| 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 |
0.31 |
|
| 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 |
0.316 |
|
| 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 |
0.303 |
|
| 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 |
0.348 |
|
| 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 |
0.332 |
|
| 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 |
0.304 |
|
| 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 |
0.319 |
|
| 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 |
0.335 |
|
| 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 |
0.35 |
|
| 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 |
0.359 |
|
| 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 |
0.371 |
|
| 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 |
0.349 |
|
| 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 |
0.334 |
|
| 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 |
0.33 |
|
| 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 |
0.342 |
|
| 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 |
0.305 |
|
| 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 |
0.338 |
|
| 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 |
0.335 |
|
| 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 |
0.305 |
|
| 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 |
0.35 |
|
| 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 |
0.362 |
|
| 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 |
0.315 |
|
| 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 |
0.355 |
|
| 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 |
0.362 |
|
| Show low-probability matches. |