Inter and Intra-Annual Spatio-Temporal Variability of Habitat
Suitability for Asian Elephants in India: A Random Forest Model-based
Analysis
- URL: http://arxiv.org/abs/2107.10478v1
- Date: Thu, 22 Jul 2021 06:42:54 GMT
- Title: Inter and Intra-Annual Spatio-Temporal Variability of Habitat
Suitability for Asian Elephants in India: A Random Forest Model-based
Analysis
- Authors: P. Anjali, Deepak N. Subramani
- Abstract summary: We develop a Random Forest model to estimate the species distribution of Asian elephants in India.
We observe that seasonal reduction in the suitable habitat may explain the patterns of Asian elephants and the increasing human-elephant conflict.
- Score: 1.370633147306388
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: We develop a Random Forest model to estimate the species distribution of
Asian elephants in India and study the inter and intra-annual spatiotemporal
variability of habitats suitable for them. Climatic, topographic variables and
satellite-derived Land Use/Land Cover (LULC), Net Primary Productivity (NPP),
Leaf Area Index (LAI), and Normalized Difference Vegetation Index (NDVI) are
used as predictors, and the species sighting data of Asian elephants from
Global Biodiversity Information Reserve is used to develop the Random Forest
model. A careful hyper-parameter tuning and training-validation-testing cycle
are completed to identify the significant predictors and develop a final model
that gives precision and recall of 0.78 and 0.77. The model is applied to
estimate the spatial and temporal variability of suitable habitats. We observe
that seasonal reduction in the suitable habitat may explain the migration
patterns of Asian elephants and the increasing human-elephant conflict.
Further, the total available suitable habitat area is observed to have reduced,
which exacerbates the problem. This machine learning model is intended to serve
as an input to the Agent-Based Model that we are building as part of our
Artificial Intelligence-driven decision support tool to reduce human-wildlife
conflict.
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