Junxiong Zhou | University of Minnesota Twin Cities

About Me

I am a Ph.D. student at University of Minnesota Twin Cities. I have experience in remote sensing image processing, including image fusion and classification. I am currently working on analyzing the impacts of climate changes on crop yields and Knowledge-guided machine learning for vegetation parameter retrieval.

Education

2021-present: Ph.D. Student, University of Minnesota
2018-2021: M.Sc., Beijing Normal University
2014-2018: B.E., China University of Geosciences

Research Interests

Knowledge-guided machine learning: transfer learning, data assimilation
Climate change adaptation: climate warming, crop yield
Satellite image processing: data fusion, land cover/use mapping

News

[Oct. 2024] Our paper about climate impacts on crop rotation is published in Global Change Biology.
[Aug. 2024] Our paper about sub-national scale olive mapping is published in ISPRS Journal of Photogrammetry and Remote Sensing.
[Feb. 2024] Our paper about climate warming impacts on cattle meat yields is published in Communications Earth & Environment.

First Author Publications

GCB

Changes in the yield effect of the preceding crop in the US Corn Belt under a warming climate

Zhou J, Zhu P, Kluger DM, Lobell DB, Jin Z*

Global Change Biology, 2024.

ISPRS

A deep transfer learning framework for mapping high spatiotemporal resolution LAI

Zhou J, Yang Q, Liu L, Kang Y, Jia X, Chen M, Ghosh R, Xu S, Jiang C, Guan K, Kumar V, Jin Z*

ISPRS Journal of Photogrammetry and Remote Sensing, 2023.

RSE

Sensitivity of six typical spatiotemporal fusion methods to different influential factors A comparative study for a normalized difference vegetation index time series reconstruction

Zhou J, Chen J, Chen X*, Zhu X, Qiu Y, Song H, Rao Y, Zhang C, Cao X, Cui X

Remote Sensing of Environment, 2021.

SRS

A geometric misregistration resistant data fusion approach for adding red-edge (RE) and short-wave infrared (SWIR) bands to high spatial resolution imagery

Zhou J, Qiu Y, Chen J*, Chen X

Science of Remote Sensing, 2021.

Selected Coauthor Publications

[12] Lin C, Zhou J, Yin L, Bouabid R, Mulla D, Benami E, Jin Z*. (2024). Sub-national scale mapping of individual olive trees integrating Earth observation and deep learning. ISPRS Journal of Photogrammetry and Remote Sensing, 217, 18-31.
[11] Hu Y, Li D, Deng J*, Yue Y, Zhou J, ... & Li Y. (2024). Dune Development Dominates Flow Resistance Increase in a Large Dammed River. Water Resources Research, 60(4), e2023WR036660.
[10] Yang Q, Liu L, Zhou J, Rogers M, & Jin Z*. (2024). Predicting the growth trajectory and yield of greenhouse strawberries based on knowledge-guided computer vision. Computers and Electronics in Agriculture, 220, 108911.
[9] Liu W*, Zhou J, Ma Y, Chen S, & Luo Y. (2024). Unequal impact of climate warming on meat yields of global cattle farming. Communications Earth & Environment, 5(1), 65.
[8] Zhou Z, Zhang C*, Zou X, Zhang X, Zuo X, Zhang Z, Zhou J, & Cao Z. (2024). Estimating lateral cover of vegetation and gravel using NDVI and albedo. CATENA, 239, 107899.
[7] Yang Q, Liu L, Zhou J, Ghosh R, Peng B, Guan K, ... & Jin Z*. (2023). A flexible and efficient knowledge-guided machine learning data assimilation (KGML-DA) framework for agroecosystem prediction in the US Midwest. Remote Sensing of Environment, 299, 113880.
[6] Yin L, Ghosh R, Lin C, Hale D, Weigl C, Obarowski J, Zhou J, ... & Jin Z*. (2023). Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin. Remote Sensing of Environment, 295, 113695.
[5] Bai Y, Li S*, Zhou J, Liu M, & Guo Q. (2023). Revisiting vegetation activity of Mongolian Plateau using multiple remote sensing datasets. Agricultural and Forest Meteorology, 341, 109649.
[4] Hu Y, Li D, Deng J*, Yue Y, Zhou J, Chai Y, & Li Y. (2022). Mechanisms Controlling Water‐Level Variations in the Middle Yangtze River Following the Operation of the Three Gorges Dam. Water Resources Research, 58(10), e2022WR032338.
[3] Zhu X, Zhan W, Zhou J, Chen X, Liang Z, Xu S, & Chen J*. (2022). A novel framework to assess all-round performances of spatiotemporal fusion models. Remote Sensing of Environment, 274, 113002.
[2] Liu S, Zhou J, Qiu Y, Chen J*, Zhu X, & Chen H. (2022). The FIRST model: Spatiotemporal fusion incorporating spectral information autocorrelation. Remote sensing of Environment, 279, 113111.
[1] Qiu Y, Zhou J, Chen J*, & Chen X. (2021). Spatiotemporal fusion method to simultaneously generate full-length normalized difference vegetation index time series (SSFIT). International Journal of Applied Earth Observation and Geoinformation, 100, 102333.

Services

Journal Reviewers

Skills

Remote pilot Certificate