An Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa Rica
| Autor: | Andrés Espejo, Alfredo Fernández-Landa, Lucio Pedroni, Stavros Papageorgiou, Erick Fernandes, Iñigo Escamochero, Juan Felipe Villegas, María Luz Guillén-Climent, Miguel Marchamalo, Jesús Fernández-Moya, Pablo Rodríguez-Noriega, Javier Bonatti, Nur Algeet-Abarquero, Felipe García |
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| Rok vydání: | 2016 |
| Předmět: |
Multivariate statistics
010504 meteorology & atmospheric sciences Land cover 010501 environmental sciences 01 natural sciences forest open source Software deforestation Satellite imagery lcsh:Science 0105 earth and related environmental sciences Remote sensing Random Forest business.industry ORFEO Random forest python Forest age Greenhouse gas Operational framework General Earth and Planetary Sciences Environmental science lcsh:Q business Landsat Cartography IR MAD QGIS |
| Zdroj: | Remote Sensing Volume 8 Issue 7 Pages: 593 Remote Sensing, Vol 8, Iss 7, p 593 (2016) |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs8070593 |
| Popis: | REDD+ implementation requires robust, consistent, accurate and transparent national land cover historical data and monitoring systems. Satellite imagery is the only data source with enough periodicity to provide consistent land cover information in a cost-effective way. The main aim of this paper is the creation of an operational framework for monitoring land cover dynamics based on Landsat imagery and open-source software. The methodology integrates the entire land cover and land cover change mapping processes to produce a consistent series of Land Cover maps. The consistency of the time series is achieved through the application of a single trained machine learning algorithm to radiometrically normalized imagery using iteratively re-weighted multivariate alteration detection (IR-MAD) across all dates of the historical period. As a result, seven individual Land Cover maps of Costa Rica were produced from 1985/1986 to 2013/2014. Post-classification land cover change detection was performed to evaluate the land cover dynamics in Costa Rica. The validation of the land cover maps showed an overall accuracy of 87% for the 2013/2014 map, 93% for the 2000/2001 map and 89% for the 1985/1986 map. Land cover changes between forest and non-forest classes were validated for the period between 2001 and 2011, obtaining an overall accuracy of 86%. Forest age-classes were generated through a multi-temporal analysis of the maps. By linking deforestation dynamics with forest age, a more accurate discussion of the carbon emissions along the time series can be presented. |
| Databáze: | OpenAIRE |
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