Open AccessEngaging Stakeholders: Assessing Accuracy of Participatory Mapping of Land Cover in Panama
Author(s) -
VergaraAsenjo Gerardo,
Sharma Divya,
Potvin Catherine
Publication year - 2015
Publication title -
conservation letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.153
H-Index - 79
ISSN - 1755-263X
DOI - 10.1111/conl.12161
Subject(s) - citizen journalism , land cover , indigenous , environmental resource management , remote sensing , geography , decision tree , identification (biology) , cover (algebra) , land use , environmental planning , computer science , environmental science , data mining , ecology , mechanical engineering , world wide web , engineering , biology
Full and effective participation of indigenous peoples and local communities, and high accuracy estimates are two current requirements for the purposes of monitoring forests at international level. We produced two land cover maps, both of which were based on digital image processing (decision trees) using Rapideye imagery, and a land cover participatory map, for indigenous territories of eastern Panama. Accuracy of the three maps was evaluated using field data. Classification that was based on participatory mapping gave best overall accuracy of 83.7% (κ = 0.783), followed by the decision tree that included textural variables (DT2: overall accuracy of 79.9%, κ = 0.757). We have demonstrated for the first time that local knowledge can improve land cover classification and facilitate the identification of forest degradation. The plea of the UNFCC for the full and effective participation of local and indigenous people could, therefore, improve the accuracy of monitoring.