J
Jan van Aardt
Researcher at Rochester Institute of Technology
Publications - 112
Citations - 2677
Jan van Aardt is an academic researcher from Rochester Institute of Technology. The author has contributed to research in topics: Lidar & Hyperspectral imaging. The author has an hindex of 24, co-authored 109 publications receiving 2161 citations. Previous affiliations of Jan van Aardt include Katholieke Universiteit Leuven & Council of Scientific and Industrial Research.
Papers
More filters
Journal ArticleDOI
Assessment of image fusion procedures using entropy, image quality, and multispectral classification
TL;DR: Images fusion procedures for the fusion of multi-spectral ASTER data and a RadarSAT-1 SAR scene are explored to determine which fusion procedure merged the largest amount of SAR texture into the ASTER scenes, while also preserving the spectral content.
Journal ArticleDOI
Detection of biotic stress (Venturia inaequalis) in apple trees using hyperspectral data: Non-parametric statistical approaches and physiological implications
TL;DR: The use of hyperspectral approaches for early detection of plant stress caused by Venturia inaequalis (apple scab) was investigated to move towards more efficient and reduced application of pesticides, fertilizers or other crop management treatments in apple orchards.
Journal ArticleDOI
Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system
Moses Azong Cho,Renaud Mathieu,Gregory P. Asner,Laven Naidoo,Jan van Aardt,Abel Ramoelo,Pravesh Debba,Konrad J Wessels,Konrad J Wessels,Russell Main,Izak P.J. Smit,Barend F.N. Erasmus +11 more
TL;DR: In this article, the authors investigated the utility of the Carnegie Airborne Observatory (CAO) hyperspectral data, and WorldView-2 and Quickbird multispectral spectral data and a combined spectral+tree height dataset (derived from the CAO LiDAR system) for mapping seven common savanna tree species or genera in the Sabi Sands Reserve and communal lands adjacent to Kruger National Park, South Africa.
Journal ArticleDOI
Influence of measurement set-up of ground-based LiDAR for derivation of tree structure
TL;DR: In this article, the authors investigated the influence of a geometric laser measurement pattern and shadow effect on the accuracy of a quantitative mathematical description of individual tree structure using a terrestrial laser system.
Journal ArticleDOI
Forest Volume and Biomass Estimation Using Small-Footprint Lidar-Distributional Parameters on a Per-Segment Basis
TL;DR: In this article, a lidar-based, object-oriented approach to forest volume and aboveground biomass modeling is presented, which is based on segmentation objects, hierarchical in terms of area and ranging from 0.035 to 5.632 ha/object.