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Data · dataset · 2025

Evaluation of the accuracy of multispectral land cover classification algorithms: Comparison of AI-based Machine Learning, Maximum Likelihood, and Mahalanobis Distance Algorithms

Listed in Borealis

These are field data of forest types, species and extent of land cover type, including grassland, water extent.

Description

The data were the basis for analysis of forest degradation as depicted by a set of multispectral band-ratio indices and their relationship to climate variables and climate change data derived from General Circulation Models (GCM). These data allowed for the mapping of forest condition as related to forest degradation as a function of past and future climate.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Ecological applications 71%
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
Borealisdoi:10.5683/SP3/PQ6GGK13 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:4102enrichment · borealisdata cataxonomy-embedding@1.1.0title+keywords+description (71%)
concepts[field].dataverse_subject:earth-and-environmental-sciencessource · borealisdata caconnector:borealisdata_ca@1.0.0/subjects
concepts[field].local:field:earth-environmentalmapping · borealisdata caconnector:borealisdata_ca@1.0.0/subjects
created_datesource · borealisdata caconnector:borealisdata_ca@1.0.0
descriptionsource · borealisdata caconnector:borealisdata_ca@1.0.0/description
publication_datesource · borealisdata caconnector:borealisdata_ca@1.0.0
titlesource · borealisdata caconnector:borealisdata_ca@1.0.0/name
updated_datesource · borealisdata caconnector:borealisdata_ca@1.0.0
version_labelsource · borealisdata caconnector:borealisdata_ca@1.0.0