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Related papers: Bird Distribution Modelling using Remote Sensing a…

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Monitoring of bird populations has played a vital role in conservation efforts and in understanding biodiversity loss. The automation of this process has been facilitated by both sensing technologies, such as passive acoustic monitoring,…

Machine Learning · Computer Science 2021-08-23 Irina Tolkova , Brian Chu , Marcel Hedman , Stefan Kahl , Holger Klinck

Biodiversity research requires complete and detailed information to study ecosystem dynamics at different scales. Employing data-driven methods like Machine Learning is getting traction in ecology and more specific biodiversity, offering…

Quantitative Methods · Quantitative Biology 2025-10-27 Stylianos Stasinos , Martino Mensio , Elena Lazovik , Athanasios Trantas

Lifemapper (http://www.lifemapper.org) is a predictive electronic atlas of the Earth's biological biodiversity. Using a screensaver version of the GARP genetic algorithm for modeling species distributions, Lifemapper harnesses vast…

Quantitative Methods · Quantitative Biology 2011-11-09 David R. B. Stockwell , James H. Beach , Aimee Stewart , Gregory Vorontsov , David Vieglais , Ricardo Scachetti Pereira

This paper presents an evaluation of several approaches of plants species distribution modeling based on spatial, environmental and co-occurrences data using machine learning methods. In particular, we re-evaluate the environmental…

Neural and Evolutionary Computing · Computer Science 2019-09-20 Benjamin Deneu , Maximilien Servajean , Christophe Botella , Alexis Joly

Animals often exhibit changes in their behavior during migration. Telemetry data provide a way to observe geographic position of animals over time, but not necessarily changes in the dynamics of the movement process. Continuous-time models…

Applications · Statistics 2018-03-30 Mevin B. Hooten , Henry R. Scharf , Trevor J. Hefley , Aaron T. Pearse , Mitch D. Weegman

Forests play a crucial role in Earth's system processes and provide a suite of social and economic ecosystem services, but are significantly impacted by human activities, leading to a pronounced disruption of the equilibrium within…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Arthur Ouaknine , Teja Kattenborn , Etienne Laliberté , David Rolnick

The presence of species provides key insights into the ecological properties of a location such as land cover, climatic conditions or even soil properties. We propose a method to predict such ecological properties directly from remote…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Valerie Zermatten , Javiera Castillo-Navarro , Pallavi Jain , Devis Tuia , Diego Marcos

Detecting flying animals (e.g., birds, bats, and insects) using weather radar helps gain insights into animal movement and migration patterns, aids in management efforts (such as biosecurity) and enhances our understanding of the…

Machine Learning · Computer Science 2024-08-09 Mubin Ul Haque , Joel Janek Dabrowski , Rebecca M. Rogers , Hazel Parry

Climate change is accelerating the frequency and severity of unprecedented events, deviating from established patterns. Predicting these out-of-distribution (OOD) events is critical for assessing risks and guiding climate adaptation. While…

Machine Learning · Computer Science 2025-09-16 Maria Conchita Agana Navarro , Geng Li , Theo Wolf , María Pérez-Ortiz

Vegetation is the natural linkage connecting soil, atmosphere and water. It can represent the change of land cover to a certain extent and serve as an indicator for global change research. Methods for measuring coverage can be divided into…

Image and Video Processing · Electrical Eng. & Systems 2019-09-11 Chunxue Wu , Bobo Ju , Naixue Xiong , Guisong Yang , Yan Wu , Hongming Yang , Jiaying Huang , Zhiyong Xu

Radar must adapt to changing environments, and we propose changepoint detection as a method to do so. In the world of increasingly congested radio frequencies, radars must adapt to avoid interference. Many radar systems employ the…

Systems and Control · Electrical Eng. & Systems 2022-07-15 Samuel Haug , Austin Egbert , Robert J. Marks , Charles Baylis , Anthony Martone

Animal sounds can be recognised automatically by machine learning, and this has an important role to play in biodiversity monitoring. Yet despite increasingly impressive capabilities, bioacoustic species classifiers still exhibit imbalanced…

Improved monitoring and associated inferential tools to efficiently identify declining bird populations, particularly of rare or sparsely distributed species, is key to informed conservation and management across large spatio-temporal…

Populations and Evolution · Quantitative Biology 2021-09-07 Jeffrey W. Doser , Aaron S. Weed , Elise F. Zipkin , Kathryn M. Miller , Andrew O. Finley

The constant increase in energy consumption has created the necessity of extending the energy transmission and distribution network. Placement of powerlines represent a risk for bird population. Hence, better understanding of deaths induced…

Methodology · Statistics 2023-03-06 Jorge Sicacha-Parada , Diego Pavon-Jordan , Ingelin Steinsland , Roel May , Bård Stokke

We make a case for "planetary computing" -- infrastructure to handle the ingestion, transformation, analysis and publication of global data products for furthering environmental science and enabling better informed policy-making. We draw on…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-04 Patrick Ferris , Michael Dales , Sadiq Jaffer , Amelia Holcomb , Eleanor Toye Scott , Thomas Swinfield , Alison Eyres , Andrew Balmford , David Coomes , Srinivasan Keshav , Anil Madhavapeddy

Rapid biodiversity loss underscore the urgency of effective monitoring, yet manual surveys remain resource-intensive. While on-device AI offers a scalable alternative, its performance in the wild is often challenged by environmental…

Artificial Intelligence · Computer Science 2026-05-19 Jiaxing Li , Hao Fang , Chi Xu , Miao Zhang , Jiangchuan Liu , William I. Atlas , Katrina M. Connors , Mark A. Spoljaric

Efficient on-device models have become attractive for near-sensor insight generation, of particular interest to the ecological conservation community. For this reason, deep learning researchers are proposing more approaches to develop lower…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Emmanuel Azuh Mensah , Joban Mand , Yueheng Ou , Min Jang , Kurtis Heimerl

Change detection is an essential and widely utilized task in remote sensing that aims to detect and analyze changes occurring in the same geographical area over time, which has broad applications in urban development, agricultural surveys,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-11 Guangliang Cheng , Yunmeng Huang , Xiangtai Li , Shuchang Lyu , Zhaoyang Xu , Qi Zhao , Shiming Xiang

Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and…

Technology is increasingly used in Nature Reserves and National Parks around the world to support conservation efforts. Endangered species, such as the Eurasian Lynx (Lynx lynx), are monitored by a network of automatic photo traps. Yet,…