Jonghan Ko
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View article: MODIS-based Maize Vegetation Indices and Yield Maps for the Seven US Corn Belt States
MODIS-based Maize Vegetation Indices and Yield Maps for the Seven US Corn Belt States Open
This study developed a remote sensing-integrated crop model (RSCM) incorporating machine learning (ML) methodologies to predict maize yields across the US Corn Belt. The framework integrated MODIS vegetation indices with AgERA5 meteorologi…
View article: An Evaluation of the Economic Value and Effectiveness of Agro-Healing Programs
An Evaluation of the Economic Value and Effectiveness of Agro-Healing Programs Open
View article: Analysis of Riverbed Sediment Distribution and Key Contributing Factors: A Deep Learning-based Approach
Analysis of Riverbed Sediment Distribution and Key Contributing Factors: A Deep Learning-based Approach Open
View article: Climate Change Alters Ecological Niches and Distribution of Two Major Forest Species in Korea, Accelerating the Pace of Forest Succession
Climate Change Alters Ecological Niches and Distribution of Two Major Forest Species in Korea, Accelerating the Pace of Forest Succession Open
Temperate forest ecosystems in Korea are currently undergoing a successional transition from Pinus densiflora Siebold & Zucc. (evergreen conifer) communities to Quercus mongolica Fisch. ex Ledeb. (deciduous broadleaf) communities. This stu…
View article: Impact of calibration strategy and data on wheat simulation with the DSSAT‐Nwheat model
Impact of calibration strategy and data on wheat simulation with the DSSAT‐Nwheat model Open
Cropping system models (CSMs) are valuable tools for analyzing genotype, environment, and management (G × E × M) interactions in crop production. To apply a CSM in a new region with specific soils, climate, and cultivars, proper calibratio…
View article: Analysis of Aquifer Resilience and Stress in Western Jeju‘s Mid-Mountainous Region: Impacts of Climate Change and Extreme Weather Events
Analysis of Aquifer Resilience and Stress in Western Jeju‘s Mid-Mountainous Region: Impacts of Climate Change and Extreme Weather Events Open
View article: Assessing maize growth and yield using a remote sensing–integrated crop model enhanced with lasso and ridge regression
Assessing maize growth and yield using a remote sensing–integrated crop model enhanced with lasso and ridge regression Open
View article: Evaluation of Cloud Mask Performance of KOMPSAT-3 Top-of-Atmosphere Reflectance Incorporating Deeplabv3+ with Resnet 101 Model
Evaluation of Cloud Mask Performance of KOMPSAT-3 Top-of-Atmosphere Reflectance Incorporating Deeplabv3+ with Resnet 101 Model Open
Cloud detection is a crucial task in satellite remote sensing, influencing applications such as vegetation indices, land use analysis, and renewable energy estimation. This study evaluates the performance of cloud masks generated for KOMPS…
View article: Rscm: A Remote Sensing-Integrated Crop Model for Field-to-Regional Scale Yield Forecasting
Rscm: A Remote Sensing-Integrated Crop Model for Field-to-Regional Scale Yield Forecasting Open
View article: Deep learning-enhanced remote sensing-integrated crop modeling for rice yield prediction
Deep learning-enhanced remote sensing-integrated crop modeling for rice yield prediction Open
This study introduces a novel crop modeling approach based on cutting-edge computational tools to advance crop production monitoring methodologies, and, thereby, tackle global food security issues. Our approach pioneers integrating deep le…
View article: Combining machine learning and remote sensing-integrated crop modeling for rice and soybean crop simulation
Combining machine learning and remote sensing-integrated crop modeling for rice and soybean crop simulation Open
Machine learning (ML) techniques offer a promising avenue for improving the integration of remote sensing data into mathematical crop models, thereby enhancing crop growth prediction accuracy. A critical variable for this integration is th…
View article: Climate Change and an Agronomic Journey from the Past to the Present for the Future: A Past Reference Investigation and Current Experiment (PRICE) Study
Climate Change and an Agronomic Journey from the Past to the Present for the Future: A Past Reference Investigation and Current Experiment (PRICE) Study Open
According to numerous chamber and free-air CO2 enrichment (FACE) studies with artificially raised CO2 concentration and/or temperature, it appears that increasing atmospheric CO2 concentrations ([CO2]) stimulates crop yield. However, there…
View article: Improving Reliability in Reconstruction of Landsat EVI Seasonal Trajectory over Cloud-Prone, Fragmented, and Mosaic Agricultural Landscapes
Improving Reliability in Reconstruction of Landsat EVI Seasonal Trajectory over Cloud-Prone, Fragmented, and Mosaic Agricultural Landscapes Open
Although the Landsat 30 m Enhanced Vegetation Index (EVI) products are important input variables in land surface models, recurring Landsat 5/7 EVI time series over cloud-prone, fragmented, and mosaic agricultural landscapes is still a grea…
View article: Construction of a new LED chamber to measure net ecosystem exchange in low vegetation and validation study in grain crops
Construction of a new LED chamber to measure net ecosystem exchange in low vegetation and validation study in grain crops Open
View article: Development of a Radiometric Calibration Method for Multispectral Images of Croplands Obtained with a Remote-Controlled Aerial System
Development of a Radiometric Calibration Method for Multispectral Images of Croplands Obtained with a Remote-Controlled Aerial System Open
A remote sensing (RS) platform consisting of a remote-controlled aerial vehicle (RAV) can be used to monitor crop, environmental conditions, and productivity in agricultural areas. However, the current methods for the calibration of RAV-ac…
View article: Application cases of remote sensing-integrated crop model to simulate and predict crop yield with satellite images
Application cases of remote sensing-integrated crop model to simulate and predict crop yield with satellite images Open
The remote sensing-integrated crop model (RSCM) was designed to simulate crop growth processes and yield using remote sensing data. The RSCM is based on the radiation use efficiency (RUE) model and employs a within-season calibration proce…
View article: Assimilation of Deep Learning and Machine Learning Schemes into a Remote Sensing-Incorporated Crop Model to Simulate Barley and Wheat Productivities
Assimilation of Deep Learning and Machine Learning Schemes into a Remote Sensing-Incorporated Crop Model to Simulate Barley and Wheat Productivities Open
Deep learning (DL) and machine learning (ML) procedures are prevailing data-driven schemes capable of advancing crop-modelling practices that assimilate these techniques into a mathematical crop model. A DL or ML modelling scheme can effec…
View article: Remote Sensing-Based Evaluation of Heat Stress Damage on Paddy Rice Using NDVI and PRI Measured at Leaf and Canopy Scales
Remote Sensing-Based Evaluation of Heat Stress Damage on Paddy Rice Using NDVI and PRI Measured at Leaf and Canopy Scales Open
Extremely high air temperature at the heading stage of paddy rice causes a yield reduction due to the increasing spikelet sterility. Quantifying the damage to crops caused by high temperatures can lead to more accurate estimates of crop yi…
View article: Effects of Tillage System, Sowing Date, and Weather Course on Yield of Double-Crop Soybeans Cultivated in Drained Paddy Fields
Effects of Tillage System, Sowing Date, and Weather Course on Yield of Double-Crop Soybeans Cultivated in Drained Paddy Fields Open
In temperate monsoon areas, major constraints of soybean production in drained paddy fields are excess soil water during monsoon seasons. To further understand how agronomic practices and weather course affect the yield of soybeans, we con…
View article: Incorporation of machine learning and deep neural network approaches into a remote sensing-integrated crop model for the simulation of rice growth
Incorporation of machine learning and deep neural network approaches into a remote sensing-integrated crop model for the simulation of rice growth Open
View article: Simulation of Spatiotemporal Variations in Cotton Lint Yield in the Texas High Plains
Simulation of Spatiotemporal Variations in Cotton Lint Yield in the Texas High Plains Open
This study aimed to simulate the spatiotemporal variation in cotton (Gossypium hirsutum L.) growth and lint yield using a remote sensing-integrated crop model (RSCM) for cotton. The developed modeling scheme incorporated proximal sensing d…
View article: Simulation of Staple Crop Yields for Determination of Regional Impacts of Climate Change: A Case Study in Chonnam Province, Republic of Korea
Simulation of Staple Crop Yields for Determination of Regional Impacts of Climate Change: A Case Study in Chonnam Province, Republic of Korea Open
This study sought to simulate regional variation in staple crop yields in Chonnam Province, Republic of Korea (ROK), in future environments under climate change based on the calibration of crop models in the Decision Support System for Agr…
View article: Simulation of Crop Yields Grown under Agro-Photovoltaic Panels: A Case Study in Chonnam Province, South Korea
Simulation of Crop Yields Grown under Agro-Photovoltaic Panels: A Case Study in Chonnam Province, South Korea Open
Agro-photovoltaic systems are of interest to the agricultural industry because they can produce both electricity and crops in the same farm field. In this study, we aimed to simulate staple crop yields under agro-photovoltaic panels (AVP) …
View article: Contribution of Biophysical Factors to Regional Variations of Evapotranspiration and Seasonal Cooling Effects in Paddy Rice in South Korea
Contribution of Biophysical Factors to Regional Variations of Evapotranspiration and Seasonal Cooling Effects in Paddy Rice in South Korea Open
Previous studies have observed seasonal cooling effects in paddy rice as compared to temperate forest through enhanced evapotranspiration (ET) in Northeast Asia, while rare studies have revealed biophysical factors responsible for spatial …
View article: Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea
Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea Open
Prediction of rice yields at pixel scale rather than county scale can benefit crop management and scientific understanding because it is useful for monitoring how crop yields respond to various agricultural systems and environmental factor…
View article: The Spatial Maps of Paddy Rice Yield over Northeast Asia Using COMS Geostationary Satellite and Reanalysis Meteorological Data
The Spatial Maps of Paddy Rice Yield over Northeast Asia Using COMS Geostationary Satellite and Reanalysis Meteorological Data Open
This study estimated rice yield maps for Northeast Asia by using the Communication, Ocean and Meteorological satellite (COMS), Terra satellite, and Regional Data Assimilation and Prediction System (RDAPS) of the numerical model. The rice y…
View article: The spatial data of paddy rice classification over Northeast Asia using COMS geostationary satellite
The spatial data of paddy rice classification over Northeast Asia using COMS geostationary satellite Open
The Korea Aerospace Research Institute (KARI) estimated paddy rice classification maps over Northeast Asia using the Cheonian geostationary orbiting satellite (COMS: Communication, Ocean and Meteorological Satellite) data. In the case of c…
View article: Simulation of Wheat Productivity Using a Model Integrated With Proximal and Remotely Controlled Aerial Sensing Information
Simulation of Wheat Productivity Using a Model Integrated With Proximal and Remotely Controlled Aerial Sensing Information Open
A crop model incorporating proximal sensing images from a remote-controlled aerial system (RAS) can serve as an enhanced alternative for monitoring field-based geospatial crop productivity. This study aimed to investigate wheat productivit…
View article: Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite
Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite Open
Acquiring accurate and timely information on the spatial distribution of paddy rice fields and the corresponding yield is an important first step in meeting the regional and global food security needs. In this study, using dense vegetation…
View article: Two-Dimensional Simulation of Barley Growth and Yield Using a Model Integrated with Remote-Controlled Aerial Imagery
Two-Dimensional Simulation of Barley Growth and Yield Using a Model Integrated with Remote-Controlled Aerial Imagery Open
It is important to be able to predict the yield and monitor the growth conditions of crops in the field to increase productivity. One way to assess field-based geospatial crop productivity is by integrating a crop model with a remote-contr…