Tree canopy density thresholds for improved forests cover estimation in protected areas of Madagascar

Rafanoharana, Serge Claudio; Andrianambinina, Fatany Ollier Duranton; Rasamuel, Henintsoa Andry; Waeber, Patrick; Ganzhorn, Joerg Ulrich; Wilmé, Lucienne (2023). Tree canopy density thresholds for improved forests cover estimation in protected areas of Madagascar Environmental Research Communications, 5(7), 071003. Institute of Physics Publishing 10.1088/2515-7620/ace87f

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The rich endemic biodiversity of Madagascar is concentrated in different types of natural forests primarily conserved within the network of protected areas (PAs). Since 1990, remote sensing has been utilized to monitor forest cover. The latest forest cover map generated using these techniques provides accurate estimates of natural forest cover within the PAs network. However, the standardized application of Tree Canopy Density (TCD), as used in global assessments of forest cover, yields erroneous estimates for different forest types in Madagascar because the standard TCD cannot be globally applied to all types of forests. Our study aims to utilize global remote sensing data at the scale of PAs to identify specific TCD thresholds for individual PAs. Starting from the year 2000 data, the application of these thresholds will allow us to estimate deforestation in subsequent years at reduced costs. We used the official PA boundaries, a reliable forest cover map at the national scale, and the TCDs published at a global scale to infer the values of TCD to be applied in each PA. The standard TCD threshold above 30% overestimates humid and dry forests and underestimates dry spiny forests in Madagascar. Our specific TCD thresholds inferred for each PA accurately estimate the forest cover in the vast majority of PAs. Using these specific TCD thresholds will allow for improved monitoring of forest cover within the network of PAs. The methodology detailed here can also be applied in other geographic regions, and future improvements in data on forest cover—both remotely sensed and field-collected—will enhance our ability to estimate forest cover and its changes over time.

Item Type:	Journal Article (Original Article)
Division/Institute:	School of Agricultural, Forest and Food Sciences HAFL
Name:	Rafanoharana, Serge Claudio; Andrianambinina, Fatany Ollier Duranton; Rasamuel, Henintsoa Andry; Waeber, Patrick0000-0002-3229-0124; Ganzhorn, Joerg Ulrich and Wilmé, Lucienne
ISSN:	2515-7620
Publisher:	Institute of Physics Publishing
Language:	English
Submitter:	Patrick Waeber
Date Deposited:	03 Aug 2023 14:21
Last Modified:	03 Aug 2023 14:21
Publisher DOI:	10.1088/2515-7620/ace87f
ARBOR DOI:	10.24451/arbor.19700
URI:	https://arbor.bfh.ch/id/eprint/19700