FROM-GC: 30 m global cropland extent derived through multisource data integration. - Le Yu 001; Jie Wang 036; Nicholas Clinton; Qinchuan Xin; Liheng Zhong; Yanlei Chen; Peng Gong 002 (Int. J. Digit. Earth, 2013)

A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US. - Qinchuan Xin; Peng Gong 002; Chaoqing Yu; Le Yu 001; Mark Broich; Andrew E. Suyker; Ranga B. Myneni (Remote. Sens., 2013)

Dynamic assessment of the impact of drought on agricultural yield and scale-dependent return periods over large geographic regions. - Chaoqing Yu; Changsheng Li; Qinchuan Xin; Han Chen; Jie Zhang; Feng Zhang; Xuecao Li; Nick Clinton; Xiao Huang; Yali Yue; Peng Gong 002 (Environ. Model. Softw., 2014)

Mapping Crop Cycles in China Using MODIS-EVI Time Series. - Le Li; Mark A. Friedl; Qinchuan Xin; Josh M. Gray; Yaozhong Pan; Steve Frolking (Remote. Sens., 2014)

Combining Crop Proportion Phenology Index models with machine learning algorithms for estimating winter wheat areas. - Le Li; Yaozhong Pan; Qinchuan Xin (IGARSS, 2016)

Effects of the partitioning of diffuse and direct solar radiation on satellite-based modeling of crop gross primary production. - Qinchuan Xin; Peng Gong 002; Andrew E. Suyker; Yali Si (Int. J. Appl. Earth Obs. Geoinformation, 2016)

Propagating Updates of Residential Areas in Multi-Representation Databases Using Constrained Delaunay Triangulations. - Xinchang Zhang 002; Taisheng Guo; Jianfeng Huang; Qinchuan Xin (ISPRS Int. J. Geo Inf., 2016)

Quantifying Multi-Decadal Change of Planted Forest Cover Using Airborne LiDAR and Landsat Imagery. - Xiaoyi Wang; Huabing Huang; Peng Gong 002; Gregory S. Biging; Qinchuan Xin; Yanlei Chen; Jun Yang 016; Caixia Liu 002 (Remote. Sens., 2016)

High Resolution Mapping of Cropping Cycles by Fusion of Landsat and MODIS Data. - Le Li; Yaolong Zhao; Yingchun Fu; Yaozhong Pan; Le Yu 001; Qinchuan Xin (Remote. Sens., 2017)

Satellite-Based Models Need Improvements on Simulating Annual Gross Primary Productivity: A Comparison of Six Models for Regional Modeling of Deciduous Broadleaf Forests. - Le Li; Yaolong Zhao; Yingchun Fu; Qinchuan Xin (Remote. Sens., 2018)

Extracting Building Boundaries from High Resolution Optical Images and LiDAR Data by Integrating the Convolutional Neural Network and the Active Contour Model. - Ying Sun; Xinchang Zhang 002; Xiaoyang Zhao; Qinchuan Xin (Remote. Sens., 2018)

The Application of Discrete Wavelet Transform with Improved Partial Least-Squares Method for the Estimation of Soil Properties with Visible and Near-Infrared Spectral Data. - Guoqiang Wang; Wei Wang; Qingqing Fang; Hong Jiang; Qinchuan Xin; Baolin Xue (Remote. Sens., 2018)

Characterizing Tree Species of a Tropical Wetland in Southern China at the Individual Tree Level Based on Convolutional Neural Network. - Ying Sun; Qinchuan Xin; Jianfeng Huang; Bo Huang 001; Hongsheng Zhang 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019)

Automated Surface Water Extraction Combining Sentinel-2 Imagery and OpenStreetMap Using Presence and Background Learning (PBL) Algorithm. - Zhiqiang Zhang; Xinchang Zhang 002; Xin Jiang; Qinchuan Xin; Zurui Ao; Qiting Zuo; Liyan Chen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019)

Topology-Preserving and Geometric Feature-Correction Watermarking of Vector Maps. - Xu Xi; Xinchang Zhang 002; Ying Sun; Xin Jiang; Qinchuan Xin (IEEE Access, 2020)

Evaluations and comparisons of rule-based and machine-learning-based methods to retrieve satellite-based vegetation phenology using MODIS and USA National Phenology Network data. - Qinchuan Xin; Jing Li; Ziming Li; Yaoming Li; Xuewen Zhou (Int. J. Appl. Earth Obs. Geoinformation, 2020)

A Deep Learning Method for Detecting Leaf Phenology from Phenocam Imagery. - Mengying Cao; Qinchuan Xin (IGARSS, 2021)

Corner-Guided Building Polygon Construction from Aerial Images using Deep Multitask Learning. - Ziming Li; Qinchuan Xin (IGARSS, 2021)

Development of a global annual land surface phenology dataset for 1982-2018 from the AVHRR data by implementing multiple phenology retrieving methods. - Wei Wu; Ying Sun; Kun Xiao; Qinchuan Xin (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Constructing 10-m NDVI Time Series From Landsat 8 and Sentinel 2 Images Using Convolutional Neural Networks. - Zurui Ao; Ying Sun; Qinchuan Xin (IEEE Geosci. Remote. Sens. Lett., 2021)

Identifying Leaf Phenology of Deciduous Broadleaf Forests from PhenoCam Images Using a Convolutional Neural Network Regression Method. - Mengying Cao; Ying Sun; Xin Jiang; Ziming Li; Qinchuan Xin (Remote. Sens., 2021)

A Deep Learning-Based Framework for Automated Extraction of Building Footprint Polygons from Very High-Resolution Aerial Imagery. - Ziming Li; Qinchuan Xin; Ying Sun; Mengying Cao (Remote. Sens., 2021)

Attention-Guided Label Refinement Network for Semantic Segmentation of Very High Resolution Aerial Orthoimages. - Jianfeng Huang; Xinchang Zhang 002; Ying Sun; Qinchuan Xin (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Arbitrary-Shaped Building Boundary-Aware Detection With Pixel Aggregation Network. - Xin Jiang; Xinchang Zhang 002; Qinchuan Xin; Xu Xi; Pengcheng Zhang (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

A Global Annual Vegetation Phenology Dataset Derived from GIMMS LAI 3G Time Series for 1982-2015. - Wei Wu; Qinchuan Xin (IGARSS, 2022)

Counting trees in a subtropical mega city using the instance segmentation method. - Ying Sun; Ziming Li; Huagui He; Liang Guo 010; Xinchang Zhang 002; Qinchuan Xin (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Fine-Grained Building Change Detection From Very High-Spatial-Resolution Remote Sensing Images Based on Deep Multitask Learning. - Ying Sun; Xinchang Zhang 002; Jianfeng Huang; Haiying Wang 010; Qinchuan Xin (IEEE Geosci. Remote. Sens. Lett., 2022)

Gap-Filling and Missing Information Recovery for Time Series of MODIS Data Using Deep Learning-Based Methods. - Yidan Wang; Xuewen Zhou; Zurui Ao; Kun Xiao; Chenxi Yan; Qinchuan Xin (Remote. Sens., 2022)

Ecological Responses to Climate Change and Human Activities in the Arid and Semi-Arid Regions of Xinjiang in China. - Yanqing Zhou; Yaoming Li; Wei Li; Feng Li 062; Qinchuan Xin (Remote. Sens., 2022)

Deep Learning-Based Spatiotemporal Data Fusion Using a Patch-to-Pixel Mapping Strategy and Model Comparisons. - Zurui Ao; Ying Sun; Xiaoyu Pan; Qinchuan Xin (IEEE Trans. Geosci. Remote. Sens., 2022)

A Densely Attentive Refinement Network for Change Detection Based on Very-High-Resolution Bitemporal Remote Sensing Images. - Ziming Li; Chenxi Yan; Ying Sun; Qinchuan Xin (IEEE Trans. Geosci. Remote. Sens., 2022)

A Meteorology-Driven Lstm For Predicting Time Series Of Vegetation Leaf Area Index In Land Surface Model. - Zhenhua Xiong; Qinchuan Xin; Zhicheng Zhang; Hanliang Gui (IGARSS, 2023)

Characterizing Spring Phenological Changes of the Land Surface across the Conterminous United States from 2001 to 2021. - Wei Wu; Qinchuan Xin (Remote. Sens., 2023)

Global Annual Land Surface Phenology (GALSP) product (1982-2018). - Wei Wu; Qinchuan Xin (Zenodo, 2023)

High-resolution mapping of paddy rice fields from unmanned airborne vehicle images using enhanced-TransUnet. - Chenxi Yan; Ziming Li; Zhicheng Zhang; Ying Sun; Yidan Wang; Qinchuan Xin (Comput. Electron. Agric., 2023)

A refined supply-demand framework for ecosystem services boosts assessment on the Sustainable Developmant Goals V1. - Feng Li 062; Qinchuan Xin; Ying Sun; Yujiu Xiong (Zenodo, 2023)

Mapping Irrigated Croplands from Sentinel-2 Images Using Deep Convolutional Neural Networks. - Wei Li; Ying Sun; Yanqing Zhou; Lu Gong; Yaoming Li; Qinchuan Xin (Remote. Sens., 2023)

An Adaptive Multiscale Generative Adversarial Network for the Spatiotemporal Fusion of Landsat and MODIS Data. - Xiaoyu Pan; Muyuan Deng; Zurui Ao; Qinchuan Xin (Remote. Sens., 2023)

A Refined Supply-demand Framework to Quantify variability in Ecosystem Services Related to Surface Water in support of Sustainable Development Goals. - Feng Li 062; Qinchuan Xin; Zheng Fu; Ying Sun; Yujiu Xiong (Zenodo, 2024)

An attention-enhanced spatial-temporal high-resolution network for irrigated area mapping using multitemporal Sentinel-2 images. - Wei Li; Qinchuan Xin; Ying Sun; Yanqing Zhou; Jiangyue Li; Yidan Wang; Yu Sun; Guangyu Wang; Ren Xu; Lu Gong; Yaoming Li (Int. J. Appl. Earth Obs. Geoinformation, 2024)

Better representation of vegetation phenology improves estimations of annual gross primary productivity. - Hanliang Gui; Qinchuan Xin; Xuewen Zhou; Wei Wu; Zhenhua Xiong (Ecol. Informatics, 2024)

High Spatial Resolution Soil Moisture Improves Crop Yield Estimation. - Ruiwen Mai; Qinchuan Xin; Jianxiu Qiu; Qianfeng Wang; Peng Zhu (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

A Refined Supply-demand Framework to Quantify variability in Ecosystem Services Related to Surface Water in support of Sustainable Development Goals. - Feng Li 062; Qinchuan Xin; Zheng Fu; Ying Sun; Yujiu Xiong (Zenodo, 2024)

Developing a Multi-Scale Convolutional Neural Network for Spatiotemporal Fusion to Generate MODIS-like Data Using AVHRR and Landsat Images. - Zhicheng Zhang; Zurui Ao; Wei Wu; Yidan Wang; Qinchuan Xin (Remote. Sens., 2024)

A Refined Supply-demand Framework to Quantify Variability in Ecosystem Services Related to Surface Water in Support of Sustainable Development Goals. - Feng Li 062; Qinchuan Xin; Zheng Fu; Ying Sun; Yujiu Xiong (Zenodo, 2024)

Predicting time series of vegetation leaf area index across North America based on climate variables for land surface modeling using attention-enhanced LSTM. - Zhenhua Xiong; Zhicheng Zhang; Hanliang Gui; Peng Zhu; Ying Sun; Xuewen Zhou; Kun Xiao; Qinchuan Xin (Int. J. Digit. Earth, 2024)

Ultra-High Spatial Resolution Mapping of Urban Forest Canopy Height With Multimodal Remote Sensing Data and Deep Learning Method. - Kun Xiao; Xiaoyang Zhao; Ying Ding; Chen Huang; Jueyu Lin; Yuxuan Mai; Ying Sun; Qinchuan Xin (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

A Meteorology-Driven Transformer Network to Predict Soil Moisture for Agriculture Drought Forecasting. - Zhenhua Xiong; Zhicheng Zhang; Hanliang Gui; Xiaoyou Chen; Shi Hu; Lun Gao; He Yang; Jianxiu Qiu; Qinchuan Xin (IEEE Trans. Geosci. Remote. Sens., 2025)