
https://repository.urosario.edu.co/handle/10336/43363
Palabra clave:
Sensoramiento remoto
Computación en la nube
Datos observación de la tierra
Radar de Apertura Sintetica
Deforestación
Monitoreo
Remote sensing
Cloud computing
Synthetic Aperture Radar
Earth Observations
Deforestation
Monitoring
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Attribution-NonCommercial-ShareAlike 4.0 International
id EDOCUR2_4cb5a291587482bc58c5bd47b57bb164
oai_identifier_str oai:repository.urosario.edu.co:10336/43363
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
dc.title.none.fl_str_mv Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
dc.title.TranslatedTitle.none.fl_str_mv Nuevos métodos y tecnologías para mejorar el monitoreo y la comprensión de la dinámica del uso y la cobertura del suelo basados en la observación terrestre por satélite. El caso del monitoreo forestal en Colombia
title Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
spellingShingle Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
Sensoramiento remoto
Computación en la nube
Datos observación de la tierra
Radar de Apertura Sintetica
Deforestación
Monitoreo
Remote sensing
Cloud computing
Synthetic Aperture Radar
Earth Observations
Deforestation
Monitoring
title_short Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
title_full Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
title_fullStr Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
title_full_unstemmed Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
title_sort Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
dc.contributor.advisor.none.fl_str_mv Clerici, Nicola
dc.subject.none.fl_str_mv Sensoramiento remoto
Computación en la nube
Datos observación de la tierra
Radar de Apertura Sintetica
Deforestación
Monitoreo
topic Sensoramiento remoto
Computación en la nube
Datos observación de la tierra
Radar de Apertura Sintetica
Deforestación
Monitoreo
Remote sensing
Cloud computing
Synthetic Aperture Radar
Earth Observations
Deforestation
Monitoring
dc.subject.keyword.none.fl_str_mv Remote sensing
Cloud computing
Synthetic Aperture Radar
Earth Observations
Deforestation
Monitoring
description El objetivo general de este proyecto es desarrollar y aplicar enfoques innovadores relacionados con sensores de Observación Terrestre por satélite, desarrollar métodos analíticos y tecnologías para gestionar y procesar Big Data, proporcionando sistemas de monitoreo consistentes, transparentes, robustos y rentables para proyectos destinados a reducir la deforestación y la degradación forestal. Este proyecto también diseñará un sistema de monitoreo forestal robusto, consistente y rentable, que integrará múltiples enfoques analíticos para proporcionar productos con valor agregado espacialmente explícitos a actores y usuarios involucrados en iniciativas para reducir la degradación forestal y la deforestación. Los objetivos específicos del proyecto son: 1. Desarrollar y aplicar una metodología para evaluar el cumplimiento de acuerdos de cero deforestación, aplicada a 2615 fincas ganaderas asociadas al proyecto Ganadería Colombiana Sostenible mediante el procesamiento de imágenes de radar de apertura sintética de banda L tipo phased array (PALSAR) de los Satélites de Observación Avanzada de la Tierra (ALOS). 2. Diseñar y evaluar una infraestructura de computación en la nube para la ingesta de big data de teledetección (gran volumen, gran velocidad, gran variedad) para el monitoreo forestal. La evaluación de la infraestructura digital o nube se basará en especificaciones técnicas y recursos financieros necesarios para estar completamente operativa. 3. Desarrollar e integrar en la infraestructura digital basada en la nube, enfoques analíticos y algoritmos para generar productos forestales específicos con valor agregado para múltiples actores y usuarios involucrados en iniciativas asociadas con la reducción de la degradación forestal y la deforestación.
publishDate 2023
dc.date.created.none.fl_str_mv 2023-09-07
dc.date.accessioned.none.fl_str_mv 2024-09-02T12:38:36Z
dc.date.available.none.fl_str_mv 2024-09-02T12:38:36Z
dc.type.none.fl_str_mv bachelorThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.document.none.fl_str_mv Trabajo de grado
dc.type.spa.none.fl_str_mv Trabajo de grado
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/43363
url https://repository.urosario.edu.co/handle/10336/43363
dc.language.iso.none.fl_str_mv spa
language spa
dc.rights.*.fl_str_mv Attribution-NonCommercial-ShareAlike 4.0 International
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.none.fl_str_mv Abierto (Texto Completo)
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
rights_invalid_str_mv Attribution-NonCommercial-ShareAlike 4.0 International
Abierto (Texto Completo)
http://creativecommons.org/licenses/by-nc-sa/4.0/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.none.fl_str_mv 81 pp
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad del Rosario
Universidad de Granada. Facultad de Filosofía y Letras
dc.publisher.department.none.fl_str_mv Escuela de Medicina y Ciencias de la Salud
dc.publisher.program.none.fl_str_mv Doctorado en Ciencias Biomédicas y Biológicas
publisher.none.fl_str_mv Universidad del Rosario
Universidad de Granada. Facultad de Filosofía y Letras
institution Universidad del Rosario
dc.source.bibliographicCitation.none.fl_str_mv Reiche, Johannes; Lucas, Richard; Mitchell, Anthea L.; Verbesselt, Jan; Hoekman, Dirk H.; Haarpaintner, Jörg; Kellndorfer, Josef M.; Rosenqvist, Ake; Lehmann, Eric A.; Woodcock, Curtis E.; Seifert, Frank Martin; Herold, Martin (2016) Combining satellite data for better tropical forest monitoring. En: Nature Climate Change. Vol. 6; No. 2; pp. 120 - 122; 17586798; Disponible en: http://dx.doi.org/10.1038/nclimate2919. Disponible en: 10.1038/nclimate2919.
Hansen, Matthew C.; Stehman, Stephen V.; Potapov, Peter V. (2010) Quantification of global gross forest cover loss. En: Proceedings of the National Academy of Sciences of the United States of America. Vol. 107; No. 19; pp. 8650 - 8655; 00278424; Disponible en: 10.1073/pnas.0912668107.
Onoda, Masami; Young, Oran R. (2017) Satellite earth observations and their impact on society and policy. : Springer Singapure; 978-981-10-3713-9;
Ustin, Susan L.; Middleton, Elizabeth M. (2021) Current and near-term advances in Earth observation for ecological applications. En: Ecological Processes. Vol. 10; No. 1; pp. 1 - 57; 21921709; Disponible en: 10.1186/s13717-020-00255-4.
Mitchell, Anthea L.; Rosenqvist, Ake; Mora, Brice (2017) Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+. En: Carbon Balance and Management. Vol. 12; No. 1; 17500680; Disponible en: 10.1186/s13021-017-0078-9.
Kasischke, Eric S.; Melack, John M.; Dobson, M. Craig (1997) The use of imaging radars for ecological applications. En: Remote Sensing of Environment. Vol. 59; No. 2; pp. 141 - 156; 00344257; Disponible en: 10.1016/S0034-4257(96)00148-4.
Eriksson, Leif E. B.; Fransson, Johan E. S.; Soja, Maciej J.; Santoro, Maurizio (2012) Backscatter signatures of wind-thrown forest in satellite SAR images. pp. 6435 - 6438; IEEE; 978-1-4673-1159-5 978-1-4673-1160-1 978-1-4673-1158-8; Consultado en: 2023/05/01/. Disponible en: http://ieeexplore.ieee.org/document/6352732/. Disponible en: 10.1109/IGARSS.2012.6352732.
Rüetschi, Marius; Small, David; Waser, Lars (2019) Rapid Detection of Windthrows Using Sentinel-1 C-Band SAR Data. En: Remote Sensing. Vol. 11; No. 2; pp. 115 2072-4292; Consultado en: 2023/05/01/. Disponible en: http://www.mdpi.com/2072-4292/11/2/115. Disponible en: 10.3390/rs11020115.
M. Susan Moran (1999) Principles and Applications of Imaging Radar, Manual of Remote Sensing, 3rd Edition, Volume 2. En: Eos, Transactions American Geophysical Union. Vol. 80; pp. 67 - 67–67; Consultado en: 2023/05/01/. Disponible en: https://explore.openaire.eu/search/publication?articleId=doi_________::4e8ab132e4212e03780d8352c235c416.
Lopes, A.; Touzi, R.; Nezry, E. (1990) Adaptive speckle filters and scene heterogeneity. En: IEEE Trans. Geosci. Remote Sensing. Vol. 28; No. 6; pp. 992 - 1000; 01962892; Consultado en: 2023/04/30/. Disponible en: http://ieeexplore.ieee.org/document/62623/. Disponible en: 10.1109/36.62623.
Werner, Charles; Wegmüller, Urs; Strozzi, Tazio; Wiesmann, Andreas (2000) GAMMA SAR and interferometric processing software. En: European Space Agency, (Special Publication) ESA SP. No. 461; pp. 211 - 219; 03796566;
Olofsson, Pontus; Foody, Giles M.; Stehman, Stephen V.; Woodcock, Curtis E. (2013) Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. En: Remote Sensing of Environment. Vol. 129; pp. 122 - 131; 00344257; Disponible en: http://dx.doi.org/10.1016/j.rse.2012.10.031. Disponible en: 10.1016/j.rse.2012.10.031.
Pal, Mahesh (2003) Random forests for land cover classification.
Galindo, G; Espejo, O. J; Rubiano, J. C; Vergara, L. K; Cabrera, E (2014) Protocolo de procesamiento digital de imágenes para la cuantificación de la deforestacion en Colombia V.2. En: IDEAM, Instituto de Hidrología, Metereología y Estudios Ambientales. pp. 1 - 225; Disponible en: 10.4324/9781315780245.
Tatsumi, Kenichi; Yamashiki, Yosuke; Canales Torres, Miguel Angel; Taipe, Cayo Leonidas Ramos (2015) Crop classification of upland fields using Random forest of time-series Landsat 7 ETM+ data. En: Computers and Electronics in Agriculture. Vol. 115; pp. 171 - 179; 01681699; Consultado en: 2023/04/23/. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0168169915001234. Disponible en: 10.1016/j.compag.2015.05.001.
Wang, Jie; Zhao, Yuanyuan; Li, Congcong; Yu, Le; Liu, Desheng; Gong, Peng (2015) Mapping global land cover in 2001 and 2010 with spatial-temporal consistency at 250m resolution. En: ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 103; pp. 38 - 47; 09242716; Consultado en: 2023/04/23/. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0924271614000707. Disponible en: 10.1016/j.isprsjprs.2014.03.007.
Nielsen, Allan a.; Conradsen, Knut.; Simpson, J., James (1998) Multivariate Alteration Detection (MAD) in Multispectral, Bi-temporal Image Data: A new approach to change detection studies. En: Technical Report. Vol. 1; No. 97; pp. 1 - 28; 1098-6596; Disponible en: http://orbit.dtu.dk/en/publications/multivariate-alteration-detection-mad-in-multispectral-bitemporal-image-data-a-new-approach-to-change-detction-studies%288324cbcc-e13d-4770-b52b-c12ed66a4ba2%29.html.
Asner, Gregory P. (2009) Automated mapping of tropical deforestation and forest degradation: CLASlite. En: Journal of Applied Remote Sensing. Vol. 3; No. 1; pp. 033543 1931-3195; Disponible en: 10.1117/1.3223675.
Li, Jian; Roy, David P. (2017) A global analysis of Sentinel-2a, Sentinel-2b and Landsat-8 data revisit intervals and implications for terrestrial monitoring. En: Remote Sensing. Vol. 9; No. 9; 20724292; Disponible en: 10.3390/rs9090902.
Helder, Dennis L.; Karki, Sadhana; Bhatt, Rajendra; Micijevic, Esad; Aaron, David; Jasinski, Benjamin (2012) Radiometric calibration of the jandsat MSS sensor series. En: IEEE Transactions on Geoscience and Remote Sensing. Vol. 50; No. 6; pp. 2380 - 2399; 01962892; Disponible en: 10.1109/TGRS.2011.2171351.
Masek, Jeffrey G.; Wulder, Michael A.; Markham, Brian; McCorkel, Joel; Crawford, Christopher J.; Storey, James; Jenstrom, Del T. (2020) Landsat 9: Empowering open science and applications through continuity. En: Remote Sensing of Environment. Vol. 248; No. April; 00344257; Disponible en: 10.1016/j.rse.2020.111968.
Koch, Alexander; Kaplan, Jed O. (2022) Tropical forest restoration under future climate change. En: Nat. Clim. Chang. Vol. 12; No. 3; pp. 279 - 283; 1758-678X, 1758-6798; Consultado en: 2023/05/15/. Disponible en: https://www.nature.com/articles/s41558-022-01289-6. Disponible en: 10.1038/s41558-022-01289-6.
Pedraza, Carlos; Clerici, Nicola; Forero, Cristian Fabián; Melo, América; Navarrete, Diego; Lizcano, Diego; Zuluaga, Andrés Felipe; Delgado, Juliana; Galindo, Gustavo (2018) Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR. En: Remote Sensing. Vol. 10; No. 9; pp. 1 - 8; 20724292; Disponible en: 10.3390/rs10091464.
Quiñones, Marcela J.; Vissers, Martin; Pacheco-Pascaza, Ana María; Flórez, Carlos; Estupiñán-Suárez, Lina Maria; César, Aponte; Úrsula, Jaramillo; Claudia, Huertas; Dirk, Hoekman (2016) Un enfoque ecosistémico para el análisis de una serie densa de tiempo de imágenes de radar Alos PALSAR, para el mapeo de zonas inundadas en el territorio continental colombiano. En: Biotacol. Vol. 16; No. 3; pp. 63 - 84; 01245376; Consultado en: 2023/05/13/. Disponible en: http://hdl.handle.net/20.500.11761/9353. Disponible en: 10.21068/c2016s01a04.
Hoekman, Dirk H.; Quiñones, Marcela J. (2002) Biophysical forest type characterization in the Colombian Amazon by airborne polarimetric SAR. En: IEEE Transactions on Geoscience and Remote Sensing. Vol. 40; No. 6; pp. 1288 - 1300;
Anaya, Jesús A.; Rodríguez-Buriticá, Susana; Londoño, María C. (2023) Clasificación de cobertura vegetal con resolución espacial de 10 metros en bosques del Caribe colombiano basado en misiones Sentinel 1 y 2. En: Rev. Teledetec. No. 61; pp. 29 - 41; 1988-8740, 1133-0953; Consultado en: 2023/05/13/. Disponible en: https://polipapers.upv.es/index.php/raet/article/view/17655. Disponible en: 10.4995/raet.2023.17655.
Hoekman, D.H.; Quinones, M.J. (2000) Land cover type and biomass classification using AirSAR data for evaluation of monitoring scenarios in the Colombian Amazon. En: IEEE Trans. Geosci. Remote Sensing. Vol. 38; No. 2; pp. 685 - 696; 0196-2892, 1558-0644; Consultado en: 2023/05/14/. Disponible en: https://ieeexplore.ieee.org/document/841998/. Disponible en: 10.1109/36.841998.
Hoekman, D.H.; Quinones, M.J. (1997) Land cover type and forest biomass assessment in the Colombian Amazon. En: IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing. Vol. 4;
Ayala, Carlos Flórez; Suárez, Lina M Estupiñán; Rojas, Sergio; Aponte, Cesar (2015) de Colombia Identification and mapping of Colombian inland wetlands. pp. 1 - 22;
Estupinan-Suarez, L.M.; Florez-Ayala, C.; Quinones, M.J.; Pacheco, A.M.; Santos, A.C. (2015) Detection and characterizacion of Colombian wetlands using Alos Palsar and MODIS imagery. En: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. Vol. XL-7/W3; pp. 375 - 382; 2194-9034; Consultado en: 2023/05/13/. Disponible en: https://isprs-archives.copernicus.org/articles/XL-7-W3/375/2015/. Disponible en: 10.5194/isprsarchives-XL-7-W3-375-2015.
Palomino-Ángel, Sebastián; Anaya-Acevedo, Jesús A.; Simard, Marc; Liao, Tien-Hao; Jaramillo, Fernando (2019) Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry. En: Water. Vol. 11; No. 5; pp. 875 2073-4441; Consultado en: 2023/05/13/. Disponible en: https://www.mdpi.com/2073-4441/11/5/875. Disponible en: 10.3390/w11050875.
González, J.J.; Etter, A.A.; Sarmiento, A.H.; Orrego, S.A.; Ramírez, C.; Cabrera, E.; Vargas, D.; Galindo, G.; García, M.C.; Ordoñez, M.F. (2011) Análisis de tendencias y patrones espaciales de deforestación en Colombia. pp. 64 Bogotá D.C., Colombia: Instituto de Hidrología, Meteorología y Estudios Ambientales-IDEAM;
Persaud, H.; Cabrera, I (2021) Eficiencia de las imágenes de radar para el monitoreo a tiempo casi real de bosques tropicales en Guyana. En: Scielo.Org.Pe. Vol. 28; No. 3; pp. 577 - 592; Disponible en: http://www.scielo.org.pe/scielo.php?pid=S2413-32992021000300577&script=sci_arttext.
Lucas, Richard; Rebelo, Lisa Maria; Fatoyinbo, Lola; Rosenqvist, Ake; Itoh, Takuya; Shimada, Masanobu; Simard, Marc; Souza-Filho, Pedro Walfir; Thomas, Nathan; Trettin, Carl; Accad, Arnon; Carreiras, Joao; Hilarides, Lammert (2014) Contribution of L-band SAR to systematic global mangrove monitoring. En: Marine and Freshwater Research. Vol. 65; No. 7; pp. 589 - 603; 13231650; Disponible en: 10.1071/MF13177.
Motohka, Takeshi; Shimada, Masanobu; Uryu, Yumiko; Setiabudi, Budi (2014) Using time series PALSAR gamma nought mosaics for automatic detection of tropical deforestation: A test study in Riau, Indonesia. En: Remote Sensing of Environment. Vol. 155; pp. 79 - 88; 00344257; Disponible en: http://dx.doi.org/10.1016/j.rse.2014.04.012. Disponible en: 10.1016/j.rse.2014.04.012.
Prudente, Victor Hugo Rohden; Martins, Vitor Souza; Vieira, Denis Corte; Silva, Nildson Rodrigues de França e.; Adami, Marcos; Sanches, Ieda Del Arco (2020) Limitations of cloud cover for optical remote sensing of agricultural areas across South America. En: Remote Sensing Applications: Society and Environment. Vol. 20; No. September; pp. 100414 23529385; Disponible en: https://doi.org/10.1016/j.rsase.2020.100414. Disponible en: 10.1016/j.rsase.2020.100414.
van Oostende, Marit; Hieronymi, Martin; Krasemann, Hajo; Baschek, Burkard; Röttgers, Rüdiger (2022) Correction of inter-mission inconsistencies in merged ocean colour satellite data. En: Frontiers in Remote Sensing. Vol. 3; No. July; pp. 1 - 17; Disponible en: 10.3389/frsen.2022.882418.
Joshi, Neha; Baumann, Matthias; Ehammer, Andrea; Fensholt, Rasmus; Grogan, Kenneth; Hostert, Patrick; Jepsen, Martin Rudbeck; Kuemmerle, Tobias; Meyfroidt, Patrick; Mitchard, Edward T.A.; Reiche, Johannes; Ryan, Casey M.; Waske, Björn (2016) A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring. En: Remote Sensing. Vol. 8; No. 1; pp. 1 - 23; 20724292; Disponible en: 10.3390/rs8010070.
Joshi, Neha; Mitchard, Edward T.A.; Woo, Natalia; Torres, Jorge; Moll-Rocek, Julian; Ehammer, Andrea; Collins, Murray; Jepsen, Martin R.; Fensholt, Rasmus (2015) Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data. En: Environmental Research Letters. Vol. 10; No. 3; pp. 34014 17489326; Disponible en: http://dx.doi.org/10.1088/1748-9326/10/3/034014. Disponible en: 10.1088/1748-9326/10/3/034014.
Murillo-Sandoval, Paulo J.; Kilbride, John; Tellman, Elizabeth; Wrathall, David; Van Den Hoek, Jamon; Kennedy, Robert E. (2023) The post-conflict expansion of coca farming and illicit cattle ranching in Colombia. pp. 1 - 10; Nature Publishing Group UK; Disponible en: https://doi.org/10.1038/s41598-023-28918-0.
Anaya, Jesús A.; Gutiérrez-Vélez, Víctor H.; Pacheco-Pascagaza, Ana M.; Palomino-Ángel, Sebastián; Han, Natasha; Balzter, Heiko (2020) Drivers of Forest Loss in a Megadiverse Hotspot on the Pacific Coast of Colombia. En: Remote Sensing. Vol. 12; No. 8; pp. 1235 2072-4292; Consultado en: 2023/05/14/. Disponible en: https://www.mdpi.com/2072-4292/12/8/1235. Disponible en: 10.3390/rs12081235.
Lukas Emele Anke Herold, Martin Cames, Anne Siemons; Vanessa Cook (Öko-Institut e.V.) (2013) The Development of Climate Negotiations in View of Warsaw (COP 19). : European Parliamentary Research Service; Disponible en: https://policycommons.net/artifacts/1340275/the-development-of-climate-negotiations-in-view-of-warsaw-cop-19/.
Jafarbiglu, Hamid; Pourreza, Alireza (2023) Impact of sun-view geometry on canopy spectral reflectance variability. En: ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 196; pp. 270 - 286; 09242716; Consultado en: 2023/06/27/21:56:30. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0924271622003161. Disponible en: 10.1016/j.isprsjprs.2022.12.002.
Camarretta, Nicolò; Harrison, Peter A.; Bailey, Tanya; Potts, Brad; Lucieer, Arko; Davidson, Neil; Hunt, Mark (2020) Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches. En: New Forests. Vol. 51; No. 4; pp. 573 - 596; 0169-4286, 1573-5095; Consultado en: 2023/06/28/19:03:09. Disponible en: http://link.springer.com/10.1007/s11056-019-09754-5. Disponible en: 10.1007/s11056-019-09754-5.
Asner, Gregory P. (2009) Automated mapping of tropical deforestation and forest degradation: CLASlite. En: Journal of Applied Remote Sensing. Vol. 3; No. 1; pp. 033543 1931-3195; Disponible en: 10.1117/1.3223675.
Microsoft Open Source; McFarland, Matt; Emanuele, Rob; Morris, Dan; Augspurger, Tom (2022) microsoft/PlanetaryComputer: October 2022. : Zenodo; Disponible en: https://doi.org/10.5281/zenodo.7261897.
Urrea, Viviana; Ochoa, Andrés; Mesa, Oscar (2019) Seasonality of Rainfall in Colombia. En: Water Resources Research. Vol. 55; No. 5; pp. 4149 - 4162; 0043-1397, 1944-7973; Consultado en: 2023/08/14/19:37:26. Disponible en: https://onlinelibrary.wiley.com/doi/abs/10.1029/2018WR023316. Disponible en: 10.1029/2018WR023316.
Storey, James; Scaramuzza, Pasquale; Schmidt, Gail; Barsi, Julia (2005) LANDSAT 7 SCAN LINE CORRECTOR-OFF GAP-FILLED PRODUCT DEVELOPMENT.
Rahaman, Khan; Hassan, Quazi; Ahmed, M. (2017) Pan-Sharpening of Landsat-8 Images and Its Application in Calculating Vegetation Greenness and Canopy Water Contents. En: ISPRS International Journal of Geo-Information. Vol. 6; No. 6; pp. 168 2220-9964; Consultado en: 2024/03/05/00:52:29. Disponible en: https://www.mdpi.com/2220-9964/6/6/168. Disponible en: 10.3390/ijgi6060168.
Xie, Lifeng; Wu, Weicheng; Huang, Xiaolan; Ou, Penghui; Lin, Ziyu; Zhiling, Wang; Song, Yong; Lang, Tao; Huangfu, Wenchao; Zhang, Yang; Zhou, Xiaoting; Fu, Xiao; Li, Jie; Jiang, Jingheng; Zhang, Ming; Zhang, Zhenjiang; Qin, Yaozu; Peng, Shanling; Shao, Chongjian; Bai, Yonghui (2020) Mining and Restoration Monitoring of Rare Earth Element (REE) Exploitation by New Remote Sensing Indicators in Southern Jiangxi, China. En: Remote Sensing. Vol. 12; No. 21; pp. 3558 2072-4292; Consultado en: 2024/03/04/21:09:06. Disponible en: https://www.mdpi.com/2072-4292/12/21/3558. Disponible en: 10.3390/rs12213558.
Reif, Molly K; Theel, Heather J (2017) Remote sensing for restoration ecology: Application for restoring degraded, damaged, transformed, or destroyed ecosystems. En: Integrated Environmental Assessment and Management. Vol. 13; No. 4; pp. 614 - 630; 1551-3777, 1551-3793; Consultado en: 2024/03/04/19:50:16. Disponible en: https://setac.onlinelibrary.wiley.com/doi/10.1002/ieam.1847. Disponible en: 10.1002/ieam.1847.
Klemas, Victor (2013) Using Remote Sensing to Select and Monitor Wetland Restoration Sites: An Overview. En: Journal of Coastal Research. Vol. 289; pp. 958 - 970; 0749-0208, 1551-5036; Consultado en: 2024/03/04/19:44:58. Disponible en: http://www.bioone.org/doi/abs/10.2112/JCOASTRES-D-12-00170.1. Disponible en: 10.2112/JCOASTRES-D-12-00170.1.
Shuman, Craig S.; Ambrose, Richard F. (2003) A Comparison of Remote Sensing and Ground‐Based Methods for Monitoring Wetland Restoration Success. En: Restoration Ecology. Vol. 11; No. 3; pp. 325 - 333; 1061-2971, 1526-100X; Consultado en: 2024/03/04/19:44:45. Disponible en: https://onlinelibrary.wiley.com/doi/10.1046/j.1526-100X.2003.00182.x. Disponible en: 10.1046/j.1526-100X.2003.00182.x.
Camarretta, Nicolò; Harrison, Peter A.; Bailey, Tanya; Potts, Brad; Lucieer, Arko; Davidson, Neil; Hunt, Mark (2020) Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches. En: New Forests. Vol. 51; No. 4; pp. 573 - 596; 0169-4286, 1573-5095; Consultado en: 2024/03/04/19:44:27. Disponible en: http://link.springer.com/10.1007/s11056-019-09754-5. Disponible en: 10.1007/s11056-019-09754-5.
Lewis, Simon L; Edwards, David P; Galbraith, David (2015) Increasing human dominance of tropical forests. En: Science. Vol. 349; No. 6250; pp. 827 - 832; 10959203; Disponible en: 10.1126/science.aaa9932.
Shimada, Masanobu; Itoh, Takuya; Motooka, Takeshi; Watanabe, Manabu; Shiraishi, Tomohiro; Thapa, Rajesh; Lucas, Richard (2014) New global forest/non-forest maps from ALOS PALSAR data (2007-2010). En: Remote Sensing of Environment. Vol. 155; pp. 13 - 31; 00344257; Disponible en: http://dx.doi.org/10.1016/j.rse.2014.04.014. Disponible en: 10.1016/j.rse.2014.04.014.
Rodriguez, N.; Armenteras, D.; Morales, M.; Romero, M. (2006) Ecosistemas de los Andes Colombianos. pp. 154 p Bogotá, Colombia: Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 958-8151-30-9;
Teluguntla, Pardhasaradhi; Thenkabail, Prasad S; Oliphant, Adam; Xiong, Jun; Gumma, Murali Krishna; Congalton, Russell G.; Yadav, Kamini; Huete, Alfredo (2018) A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform. En: ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 144; pp. 325 - 340; 09242716; Consultado en: 2023/04/23/17:59:24. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0924271618302090. Disponible en: 10.1016/j.isprsjprs.2018.07.017.
Deng, J. S.; Wang, K.; Deng, Y. H.; Qi, G. J. (2008) PCA‐based land‐use change detection and analysis using multitemporal and multisensor satellite data. En: International Journal of Remote Sensing. Vol. 29; No. 16; pp. 4823 - 4838; 0143-1161, 1366-5901; Consultado en: 2024/03/11/14:46:27. Disponible en: https://www.tandfonline.com/doi/full/10.1080/01431160801950162. Disponible en: 10.1080/01431160801950162.
DeFries, Ruth; Achard, Frédéric; Brown, Sandra; Herold, Martin; Murdiyarso, Daniel; Schlamadinger, Bernhard; De Souza, Carlos (2007) Earth observations for estimating greenhouse gas emissions from deforestation in developing countries. En: Environmental Science & Policy. Vol. 10; No. 4; pp. 385 - 394; 14629011; Consultado en: 2024/03/11/14:47:35. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S146290110700024X. Disponible en: 10.1016/j.envsci.2007.01.010.
Ruiz-Ramos, Javier; Marino, Armando; Boardman, Carl; Suarez, Juan (2020) Continuous forest monitoring using cumulative sums of sentinel-1 timeseries. En: Remote Sensing. Vol. 12; No. 18; 20724292; Disponible en: 10.3390/RS12183061.
Flores, Africa; K. Herndon; Rajesh Thapa; Emil Cherrington (2019) Synthetic Aperture Radar (SAR) Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation. Consultado en: 2023/04/30/22:04:00. Disponible en: https://gis1.servirglobal.net/TrainingMaterials/SAR/SARHB_FullRes.pdf. Disponible en: 10.25966/NR2C-S697.
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spelling Clerici, Nicola450811600Pedraza Peñaloza, Carlos AlbertoDoctor en Ciencias Biomédicas y BiológicasDoctoradoFull time7b3a9d98-e084-4451-b12e-058e0ba5d739-12024-09-02T12:38:36Z2024-09-02T12:38:36Z2023-09-07El objetivo general de este proyecto es desarrollar y aplicar enfoques innovadores relacionados con sensores de Observación Terrestre por satélite, desarrollar métodos analíticos y tecnologías para gestionar y procesar Big Data, proporcionando sistemas de monitoreo consistentes, transparentes, robustos y rentables para proyectos destinados a reducir la deforestación y la degradación forestal. Este proyecto también diseñará un sistema de monitoreo forestal robusto, consistente y rentable, que integrará múltiples enfoques analíticos para proporcionar productos con valor agregado espacialmente explícitos a actores y usuarios involucrados en iniciativas para reducir la degradación forestal y la deforestación. Los objetivos específicos del proyecto son: 1. Desarrollar y aplicar una metodología para evaluar el cumplimiento de acuerdos de cero deforestación, aplicada a 2615 fincas ganaderas asociadas al proyecto Ganadería Colombiana Sostenible mediante el procesamiento de imágenes de radar de apertura sintética de banda L tipo phased array (PALSAR) de los Satélites de Observación Avanzada de la Tierra (ALOS). 2. Diseñar y evaluar una infraestructura de computación en la nube para la ingesta de big data de teledetección (gran volumen, gran velocidad, gran variedad) para el monitoreo forestal. La evaluación de la infraestructura digital o nube se basará en especificaciones técnicas y recursos financieros necesarios para estar completamente operativa. 3. Desarrollar e integrar en la infraestructura digital basada en la nube, enfoques analíticos y algoritmos para generar productos forestales específicos con valor agregado para múltiples actores y usuarios involucrados en iniciativas asociadas con la reducción de la degradación forestal y la deforestación.The general objective of this project is to develop and apply innovative approaches related to satellite Earth Observation sensors, develop analytical methods and technologies to manage and process Big Data, providing consistent, transparent, robust, and cost-efficient monitoring systems for projects aimed to reduce deforestation and forest degradation. This project will also design a robust, consistent, and cost-efficient forest monitoring system, that will integrate multiple analytical approaches to provide spatially explicit value-added products to actors and users involved in initiatives to reduce forest degradation and deforestation. Specific objectives of the project are: 1. Develop and apply a methodology to assess the compliance to zero deforestation agreements, applied to 2615 livestock farms associated with the Sustainable Colombian Livestock project through the processing of Advanced Land Observations Satellites (ALOS) Phased Array Type L-band Synthetic Aperture Radar (PALSAR) imagery. 2. Design and evaluate a cloud-based computing infrastructure to ingest remote sensing big data (big volume, big velocity, big variety)for forest monitoring. The assessment of the digital infrastructure or cloud will be based on technical specifications and financial resources needed to be fully operational. 3. Develop and integrate in the cloud-based digital infrastructure, analytical approaches and algorithms to generate specific value-added forest products for multiple actor and users involved in initiatives associated to reduction of forest degradation and deforestation.81 ppapplication/pdfhttps://repository.urosario.edu.co/handle/10336/43363spaUniversidad del RosarioUniversidad de Granada. Facultad de Filosofía y LetrasEscuela de Medicina y Ciencias de la SaludDoctorado en Ciencias Biomédicas y BiológicasAttribution-NonCommercial-ShareAlike 4.0 InternationalAbierto (Texto Completo)PARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe.http://creativecommons.org/licenses/by-nc-sa/4.0/http://purl.org/coar/access_right/c_abf2Reiche, Johannes; Lucas, Richard; Mitchell, Anthea L.; Verbesselt, Jan; Hoekman, Dirk H.; Haarpaintner, Jörg; Kellndorfer, Josef M.; Rosenqvist, Ake; Lehmann, Eric A.; Woodcock, Curtis E.; Seifert, Frank Martin; Herold, Martin (2016) Combining satellite data for better tropical forest monitoring. En: Nature Climate Change. Vol. 6; No. 2; pp. 120 - 122; 17586798; Disponible en: http://dx.doi.org/10.1038/nclimate2919. Disponible en: 10.1038/nclimate2919.Hansen, Matthew C.; Stehman, Stephen V.; Potapov, Peter V. (2010) Quantification of global gross forest cover loss. En: Proceedings of the National Academy of Sciences of the United States of America. Vol. 107; No. 19; pp. 8650 - 8655; 00278424; Disponible en: 10.1073/pnas.0912668107.Onoda, Masami; Young, Oran R. (2017) Satellite earth observations and their impact on society and policy. : Springer Singapure; 978-981-10-3713-9;Ustin, Susan L.; Middleton, Elizabeth M. (2021) Current and near-term advances in Earth observation for ecological applications. En: Ecological Processes. Vol. 10; No. 1; pp. 1 - 57; 21921709; Disponible en: 10.1186/s13717-020-00255-4.Mitchell, Anthea L.; Rosenqvist, Ake; Mora, Brice (2017) Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+. En: Carbon Balance and Management. Vol. 12; No. 1; 17500680; Disponible en: 10.1186/s13021-017-0078-9.Kasischke, Eric S.; Melack, John M.; Dobson, M. Craig (1997) The use of imaging radars for ecological applications. En: Remote Sensing of Environment. Vol. 59; No. 2; pp. 141 - 156; 00344257; Disponible en: 10.1016/S0034-4257(96)00148-4.Eriksson, Leif E. B.; Fransson, Johan E. S.; Soja, Maciej J.; Santoro, Maurizio (2012) Backscatter signatures of wind-thrown forest in satellite SAR images. pp. 6435 - 6438; IEEE; 978-1-4673-1159-5 978-1-4673-1160-1 978-1-4673-1158-8; Consultado en: 2023/05/01/. Disponible en: http://ieeexplore.ieee.org/document/6352732/. Disponible en: 10.1109/IGARSS.2012.6352732.Rüetschi, Marius; Small, David; Waser, Lars (2019) Rapid Detection of Windthrows Using Sentinel-1 C-Band SAR Data. En: Remote Sensing. Vol. 11; No. 2; pp. 115 2072-4292; Consultado en: 2023/05/01/. Disponible en: http://www.mdpi.com/2072-4292/11/2/115. Disponible en: 10.3390/rs11020115.M. Susan Moran (1999) Principles and Applications of Imaging Radar, Manual of Remote Sensing, 3rd Edition, Volume 2. En: Eos, Transactions American Geophysical Union. Vol. 80; pp. 67 - 67–67; Consultado en: 2023/05/01/. Disponible en: https://explore.openaire.eu/search/publication?articleId=doi_________::4e8ab132e4212e03780d8352c235c416.Lopes, A.; Touzi, R.; Nezry, E. (1990) Adaptive speckle filters and scene heterogeneity. En: IEEE Trans. Geosci. Remote Sensing. Vol. 28; No. 6; pp. 992 - 1000; 01962892; Consultado en: 2023/04/30/. Disponible en: http://ieeexplore.ieee.org/document/62623/. Disponible en: 10.1109/36.62623.Werner, Charles; Wegmüller, Urs; Strozzi, Tazio; Wiesmann, Andreas (2000) GAMMA SAR and interferometric processing software. En: European Space Agency, (Special Publication) ESA SP. No. 461; pp. 211 - 219; 03796566;Olofsson, Pontus; Foody, Giles M.; Stehman, Stephen V.; Woodcock, Curtis E. (2013) Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. En: Remote Sensing of Environment. Vol. 129; pp. 122 - 131; 00344257; Disponible en: http://dx.doi.org/10.1016/j.rse.2012.10.031. Disponible en: 10.1016/j.rse.2012.10.031.Pal, Mahesh (2003) Random forests for land cover classification. Galindo, G; Espejo, O. J; Rubiano, J. C; Vergara, L. K; Cabrera, E (2014) Protocolo de procesamiento digital de imágenes para la cuantificación de la deforestacion en Colombia V.2. En: IDEAM, Instituto de Hidrología, Metereología y Estudios Ambientales. pp. 1 - 225; Disponible en: 10.4324/9781315780245.Tatsumi, Kenichi; Yamashiki, Yosuke; Canales Torres, Miguel Angel; Taipe, Cayo Leonidas Ramos (2015) Crop classification of upland fields using Random forest of time-series Landsat 7 ETM+ data. En: Computers and Electronics in Agriculture. Vol. 115; pp. 171 - 179; 01681699; Consultado en: 2023/04/23/. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0168169915001234. Disponible en: 10.1016/j.compag.2015.05.001.Wang, Jie; Zhao, Yuanyuan; Li, Congcong; Yu, Le; Liu, Desheng; Gong, Peng (2015) Mapping global land cover in 2001 and 2010 with spatial-temporal consistency at 250m resolution. En: ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 103; pp. 38 - 47; 09242716; Consultado en: 2023/04/23/. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0924271614000707. Disponible en: 10.1016/j.isprsjprs.2014.03.007.Nielsen, Allan a.; Conradsen, Knut.; Simpson, J., James (1998) Multivariate Alteration Detection (MAD) in Multispectral, Bi-temporal Image Data: A new approach to change detection studies. En: Technical Report. Vol. 1; No. 97; pp. 1 - 28; 1098-6596; Disponible en: http://orbit.dtu.dk/en/publications/multivariate-alteration-detection-mad-in-multispectral-bitemporal-image-data-a-new-approach-to-change-detction-studies%288324cbcc-e13d-4770-b52b-c12ed66a4ba2%29.html.Asner, Gregory P. (2009) Automated mapping of tropical deforestation and forest degradation: CLASlite. En: Journal of Applied Remote Sensing. Vol. 3; No. 1; pp. 033543 1931-3195; Disponible en: 10.1117/1.3223675.Li, Jian; Roy, David P. (2017) A global analysis of Sentinel-2a, Sentinel-2b and Landsat-8 data revisit intervals and implications for terrestrial monitoring. En: Remote Sensing. Vol. 9; No. 9; 20724292; Disponible en: 10.3390/rs9090902.Helder, Dennis L.; Karki, Sadhana; Bhatt, Rajendra; Micijevic, Esad; Aaron, David; Jasinski, Benjamin (2012) Radiometric calibration of the jandsat MSS sensor series. En: IEEE Transactions on Geoscience and Remote Sensing. Vol. 50; No. 6; pp. 2380 - 2399; 01962892; Disponible en: 10.1109/TGRS.2011.2171351.Masek, Jeffrey G.; Wulder, Michael A.; Markham, Brian; McCorkel, Joel; Crawford, Christopher J.; Storey, James; Jenstrom, Del T. (2020) Landsat 9: Empowering open science and applications through continuity. En: Remote Sensing of Environment. Vol. 248; No. April; 00344257; Disponible en: 10.1016/j.rse.2020.111968.Koch, Alexander; Kaplan, Jed O. (2022) Tropical forest restoration under future climate change. En: Nat. Clim. Chang. Vol. 12; No. 3; pp. 279 - 283; 1758-678X, 1758-6798; Consultado en: 2023/05/15/. Disponible en: https://www.nature.com/articles/s41558-022-01289-6. Disponible en: 10.1038/s41558-022-01289-6.Pedraza, Carlos; Clerici, Nicola; Forero, Cristian Fabián; Melo, América; Navarrete, Diego; Lizcano, Diego; Zuluaga, Andrés Felipe; Delgado, Juliana; Galindo, Gustavo (2018) Zero deforestation agreement assessment at farm level in Colombia using ALOS PALSAR. En: Remote Sensing. Vol. 10; No. 9; pp. 1 - 8; 20724292; Disponible en: 10.3390/rs10091464.Quiñones, Marcela J.; Vissers, Martin; Pacheco-Pascaza, Ana María; Flórez, Carlos; Estupiñán-Suárez, Lina Maria; César, Aponte; Úrsula, Jaramillo; Claudia, Huertas; Dirk, Hoekman (2016) Un enfoque ecosistémico para el análisis de una serie densa de tiempo de imágenes de radar Alos PALSAR, para el mapeo de zonas inundadas en el territorio continental colombiano. En: Biotacol. Vol. 16; No. 3; pp. 63 - 84; 01245376; Consultado en: 2023/05/13/. Disponible en: http://hdl.handle.net/20.500.11761/9353. Disponible en: 10.21068/c2016s01a04.Hoekman, Dirk H.; Quiñones, Marcela J. (2002) Biophysical forest type characterization in the Colombian Amazon by airborne polarimetric SAR. En: IEEE Transactions on Geoscience and Remote Sensing. Vol. 40; No. 6; pp. 1288 - 1300;Anaya, Jesús A.; Rodríguez-Buriticá, Susana; Londoño, María C. (2023) Clasificación de cobertura vegetal con resolución espacial de 10 metros en bosques del Caribe colombiano basado en misiones Sentinel 1 y 2. En: Rev. Teledetec. No. 61; pp. 29 - 41; 1988-8740, 1133-0953; Consultado en: 2023/05/13/. Disponible en: https://polipapers.upv.es/index.php/raet/article/view/17655. Disponible en: 10.4995/raet.2023.17655.Hoekman, D.H.; Quinones, M.J. (2000) Land cover type and biomass classification using AirSAR data for evaluation of monitoring scenarios in the Colombian Amazon. En: IEEE Trans. Geosci. Remote Sensing. Vol. 38; No. 2; pp. 685 - 696; 0196-2892, 1558-0644; Consultado en: 2023/05/14/. Disponible en: https://ieeexplore.ieee.org/document/841998/. Disponible en: 10.1109/36.841998.Hoekman, D.H.; Quinones, M.J. (1997) Land cover type and forest biomass assessment in the Colombian Amazon. En: IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing. Vol. 4;Ayala, Carlos Flórez; Suárez, Lina M Estupiñán; Rojas, Sergio; Aponte, Cesar (2015) de Colombia Identification and mapping of Colombian inland wetlands. pp. 1 - 22;Estupinan-Suarez, L.M.; Florez-Ayala, C.; Quinones, M.J.; Pacheco, A.M.; Santos, A.C. (2015) Detection and characterizacion of Colombian wetlands using Alos Palsar and MODIS imagery. En: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. Vol. XL-7/W3; pp. 375 - 382; 2194-9034; Consultado en: 2023/05/13/. Disponible en: https://isprs-archives.copernicus.org/articles/XL-7-W3/375/2015/. Disponible en: 10.5194/isprsarchives-XL-7-W3-375-2015.Palomino-Ángel, Sebastián; Anaya-Acevedo, Jesús A.; Simard, Marc; Liao, Tien-Hao; Jaramillo, Fernando (2019) Analysis of Floodplain Dynamics in the Atrato River Colombia Using SAR Interferometry. En: Water. Vol. 11; No. 5; pp. 875 2073-4441; Consultado en: 2023/05/13/. Disponible en: https://www.mdpi.com/2073-4441/11/5/875. Disponible en: 10.3390/w11050875.González, J.J.; Etter, A.A.; Sarmiento, A.H.; Orrego, S.A.; Ramírez, C.; Cabrera, E.; Vargas, D.; Galindo, G.; García, M.C.; Ordoñez, M.F. (2011) Análisis de tendencias y patrones espaciales de deforestación en Colombia. pp. 64 Bogotá D.C., Colombia: Instituto de Hidrología, Meteorología y Estudios Ambientales-IDEAM;Persaud, H.; Cabrera, I (2021) Eficiencia de las imágenes de radar para el monitoreo a tiempo casi real de bosques tropicales en Guyana. En: Scielo.Org.Pe. Vol. 28; No. 3; pp. 577 - 592; Disponible en: http://www.scielo.org.pe/scielo.php?pid=S2413-32992021000300577&script=sci_arttext.Lucas, Richard; Rebelo, Lisa Maria; Fatoyinbo, Lola; Rosenqvist, Ake; Itoh, Takuya; Shimada, Masanobu; Simard, Marc; Souza-Filho, Pedro Walfir; Thomas, Nathan; Trettin, Carl; Accad, Arnon; Carreiras, Joao; Hilarides, Lammert (2014) Contribution of L-band SAR to systematic global mangrove monitoring. En: Marine and Freshwater Research. Vol. 65; No. 7; pp. 589 - 603; 13231650; Disponible en: 10.1071/MF13177.Motohka, Takeshi; Shimada, Masanobu; Uryu, Yumiko; Setiabudi, Budi (2014) Using time series PALSAR gamma nought mosaics for automatic detection of tropical deforestation: A test study in Riau, Indonesia. En: Remote Sensing of Environment. Vol. 155; pp. 79 - 88; 00344257; Disponible en: http://dx.doi.org/10.1016/j.rse.2014.04.012. Disponible en: 10.1016/j.rse.2014.04.012.Prudente, Victor Hugo Rohden; Martins, Vitor Souza; Vieira, Denis Corte; Silva, Nildson Rodrigues de França e.; Adami, Marcos; Sanches, Ieda Del Arco (2020) Limitations of cloud cover for optical remote sensing of agricultural areas across South America. En: Remote Sensing Applications: Society and Environment. Vol. 20; No. September; pp. 100414 23529385; Disponible en: https://doi.org/10.1016/j.rsase.2020.100414. Disponible en: 10.1016/j.rsase.2020.100414.van Oostende, Marit; Hieronymi, Martin; Krasemann, Hajo; Baschek, Burkard; Röttgers, Rüdiger (2022) Correction of inter-mission inconsistencies in merged ocean colour satellite data. En: Frontiers in Remote Sensing. Vol. 3; No. July; pp. 1 - 17; Disponible en: 10.3389/frsen.2022.882418.Joshi, Neha; Baumann, Matthias; Ehammer, Andrea; Fensholt, Rasmus; Grogan, Kenneth; Hostert, Patrick; Jepsen, Martin Rudbeck; Kuemmerle, Tobias; Meyfroidt, Patrick; Mitchard, Edward T.A.; Reiche, Johannes; Ryan, Casey M.; Waske, Björn (2016) A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring. En: Remote Sensing. Vol. 8; No. 1; pp. 1 - 23; 20724292; Disponible en: 10.3390/rs8010070.Joshi, Neha; Mitchard, Edward T.A.; Woo, Natalia; Torres, Jorge; Moll-Rocek, Julian; Ehammer, Andrea; Collins, Murray; Jepsen, Martin R.; Fensholt, Rasmus (2015) Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data. En: Environmental Research Letters. Vol. 10; No. 3; pp. 34014 17489326; Disponible en: http://dx.doi.org/10.1088/1748-9326/10/3/034014. Disponible en: 10.1088/1748-9326/10/3/034014.Murillo-Sandoval, Paulo J.; Kilbride, John; Tellman, Elizabeth; Wrathall, David; Van Den Hoek, Jamon; Kennedy, Robert E. (2023) The post-conflict expansion of coca farming and illicit cattle ranching in Colombia. pp. 1 - 10; Nature Publishing Group UK; Disponible en: https://doi.org/10.1038/s41598-023-28918-0.Anaya, Jesús A.; Gutiérrez-Vélez, Víctor H.; Pacheco-Pascagaza, Ana M.; Palomino-Ángel, Sebastián; Han, Natasha; Balzter, Heiko (2020) Drivers of Forest Loss in a Megadiverse Hotspot on the Pacific Coast of Colombia. En: Remote Sensing. Vol. 12; No. 8; pp. 1235 2072-4292; Consultado en: 2023/05/14/. Disponible en: https://www.mdpi.com/2072-4292/12/8/1235. Disponible en: 10.3390/rs12081235.Lukas Emele Anke Herold, Martin Cames, Anne Siemons; Vanessa Cook (Öko-Institut e.V.) (2013) The Development of Climate Negotiations in View of Warsaw (COP 19). : European Parliamentary Research Service; Disponible en: https://policycommons.net/artifacts/1340275/the-development-of-climate-negotiations-in-view-of-warsaw-cop-19/.Jafarbiglu, Hamid; Pourreza, Alireza (2023) Impact of sun-view geometry on canopy spectral reflectance variability. En: ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 196; pp. 270 - 286; 09242716; Consultado en: 2023/06/27/21:56:30. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0924271622003161. Disponible en: 10.1016/j.isprsjprs.2022.12.002.Camarretta, Nicolò; Harrison, Peter A.; Bailey, Tanya; Potts, Brad; Lucieer, Arko; Davidson, Neil; Hunt, Mark (2020) Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches. En: New Forests. Vol. 51; No. 4; pp. 573 - 596; 0169-4286, 1573-5095; Consultado en: 2023/06/28/19:03:09. Disponible en: http://link.springer.com/10.1007/s11056-019-09754-5. Disponible en: 10.1007/s11056-019-09754-5.Asner, Gregory P. (2009) Automated mapping of tropical deforestation and forest degradation: CLASlite. En: Journal of Applied Remote Sensing. Vol. 3; No. 1; pp. 033543 1931-3195; Disponible en: 10.1117/1.3223675.Microsoft Open Source; McFarland, Matt; Emanuele, Rob; Morris, Dan; Augspurger, Tom (2022) microsoft/PlanetaryComputer: October 2022. : Zenodo; Disponible en: https://doi.org/10.5281/zenodo.7261897.Urrea, Viviana; Ochoa, Andrés; Mesa, Oscar (2019) Seasonality of Rainfall in Colombia. En: Water Resources Research. Vol. 55; No. 5; pp. 4149 - 4162; 0043-1397, 1944-7973; Consultado en: 2023/08/14/19:37:26. Disponible en: https://onlinelibrary.wiley.com/doi/abs/10.1029/2018WR023316. Disponible en: 10.1029/2018WR023316.Storey, James; Scaramuzza, Pasquale; Schmidt, Gail; Barsi, Julia (2005) LANDSAT 7 SCAN LINE CORRECTOR-OFF GAP-FILLED PRODUCT DEVELOPMENT. Rahaman, Khan; Hassan, Quazi; Ahmed, M. (2017) Pan-Sharpening of Landsat-8 Images and Its Application in Calculating Vegetation Greenness and Canopy Water Contents. En: ISPRS International Journal of Geo-Information. Vol. 6; No. 6; pp. 168 2220-9964; Consultado en: 2024/03/05/00:52:29. Disponible en: https://www.mdpi.com/2220-9964/6/6/168. Disponible en: 10.3390/ijgi6060168.Xie, Lifeng; Wu, Weicheng; Huang, Xiaolan; Ou, Penghui; Lin, Ziyu; Zhiling, Wang; Song, Yong; Lang, Tao; Huangfu, Wenchao; Zhang, Yang; Zhou, Xiaoting; Fu, Xiao; Li, Jie; Jiang, Jingheng; Zhang, Ming; Zhang, Zhenjiang; Qin, Yaozu; Peng, Shanling; Shao, Chongjian; Bai, Yonghui (2020) Mining and Restoration Monitoring of Rare Earth Element (REE) Exploitation by New Remote Sensing Indicators in Southern Jiangxi, China. En: Remote Sensing. Vol. 12; No. 21; pp. 3558 2072-4292; Consultado en: 2024/03/04/21:09:06. Disponible en: https://www.mdpi.com/2072-4292/12/21/3558. Disponible en: 10.3390/rs12213558.Reif, Molly K; Theel, Heather J (2017) Remote sensing for restoration ecology: Application for restoring degraded, damaged, transformed, or destroyed ecosystems. En: Integrated Environmental Assessment and Management. Vol. 13; No. 4; pp. 614 - 630; 1551-3777, 1551-3793; Consultado en: 2024/03/04/19:50:16. Disponible en: https://setac.onlinelibrary.wiley.com/doi/10.1002/ieam.1847. Disponible en: 10.1002/ieam.1847.Klemas, Victor (2013) Using Remote Sensing to Select and Monitor Wetland Restoration Sites: An Overview. En: Journal of Coastal Research. Vol. 289; pp. 958 - 970; 0749-0208, 1551-5036; Consultado en: 2024/03/04/19:44:58. Disponible en: http://www.bioone.org/doi/abs/10.2112/JCOASTRES-D-12-00170.1. Disponible en: 10.2112/JCOASTRES-D-12-00170.1.Shuman, Craig S.; Ambrose, Richard F. (2003) A Comparison of Remote Sensing and Ground‐Based Methods for Monitoring Wetland Restoration Success. En: Restoration Ecology. Vol. 11; No. 3; pp. 325 - 333; 1061-2971, 1526-100X; Consultado en: 2024/03/04/19:44:45. Disponible en: https://onlinelibrary.wiley.com/doi/10.1046/j.1526-100X.2003.00182.x. Disponible en: 10.1046/j.1526-100X.2003.00182.x.Camarretta, Nicolò; Harrison, Peter A.; Bailey, Tanya; Potts, Brad; Lucieer, Arko; Davidson, Neil; Hunt, Mark (2020) Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches. En: New Forests. Vol. 51; No. 4; pp. 573 - 596; 0169-4286, 1573-5095; Consultado en: 2024/03/04/19:44:27. Disponible en: http://link.springer.com/10.1007/s11056-019-09754-5. Disponible en: 10.1007/s11056-019-09754-5.Lewis, Simon L; Edwards, David P; Galbraith, David (2015) Increasing human dominance of tropical forests. En: Science. Vol. 349; No. 6250; pp. 827 - 832; 10959203; Disponible en: 10.1126/science.aaa9932.Shimada, Masanobu; Itoh, Takuya; Motooka, Takeshi; Watanabe, Manabu; Shiraishi, Tomohiro; Thapa, Rajesh; Lucas, Richard (2014) New global forest/non-forest maps from ALOS PALSAR data (2007-2010). En: Remote Sensing of Environment. Vol. 155; pp. 13 - 31; 00344257; Disponible en: http://dx.doi.org/10.1016/j.rse.2014.04.014. Disponible en: 10.1016/j.rse.2014.04.014.Rodriguez, N.; Armenteras, D.; Morales, M.; Romero, M. (2006) Ecosistemas de los Andes Colombianos. pp. 154 p Bogotá, Colombia: Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 958-8151-30-9;Teluguntla, Pardhasaradhi; Thenkabail, Prasad S; Oliphant, Adam; Xiong, Jun; Gumma, Murali Krishna; Congalton, Russell G.; Yadav, Kamini; Huete, Alfredo (2018) A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform. En: ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 144; pp. 325 - 340; 09242716; Consultado en: 2023/04/23/17:59:24. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0924271618302090. Disponible en: 10.1016/j.isprsjprs.2018.07.017.Deng, J. S.; Wang, K.; Deng, Y. H.; Qi, G. J. (2008) PCA‐based land‐use change detection and analysis using multitemporal and multisensor satellite data. En: International Journal of Remote Sensing. Vol. 29; No. 16; pp. 4823 - 4838; 0143-1161, 1366-5901; Consultado en: 2024/03/11/14:46:27. Disponible en: https://www.tandfonline.com/doi/full/10.1080/01431160801950162. Disponible en: 10.1080/01431160801950162.DeFries, Ruth; Achard, Frédéric; Brown, Sandra; Herold, Martin; Murdiyarso, Daniel; Schlamadinger, Bernhard; De Souza, Carlos (2007) Earth observations for estimating greenhouse gas emissions from deforestation in developing countries. En: Environmental Science & Policy. Vol. 10; No. 4; pp. 385 - 394; 14629011; Consultado en: 2024/03/11/14:47:35. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S146290110700024X. Disponible en: 10.1016/j.envsci.2007.01.010.Ruiz-Ramos, Javier; Marino, Armando; Boardman, Carl; Suarez, Juan (2020) Continuous forest monitoring using cumulative sums of sentinel-1 timeseries. En: Remote Sensing. Vol. 12; No. 18; 20724292; Disponible en: 10.3390/RS12183061.Flores, Africa; K. Herndon; Rajesh Thapa; Emil Cherrington (2019) Synthetic Aperture Radar (SAR) Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation. Consultado en: 2023/04/30/22:04:00. Disponible en: https://gis1.servirglobal.net/TrainingMaterials/SAR/SARHB_FullRes.pdf. Disponible en: 10.25966/NR2C-S697.instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURSensoramiento remotoComputación en la nubeDatos observación de la tierraRadar de Apertura SinteticaDeforestaciónMonitoreoRemote sensingCloud computingSynthetic Aperture RadarEarth ObservationsDeforestationMonitoringNovel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in ColombiaNuevos métodos y tecnologías para mejorar el monitoreo y la comprensión de la dinámica del uso y la cobertura del suelo basados en la observación terrestre por satélite. 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