Fei Yuan, Ph.D. - Publications

Affiliations: 
2004 University of Minnesota, Twin Cities, Minneapolis, MN 
Area:
Forestry and Wildlife Agriculture, Environmental Sciences, Physical Geography, Remote Sensing

24 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Blackman R, Yuan F. Detecting Long-Term Urban Forest Cover Change and Impacts of Natural Disasters Using High-Resolution Aerial Images and LiDAR Data Remote Sensing. 12: 1820. DOI: 10.3390/Rs12111820  0.308
2020 Dong R, Miao Y, Wang X, Chen Z, Yuan F, Zhang W, Li H. Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages Remote Sensing. 12: 1139. DOI: 10.3390/Rs12071139  0.313
2019 Huang S, Miao Y, Yuan F, Cao Q, Ye H, Lenz-Wiedemann VI, Bareth G. In-Season Diagnosis of Rice Nitrogen Status Using Proximal Fluorescence Canopy Sensor at Different Growth Stages Remote Sensing. 11: 1847. DOI: 10.3390/Rs11161847  0.3
2019 Li S, Yuan F, Ata-UI-Karim ST, Zheng H, Cheng T, Liu X, Tian Y, Zhu Y, Cao W, Cao Q. Combining Color Indices and Textures of UAV-Based Digital Imagery for Rice LAI Estimation Remote Sensing. 11: 1763. DOI: 10.3390/Rs11151763  0.346
2018 Mullen K, Yuan F, Mitchell M. The Mountain Pine Beetle Epidemic in the Black Hills, South Dakota: The Consequences of Long Term Fire Policy, Climate Change and the Use of Remote Sensing to Enhance Mitigation Journal of Geography and Geology. 10: 69. DOI: 10.5539/Jgg.V10N1P69  0.329
2018 Cao Q, Miao Y, Shen J, Yuan F, Cheng S, Cui Z. Evaluating Two Crop Circle Active Canopy Sensors for In-Season Diagnosis of Winter Wheat Nitrogen Status Agronomy. 8: 201. DOI: 10.3390/Agronomy8100201  0.302
2017 Lu J, Miao Y, Shi W, Li J, Yuan F. Evaluating different approaches to non-destructive nitrogen status diagnosis of rice using portable RapidSCAN active canopy sensor. Scientific Reports. 7: 14073. PMID 29074943 DOI: 10.1038/S41598-017-14597-1  0.316
2017 Huang S, Miao Y, Yuan F, Gnyp M, Yao Y, Cao Q, Wang H, Lenz-Wiedemann V, Bareth G. Potential of RapidEye and WorldView-2 Satellite Data for Improving Rice Nitrogen Status Monitoring at Different Growth Stages Remote Sensing. 9: 227. DOI: 10.3390/Rs9030227  0.332
2016 Nagel P, Yuan F. High-resolution Land Cover and Impervious Surface Classifications in the Twin Cities Metropolitan Area with NAIP Imagery Photogrammetric Engineering and Remote Sensing. 82: 63-71. DOI: 10.14358/Pers.83.1.63  0.346
2015 Huang S, Miao Y, Zhao G, Yuan F, Ma X, Tan C, Yu W, Gnyp ML, Lenz-Wiedemann VIS, Rascher U, Bareth G. Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China Remote Sensing. 7: 10646-10667. DOI: 10.3390/Rs70810646  0.355
2015 Zhao Q, Lenz-Wiedemann VIS, Yuan F, Jiang R, Miao Y, Zhang F, Bareth G. Investigating Within-Field Variability of Rice from High Resolution Satellite Imagery in Qixing Farm County, Northeast China Isprs International Journal of Geo-Information. 4: 236-261. DOI: 10.3390/Ijgi4010236  0.368
2015 Cao Q, Miao Y, Shen J, Yu W, Yuan F, Cheng S, Huang S, Wang H, Yang W, Liu F. Improving in-season estimation of rice yield potential and responsiveness to topdressing nitrogen application with Crop Circle active crop canopy sensor Precision Agriculture. DOI: 10.1007/S11119-015-9412-Y  0.346
2014 Nagel P, Cook BJ, Yuan F. High Spatial-Resolution Land Cover Classification and Wetland Mapping over Large Areas Using Integrated Geospatial Technologies International Journal of Remote Sensing Applications. 4: 71. DOI: 10.14355/Ijrsa.2014.0402.01  0.331
2014 Yuan F, Wang C, Mitchell M. Spatial patterns of land surface phenology relative to monthly climate variations: US Great Plains Giscience & Remote Sensing. 51: 30-50. DOI: 10.1080/15481603.2014.883210  0.327
2014 Li F, Miao Y, Feng G, Yuan F, Yue S, Gao X, Liu Y, Liu B, Ustin SL, Chen X. Improving estimation of summer maize nitrogen status with red edge-based spectral vegetation indices Field Crops Research. 157: 111-123. DOI: 10.1016/J.Fcr.2013.12.018  0.339
2014 Gnyp ML, Miao Y, Yuan F, Ustin SL, Yu K, Yao Y, Huang S, Bareth G. Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages Field Crops Research. 155: 42-55. DOI: 10.1016/J.Fcr.2013.09.023  0.303
2012 Paudel S, Yuan F. Assessing landscape changes and dynamics using patch analysis and GIS modeling International Journal of Applied Earth Observation and Geoinformation. 16: 66-76. DOI: 10.1016/J.Jag.2011.12.003  0.335
2010 Mitchell M, Yuan F. Assessing forest fire and vegetation recovery in the black hills, South Dakota Giscience and Remote Sensing. 47: 276-299. DOI: 10.2747/1548-1603.47.2.276  0.332
2009 Morton TA, Yuan F. Analysis of population dynamics using satellite remote sensing and US census data Geocarto International. 24: 143-163. DOI: 10.1080/10106040802460715  0.303
2008 Yuan F, Wu C, Bauer ME. Comparison of Spectral Analysis Techniques for Impervious Surface Estimation Using Landsat Imagery Photogrammetric Engineering and Remote Sensing. 74: 1045-1055. DOI: 10.14358/Pers.74.8.1045  0.346
2008 Yuan F. Land-cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling International Journal of Remote Sensing. 29: 1169-1184. DOI: 10.1080/01431160701294703  0.358
2007 Yuan F, Bauer ME. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery Remote Sensing of Environment. 106: 375-386. DOI: 10.1016/J.Rse.2006.09.003  0.312
2005 Yuan F, Bauer ME, Heinert NJ, Holden GR. Multi‐level Land Cover Mapping of the Twin Cities (Minnesota) Metropolitan Area with Multi‐seasonal Landsat TM/ETM+ Data Geocarto International. 20: 5-13. DOI: 10.1080/10106040508542340  0.351
2005 Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME. Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing Remote Sensing of Environment. 98: 317-328. DOI: 10.1016/J.Rse.2005.08.006  0.358
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