Abstract
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.
Highlights
Carbon Decisions International (CDI), Residencial La Castilla, Paraíso de Cartago 30201, Costa Rica; AFOLU Global Services, C/Jimenez Diaz, Pozuelo Alarcón 28224, Spain; Academic Editors: Ioannis Gitas and Prasad S
The choice of historical period for the design of the land cover (LC) time series takes into account two major government policies and actions relative to forest conservation in Costa Rica: (1) the launch of the
The choice of historical period for the design of the LC time series takes into account two major 1996; and (2) the endorsement of Ecomercados II project by law (7 March 2008), which scaled up the government policies and actions relative to forest conservation in Costa Rica: (1) the launch of the Taking these(PES)
Summary
Carbon Decisions International (CDI), Residencial La Castilla, Paraíso de Cartago 30201, Costa Rica; AFOLU Global Services, C/Jimenez Diaz, Pozuelo Alarcón 28224, Spain; Academic Editors: Ioannis Gitas and Prasad S. Satellite imagery is the only data source with enough periodicity to provide consistent land cover information in a cost-effective way. 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. 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. Land cover changes between forest and non-forest classes were validated for the period between 2001 and 2011, obtaining an overall accuracy of 86%. By linking deforestation dynamics with forest age, a more accurate discussion of the carbon emissions along the time series can be presented
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