Kết quả tìm kiếm - "Remote Sensing in Ecology and Conservation"

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  1. 1

    Near real‐time monitoring of wading birds using uncrewed aircraft systems and computer vision Bằng Ethan P. White, Lindsey Garner, Ben G. Weinstein, Henry Senyondo, Andrew Ortega, Ashley Steinkraus, Glenda M. Yenni, Peter Frederick, S. K. Morgan Ernest

    Được phát hành 2025-06-01

    Wildlife population monitoring over large geographic areas is increasingly feasible due to developments in aerial survey methods coupled with the use of computer vision models for identifying and classifying individual organisms. However, aerial surveys still occur infrequently, and there are often...

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  2. 2

    Illuminating the Arctic: Unveiling seabird responses to artificial light during polar darkness through citizen science and remote sensing Bằng Kaja Balazy, Dariusz Jakubas, Andrzej Kotarba, Katarzyna Wojczulanis‐Jakubas

    Được phát hành 2025-06-01

    Abstract Artificial light at night (ALAN) has global impacts on animals, often negative, yet its effects in polar regions remains largely underexplored. These regions experience prolonged darkness during the polar night, while human activity and artificial lighting are rapidly increasing. In this st...

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  3. 3

    A comparison of established and digital surface model (DSM) ‐based methods to determine population estimates and densities for king penguin colonies, using fixed‐wing drone and sat... Bằng J. Coleman, N. Fenney, P.N. Trathan, A. Fox, E. Fox, A. Bennison, L. Ireland, M.A. Collins, P.R. Hollyman

    Được phát hành 2025-06-01

    Abstract Drones are being increasingly used to monitor wildlife populations; their large spatial coverage and minimal disturbance make them ideal for use in remote environments where access and time are limited. The methods used to count resulting imagery need consideration as they can be time‐consu...

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  4. 4

    Mapping oil palm plantations and their implications on forest and great ape habitat loss in Central Africa Bằng Mohammed S. Ozigis, Serge Wich, Adrià Descals, Zoltan Szantoi, Erik Meijaard

    Được phát hành 2025-06-01

    Abstract Oil palm (Elaeis guineensis) cultivation in Central Africa (CA) has become important because of the increased global demand for vegetable oils. The region is highly suitable for the cultivation of oil palm and this increases pressure on forest biodiversity in the region. Accurate maps are t...

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  5. 5

    The untapped potential of camera traps for farmland biodiversity monitoring: current practice and outstanding agroecological questions Bằng Stephanie Roilo, Tim R. Hofmeester, Magali Frauendorf, Anna Widén, Anna F. Cord

    Được phát hành 2025-06-01

    Abstract Agroecosystems are experiencing a biodiversity crisis. Biodiversity monitoring is needed to inform conservation, but existing monitoring schemes lack standardisation and are biased towards birds, insects and plants. Automated monitoring techniques offer a promising solution, but while passi...

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  6. 6

    A random encounter model for wildlife density estimation with vertically oriented camera traps Bằng Shuiqing He, J. Marcus Rowcliffe, Hanzhe Lin, Chris Carbone, Yorick Liefting, Shyam K. Thapa, Bishnu P. Shrestha, Patrick A. Jansen

    Được phát hành 2025-06-01

    Abstract The random encounter model (REM) estimates animal densities from camera‐trap data by correcting capture rates for a set of biological variables of the animals (average group size, speed and activity level) and characteristics of camera sensors. The REM has been widely used for setups in whi...

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  7. 7

    Quantifying range‐ and topographical biases in weather surveillance radar measures of migratory bird activity Bằng Miguel F. Jimenez, Birgen Haest, Ali Khalighifar, Annika L. Abbott, Abigail Feuka, Aitao Liu, Kyle G. Horton

    Được phát hành 2025-06-01

    Abstract Weather radar systems have become a central tool in the study of nocturnal bird migration. Yet, while studies have sought to validate weather radar data through comparison to other sampling techniques, few have explicitly examined the impact of range and topographical blockage on sampling d...

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  8. 8

    Examining wildfire dynamics using ECOSTRESS data with machine learning approaches: the case of South‐Eastern Australia's black summer Bằng Yuanhui Zhu, Shakthi B. Murugesan, Ivone K. Masara, Soe W. Myint, Joshua B. Fisher

    Được phát hành 2025-06-01

    Wildfires are increasing in risk and prevalence. The most destructive wildfires in decades in Australia occurred in 2019–2020. However, there is still a challenge in developing effective models to understand the likelihood of wildfire spread (susceptibility) and pre‐fire vegetation conditions. The r...

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