Identifying Reliable Opportunistic Data for Species Distribution Modeling: A Benchmark Data Optimization Approach

Identifying Reliable Opportunistic Data for Species Distribution Modeling: A Benchmark Data Optimization Approach

The purpose of this study is to increase the number of species occurrence data by integrating opportunistic data with Global Biodiversity Information Facility (GBIF) benchmark data via a novel optimization technique. The optimization method utilizes Natural Language Processing (NLP) and a simulated...

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Bibliographic Details
Main Authors: Yu-Pin Lin, Wei-Chih Lin, Wan-Yu Lien, Johnathen Anthony, Joy R. Petway
Format: Article
Language:English
Published: MDPI AG 2017-11-01
Series:Environments
Subjects:
optimal data selection
data combination
opportunistic data
species modeling
Online Access:https://www.mdpi.com/2076-3298/4/4/81

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