Zhenong Jin
Zhenong Jin
Verifierad e-postadress på umn.edu
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Smallholder maize area and yield mapping at national scales with Google Earth Engine
Z Jin, G Azzari, C You, S Di Tommaso, S Aston, M Burke, DB Lobell
Remote Sensing of Environment 228, 115-128, 2019
732019
Methane emissions from an alpine wetland on the Tibetan Plateau: Neglected but vital contribution of the nongrowing season
W Song, H Wang, G Wang, L Chen, Z Jin, Q Zhuang, JS He
Journal of Geophysical Research: Biogeosciences 120 (8), 1475-1490, 2015
732015
Water Use Efficiency as a Constraint and Target for Improving the Resilience and Productivity of C3 and C4 Crops
ADB Leakey, JN Ferguson, CP Pignon, A Wu, Z Jin, GL Hammer, ...
Annual review of plant biology 70, 781-808, 2019
572019
The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2
Z Jin, Q Zhuang, J Wang, SV Archontoulis, Z Zobel, VR Kotamarthi
Global change biology 23 (7), 2687-2704, 2017
572017
Phenology shift from 1989 to 2008 on the Tibetan Plateau: an analysis with a process-based soil physical model and remote sensing data
Z Jin, Q Zhuang, JS He, T Luo, Y Shi
Climatic Change 119 (2), 435-449, 2013
572013
Eyes in the Sky, Boots on the Ground: Assessing Satellite-and Ground-Based Approaches to Crop Yield Measurement and Analysis
DB Lobell, G Azzari, M Burke, S Gourlay, Z Jin, T Kilic, S Murray
American Journal of Agricultural Economics, 2019
55*2019
Increasing drought and diminishing benefits of elevated carbon dioxide for soybean yields across the US Midwest
Z Jin, EA Ainsworth, ADB Leakey, DB Lobell
Global change biology 24 (2), e522-e533, 2018
532018
Improving the accuracy of satellite-based high-resolution yield estimation: A test of multiple scalable approaches
Z Jin, G Azzari, DB Lobell
Agricultural and Forest Meteorology 247, 207-220, 2017
512017
Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa
Z Jin, G Azzari, M Burke, S Aston, DB Lobell
Remote Sensing 9 (9), 931, 2017
452017
Crop model-and satellite imagery-based recommendation tool for variable rate N fertilizer application for the US Corn system
Z Jin, R Prasad, J Shriver, Q Zhuang
Precision Agriculture 18 (5), 779-800, 2017
422017
Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches
Z Jin, Q Zhuang, Z Tan, JS Dukes, B Zheng, JM Melillo
Global change biology 22 (9), 3112-3126, 2016
382016
Net exchanges of methane and carbon dioxide on the Qinghai-Tibetan Plateau from 1979 to 2100
Z Jin, Q Zhuang, JS He, X Zhu, W Song
Environmental Research Letters 10 (8), 085007, 2015
332015
Towards a multiscale crop modelling framework for climate change adaptation assessment
B Peng, K Guan, J Tang, EA Ainsworth, S Asseng, CJ Bernacchi, ...
Nature Plants 6 (4), 338-348, 2020
252020
The important but weakening maize yield benefit of grain filling prolongation in the US Midwest
P Zhu, Z Jin, Q Zhuang, P Ciais, C Bernacchi, X Wang, D Makowski, ...
Global change biology 24 (10), 4718-4730, 2018
162018
Soil thermal dynamics of terrestrial ecosystems of the conterminous United States from 1948 to 2008: an analysis with a process-based soil physical model and AmeriFlux data
G Hao, Q Zhuang, J Pan, Z Jin, X Zhu, S Liu
Climatic change 126 (1), 135-150, 2014
132014
How much will precision nitrogen management pay off? An evaluation based on simulating thousands of corn fields over the US Corn-Belt
Z Jin, SV Archontoulis, DB Lobell
Field Crops Research 240, 12-22, 2019
82019
Detecting in-season crop nitrogen stress of corn for field trials using UAV-and CubeSat-based multispectral sensing
Y Cai, K Guan, E Nafziger, G Chowdhary, B Peng, Z Jin, S Wang, S Wang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019
62019
Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification From VHR Imagery
ZY Lv, GF Li, ZN Jin, JA Benediktsson, GM Foody
IEEE Transactions on Geoscience and Remote Sensing, 2020
52020
Uniting remote sensing, crop modelling and economics for agricultural risk management
E Benami, Z Jin, MR Carter, A Ghosh, RJ Hijmans, A Hobbs, B Kenduiywo, ...
Nature Reviews Earth & Environment, 1-20, 2021
32021
The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield
TE Franz, S Pokal, JP Gibson, Y Zhou, H Gholizadeh, FA Tenorio, ...
Field Crops Research 252, 107788, 2020
32020
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Artiklar 1–20