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1. Species distribution models (SDM) are tools used to determine environmental features that influence the geographic distribution of species' abundance and have been used to analyze presence-only records. Analysis of presence-only records…

Populations and Evolution · Quantitative Biology 2013-12-05 Trevor Hefley , Andrew Tyre , David Baasch , Erin Blankenship

This paper proposes the problem of modeling video sequences of dynamic swarms (DS). We define DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local…

Computer Vision and Pattern Recognition · Computer Science 2011-02-08 Bernard Ghanem , Narendra Ahuja

Biodiversity is declining at an unprecedented rate, impacting ecosystem services necessary to ensure food, water, and human health and well-being. Understanding the distribution of species and their habitats is crucial for conservation…

In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting environmental conditions to species occurrences.…

Machine Learning · Computer Science 2024-03-13 Robin Zbinden , Nina van Tiel , Marc Rußwurm , Devis Tuia

Accurately identifying spatial patterns of species distribution is crucial for scientific insight and societal benefit, aiding our understanding of species fluctuations. The increasing quantity and quality of ecological datasets present…

We address an important problem in ecology called Species Distribution Modeling (SDM), whose goal is to predict whether a species exists at a certain position on Earth. In particular, we tackle a challenging version of this task, where we…

Machine Learning · Computer Science 2024-10-24 Shiran Yuan , Hao Zhao

Marine mammals are increasingly vulnerable to human disturbance and climate change. Their diving behavior leads to limited visual access during data collection, making studying the abundance and distribution of marine mammals challenging.…

Presence-absence data is defined by vectors or matrices of zeroes and ones, where the ones usually indicate a "presence" in a certain place. Presence-absence data occur for example when investigating geographical species distributions,…

Methodology · Statistics 2021-11-24 Gabriele d'Angella , Christian Hennig

The difficulty of monitoring biodiversity at fine scales and over large areas limits ecological knowledge and conservation efforts. To fill this gap, Species Distribution Models (SDMs) predict species across space from spatially explicit…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Lukas Picek , Christophe Botella , Maximilien Servajean , César Leblanc , Rémi Palard , Théo Larcher , Benjamin Deneu , Diego Marcos , Pierre Bonnet , Alexis Joly

Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description for species distribution response along environmental…

Methodology · Statistics 2021-11-08 Jarno Vanhatalo , Marcelo Hartmann , Lari Veneranta

Conservation science depends on an accurate understanding of what's happening in a given ecosystem. How many species live there? What is the makeup of the population? How is that changing over time? Species Distribution Modeling (SDM) seeks…

Machine Learning · Computer Science 2021-07-23 Sara Beery , Elijah Cole , Joseph Parker , Pietro Perona , Kevin Winner

Citizen science biodiversity data present great opportunities for ecology and conservation across vast spatial and temporal scales. However, the opportunistic nature of these data lacks the sampling structure required by modeling…

Machine Learning · Computer Science 2025-04-15 Nahian Ahmed , Mark Roth , Tyler A. Hallman , W. Douglas Robinson , Rebecca A. Hutchinson

Spatially-explicit estimates of population density, together with appropriate estimates of uncertainty, are required in many management contexts. Density Surface Models (DSMs) are a two-stage approach for estimating spatially-varying…

Methodology · Statistics 2021-02-25 Mark V Bravington , David L Miller , Sharon L Hedley

Accurately capturing the full-range response of structures is crucial in structural health monitoring (SHM) for ensuring safety and operational integrity. However, limited sensor deployment due to cost, accessibility, or scale often hinders…

Computational Engineering, Finance, and Science · Computer Science 2025-09-25 Wingho Feng , Quanwang Li , Chen Wang , Jian-sheng Fan

In fisheries ecology, species abundance data are often collected by multiple surveys, each with unique characteristics. This article is motivated by a dataset of Atlantic sea scallop abundance records along the northeast coast of the United…

Applications · Statistics 2026-04-03 Quan Vu , Francis K. C. Hui , A. H. Welsh , Samuel Muller , Eva Cantoni , Christopher R. Haak

Species distribution models (SDMs) are widely used to predict species' geographic distributions, serving as critical tools for ecological research and conservation planning. Typically, SDMs relate species occurrences to environmental…

Machine Learning · Computer Science 2025-08-12 Hager Radi Abdelwahed , Mélisande Teng , Robin Zbinden , Laura Pollock , Hugo Larochelle , Devis Tuia , David Rolnick

The trade-off in remote sensing instruments that balances the spatial resolution and temporal frequency limits our capacity to monitor spatial and temporal dynamics effectively. The spatiotemporal data fusion technique is considered as a…

Computer Vision and Pattern Recognition · Computer Science 2017-10-11 Qing Cheng , Huiqing Liu , Huanfeng Shen , Penghai Wu , Liangpei Zhang

The challenge in fine-grained visual categorization lies in how to explore the subtle differences between different subclasses and achieve accurate discrimination. Previous research has relied on large-scale annotated data and pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2024-05-16 Tianxu Wu , Shuo Ye , Shuhuang Chen , Qinmu Peng , Xinge You

We focus on species distribution modeling using global-scale presence-only data, leveraging geographical and environmental features to map species ranges, as in previous studies. However, we innovate by integrating taxonomic classification…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Srikumar Sastry , Xin Xing , Aayush Dhakal , Subash Khanal , Adeel Ahmad , Nathan Jacobs

Point counts (PCs) are widely used in biodiversity surveys, but despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability…