Chunyuan Diao

1.5k total citations
41 papers, 1.2k citations indexed

About

Chunyuan Diao is a scholar working on Ecology, Global and Planetary Change and Ecological Modeling. According to data from OpenAlex, Chunyuan Diao has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Ecology, 16 papers in Global and Planetary Change and 11 papers in Ecological Modeling. Recurrent topics in Chunyuan Diao's work include Remote Sensing in Agriculture (31 papers), Remote-Sensing Image Classification (11 papers) and Species Distribution and Climate Change (11 papers). Chunyuan Diao is often cited by papers focused on Remote Sensing in Agriculture (31 papers), Remote-Sensing Image Classification (11 papers) and Species Distribution and Climate Change (11 papers). Chunyuan Diao collaborates with scholars based in United States, China and Sweden. Chunyuan Diao's co-authors include Le Wang, Zhenfeng Shao, Pan Yin, Jiajun Cai, Dameng Yin, Jian Wu, Lei Zhou, Qimin Cheng, Jie Zhang and Ming Liu and has published in prestigious journals such as The Science of The Total Environment, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Chunyuan Diao

38 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chunyuan Diao United States 17 618 505 308 249 207 41 1.2k
Pieter Kempeneers Belgium 21 743 1.2× 420 0.8× 324 1.1× 392 1.6× 250 1.2× 60 1.3k
Emma Izquierdo‐Verdiguier Spain 16 485 0.8× 295 0.6× 254 0.8× 268 1.1× 207 1.0× 60 982
Raphaël d’Andrimont Italy 15 683 1.1× 414 0.8× 224 0.7× 340 1.4× 222 1.1× 38 1.2k
Cláudio Almeida Brazil 15 507 0.8× 566 1.1× 198 0.6× 258 1.0× 94 0.5× 41 1.2k
Andreas Rabe Germany 10 759 1.2× 612 1.2× 432 1.4× 343 1.4× 336 1.6× 16 1.3k
Sherrie Wang United States 13 538 0.9× 317 0.6× 195 0.6× 259 1.0× 218 1.1× 31 1.1k
Desiré Paelinckx Belgium 10 678 1.1× 392 0.8× 242 0.8× 295 1.2× 175 0.8× 37 1.2k
Luís Marcelo Tavares de Carvalho Brazil 16 592 1.0× 453 0.9× 394 1.3× 258 1.0× 286 1.4× 65 1.2k
Guillermo Castilla Canada 18 714 1.2× 463 0.9× 223 0.7× 607 2.4× 150 0.7× 37 1.3k
Yuchu Qin China 19 526 0.9× 336 0.7× 108 0.4× 573 2.3× 151 0.7× 31 1.2k

Countries citing papers authored by Chunyuan Diao

Since Specialization
Citations

This map shows the geographic impact of Chunyuan Diao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chunyuan Diao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chunyuan Diao more than expected).

Fields of papers citing papers by Chunyuan Diao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chunyuan Diao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chunyuan Diao. The network helps show where Chunyuan Diao may publish in the future.

Co-authorship network of co-authors of Chunyuan Diao

This figure shows the co-authorship network connecting the top 25 collaborators of Chunyuan Diao. A scholar is included among the top collaborators of Chunyuan Diao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chunyuan Diao. Chunyuan Diao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Wang, Le, Chunyuan Diao, Mingming Jia, et al.. (2024). National scale sub-meter mangrove mapping using an augmented border training sample method. ISPRS Journal of Photogrammetry and Remote Sensing. 220. 156–171. 3 indexed citations
4.
Diao, Chunyuan, et al.. (2024). Multistream STGAN: A Spatiotemporal Image Fusion Model With Improved Temporal Transferability. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 1562–1576. 4 indexed citations
5.
Liu, Yin, et al.. (2024). CropSight: Towards a large-scale operational framework for object-based crop type ground truth retrieval using street view and PlanetScope satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing. 216. 66–89. 8 indexed citations
6.
Lv, Ziqi, Yang Song, Chunyuan Diao, et al.. (2024). Spatial-spectral joint preprocessing for hyperspectral image analysis using 3D-ResNet: Application to coal ash content estimation. Measurement. 246. 116535–116535. 3 indexed citations
7.
Diao, Chunyuan, et al.. (2024). EMET: An emergence-based thermal phenological framework for near real-time crop type mapping. ISPRS Journal of Photogrammetry and Remote Sensing. 215. 271–291. 8 indexed citations
8.
Diao, Chunyuan, et al.. (2023). Monitoring spring leaf phenology of individual trees in a temperate forest fragment with multi-scale satellite time series. Remote Sensing of Environment. 297. 113790–113790. 11 indexed citations
9.
Liu, Yin, et al.. (2023). CropSow: An integrative remotely sensed crop modeling framework for field-level crop planting date estimation. ISPRS Journal of Photogrammetry and Remote Sensing. 202. 334–355. 6 indexed citations
10.
Diao, Chunyuan, et al.. (2023). Towards Scalable Within-Season Crop Mapping With Phenology Normalization and Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 1390–1402. 16 indexed citations
11.
Diao, Chunyuan, et al.. (2023). A Phenology-guided Bayesian-CNN (PB-CNN) framework for soybean yield estimation and uncertainty analysis. ISPRS Journal of Photogrammetry and Remote Sensing. 205. 50–73. 14 indexed citations
12.
Diao, Chunyuan, et al.. (2022). Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology. Remote Sensing. 14(9). 1957–1957. 21 indexed citations
13.
Gao, Feng, Martha C. Anderson, David M. Johnson, et al.. (2021). Towards Routine Mapping of Crop Emergence within the Season Using the Harmonized Landsat and Sentinel-2 Dataset. Remote Sensing. 13(24). 5074–5074. 22 indexed citations
14.
Lv, Xianwei, et al.. (2021). Improved object-based convolutional neural network (IOCNN) to classify very high-resolution remote sensing images. International Journal of Remote Sensing. 42(21). 8318–8344. 13 indexed citations
15.
Diao, Chunyuan, et al.. (2021). A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion. Remote Sensing. 13(24). 5005–5005. 26 indexed citations
16.
Diao, Chunyuan. (2019). Innovative pheno-network model in estimating crop phenological stages with satellite time series. ISPRS Journal of Photogrammetry and Remote Sensing. 153. 96–109. 16 indexed citations
17.
Zhou, Lei, Jian Wu, Xinyu Mo, et al.. (2017). Quantitative and detailed spatiotemporal patterns of drought in China during 2001–2013. The Science of The Total Environment. 589. 136–145. 65 indexed citations
18.
Wang, Le, Shi Chen, Chunyuan Diao, Wenjie Ji, & Dameng Yin. (2016). A survey of methods incorporating spatial information in image classification and spectral unmixing. International Journal of Remote Sensing. 37(16). 3870–3910. 58 indexed citations
19.
Wu, Jian, Lei Zhou, Ming Liu, et al.. (2012). Establishing and assessing the Integrated Surface Drought Index (ISDI) for agricultural drought monitoring in mid-eastern China. International Journal of Applied Earth Observation and Geoinformation. 23. 397–410. 114 indexed citations
20.
Diao, Chunyuan. (1989). A PRELIMINARY STUDY ON THE URBAN GEOMORPHOLOGY IN SICHUAN PROVINCE. Journal of Southwest China Normal University. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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