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Automated visitor and wildlife monitoring with camera traps and machine learning Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-30 Veronika Mitterwallner, Anne Peters, Hendrik Edelhoff, Gregor Mathes, Hien Nguyen, Wibke Peters, Marco Heurich, Manuel J. Steinbauer
As human activities in natural areas increase, understanding human–wildlife interactions is crucial. Big data approaches, like large-scale camera trap studies, are becoming more relevant for studying these interactions. In addition, open-source object detection models are rapidly improving and have great potential to enhance the image processing of camera trap data from human and wildlife activities
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A semi-automated camera trap distance sampling approach for population density estimation Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-28 Maik Henrich, Mercedes Burgueño, Jacqueline Hoyer, Timm Haucke, Volker Steinhage, Hjalmar S. Kühl, Marco Heurich
Camera traps have become important tools for the monitoring of animal populations. However, the study-specific estimation of animal detection probabilities is key if unbiased abundance estimates of unmarked species are to be obtained. Since this process can be very time-consuming, we developed the first semi-automated workflow for animals of any size and shape to estimate detection probabilities and
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Quantifying wetness variability in aapa mires with Sentinel-2: towards improved monitoring of an EU priority habitat Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-18 Tytti Jussila, Risto K. Heikkinen, Saku Anttila, Kaisu Aapala, Mikko Kervinen, Juha Aalto, Petteri Vihervaara
Aapa mires are waterlogged northern peatland ecosystems characterized by a patterned surface structure where water-filled depressions (‘flarks’) alternate with drier hummock strings. As one of the EU Habitat Directive priority habitats, aapa mires are important for biodiversity and carbon cycling, harbouring several red-listed species and supporting unique species communities. Due to their sensitivity
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Global disparity of camera trap research allocation and defaunation risk of terrestrial mammals Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-17 Badru Mugerwa, Jürgen Niedballa, Aimara Planillo, Douglas Sheil, Stephanie Kramer-Schadt, Andreas Wilting
Quantifying and monitoring the risk of defaunation and extinction require assessing and monitoring biodiversity in impacted regions. Camera traps that photograph animals as they pass sensors have revolutionized wildlife assessment and monitoring globally. We conducted a global review of camera trap research on terrestrial mammals over the last two decades. We assessed if the spatial distribution of
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Combining environmental DNA with remote sensing variables to map fish species distributions along a large river Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-17 Shuo Zong, Jeanine Brantschen, Xiaowei Zhang, Camille Albouy, Alice Valentini, Heng Zhang, Florian Altermatt, Loïc Pellissier
Biodiversity loss in river ecosystems is much faster and more severe than in terrestrial systems, and spatial conservation and restoration plans are needed to halt this erosion. Reliable and highly resolved data on the state of and change in biodiversity and species distributions are critical for effective measures. However, high-resolution maps of fish distribution remain limited for large riverine
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Automatically drawing vegetation classification maps using digital time-lapse cameras in alpine ecosystems Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-10 Ryotaro Okamoto, Reiko Ide, Hiroyuki Oguma
Alpine ecosystems are particularly vulnerable to climate change. Monitoring the distribution of alpine vegetation is required to plan practical conservation activities. However, conventional field observations, airborne and satellite remote sensing are difficult in terms of coverage, cost and resolution in alpine areas. Ground-based time-lapse cameras have been used to observe the regions' snowmelt
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Deep learning-based training data augmentation combined with post-classification improves the classification accuracy for dominant and scattered invasive forest tree species Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-08-09 Szilárd Balázs Likó, Imre J. Holb, Viktor Oláh, Péter Burai, Szilárd Szabó
Species composition of forests is a very important component from the point of view of nature conservation and forestry. We aimed to identify 10 tree species in a hilly forest stand using a hyperspectral aerial image with a particular focus on two invasive species, namely Ailanthus tree and black locust. Deep learning-based training data augmentation (TDA) and post-classification techniques were tested
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Remote sensing of Antarctic polychaete reefs (Serpula narconensis): reproducible workflows for quantifying benthic structural complexity with action cameras, remotely operated vehicles and structure-from-motion photogrammetry Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-25 Juan C. Montes-Herrera, Nicole Hill, Vonda J. Cummings, Glenn J. Johnstone, Jonathan S. Stark, Vanessa Lucieer
Quantifying the structural complexity provided by biogenic habitat structures is important in ecology, conservation and management, and yet remains a challenging task, particularly in deep sea and polar environments, that current photogrammetry tools can alleviate. In this study, we demonstrate how small remotely operated vehicles and compact underwater GoPro® action cameras can be easily integrated
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Estimating animal density using the Space-to-Event model and bootstrap resampling with motion-triggered camera-trap data Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-24 Arnaud Lyet, Scott Waller, Thierry Chambert, Pelayo Acevedo, Eric Howe, Hjalmar S. Kühl, Robin Naidoo, Timothy O'Brien, Pablo Palencia, Svetlana V. Soutyrina, Joaquin Vicente, Oliver R. Wearn, Thomas N. E. Gray
Over the past few decades, the use of camera-traps has revolutionized our ability to monitor populations of wild terrestrial mammals. While methods to estimate abundance from individually-identifiable animals are well-established, they are mostly restricted to species with clear natural markings or else necessitate invasive and often costly animal tagging campaigns. Estimating abundance or density
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Mapping tree cover expansion in Montana, U.S.A. rangelands using high-resolution historical aerial imagery Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-19 Scott L. Morford, Brady W. Allred, Eric R. Jensen, Jeremy D. Maestas, Kristopher R. Mueller, Catherine L. Pacholski, Joseph T. Smith, Jason D. Tack, Kyle N. Tackett, David E. Naugle
Worldwide, trees are colonizing rangelands with high conservation value. The introduction of trees into grasslands and shrublands causes large-scale changes in ecosystem structure and function, which have cascading impacts on ecosystem services, biodiversity, and agricultural economies. Satellites are increasingly being used to track tree cover at continental to global scales, but these methods can
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Efficacy of machine learning image classification for automated occupancy-based monitoring Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-10 Robert C. Lonsinger, Marlin M. Dart, Randy T. Larsen, Robert N. Knight
Remote cameras have become a widespread data-collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad-scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric
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Both Landsat- and LiDAR-derived measures predict forest bee response to large-scale wildfire Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-10 Sara M. Galbraith, Jonathon J. Valente, Christopher J. Dunn, James W. Rivers
Large-scale disturbances such as wildfire can have profound impacts on the composition, structure, and functioning of ecosystems. Bees are critical pollinators in natural settings and often respond positively to wildfires, particularly in forests where wildfire leads to more open conditions and increased floral resources. The use of Light Detection and Ranging (LiDAR) provides opportunities for quantifying
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Recurring bleaching events disrupt the spatial properties of coral reef benthic communities across scales Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-10 Helen V. Ford, Jamison M. Gove, John R. Healey, Andrew J. Davies, Nicholas A. J. Graham, Gareth J. Williams
Marine heatwaves are causing recurring coral bleaching events on tropical reefs that are driving ecosystem change. Yet, little is known about how bleaching and subsequent coral mortality impacts the spatial properties of tropical seascapes, such as patterns of organism spatial clustering and heterogeneity across scales. Changes in these spatial properties can offer insight into ecosystem recovery potential
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Invasion in the Niger Delta: remote sensing of mangrove conversion to invasive Nypa fruticans from 2015 to 2020 Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-07-03 Abigail Barenblitt, Lola Fatoyinbo, Nathan Thomas, Atticus Stovall, Celio de Sousa, Chukwuebuka Nwobi, Laura Duncanson
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Gray whale detection in satellite imagery using deep learning Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-06-22 Katherine M. Green, Mala K. Virdee, Hannah C. Cubaynes, Angelica I. Aviles-Rivero, Peter T. Fretwell, Patrick C. Gray, David W. Johnston, Carola-Bibiane Schönlieb, Leigh G. Torres, Jennifer A. Jackson
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Treeline remote sensing: from tracking treeline shifts to multi-dimensional monitoring of ecotonal change Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-06-19 Matteo Garbarino, Donato Morresi, Nicolò Anselmetto, Peter J. Weisberg
Remote sensing applications have a long history in treeline research. Recent reviews have examined the topic mainly from a methodological point of view. Here, we propose a question-oriented review of remote sensing in treeline ecology to relate remote sensing methodologies to key ecological metrics and identify knowledge gaps and promising areas for future research. We performed a meta-analysis to
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Comparison of bird migration in a radar wind profiler and a dedicated bird radar Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-06-13 Nadja Weisshaupt, Maxime Hervo, Birgen Haest
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Commercial drones can provide accurate and effective monitoring of the world's rarest primate Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-06-07 Hui Zhang, Samuel T. Turvey, Shree P. Pandey, Xiqiang Song, Zhongyu Sun, Nan Wang
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Use of Airborne Laser Scanning to assess effects of understorey vegetation structure on nest-site selection and breeding performance in an Australian passerine bird Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-28 Richard S. Turner, Ophélie J. D. Lasne, Kara N. Youngentob, Shukhrat Shokirov, Helen L. Osmond, Loeske E. B. Kruuk
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Remote monitoring of short-term body mass variation in savanna ungulates Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-25 Nicolás Fuentes-Allende, Philip A. Stephens, Lynne M. MacTavish, Dougal MacTavish, Stephen G. Willis
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The vulnerability and resilience of seagrass ecosystems to marine heatwaves in New Zealand: a remote sensing analysis of seascape metrics using PlanetScope imagery Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-25 Ken Joseph E. Clemente, Mads S. Thomsen, Richard C. Zimmerman
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Global monitoring of soil multifunctionality in drylands using satellite imagery and field data Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-24 R. Hernández-Clemente, A. Hornero, V. Gonzalez-Dugo, M. Berdugo, J. L. Quero, J. C. Jiménez, F. T. Maestre
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Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R-CNN Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-13 James G. C. Ball, Sebastian H. M. Hickman, Tobias D. Jackson, Xian Jing Koay, James Hirst, William Jay, Matthew Archer, Mélaine Aubry-Kientz, Grégoire Vincent, David A. Coomes
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Capturing long-tailed individual tree diversity using an airborne imaging and a multi-temporal hierarchical model Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-10 Ben G. Weinstein, Sergio Marconi, Sarah J. Graves, Alina Zare, Aditya Singh, Stephanie A. Bohlman, Lukas Magee, Daniel J. Johnson, Phillip A. Townsend, Ethan P. White
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Reindeer control over shrubification in subarctic wetlands: spatial analysis based on unoccupied aerial vehicle imagery Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-09 Miguel Villoslada, Henni Ylänne, Sari Juutinen, Tiina H. M. Kolari, Pasi Korpelainen, Teemu Tahvanainen, Franziska Wolff, Timo Kumpula
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BatNet: a deep learning-based tool for automated bat species identification from camera trap images Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-09 Gabriella Krivek, Alexander Gillert, Martin Harder, Marcus Fritze, Karina Frankowski, Luisa Timm, Liska Meyer-Olbersleben, Uwe Freiherr von Lukas, Gerald Kerth, Jaap van Schaik
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Forest edge structure from terrestrial laser scanning to explain bird biophony characteristics from acoustic indices Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-07 Tom E. Verhelst, Pieter Vangansbeke, Pieter De Frenne, Barbara D'hont, Quentin Ponette, Luc Willems, Hans Verbeeck, Kim Calders
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Detecting forest canopy gaps using unoccupied aerial vehicle RGB imagery in a species-rich subtropical forest Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-05-01 Jiale Chen, Li Wang, Tommaso Jucker, Hongzhi Da, Zhaochen Zhang, Jianbo Hu, Qingsong Yang, Xihua Wang, Yuchu Qin, Guochun Shen, Li Shu, Jian Zhang
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Characterizing aboveground biomass and tree cover of regrowing forests in Brazil using multi-source remote sensing data Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-04-27 Na Chen, Nandin-Erdene Tsendbazar, Daniela Requena Suarez, Jan Verbesselt, Martin Herold
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Challenges and solutions for automated avian recognition in aerial imagery Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-04-26 Zhongqi Miao, Stella X. Yu, Kyle L. Landolt, Mark D. Koneff, Timothy P. White, Luke J. Fara, Enrika J. Hlavacek, Bradley A. Pickens, Travis J. Harrison, Wayne M. Getz
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StrucNet: a global network for automated vegetation structure monitoring Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-04-14 Kim Calders, Benjamin Brede, Glenn Newnham, Darius Culvenor, John Armston, Harm Bartholomeus, Anne Griebel, Jodie Hayward, Samuli Junttila, Alvaro Lau, Shaun Levick, Rosalinda Morrone, Niall Origo, Marion Pfeifer, Jan Verbesselt, Martin Herold
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Fine-scale landscape phenology revealed through time-lapse imagery: implications for conservation and management of an endangered migratory herbivore Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-04-08 Christian John, Jeffrey T. Kerby, Thomas R. Stephenson, Eric Post
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Spaceborne LiDAR for characterizing forest structure across scales in the European Alps Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-03-26 Lisa Mandl, Ana Stritih, Rupert Seidl, Christian Ginzler, Cornelius Senf
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Combining unmanned aerial vehicles and satellite imagery to quantify areal extent of intertidal brown canopy-forming macroalgae Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-03-10 Pippa H. Lewis, Benjamin P. Roberts, Pippa J. Moore, Samuel Pike, Anthony Scarth, Katie Medcalf, Iain Cameron
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Seabird surveillance: combining CCTV and artificial intelligence for monitoring and research Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-03-07 Jonas Hentati-Sundberg, Agnes B. Olin, Sheetal Reddy, Per-Arvid Berglund, Erik Svensson, Mareddy Reddy, Siddharta Kasarareni, Astrid A. Carlsen, Matilda Hanes, Shreyash Kad, Olof Olsson
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Modeling approach for coastal dune habitat detection on coastal ecosystems combining very high-resolution UAV imagery and field survey Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-02-09 Emiliano Agrillo, Federico Filipponi, Riccardo Salvati, Alice Pezzarossa, Laura Casella
Earth observation (EO) data, derived from remote sensing and unmanned aerial vehicle (UAV), have been recently demonstrated to be essential tools for the ecosystem monitoring and habitat mapping, combining high technological and methodological procedures for applied ecology. However, research based on EO data analyses often tend to focus on image processing techniques, neglecting the development of
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Colony-nesting gulls restrict activity levels of a native top carnivore during the breeding season Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-02-06 Steven Guidos, Jiska van Dijk, Geir Systad, Arild Landa
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Long-term analysis of persistence and size of swallow and martin roosts in the US Great Lakes Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-01-23 Maria Carolina T. D. Belotti, Yuting Deng, Wenlong Zhao, Victoria F. Simons, Zezhou Cheng, Gustavo Perez, Elske Tielens, Subhransu Maji, Daniel Sheldon, Jeffrey F. Kelly, Kyle G. Horton
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Beyond presence mapping: predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-01-17 Todd M. Preston, Aaron N. Johnston, Kyle G. Ebenhoch, Robert H. Diehl
Non-native species maps are important tools for understanding and managing biological invasions. We demonstrate a novel approach to extend presence modeling to map fractional cover (FC) of non-native yellow sweet clover Melilotus officinalis in the Northern Great Plains, USA. We used ensembles of MaxEnt models to map FC across landscapes from satellite imagery trained from regional aerial imagery that
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Comparison of 3D structural metrics on oyster reefs using unoccupied aircraft photogrammetry and terrestrial LiDAR across a tidal elevation gradient Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2023-01-05 Justin T. Ridge, Alexandra E. DiGiacomo, Antonio B. Rodriguez, Joshua D. Himmelstein, David W. Johnston
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Remote sensing in seagrass ecology: coupled dynamics between migratory herbivorous birds and intertidal meadows observed by satellite during four decades Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-12-28 Maria Laura Zoffoli, Pierre Gernez, Simon Oiry, Laurent Godet, Sébastien Dalloyau, Bede Ffinian Rowe Davies, Laurent Barillé
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Using satellite data to assess spatial drivers of bird diversity Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-12-24 Merryn L. Hunt, George Alan Blackburn, Gavin M. Siriwardena, Luis Carrasco, Clare S. Rowland
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Current and future opportunities for satellite remote sensing to inform rewilding Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-12-16 Nathalie Pettorelli, Henrike Schulte to Bühne
Rewilding has been suggested as an effective strategy for addressing environmental challenges such as the intertwined biodiversity and climate change crises, but there is little information to guide the monitoring of rewilding projects. Since rewilding focuses on enhancing ecosystem functionality, with no defined endpoint, monitoring strategies used in restoration are often inappropriate, as they typically
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Using camera traps to monitor cyclic vole populations Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-12-02 Eivind Flittie Kleiven, Pedro Guilherme Nicolau, Sigrunn Holbek Sørbye, Jon Aars, Nigel Gilles Yoccoz, Rolf Anker Ims
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Time-series remote sensing of rice paddy expansion in the Yellow River Delta: Towards sustainable ecological conservation in the context of water scarcity Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-11-26 Chong Huang, Chenchen Zhang
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Drone-mounted audio-visual deterrence of bats: implications for reducing aerial wildlife mortality by wind turbines Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-11-25 Yuval Werber, Gadi Hareli, Omer Yinon, Nir Sapir, Yossi Yovel
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Using Unoccupied Aerial Vehicles to estimate availability and group size error for aerial surveys of coastal dolphins Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-11-24 Alexander M. Brown, Simon J. Allen, Nat Kelly, Amanda J. Hodgson
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Prospects for monitoring bird migration along the East Asian-Australasian Flyway using weather radar Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-27 Xu Shi, Cheng Hu, Joshua Soderholm, Jason Chapman, Huafeng Mao, Kai Cui, Zhijun Ma, Dongli Wu, Richard A. Fuller
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Mapping mangrove leaf area index (LAI) by combining remote sensing images with PROSAIL-D and XGBoost methods Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-25 Demei Zhao, Jianing Zhen, Yinghui Zhang, Jing Miao, Zhen Shen, Xiapeng Jiang, Junjie Wang, Jincheng Jiang, Yuzhi Tang, Guofeng Wu
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Using airborne lidar to characterize North European terrestrial high-dark-diversity habitats Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-21 Jesper Erenskjold Moeslund, Kevin Kuhlmann Clausen, Lars Dalby, Camilla Fløjgaard, Meelis Pärtel, Norbert Pfeifer, Markus Hollaus, Ane Kirstine Brunbjerg
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Long-duration remote underwater videos reveal that grazing by fishes is highly variable through time and dominated by non-indigenous species Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-21 Camille Magneville, Marie-Lou Leréec Le Bricquir, Thanos Dailianis, Grigorios Skouradakis, Thomas Claverie, Sébastien Villéger
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Characterizing bedforms in shallow seas as an integrative predictor of seafloor stability and the occurrence of macrozoobenthic species Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-18 Kasper J. Meijer, Oscar Franken, Tjisse van der Heide, Sander J. Holthuijsen, Wim Visser, Laura L. Govers, Han Olff
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Automating sandhill crane counts from nocturnal thermal aerial imagery using deep learning Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-18 Emilio Luz-Ricca, Kyle Landolt, Bradley A. Pickens, Mark Koneff
Population monitoring is essential to management and conservation efforts for migratory birds, but traditional low-altitude aerial surveys with human observers are plagued by individual observer bias and risk to flight crews. Aerial surveys that use remote sensing can reduce bias and risk, but manual counting of wildlife in imagery is laborious and may be cost-prohibitive. Therefore, automated methods
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Passive acoustic surveys reveal interactions between frugivorous birds and fruiting trees on a large forest dynamics plot Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-13 Anran Dong, Xuelian He, Yiming Deng, Luxiang Lin, Eben Goodale
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Exploring the link between spectral variance and upper canopy taxonomic diversity in a tropical forest: influence of spectral processing and feature selection Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-10-01 Colette Badourdine, Jean-Baptiste Féret, Raphaël Pélissier, Grégoire Vincent
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Imperfect detection and wildlife density estimation using aerial surveys with infrared and visible sensors Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-09-27 Zackary J. Delisle, Patrick G. McGovern, Brian G. Dillman, Robert K. Swihart
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Resource pulses and human–wildlife conflicts: linking satellite indicators and ground data on forest productivity to predict brown bear damages Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-09-24 Carlos Bautista, Julian Oeser, Tobias Kuemmerle, Nuria Selva
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Camera trapping with photos and videos: implications for ecology and citizen science Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-09-24 Sian E. Green, Philip A. Stephens, Mark J. Whittingham, Russell A. Hill
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Using unoccupied aerial vehicles to map and monitor changes in emergent kelp canopy after an ecological regime shift Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-09-21 Vienna R. Saccomanno, Tom Bell, Camille Pawlak, Charlotte K. Stanley, Katherine C. Cavanaugh, Rietta Hohman, Kirk R. Klausmeyer, Kyle Cavanaugh, Abby Nickels, Waz Hewerdine, Corey Garza, Gary Fleener, Mary Gleason
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A camera trap-based assessment of climate-driven phenotypic plasticity of seasonal moulting in an endangered carnivore Remote Sens. Ecol. Conserv. (IF 5.5) Pub Date : 2022-09-19 Lucie Laporte-Devylder, Kristine R. Ulvund, Lars Rød-Eriksen, Ola Olsson, Øystein Flagstad, Arild Landa, Nina E. Eide, Craig R. Jackson