Jinha Jung
Jinha Jung
Assistant Professor at Purdue University
Verified email at purdue.edu
Title
Cited by
Cited by
Year
Modeling acoustic diversity using soundscape recordings and LIDAR-derived metrics of vertical forest structure in a neotropical rainforest
BK Pekin, J Jung, LJ Villanueva-Rivera, BC Pijanowski, JA Ahumada
Landscape ecology 27 (10), 1513-1522, 2012
962012
Crop height monitoring with digital imagery from Unmanned Aerial System (UAS)
A Chang, J Jung, MM Maeda, J Landivar
Computers and Electronics in Agriculture 141, 232-237, 2017
872017
Ensemble multiple kernel active learning for classification of multisource remote sensing data
Y Zhang, HL Yang, S Prasad, E Pasolli, J Jung, M Crawford
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014
642014
Combined vegetation volume and “greenness” affect urban air temperature
AY Davis, J Jung, BC Pijanowski, ES Minor
Applied Geography 71, 106-114, 2016
422016
A framework for land cover classification using discrete return LiDAR data: Adopting pseudo-waveform and hierarchical segmentation
J Jung, E Pasolli, S Prasad, JC Tilton, MM Crawford
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014
372014
Temporal estimates of crop growth in sorghum and maize breeding enabled by unmanned aerial systems
NA Pugh, DW Horne, SC Murray, G Carvalho Jr, L Malambo, J Jung, ...
The Plant Phenome Journal 1 (1), 1-10, 2018
292018
Measurement and calibration of plant-height from fixed-wing UAV images
X Han, JA Thomasson, GC Bagnall, N Pugh, DW Horne, WL Rooney, ...
Sensors 18 (12), 4092, 2018
282018
Comparison of vegetation indices derived from UAV data for differentiation of tillage effects in agriculture
J Yeom, J Jung, A Chang, A Ashapure, M Maeda, A Maeda, J Landivar
Remote Sensing 11 (13), 1548, 2019
252019
A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data
A Ashapure, J Jung, J Yeom, A Chang, M Maeda, A Maeda, J Landivar
ISPRS Journal of Photogrammetry and Remote Sensing 152, 49-64, 2019
232019
Automated open cotton boll detection for yield estimation using unmanned aircraft vehicle (UAV) data
J Yeom, J Jung, A Chang, M Maeda, J Landivar
Remote Sensing 10 (12), 1895, 2018
232018
Validation of agronomic UAV and field measurements for tomato varieties
J Enciso, CA Avila, J Jung, S Elsayed-Farag, A Chang, J Yeom, ...
Computers and Electronics in Agriculture 158, 278-283, 2019
222019
Unmanned aerial system assisted framework for the selection of high yielding cotton genotypes
J Jung, M Maeda, A Chang, J Landivar, J Yeom, J McGinty
Computers and Electronics in Agriculture 152, 74-81, 2018
222018
Soundscapes reveal disturbance impacts: Biophonic response to wildfire in the Sonoran Desert Sky Islands
A Gasc, BL Gottesman, D Francomano, J Jung, M Durham, J Mateljak, ...
Landscape Ecology 33 (8), 1399-1415, 2018
212018
Prediction of maize grain yield before maturity using improved temporal height estimates of unmanned aerial systems
SL Anderson, SC Murray, L Malambo, C Ratcliff, S Popescu, D Cope, ...
The Plant Phenome Journal 2 (1), 1-15, 2019
202019
A comparative study of RGB and multispectral sensor-based cotton canopy cover modelling using multi-temporal UAS data
A Ashapure, J Jung, A Chang, S Oh, M Maeda, J Landivar
Remote Sensing 11 (23), 2757, 2019
182019
Extraction of features from LIDAR waveform data for characterizing forest structure
J Jung, MM Crawford
IEEE Geoscience and Remote Sensing Letters 9 (3), 492-496, 2011
172011
A ground based platform for high throughput phenotyping
J Enciso, M Maeda, J Landivar, J Jung, A Chang
Computers and Electronics in Agriculture 141, 286-291, 2017
152017
A two-stage approach for decomposition of ICESat waveforms
J Jung, MM Crawford
IGARSS 2008-2008 IEEE International Geoscience and Remote Sensing Symposium …, 2008
152008
Unmanned aerial system based tomato yield estimation using machine learning
A Ashapure, S Oh, TG Marconi, A Chang, J Jung, J Landivar, J Enciso
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and …, 2019
122019
The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems
J Jung, M Maeda, A Chang, M Bhandari, A Ashapure, J Landivar-Bowles
Current Opinion in Biotechnology 70, 15-22, 2021
112021
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Articles 1–20