Exploring the use of MODIS NDVI-based phenology indicators for classifying forest general habitat categories
Clerici, Nicola; Weissteiner, Christof J.; Gerard, France. 2012 Exploring the use of MODIS NDVI-based phenology indicators for classifying forest general habitat categories. Remote Sensing, 4 (6). 1781-1803. 10.3390/rs4061781Before downloading, please read NORA policies.
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The cost effective monitoring of habitats and their biodiversity remains a challenge to date. Earth Observation (EO) has a key role to play in mapping habitat and biodiversity in general, providing tools for systematic collection of environmental data. The GEO-BON European Biodiversity Observation Network project (EBONE) has recently adopted a habitat classification scheme based on General Habitat Categories (GHC) designed with an Earth Observation-perspective. Here we explore the use of NDVI-derived phenology metrics for the identification and mapping of Forest GHC. Thirty-one phenometrics were extracted from MODIS NDVI time series for Europe. Classifications to discriminate forest types were performed based on a Random Forests™ classifier in selected regions. Results indicate date phenometrics are generally more significant for forest type discrimination. The achieved class accuracies are generally not satisfactory, except for coniferous forests in homogeneous stands (77-82%). The main causes of low classification accuracies were identified as (i) the spatial resolution of the imagery (250 m) which led to mixed phenology signals; (ii) the GHC scheme classification design, which allows for parcels of heterogeneous covers, and (iii) the low number of the training samples available from field survey. A mapping strategy integrating EO-based phenology with vegetation height information is expected to be more effective than a purely phenology-based approach.
|Item Type:||Publication - Article|
|Digital Object Identifier (DOI):||10.3390/rs4061781|
|Programmes:||CEH Topics & Objectives 2009 - 2012 > Biodiversity > BD Topic 1 - Observations, Patterns, and Predictions for Biodiversity|
|Additional Information. Not used in RCUK Gateway to Research.:||This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
|Additional Keywords:||habitat monitoring, earth observation, remote sensing, phenology, NDVI, Random Forests, MODIS, forest vegetation|
|NORA Subject Terms:||Ecology and Environment
Data and Information
|Date made live:||25 Jun 2012 16:03|
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