Category: Publication
Individual canopy tree species maps for the National Ecological Observatory Network
October 17, 2024Abstract: The ecology of forest ecosystems depends on the composition of trees. Capturing fine-grained information on individual trees at broad scales provides a unique perspective on forest ecosystems, forest restoration and responses to disturbance. Individual tree data at wide extents promises to increase the scale of forest analysis, biogeographic research, and ecosystem monitoring without losing […]
Read more: Individual canopy tree species maps for the National Ecological Observatory Network »Estimating Soil Mineral Nitrogen from Data-sparse Field Experiments using Crop Model-guided Deep Learning Approach
October 3, 2024Abstract: Sandy soils are susceptible to excessive nitrogen (N) leaching under intensive crop production which is linked with the soil’s low nutrient holding capacity and high-water infiltration rate. Estimating soil mineral nitrogen (SMN) at the daily time-step is crucial in providing fertilizer recommendations balancing plant nitrogen use efficiency (NUE) and N losses to the environment. […]
Read more: Estimating Soil Mineral Nitrogen from Data-sparse Field Experiments using Crop Model-guided Deep Learning Approach »Hyperspectral signals in the soil: Plant–soil hydraulic connection and disequilibrium as mechanisms of drought tolerance and rapid recovery
August 16, 2024Abstract: Predicting soil water status remotely is appealing due to its low cost and large-scale application. During drought, plants can disconnect from the soil, causing disequilibrium between soil and plant water potentials at pre-dawn. The impact of this disequilibrium on plant drought response and recovery is not well understood, potentially complicating soil water status predictions […]
Read more: Hyperspectral signals in the soil: Plant–soil hydraulic connection and disequilibrium as mechanisms of drought tolerance and rapid recovery »Elicitating Challenges and User Needs Associated with Annotation Software for Plant Phenotyping
June 10, 2024Abstract: Artificial Intelligence (AI) has been enhancing data analysis efficiency and accuracy during plant phenotyping, which is vital for tackling global agricultural and environmental challenges. Designing a reliable AI system to assist precise plant phenotyping begins with high-quality phenotypic feature annotation, which usually involves collaboration between plant scientists and AI specialists. However, due to the […]
Read more: Elicitating Challenges and User Needs Associated with Annotation Software for Plant Phenotyping »Dealing with imperfect data for invasive species detection using multispectral imagery
June 10, 2024Abstract: Detection and monitoring invasive species can provide valuable ecological information to guide management decisions. Multispectral imagery remote sensing may be an ideal tool to address this problem by providing accurate and affordable repeat imagery. However, developing training datasets for remote sensing imagery can be riddled with issues such as matching a training site to […]
Read more: Dealing with imperfect data for invasive species detection using multispectral imagery »Spectral ecophysiology: hyperspectral pressure–volume curves to estimate leaf turgor loss
June 10, 2024Abstract: Turgor loss point (TLP) is an important proxy for plant drought tolerance, species habitat suitability, and drought-induced plant mortality risk. Thus, TLP serves as a critical tool for evaluating climate change impacts on plants, making it imperative to develop high-throughput and in situ methods to measure TLP. We developed hyperspectral pressure–volume curves (PV curves) […]
Read more: Spectral ecophysiology: hyperspectral pressure–volume curves to estimate leaf turgor loss »Null Space Analysis for Detecting Unknown Objects During Automatic Target Recognition Tasks in Sonar Data
May 14, 2024Abstract: During automatic target recognition once a detector has found points of interest the classifier is then tasked with identifying target objects from non-target objects. However, occasionally the detector may find something that is neither known false alarm nor expected target. In these cases what is the classifier to do? In this paper we define […]
Read more: Null Space Analysis for Detecting Unknown Objects During Automatic Target Recognition Tasks in Sonar Data »Segmentation Pseudo-label Generation using the Multiple Instance Learning Choquet Integral
January 31, 2024Abstract: Weakly supervised target detection and semantic segmentation (WSSS) approaches aim at learning object or pixel level classification labels from imprecise, uncertain, or ambiguous data annotations. A crucial step in WSSS is to produce pseudolabels which can be used to train a fully supervised semantic classifier. Post-hoc attention mechanisms, such as class activation mapping (CAM), […]
Read more: Segmentation Pseudo-label Generation using the Multiple Instance Learning Choquet Integral »HyperPRI: A Dataset of Hyperspectral Images for Underground Plant Root Study
November 4, 2023Abstract: Collecting and analyzing hyperspectral imagery (HSI) of plant roots over time can enhance our understanding of their function, responses to environmental factors, turnover, and relationship with the rhizosphere. Current belowground red-green-blue (RGB) root imaging studies infer such functions from physical properties like root length, volume, and surface area. HSI provides a more complete spectral […]
Read more: HyperPRI: A Dataset of Hyperspectral Images for Underground Plant Root Study »Individual tree crown maps for the National Ecological Observatory Network
November 4, 2023Abstract: The ecology of forest ecosystems depends on the composition of trees. Capturing fine-grained information on individual trees at broad scales allows an unprecedented view of forest ecosystems, forest restoration and responses to disturbance. To create detailed maps of tree species, airborne remote sensing can cover areas containing millions of trees at high spatial resolution. […]
Read more: Individual tree crown maps for the National Ecological Observatory Network »