- Undergraduate Programs
- Graduate Programs
Jan van Aardt
Phone: (585) 475-4229
B.Sc. Forestry (University of Stellenbosch, South Africa)
Hons. Forestry (University of Stellenbosch, South Africa)
MS Forestry (Virginia Tech, Virginia, USA)
PhD Forestry (Virginia Tech, Virginia, USA)
Precision agriculture - from imaging spectroscopy and lidar to operational systems using unmanned aerial systems (UAS)
- White mold risk modeling in snap bean via imaging spectroscopy & lidar
- UAS-based assessment of root yield in beets
- Yield prediction and harvest scheduling in snap bean: Spectral and structural remote sensing approaches
- Crop structural assessment towards yield and biomass (carbon) modeling: Structure-from-motion and lidar approaches
- Systems: In situ, airborne, and unmanned aerial systems (UAS)
- Collaborators: Cornell University (academic), Seneca Foods, Farm Fresh First, Love Beets (industry)
Forest inventory and canopy structure assessment using lidar remote sensing
- Fire fuel load assessment
- Structural differences along management, impact, and meteorological gradients
- Systems for vegetation structural sensing: Airborne discrete-, airborne waveform-, and terrestrial discrete return lidar
- Collaborators: University of Kentucky, Virginia Commonwealth University, United States Forest Service (USFS), Carnegie Institution for Science, The National Ecological Observatory Network (NEON), Council for Scientific and Industrial Research (South Africa)
Structural characterization of savanna vegetation using small-footprint waveform lidar and imaging spectroscopy data
- Imaging spectroscopy and lidar data fusion & pixel unmixing approaches for woody and herbaceous biomass, and land degradation assessment
- Collaborators: Carnegie Institution for Science, Council for Scientific and Industrial Research, Wits University, Kruger National Park (South Africa)
Remote sensing for disaster response
- Image- and lidar-based assessments of i) infrastructure damage, ii) flooding, and ii) debris as spatial product inputs to access restoration models
- Collaborators: Rensselaer Polytechnic Institute (RPI)
Graduate and undergraduate student advising
Adviser - graduate students
- Benjamin Roth. PhD; RIT, USA; 2018-onward; Describing attenuation in waveform lidar signals in forest canopies (tentative).
- Amirhossein Hassanzadeh. PhD; RIT, USA; 2018-onward; Hyperspectral yield modeling and harvest scheduling in snap bean - Fostering Agricultural ReMote Sensing (FARMS) Alliance (tentative).
- Fei Zhang. PhD; RIT, USA; 2019-onward; On using structure-from-motion and lidar sensing for yield modeling and harvest scheduling in snap bean - Fostering Agricultural ReMote Sensing (FARMS) Alliance (tentative).
- Grady Saunders. PhD; RIT, USA; 2018-onward; A simulation-based approach to assessing corn spectral phenology and phenomenology (tentative).
- Aditya Kunwar. MS; RIT, USA; 2018-onward; 3D structure in vegetable crops – structure-from-motion vs. lidar sensing (tentative).
- Ethan Hughes. PhD; RIT, USA; 2017-onward; Transforming White Mold Management in Snap Bean Using Remote Sensing via Unmanned Aerial Systems (tentative).
- Matthew Helvey. MS; RIT, USA; 2019-onward; UAS-based assessment of duck nest habitats - fusing hyperspectral and lidar sensing (tentative).
- Alexander Fafard. PhD; RIT, USA; 2017-onward; Global 3D change detection approaches using structure-from-motion (tentative).
- Ali Rouzbeh Kargar. PhD; RIT, USA; 2017-onward; A new 3D terrestrial lidar approach to monitoring the resilience of mangroves to sea level rise (tentative).
- Ronnie Izzo. MS; RIT, USA; 2018-2019; Combining Hyperspectral Imaging and Small Unmanned Aerial Systems for Grapevine Moisture Stress Assessment.
- McKay Williams. PhD; RIT, USA; 2015-2017; Generation, validation, and application of abundance map reference data for spectral unmixing.
- Colin Axel. PhD; RIT, USA; 2014-2016; Fusing lidar data and high spatial resolution imagery for rapid post-disaster route assessment towards improved trafficability solutions.
- Wei Yao. PhD; RIT, USA; 2012-2014; Investigating the impact of spatially-explicit sub-pixel structural variation on the assessment of vegetation structure from HyspIRI data.
- Timothy Rupright. MS; RIT, USA; 2014-2018; Deciduous species classification in the northeastern USA using imaging spectroscopy (tentative).Grant Anderson. MS; RIT, USA; 2015-2016; Assessing vineyard physiology using narrow-band remote sensing or extension to unmanned aerial systems (tentative).
- Paul Romanczyk. PhD; RIT, USA; 2010-2015; Extraction of Vegetation Biophysical Structure from Small-Footprint Full-Waveform Lidar Signals.
- Madhurima Bandyopadhyay. PhD; RIT, USA; 2011-2015; Quantifying the urban forest environment using dense discrete return LiDAR and aerial color imagery for segmentation and object-level biomass assessment.
- David Kelbe. PhD; RIT, USA; 2011-2015; Forest structure from terrestrial laser scanning – in support of remote sensing calibration/validation and operational inventory.
- Shagan Sah. MS; RIT, USA; 2011-2013; Combing coarse spatial resolution multi-temporal and high spatial resolution classification approaches for mapping of nuclear ingestion pathways.
- William (Jiaying) Wu. PhD; RIT, USA; 2008-2012; Lidar waveform preprocessing and analysis for extracting scale-invariant woody and herbaceous biomass estimates.
- Rick Labiak. MS; RIT, USA; 2010-2011; Remote sensing disaster response algorithms: Building damage and debris assessment using a stand-alone discrete return lidar approach.
- Joe McGlinchy. MS; RIT, USA; 2009-2011; Unmixing lidar waveforms into structural target components.
- Diane Sarrazin. MS; RIT, USA; 2009-2010; Fusion of waveform and hyperspectral data for improved species classification and biomass estimation.
Adviser - undergraduate students
- Kevin Kha (2019): Yield Modeling of Corn Silage with Multispectral Cubesat Imagery.
- Evan Marcellus (2018): Silicon-range moisture stress assessment in vineyards – an operational approach.
- Seth Baker (2017): Corn yield (and biomass) modeling based on structure-from-motion approaches for imagery from unmanned aerial systems (UAS).
- Sadie Wolters (2017): Towards early white mold detection in snap beans using imaging spectroscopy data.
- Lindsay Martinesu (2017): Differentiating crop treatments using UAS multispectral imagery: Fertilization in corn and fungicides in snap beans.
- Kelly Patterson (2017): Validation of techniques for reference data development - from high spatial to coarse spatial resolution imaging spectroscopy.
- Alexander Fafard (RIT; 2015): (i) Assessment of debris using LiDAR remote sensing and (ii) Construction of a cost-effective, off-the-shelf (COTS) terrestrial LiDAR system.
- Susan Kratzer (RIT; 2015): Towards assessment of vegetation structure using coarse resolution pixel unmixing (senior project).
- Ashley Miller (RIT; 2014): Canopy Segmentation using Airborne LiDAR.
- Jonathan Rowe (RIT; 2014): Ground Classification and Below Ground Response Assessment of Forested Regions using Full-Waveform LiDAR.
- Colin Axel (RIT; 2013): 3D algorithm development for a single-scan ground-based lidar system.
- Linnea Tullson (RIT; 2012): Extraction and quantification of trees from ground-based lidar point clouds.
- Thomas Yang (RIT; 2012): Extraction and quantification of planar man-made surfaces from ground-based lidar point clouds.
- Kevin Bloechl (RIT; 2012): Registration of multiple ground-based lidar point clouds.
- Jonathan Lueders (RIT; 2012): Assessing vineyard moisture status using hyperspectral remote sensing approaches.
- Matthew Brophy (RIT; 2011): Assessment of savanna herbaceous biomass using an imaging spectroscopy pixel unmixing approach.
- Allison Bright (RIT; 2010): Identification of spectral indicators of vegetation disturbance – a data mining approach.
- Robert Hammell (RIT; 2010): Identification of spectral indicators of vegetation disturbance – a data mining approach.
- Dave Kelbe (RIT; 2009): Lidar processing for aboveground biomass estimation in savanna ecosystems.
Co-adviser and/or active committee involvement
- Nicole Dutcher; RIT, USA; 2011-2013; Characterizing Wetland Vegetation Using Hyperspectral Imagery for Monitoring Purposes.
- Nahid Carter. MS; RIT, USA; 2011-2012; Classification of tree species in upstate New York towards assessing the impact of emerald ash borer infestation.
- Katherine Premo. MS; RIT, USA; 2010-2011; Invertebrate effects on sediment biogeochemistry and microphytobenthos during and after macroalgal blooms.
- Jolene Fischer. Ph.D.; University of Witwatersrand, South Africa; 2013; Three-dimensional woody vegetation structure across spatial scales and land-use intensities in a semi-arid savanna.
- Dr. Thamsanqa Mzinyane. Ph.D. University of Kwazulu-Natal, South Africa; 2012; Quantitative Assessment of the Impacts of leaf Chlorophyll, Nitrogen Content and Water Status on Growth of Eucalyptus clones using Hyperspectral Remote Sensing.
- Wesley Roberts. Ph.D.; University of Kwazulu-Natal, South Africa; 2006-2010; Image fusion for enhanced forest structure assessment.
- Dr. Solomon Tesfamichael. PhD; University of Kwazulu-Natal, South Africa; 2009; Assessment of structural attributes of even-aged Eucalyptus grandis forest plantations using small-footprint discrete return lidar data.
- Dr. Michael Gebreslasie. PhD; University of Kwazulu-Natal, South Africa; 2009; The estimation of Eucalyptus plantation forest structural attributes using medium and high spatial resolution satellite imagery.
- Dr. Mark Norris-Rogers. PhD; University of Kwazulu-Natal, South Africa; 2006; An investigation into using textural analysis and change detection techniques on medium and high spatial resolution imagery for monitoring plantation forestry operations.
Scholarships and Awards
- Rochester Institute of Technology, Board of Trustees Scholarship Award, 2015-16.
- Rochester Institute of Technology, Principal Investigators Millionaires Club, 2012.
- Rochester Institute of Technology College of Science, COS Outstanding Faculty of the Year Award, 2012.
- American Society for Photogrammetry and Remote Sensing (ASPRS), 2009 ERDAS Award for Best Scientific Paper in Remote Sensing, 2009.