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Grant support

This work was developed in the framework of the consultancy Generating a consistent historical times series of activity data from land use change for the development of Costa Rica's REDD+ Reference Level funded by the Forest Carbon Partnership Facility (FCPF). The authors are very grateful to the technicians of the institutions involved in the REDD+ process in Costa Rica, especially FONAFIFO, SINAC, INBio, IMN, PRIAS, MAG and INEC. FONAFIFO was completely involved in the technical process and decision making, supervised the methodological decisions and documents, coordinated the meetings with others institutions and provided and requested all the necessary information. IMN and SINAC participated in different workshops during the methodological design and provided historical maps, land use datasets and imagery essential for several phases of the work. INBio provided a huge volume of ground truth data to the validation process of the maps. Comments and information provided from all these local institutions were essential for the good outcome of the project.

Analysis of institutional authors

Fernandez-Moya, JesusAuthorMarchamalo, MiguelAuthor

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June 9, 2019
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An Operational Framework for Land Cover Classification in the Context of REDD plus Mechanisms. A Case Study from Costa Rica

Publicated to:Remote Sensing. 8 (7): - 2016-07-01 8(7), DOI: 10.3390/rs8070593

Authors: Fernandez-Landa, Alfredo; Algeet-Abarquero, Nur; Fernandez-Moya, Jesus; Luz Guillen-Climent, Maria; Pedroni, Lucio; Garcia, Felipe; Espejo, Andres; Felipe Villegas, Juan; Marchamalo, Miguel; Bonatti, Javier; Escamochero, Inigo; Rodriguez-Noriega, Pablo; Papageorgiou, Stavros; Fernandes, Erick;

Affiliations

AFOLU Global Serv, Pozuelo Alarcon 28224, Spain - Author
Agresta S Coop, Duque Fernan Nunez 2, Madrid 28012, Spain - Author
CDI, Residencial La Castilla 30201, Paraiso De Cart, Costa Rica - Author
CEI Montegancedo, DIMAP, Madrid 28223, Spain - Author
Freelance, Plaza Constituc 8, Madrid 28694, Spain - Author
Hidrobiología. Universidad Politécnica de Madrid - Author
UCR, San Jose 11501, Costa Rica - Author
UPM, Avda Prof Aranguren, Madrid 28040, Spain - Author
World Bank, 1818 H St NW, Washington, DC 20433 USA - Author
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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.

Keywords

AccuracyAreaBiodiversityDeforestationEfficiencyEnvironmental service paymentsForestIr madLandsatOpen sourceOrfeoOsa peninsulaPythonQgisRRandom forestRandom forest classifierSatellite imageryTm

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Remote Sensing due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2016, it was in position 7/29, thus managing to position itself as a Q1 (Primer Cuartil), in the category Remote Sensing.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 2.03, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-10, the following number of citations:

  • WoS: 6
  • Scopus: 9
  • Google Scholar: 11

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-10:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 84.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 90 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 11.95.
  • The number of mentions on the social network Facebook: 1 (Altmetric).
  • The number of mentions on the social network X (formerly Twitter): 3 (Altmetric).
  • The number of mentions in news outlets: 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/85506/

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Costa Rica; United States of America.