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Satellite-based remote sensing is instrumental in the monitoring and mitigation of the effects of anthropogenic climate change. Large scale, high resolution data derived from these sensors can be used to inform intervention and policy…
The farming industry constantly seeks the automation of different processes involved in agricultural production, such as sowing, harvesting and weed control. The use of mobile autonomous robots to perform those tasks is of great interest.…
Accurate and timely monitoring of forest canopy heights is critical for assessing forest dynamics, biodiversity, carbon sequestration as well as forest degradation and deforestation. Recent advances in deep learning techniques, coupled with…
The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar instrument that collects near-global measurements of forest structure. While expansive in scope, GEDI samples are spatially sparse and cover a small fraction of the…
Modern forest monitoring workflows increasingly benefit from the growing availability of high-resolution satellite imagery and advances in deep learning. Two persistent challenges in this context are accurate pixel-level change detection…
Fine-scale forest monitoring is essential for understanding canopy structure and its dynamics, which are key indicators of carbon stocks, biodiversity, and forest health. Deep learning is particularly effective for this task, as it…
Global environment monitoring is a task that requires additional attention in the contemporary rapid climate change environment. This includes monitoring the rate of deforestation and areas affected by flooding. Satellite imaging has…
In Canada's northern regions, linear disturbances such as roads, seismic exploration lines, and pipelines pose a significant threat to the boreal woodland caribou population (Rangifer tarandus). To address the critical need for management…
Wildfires pose a significant global threat to ecosystems worldwide, with California experiencing recurring fires due to various factors, including climate, topographical features, vegetation patterns, and human activities. This study aims…
Invasive species pose major global threats to ecosystems and agriculture. Serrated tussock (\textit{Nassella trichotoma}) is a highly competitive invasive grass species that disrupts native grasslands, reduces pasture productivity, and…
Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mapping using single-polarization SAR data remains challenging in complex environments where…
Access to highly detailed models of heterogeneous forests, spanning from the near surface to above the tree canopy at varying scales, is increasingly in demand. This enables advanced computational tools for analysis, planning, and ecosystem…
Accurate and automated sea ice classification is important for climate monitoring and maritime safety in the Arctic. While Synthetic Aperture Radar (SAR) is the operational standard because of its all-weather capability, it remains…
Accurate and timely crop yield estimation is critical for global food security, agricultural policy, and farm management. The Copernicus Sentinel-2 satellite constellation, with high spatial, temporal, and spectral resolution, has…
Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems. In this regard, evaluating the amount and quality of dead wood is of utmost interest as they are favorable indicators of…
According to the Paris Climate Change Agreement, all nations are required to submit reports on their greenhouse gas emissions and absorption every two years by 2024. Consequently, forests play a crucial role in reducing carbon emissions,…
In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) is arguably needed to capture the differences in canopy…
In large-area forest inventories a trade-off between the amount of data to be sampled and the costs of collecting the data is necessary. It is not always possible to have a very large data sample when dealing with sampling-based…
Building height is an important indicator for scientific research and practical application. However, building height products with a high spatial resolution (10m) are still very scarce. To meet the needs of high-resolution building height…
Vision-based segmentation in forested environments is a key functionality for autonomous forestry operations such as tree felling and forwarding. Deep learning algorithms demonstrate promising results to perform visual tasks such as object…