Abstract: High-resolution cameras have become very helpful for plant phenotyping by providing a mechanism for tasks such as target versus background discrimination, and the measurement and analysis of fine-above-ground plant attributes. However, the acquisition of high-resolution (HR) imagery of plant… Read More
Journal PapersJournal Papers
MIMRF Published in TGRS!
Congratulations to GatorSense alumna, Xiaoxiao Du! Her paper, titled “Multi-resolution Multi-modal Sensor Fusion For Remote Sensing Data with Label Uncertainty”, was recently published in IEEE Transactions on Geoscience and Remote Sensing. Check it out here!
Multi-Target Multiple Instance Learning for Hyperspectral Target Detection
Abstract: In remote sensing, it is often challenging to acquire or collect a large dataset that is accurately labeled. This difficulty is usually due to several issues, including but not limited to the study site’s spatial area and accessibility, errors… Read More
RhizoVision Crown Accepted to Plant Phenomics!
Machine Learning and Sensing Lab Alumni, Anand Seethepalli, and collaborators recently had a paper accepted to Plant Phenomics. The article discusses an innovative platform to help collect consistent images of root crowns for phenotyping. Check it out here!
Peanut Maturity Classification using Hyperspectral Imagery
Abstract: Seed maturity in peanut ( Arachis hypogaea L.) determines economic return to a producer because of its impact on seed weight, and critically influences seed vigor and other quality characteristics. During seed development, the inner mesocarp layer of the… Read More
Breaking down barriers between remote sensing and plant pathology
Abstract: A critical component for enhancing productivity and quality of food and fiber is the ability to quickly detect and monitor plant diseases in order to prevent or minimize losses to agricultural and forest products (Mahlein 2016). The earlier (prior to… Read More
Classifying California plant species temporally using airborne hyperspectral imagery
Abstract: Accurate knowledge of seasonal and inter-annual distributions of plant species is required for many research and management agendas that track ecosystem health. Airborne imaging spectroscopy data have been used successfully to map plant species, but often only in a… Read More
Plant species’ spectral emissivity and temperature using the hyperspectral thermal emission spectrometer (HyTES) sensor
Abstract: The thermal domain (TIR; 2.5–15 μm) delivers unique measurements of plant characteristics that are not possible in other parts of the electromagnetic spectrum. However, these TIR measurements have largely been restricted to laboratory leaf level or coarse spatial resolutions… Read More
The ECOSTRESS spectral library version 1.0. Remote Sensing of Environment
Abstract: In June 2018, the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission was launched to measure plant temperatures and better understand how they respond to stress. While the ECOSTRESS mission delivers imagery with ~60 m spatial resolution,… Read More
Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks
Abstract: Remote sensing can transform the speed, scale, and cost of biodiversity and forestry surveys. Data acquisition currently outpaces the ability to identify individual organisms in high resolution imagery. We outline an approach for identifying tree-crowns in true color, or… Read More