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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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