Xiuliang Jin
Orcid: 0000-0003-2720-6247
According to our database1,
Xiuliang Jin
authored at least 45 papers
between 2014 and 2024.
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Bibliography
2024
Satellite-Based Hydrothermal Variables Are Superior to Traditional Climate Data for Predicting Maize Yield.
IEEE Geosci. Remote. Sens. Lett., 2024
Enhancing precision of root-zone soil moisture content prediction in a kiwifruit orchard using UAV multi-spectral image features and ensemble learning.
Comput. Electron. Agric., 2024
Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data.
Comput. Electron. Agric., 2024
Evaluating drought stress response of poplar seedlings using a proximal sensing platform via multi-parameter phenotyping and two-stage machine learning.
Comput. Electron. Agric., 2024
Estimation of potato yield using a semi-mechanistic model developed by proximal remote sensing and environmental variables.
Comput. Electron. Agric., 2024
A novel framework to assess apple leaf nitrogen content: Fusion of hyperspectral reflectance and phenology information through deep learning.
Comput. Electron. Agric., 2024
Accurately estimate soybean growth stages from UAV imagery by accounting for spatial heterogeneity and climate factors across multiple environments.
Comput. Electron. Agric., 2024
Comprehensive analysis of hyperspectral features for monitoring canopy maize leaf spot disease.
Comput. Electron. Agric., 2024
A model suitable for estimating above-ground biomass of potatoes at different regional levels.
Comput. Electron. Agric., 2024
2023
Comput. Electron. Agric., December, 2023
Comput. Electron. Agric., November, 2023
Estimating potato above-ground biomass by using integrated unmanned aerial system-based optical, structural, and textural canopy measurements.
Comput. Electron. Agric., October, 2023
Estimation of Soil Moisture Using Multi-Source Remote Sensing and Machine Learning Algorithms in Farming Land of Northern China.
Remote. Sens., September, 2023
Using an optimized texture index to monitor the nitrogen content of potato plants over multiple growth stages.
Comput. Electron. Agric., September, 2023
Quantifying effect of maize tassels on LAI estimation based on multispectral imagery and machine learning methods.
Comput. Electron. Agric., August, 2023
Comparison of Different Dimensional Spectral Indices for Estimating Nitrogen Content of Potato Plants over Multiple Growth Periods.
Remote. Sens., February, 2023
UAV multispectral images for accurate estimation of the maize LAI considering the effect of soil background.
Int. J. Appl. Earth Obs. Geoinformation, 2023
2022
Predicting Wheat Leaf Nitrogen Content by Combining Deep Multitask Learning and a Mechanistic Model Using UAV Hyperspectral Images.
Remote. Sens., December, 2022
Estimation of Aboveground Biomass of Potatoes Based on Characteristic Variables Extracted from UAV Hyperspectral Imagery.
Remote. Sens., 2022
Estimation of Potato Above-Ground Biomass Using UAV-Based Hyperspectral images and Machine-Learning Regression.
Remote. Sens., 2022
Estimation of Potato Above-Ground Biomass Based on Vegetation Indices and Green-Edge Parameters Obtained from UAVs.
Remote. Sens., 2022
Maize tassel area dynamic monitoring based on near-ground and UAV RGB images by U-Net model.
Comput. Electron. Agric., 2022
2021
Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region.
Remote. Sens., 2021
Detection and Analysis of Degree of Maize Lodging Using UAV-RGB Image Multi-Feature Factors and Various Classification Methods.
ISPRS Int. J. Geo Inf., 2021
2020
Prediction of Wheat Grain Protein by Coupling Multisource Remote Sensing Imagery and ECMWF Data.
Remote. Sens., 2020
Improving Soil Thickness Estimations Based on Multiple Environmental Variables with Stacking Ensemble Methods.
Remote. Sens., 2020
Editorial for the Special Issue "Estimation of Crop Phenotyping Traits using Unmanned Ground Vehicle and Unmanned Aerial Vehicle Imagery".
Remote. Sens., 2020
2019
A Novel Approach for the Detection of Standing Tree Stems from Plot-Level Terrestrial Laser Scanning Data.
Remote. Sens., 2019
Field-Scale Rice Yield Estimation Using Sentinel-1A Synthetic Aperture Radar (SAR) Data in Coastal Saline Region of Jiangsu Province, China.
Remote. Sens., 2019
Comput. Electron. Agric., 2019
2018
A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera.
Remote. Sens., 2018
Remote Sensing of Leaf and Canopy Nitrogen Status in Winter Wheat (<i>Triticum aestivum</i> L.) Based on N-PROSAIL Model.
Remote. Sens., 2018
Time-Series Multispectral Indices from Unmanned Aerial Vehicle Imagery Reveal Senescence Rate in Bread Wheat.
Remote. Sens., 2018
Estimating genetic parameters of DSSAT-CERES model with the GLUE method for winter wheat (<i>Triticum aestivum</i> L.) production.
Comput. Electron. Agric., 2018
2017
Evaluation of Seed Emergence Uniformity of Mechanically Sown Wheat with UAV RGB Imagery.
Remote. Sens., 2017
Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information.
Int. J. Appl. Earth Obs. Geoinformation, 2017
Estimation of leaf nitrogen content of maize based on Akaike's information criterion in Beijing.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017
2016
Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data.
Remote. Sens., 2016
Quantification winter wheat LAI with HJ-1CCD image features over multiple growing seasons.
Int. J. Appl. Earth Obs. Geoinformation, 2016
2015
Assimilation of Two Variables Derived from Hyperspectral Data into the DSSAT-CERES Model for Grain Yield and Quality Estimation.
Remote. Sens., 2015
Combined Multi-Temporal Optical and Radar Parameters for Estimating LAI and Biomass in Winter Wheat Using HJ and RADARSAR-2 Data.
Remote. Sens., 2015
Estimation of Maize Residue Cover Using Landsat-8 OLI Image Spectral Information and Textural Features.
Remote. Sens., 2015
Proceedings of the Computer and Computing Technologies in Agriculture IX, 2015
2014
Newly Combined Spectral Indices to Improve Estimation of Total Leaf Chlorophyll Content in Cotton.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014
Exploring the Best Hyperspectral Features for LAI Estimation Using Partial Least Squares Regression.
Remote. Sens., 2014