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Open AccessArticle

A Model for Animal Home Range Estimation Based on the Active Learning Method

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School of Geographic and Environmental Sciences, Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
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Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China
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College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
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Key Laboratory of Metallogenic Prediction of Nonferrous Metals, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha, Hunan 410083, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(11), 490; https://doi.org/10.3390/ijgi8110490
Received: 3 September 2019 / Revised: 25 October 2019 / Accepted: 28 October 2019 / Published: 30 October 2019
Home range estimation is the basis of ecology and animal behavior research. Some popular estimators have been presented; however, they have not fully considered the impacts of terrain and obstacles. To address this defect, a novel estimator named the density-based fuzzy home range estimator (DFHRE) is proposed in this study, based on the active learning method (ALM). The Euclidean distance is replaced by the cost distance-induced geodesic distance transformation to account for the effects of terrain and obstacles. Three datasets are used to verify the proposed method, and comparisons with the kernel density-based estimator (KDE) and the local convex hulls (LoCoH) estimators and the cross validation test indicate that the proposed estimator outperforms the KDE and the LoCoH estimators. View Full-Text
Keywords: home range; cost distance; active learning method; terrain; obstacles home range; cost distance; active learning method; terrain; obstacles
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Guo, J.; Du, S.; Ma, Z.; Huo, H.; Peng, G. A Model for Animal Home Range Estimation Based on the Active Learning Method. ISPRS Int. J. Geo-Inf. 2019, 8, 490.

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