Please use this identifier to cite or link to this item:
https://hdl.handle.net/11681/42003
Title: | A multi-biome study of tree cover detection using the Forest Cover Index |
Authors: | Becker, Sarah J. Maloney, Megan C. Griffin, Andrew W. H. |
Keywords: | Forest Cover Index (FCI) NDVI Tree cover Forest cover PlanetScop Sentinel-2 Multispectral imagery Vegetation index |
Publisher: | Geospatial Research Laboratory (U.S.) Engineer Research and Development Center (U.S.) |
Series/Report no.: | Technical Report (Engineer Research and Development Center (U.S.)) ; no. ERDC/GRL TR-21-4 |
Abstract: | Tree cover maps derived from satellite and aerial imagery directly support civil and military operations. However, distinguishing tree cover from other vegetative land covers is an analytical challenge. While the commonly used Normalized Difference Vegetation Index (NDVI) can identify vegetative cover, it does not consistently distinguish between tree and low-stature vegetation. The Forest Cover Index (FCI) algorithm was developed to take the multiplicative product of the red and near infrared bands and apply a threshold to separate tree cover from non-tree cover in multispectral imagery (MSI). Previous testing focused on one study site using 2-m resolution commercial MSI from WorldView-2 and 30-m resolution imagery from Landsat-7. New testing in this work used 3-m imagery from PlanetScope and 10-m imagery from Sentinel-2 in imagery in sites across 12 biomes in South and Central America and North Korea. Overall accuracy ranged between 23% and 97% for Sentinel-2 imagery and between 51% and 98% for PlanetScope imagery. Future research will focus on automating the identification of the threshold that separates tree from other land covers, exploring use of the output for machine learning applications, and incorporating ancillary data such as digital surface models and existing tree cover maps. |
Description: | Technical Report |
Gov't Doc #: | ERDC/GRL TR-21-4 |
Rights: | Approved for Public Release; Distribution is Unlimited |
URI: | https://hdl.handle.net/11681/42003 http://dx.doi.org/10.21079/11681/42003 |
Size: | 40 pages / 3.32 MB |
Types of Materials: | |
Appears in Collections: | Technical Report |
Files in This Item:
File | Description | Size | Format | |
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ERDC-GRL TR-21-4.pdf | 3.32 MB | Adobe PDF | ![]() View/Open |