Jinha Jung

Assistant Professor

Purdue University

United States

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Jinha Jung is an Assistant Professor at Purdue University in the United States. His research areas encompass remote sensing, machine learning, and environmental monitoring, as evidenced by his recent work on unmanned aerial systems and LiDAR technologies. He has contributed to numerous projects, including the development of frameworks for automated plot extraction and biodiversity monitoring in rainforests, along with advancements in imaging techniques for satellite imagery restoration.

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Delft University of Technology

NETHERLANDS

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Songlin Fei

Purdue University

UNITED STATES

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James Camberato

Professor

Purdue University

UNITED STATES

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Juan Enciso

Professor

Texas A&M AgriLife Research

UNITED STATES

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Jinha Jung

Research Interests

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About

Articles (20)

Autonomous and Teleoperated Technologies for Comprehensive Rainforest Biodiversity Monitoring

Optimizing Camera Settings and Unmanned Aerial Vehicle Flight Methods for Imagery-Based 3D Reconstruction: Applications in Outcrop and Underground Rock Faces

Unsupervised surface water mapping with airborne LiDAR data by leveraging physical properties of water

Developing a segment anything model-based framework for automated plot extraction

Integrating Sparse LiDAR and Multisensor Time-Series Imagery From Spaceborne Platforms for Deriving Localized Canopy Height Model

Cloud restoration of optical satellite imagery using time-series spectral similarity group

Tree Species Classification from UAV Canopy Images with Deep Learning Models

Cloud Detection Using a UNet3+ Model with a Hybrid Swin Transformer and EfficientNet (UNet3+STE) for Very-High-Resolution Satellite Imagery

Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning

Temperature and electric vehicle adoption: A ZIP code-level analysis in the US

Replacement Sensor Model Generation for a Long High-Resolution Satellite Image Strip

Prediction of Cereal Rye Cover Crop Biomass and Nutrient Accumulation Using Multi-Temporal Unmanned Aerial Vehicle Based Visible-Spectrum Vegetation Indices

A Scalable Method to Improve Large-Scale Lidar Topographic Differencing Results

An Object-Based Ground Filtering of Airborne LiDAR Data for Large-Area DTM Generation

Photogrammetric 3D Scanning of Asphalt Cores for Automatic Layer Detection and Gradation Classification

Self-Filtered Learning for Semantic Segmentation of Buildings in Remote Sensing Imagery With Noisy Labels

An Unsupervised Canopy-to-Root Pathing (UCRP) Tree Segmentation Algorithm for Automatic Forest Mapping

Engaging Engineering Students with the Stakeholders for Infrastructure Planning

High-Resolution Canopy Height Model Generation and Validation Using USGS 3DEP LiDAR Data in Indiana, USA

Performance Evaluation of Parallel Structure from Motion (SfM) Processing with Public Cloud Computing and an On-Premise Cluster System for UAS Images in Agriculture

Collaborators (13)

Jaehong Oh

Richard Roth

Baijian Yang

Veronica Ancona

Junsu Leem

Brady Hardiman

Matthew Spenko

Konstantina Gkritza

Youkyung Han

Arkaprabha Bhattacharyya

Songlin Fei

James Camberato

Juan Enciso

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