| Year |
Citation |
Score |
| 2023 |
Stanimirova R, Tarrio K, Turlej K, McAvoy K, Stonebrook S, Hu KT, Arévalo P, Bullock EL, Zhang Y, Woodcock CE, Olofsson P, Zhu Z, Barber CP, Souza CM, Chen S, ... ... Friedl MA, et al. A global land cover training dataset from 1984 to 2020. Scientific Data. 10: 879. PMID 38062043 DOI: 10.1038/s41597-023-02798-5 |
0.352 |
|
| 2022 |
Moon M, Richardson AD, Milliman T, Friedl MA. A high spatial resolution land surface phenology dataset for AmeriFlux and NEON sites. Scientific Data. 9: 448. PMID 35896546 DOI: 10.1038/s41597-022-01570-5 |
0.464 |
|
| 2020 |
Elmes A, Alemohammad H, Avery R, Caylor K, Eastman JR, Fishgold L, Friedl MA, Jain M, Kohli D, Laso Bayas JC, Lunga D, McCarty JL, Pontius RG, Reinmann AB, Rogan J, et al. Accounting for Training Data Error in Machine Learning Applied to Earth Observations Remote Sensing. 12: 1034. DOI: 10.3390/Rs12061034 |
0.411 |
|
| 2020 |
Seyednasrollah B, Young AM, Li X, Milliman T, Ault T, Frolking S, Friedl M, Richardson AD. Sensitivity of Deciduous Forest Phenology to Environmental Drivers: Implications for Climate Change Impacts Across North America Geophysical Research Letters. 47. DOI: 10.1029/2019Gl086788 |
0.431 |
|
| 2020 |
Bolton DK, Gray JM, Melaas EK, Moon M, Eklundh L, Friedl MA. Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery Remote Sensing of Environment. 240: 111685. DOI: 10.1016/J.Rse.2020.111685 |
0.841 |
|
| 2020 |
Moon M, Li D, Liao W, Rigden AJ, Friedl MA. Modification of surface energy balance during springtime: The relative importance of biophysical and meteorological changes Agricultural and Forest Meteorology. 284: 107905. DOI: 10.1016/J.Agrformet.2020.107905 |
0.352 |
|
| 2019 |
Seyednasrollah B, Young AM, Hufkens K, Milliman T, Friedl MA, Frolking S, Richardson AD. Publisher Correction: Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset. Scientific Data. 6: 261. PMID 31676800 DOI: 10.1038/S41597-019-0270-8 |
0.305 |
|
| 2019 |
Seyednasrollah B, Young AM, Hufkens K, Milliman T, Friedl MA, Frolking S, Richardson AD. Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset. Scientific Data. 6: 222. PMID 31641140 DOI: 10.1038/S41597-019-0229-9 |
0.515 |
|
| 2019 |
Wang JA, Sulla-Menashe D, Woodcock CE, Sonnentag O, Keeling RF, Friedl MA. Extensive Land Cover Change Across Arctic-Boreal Northwestern North America from Disturbance and Climate Forcing. Global Change Biology. PMID 31437337 DOI: 10.1111/Gcb.14804 |
0.536 |
|
| 2019 |
Stanimirova R, Cai Z, Melaas EK, Gray JM, Eklundh L, Jönsson P, Friedl MA. An empirical assessment of the MODIS land cover dynamics and TIMESAT land surface phenology algorithms Remote Sensing. 11: 2201. DOI: 10.3390/Rs11192201 |
0.819 |
|
| 2019 |
Wang JA, Friedl MA. The role of land cover change in Arctic-boreal greening and browning trends Environmental Research Letters. 14: 125007. DOI: 10.1088/1748-9326/Ab5429 |
0.548 |
|
| 2019 |
Stanimirova R, Arévalo P, Kaufmann RK, Maus V, Lesiv M, Havlík P, Friedl MA. Sensitivity of Global Pasturelands to Climate Variation Earth's Future. 7: 1353-1366. DOI: 10.1029/2019Ef001316 |
0.477 |
|
| 2019 |
Moon M, Zhang X, Henebry GM, Liu L, Gray JM, Melaas EK, Friedl MA. Long-term continuity in land surface phenology measurements: A comparative assessment of the MODIS land cover dynamics and VIIRS land surface phenology products Remote Sensing of Environment. 226: 74-92. DOI: 10.1016/J.Rse.2019.03.034 |
0.829 |
|
| 2019 |
Sulla-Menashe D, Gray JM, Abercrombie SP, Friedl MA. Hierarchical mapping of annual global land cover 2001 to present: The MODIS Collection 6 Land Cover product Remote Sensing of Environment. 222: 183-194. DOI: 10.1016/J.Rse.2018.12.013 |
0.566 |
|
| 2018 |
Richardson AD, Hufkens K, Milliman T, Aubrecht DM, Chen M, Gray JM, Johnston MR, Keenan TF, Klosterman ST, Kosmala M, Melaas EK, Friedl MA, Frolking S. Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery. Scientific Data. 5: 180028. PMID 29533393 DOI: 10.1038/Sdata.2018.28 |
0.818 |
|
| 2018 |
Jönsson P, Cai Z, Melaas E, Friedl M, Eklundh L. A Method for Robust Estimation of Vegetation Seasonality from Landsat and Sentinel-2 Time Series Data Remote Sensing. 10: 635. DOI: 10.3390/Rs10040635 |
0.788 |
|
| 2018 |
Sulla-Menashe D, Woodcock CE, Friedl MA. Canadian boreal forest greening and browning trends: an analysis of biogeographic patterns and the relative roles of disturbance versus climate drivers Environmental Research Letters. 13: 014007. DOI: 10.1088/1748-9326/Aa9B88 |
0.469 |
|
| 2018 |
Zhang X, Liu L, Liu Y, Jayavelu S, Wang J, Moon M, Henebry GM, Friedl MA, Schaaf CB. Generation and evaluation of the VIIRS land surface phenology product Remote Sensing of Environment. 216: 212-229. DOI: 10.1016/J.Rse.2018.06.047 |
0.548 |
|
| 2018 |
Zhang X, Jayavelu S, Liu L, Friedl MA, Henebry GM, Liu Y, Schaaf CB, Richardson AD, Gray J. Evaluation of land surface phenology from VIIRS data using time series of PhenoCam imagery Agricultural and Forest Meteorology. 137-149. DOI: 10.1016/J.Agrformet.2018.03.003 |
0.502 |
|
| 2018 |
Klosterman S, Melaas E, Wang JA, Martinez A, Frederick S, O’Keefe J, Orwig DA, Wang Z, Sun Q, Schaaf C, Friedl M, Richardson AD. Fine-scale perspectives on landscape phenology from unmanned aerial vehicle (UAV) photography Agricultural and Forest Meteorology. 248: 397-407. DOI: 10.1016/J.Agrformet.2017.10.015 |
0.797 |
|
| 2018 |
Melaas EK, Sulla-Menashe D, Friedl MA. Multidecadal Changes and Interannual Variation in Springtime Phenology of North American Temperate and Boreal Deciduous Forests Geophysical Research Letters. 45: 2679-2687. DOI: 10.1002/2017Gl076933 |
0.783 |
|
| 2017 |
Hardiman BS, Wang JA, Hutyra LR, Gately CK, Getson JM, Friedl MA. Accounting for urban biogenic fluxes in regional carbon budgets. The Science of the Total Environment. 592: 366-372. PMID 28324854 DOI: 10.1016/J.Scitotenv.2017.03.028 |
0.421 |
|
| 2017 |
Wang JA, Hutyra LR, Li D, Friedl MA. Gradients of Atmospheric Temperature and Humidity Controlled by Local Urban Land-Use Intensity in Boston Journal of Applied Meteorology and Climatology. 56: 817-831. DOI: 10.1175/Jamc-D-16-0325.1 |
0.461 |
|
| 2017 |
Zhang X, Wang J, Gao F, Liu Y, Schaaf C, Friedl M, Yu Y, Jayavelu S, Gray J, Liu L, Yan D, Henebry GM. Exploration of scaling effects on coarse resolution land surface phenology Remote Sensing of Environment. 190: 318-330. DOI: 10.1016/J.Rse.2017.01.001 |
0.481 |
|
| 2016 |
Chen M, Melaas EK, Gray JM, Friedl MA, Richardson AD. A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: Impacts on carbon and water cycling under future climate scenarios. Global Change Biology. PMID 27097603 DOI: 10.1111/Gcb.13326 |
0.796 |
|
| 2016 |
Melaas EK, Wang JA, Miller DL, Friedl MA. Interactions between urban vegetation and surface urban heat islands: a case study in the Boston metropolitan region Environmental Research Letters. 11: 054020. DOI: 10.1088/1748-9326/11/5/054020 |
0.796 |
|
| 2016 |
Melaas EK, Sulla-Menashe D, Gray JM, Black TA, Morin TH, Richardson AD, Friedl MA. Multisite analysis of land surface phenology in North American temperate and boreal deciduous forests from Landsat Remote Sensing of Environment. 186: 452-464. DOI: 10.1016/J.Rse.2016.09.014 |
0.842 |
|
| 2016 |
Sulla-Menashe D, Friedl MA, Woodcock CE. Sources of bias and variability in long-term Landsat time series over Canadian boreal forests Remote Sensing of Environment. 177: 206-219. DOI: 10.1016/J.Rse.2016.02.041 |
0.493 |
|
| 2016 |
Huang X, Schneider A, Friedl MA. Mapping sub-pixel urban expansion in China using MODIS and DMSP/OLS nighttime lights Remote Sensing of Environment. 175: 92-108. DOI: 10.1016/J.Rse.2015.12.042 |
0.701 |
|
| 2016 |
Verma M, Friedl MA, Finzi A, Phillips N. Multi-criteria evaluation of the suitability of growth functions for modeling remotely sensed phenology Ecological Modelling. 323: 123-132. DOI: 10.1016/J.Ecolmodel.2015.12.005 |
0.634 |
|
| 2015 |
Melaas EK, Friedl MA, Richardson AD. Multi-scale modeling of spring phenology across Deciduous Forests in the Eastern United States. Global Change Biology. PMID 26456080 DOI: 10.1111/Gcb.13122 |
0.811 |
|
| 2015 |
Toomey M, Friedl MA, Frolking S, Hufkens K, Klosterman S, Sonnentag O, Baldocchi DD, Bernacchi CJ, Biraud SC, Bohrer G, Brzostek E, Burns SP, Coursolle C, Hollinger DY, Margolis HA, et al. Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy-scale photosynthesis. Ecological Applications : a Publication of the Ecological Society of America. 25: 99-115. PMID 26255360 DOI: 10.1890/14-0005.1 |
0.506 |
|
| 2015 |
Abercrombie SP, Friedl MA. Improving the Consistency of Multitemporal Land Cover Maps Using a Hidden Markov Model Ieee Transactions On Geoscience and Remote Sensing. DOI: 10.1109/Tgrs.2015.2463689 |
0.567 |
|
| 2015 |
Salmon J, Friedl MA, Frolking S, Wisser D, Douglas EM. Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data International Journal of Applied Earth Observation and Geoinformation. 38: 321-334. DOI: 10.1016/J.Jag.2015.01.014 |
0.478 |
|
| 2015 |
Verma M, Friedl MA, Law BE, Bonal D, Kiely G, Black TA, Wohlfahrt G, Moors EJ, Montagnani L, Marcolla B, Toscano P, Varlagin A, Roupsard O, Cescatti A, Arain MA, et al. Improving the performance of remote sensing models for capturing intra- and inter-annual variations in daily GPP: An analysis using global FLUXNET tower data Agricultural and Forest Meteorology. 214: 416-429. DOI: 10.1016/J.Agrformet.2015.09.005 |
0.65 |
|
| 2014 |
Keenan, Darby B, Felts E, Sonnentag O, Friedl MA, Hufkens K, O'Keef J, Klosterman S, Munger JW, Toome M, Richardson AD. Tracking forest phenology and seasonal physiology using digital repeat photography: a critical assessment. Ecological Applications : a Publication of the Ecological Society of America. 24: 1478-89. PMID 29160668 DOI: 10.1890/13-0652.1 |
0.491 |
|
| 2014 |
Gray JM, Frolking S, Kort EA, Ray DK, Kucharik CJ, Ramankutty N, Friedl MA. Direct human influence on atmospheric CO2 seasonality from increased cropland productivity. Nature. 515: 398-401. PMID 25409830 DOI: 10.1038/Nature13957 |
0.391 |
|
| 2014 |
Klosterman ST, Hufkens K, Gray JM, Melaas E, Sonnentag O, Lavine I, Mitchell L, Norman R, Friedl MA, Richardson AD. Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery Biogeosciences. 11: 4305-4320. DOI: 10.5194/Bg-11-4305-2014 |
0.815 |
|
| 2014 |
Verma M, Friedl MA, Richardson AD, Kiely G, Cescatti A, Law BE, Wohlfahrt G, Gielen B, Roupsard O, Moors EJ, Toscano P, Vaccari FP, Gianelle D, Bohrer G, Varlagin A, et al. Remote sensing of annual terrestrial gross primary productivity from MODIS: An assessment using the FLUXNET la Thuile data set Biogeosciences. 11: 2185-2200. DOI: 10.5194/Bg-11-2185-2014 |
0.682 |
|
| 2014 |
Li L, Friedl MA, Xin Q, Gray J, Pan Y, Frolking S. Mapping crop cycles in China using MODIS-EVI time series Remote Sensing. 6: 2473-2493. DOI: 10.3390/Rs6032473 |
0.501 |
|
| 2014 |
Gray J, Friedl M, Frolking S, Ramankutty N, Nelson A, Gumma MK. Mapping Asian Cropping Intensity With MODIS Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7: 3373-3379. DOI: 10.1109/Jstars.2014.2344630 |
0.541 |
|
| 2014 |
Friedl MA, Gray JM, Melaas EK, Richardson AD, Hufkens K, Keenan TF, Bailey A, O'Keefe J. A tale of two springs: Using recent climate anomalies to characterize the sensitivity of temperate forest phenology to climate change Environmental Research Letters. 9. DOI: 10.1088/1748-9326/9/5/054006 |
0.799 |
|
| 2014 |
Keenan TF, Gray J, Friedl MA, Toomey M, Bohrer G, Hollinger DY, Munger JW, O'Keefe J, Schmid HP, Wing IS, Yang B, Richardson AD. Net carbon uptake has increased through warming-induced changes in temperate forest phenology Nature Climate Change. 4: 598-604. DOI: 10.1038/Nclimate2253 |
0.373 |
|
| 2014 |
Cai S, Liu D, Sulla-Menashe D, Friedl MA. Enhancing MODIS land cover product with a spatial-temporal modeling algorithm Remote Sensing of Environment. 147: 243-255. DOI: 10.1016/J.Rse.2014.03.012 |
0.534 |
|
| 2014 |
Sulla-Menashe D, Kennedy RE, Yang Z, Braaten J, Krankina ON, Friedl MA. Detecting forest disturbance in the Pacific Northwest from MODIS time series using temporal segmentation Remote Sensing of Environment. 151: 114-123. DOI: 10.1016/J.Rse.2013.07.042 |
0.569 |
|
| 2014 |
Huang X, Friedl MA. Distance metric-based forest cover change detection using MODIS time series International Journal of Applied Earth Observation and Geoinformation. 29: 78-92. DOI: 10.1016/J.Jag.2014.01.004 |
0.72 |
|
| 2014 |
Glanz H, Carvalho L, Sulla-Menashe D, Friedl MA. A parametric model for classifying land cover and evaluating training data based on multi-temporal remote sensing data Isprs Journal of Photogrammetry and Remote Sensing. 97: 219-228. DOI: 10.1016/J.Isprsjprs.2014.09.004 |
0.817 |
|
| 2014 |
Martellozzo F, Ramankutty N, Hall RJ, Price DT, Purdy B, Friedl MA. Urbanization and the loss of prime farmland: a case study in the Calgary-Edmonton corridor of Alberta Regional Environmental Change. DOI: 10.1007/S10113-014-0658-0 |
0.45 |
|
| 2013 |
Justice CO, Román MO, Csiszar I, Vermote EF, Wolfe RE, Hook SJ, Friedl M, Wang Z, Schaaf CB, Miura T, Tschudi M, Riggs G, Hall DK, Lyapustin AI, Devadiga S, et al. Land and cryosphere products from Suomi NPP VIIRS: Overview and status. Journal of Geophysical Research. Atmospheres : Jgr. 118: 9753-9765. PMID 25821661 DOI: 10.1002/Jgrd.50771 |
0.433 |
|
| 2013 |
Frolking S, Milliman T, Seto KC, Friedl MA. A global fingerprint of macro-scale changes in urban structure from 1999 to 2009 Environmental Research Letters. 8. DOI: 10.1088/1748-9326/8/2/024004 |
0.391 |
|
| 2013 |
Melaas EK, Friedl MA, Zhu Z. Detecting interannual variation in deciduous broadleaf forest phenology using Landsat TM/ETM+ data Remote Sensing of Environment. 132: 176-185. DOI: 10.1016/J.Rse.2013.01.011 |
0.84 |
|
| 2013 |
Bolton DK, Friedl MA. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics Agricultural and Forest Meteorology. 173: 74-84. DOI: 10.1016/J.Agrformet.2013.01.007 |
0.47 |
|
| 2013 |
Melaas EK, Richardson AD, Friedl MA, Dragoni D, Gough CM, Herbst M, Montagnani L, Moors E. Using FLUXNET data to improve models of springtime vegetation activity onset in forest ecosystems Agricultural and Forest Meteorology. 171: 46-56. DOI: 10.1016/J.Agrformet.2012.11.018 |
0.801 |
|
| 2012 |
Liu C, Ray S, Hooker G, Friedl M. Functional factor analysis for periodic remote sensing data Annals of Applied Statistics. 6: 601-624. DOI: 10.1214/11-Aoas518 |
0.361 |
|
| 2012 |
Hufkens K, Friedl MA, Keenan TF, Sonnentag O, Bailey A, O'Keefe J, Richardson AD. Ecological impacts of a widespread frost event following early spring leaf-out Global Change Biology. 18: 2365-2377. DOI: 10.1111/J.1365-2486.2012.02712.X |
0.463 |
|
| 2012 |
Stehman SV, Olofsson P, Woodcock CE, Herold M, Friedl MA. A global land-cover validation data set, II: Augmenting a stratified sampling design to estimate accuracy by region and land-cover class International Journal of Remote Sensing. 33: 6975-6993. DOI: 10.1080/01431161.2012.695092 |
0.315 |
|
| 2012 |
Olofsson P, Stehman SV, Woodcock CE, Sulla-Menashe D, Sibley AM, Newell JD, Friedl MA, Herold M. A global land-cover validation data set, part I: Fundamental design principles International Journal of Remote Sensing. 33: 5768-5788. DOI: 10.1080/01431161.2012.674230 |
0.349 |
|
| 2012 |
Baccini A, Goetz SJ, Walker WS, Laporte NT, Sun M, Sulla-Menashe D, Hackler J, Beck PSA, Dubayah R, Friedl MA, Samanta S, Houghton RA. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps Nature Climate Change. 2: 182-185. DOI: 10.1038/Nclimate1354 |
0.695 |
|
| 2012 |
Avitabile V, Baccini A, Friedl MA, Schmullius C. Capabilities and limitations of Landsat and land cover data for aboveground woody biomass estimation of Uganda Remote Sensing of Environment. 117: 366-380. DOI: 10.1016/J.Rse.2011.10.012 |
0.775 |
|
| 2012 |
Hufkens K, Friedl M, Sonnentag O, Braswell BH, Milliman T, Richardson AD. Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology Remote Sensing of Environment. 117: 307-321. DOI: 10.1016/J.Rse.2011.10.006 |
0.535 |
|
| 2012 |
Sonnentag O, Hufkens K, Teshera-Sterne C, Young AM, Friedl M, Braswell BH, Milliman T, O'Keefe J, Richardson AD. Digital repeat photography for phenological research in forest ecosystems Agricultural and Forest Meteorology. 152: 159-177. DOI: 10.1016/J.Agrformet.2011.09.009 |
0.4 |
|
| 2011 |
Pflugmacher D, Krankina ON, Cohen WB, Friedl MA, Sulla-Menashe D, Kennedy RE, Nelson P, Loboda TV, Kuemmerle T, Dyukarev E, Elsakov V, Kharuk VI. Comparison and assessment of coarse resolution land cover maps for Northern Eurasia Remote Sensing of Environment. 115: 3539-3553. DOI: 10.1016/J.Rse.2011.08.016 |
0.534 |
|
| 2011 |
Sulla-Menashe D, Friedl MA, Krankina ON, Baccini A, Woodcock CE, Sibley A, Sun G, Kharuk V, Elsakov V. Hierarchical mapping of Northern Eurasian land cover using MODIS data Remote Sensing of Environment. 115: 392-403. DOI: 10.1016/J.Rse.2010.09.010 |
0.762 |
|
| 2011 |
Van der Molen MK, Dolman AJ, Ciais P, Eglin T, Gobron N, Law BE, Meir P, Peters W, Phillips OL, Reichstein M, Chen T, Dekker SC, Doubková M, Friedl MA, Jung M, et al. Drought and ecosystem carbon cycling Agricultural and Forest Meteorology. 151: 765-773. DOI: 10.1016/J.Agrformet.2011.01.018 |
0.31 |
|
| 2010 |
Richardson AD, Black TA, Ciais P, Delbart N, Friedl MA, Gobron N, Hollinger DY, Kutsch WL, Longdoz B, Luyssaert S, Migliavacca M, Montagnani L, Munger JW, Moors E, Piao S, et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 365: 3227-46. PMID 20819815 DOI: 10.1098/Rstb.2010.0102 |
0.49 |
|
| 2010 |
Zhang X, Goldberg M, Tarpley D, Friedl MA, Morisette J, Kogan F, Yu Y. Drought-induced vegetation stress in southwestern North America Environmental Research Letters. 5. DOI: 10.1088/1748-9326/5/2/024008 |
0.446 |
|
| 2010 |
Ganguly S, Friedl MA, Tan B, Zhang X, Verma M. Land surface phenology from MODIS: Characterization of the Collection 5 global land cover dynamics product Remote Sensing of Environment. 114: 1805-1816. DOI: 10.1016/J.Rse.2010.04.005 |
0.704 |
|
| 2010 |
Schneider A, Friedl MA, Potere D. Mapping global urban areas using MODIS 500-m data: New methods and datasets based on 'urban ecoregions' Remote Sensing of Environment. 114: 1733-1746. DOI: 10.1016/J.Rse.2010.03.003 |
0.515 |
|
| 2010 |
Friedl MA, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang X. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets Remote Sensing of Environment. 114: 168-182. DOI: 10.1016/J.Rse.2009.08.016 |
0.719 |
|
| 2009 |
Schneider A, Friedl MA, Potere D. A new map of global urban extent from MODIS satellite data Environmental Research Letters. 4. DOI: 10.1088/1748-9326/4/4/044003 |
0.548 |
|
| 2009 |
Zhang X, Friedl MA, Schaaf CB. Sensitivity of vegetation phenology detection to the temporal resolution of satellite data International Journal of Remote Sensing. 30: 2061-2074. DOI: 10.1080/01431160802549237 |
0.464 |
|
| 2008 |
Krankina ON, Pflugmacher D, Friedl M, Cohen WB, Nelson P, Baccini A. Meeting the challenge of mapping peatlands with remotely sensed data Biogeosciences. 5: 1809-1820. DOI: 10.5194/Bg-5-1809-2008 |
0.71 |
|
| 2008 |
Schneider A, Friedl MA, Potere D. Monitoring the extent and intensity of urban areas globally using the fusion of modis 500m resolution satellite imagery and ancillary data sources International Geoscience and Remote Sensing Symposium (Igarss). 5: V346-V349. DOI: 10.1109/IGARSS.2008.4780099 |
0.428 |
|
| 2008 |
Ordoyne C, Friedl MA. Using MODIS data to characterize seasonal inundation patterns in the Florida Everglades Remote Sensing of Environment. 112: 4107-4119. DOI: 10.1016/J.Rse.2007.08.027 |
0.531 |
|
| 2007 |
Myneni RB, Yang W, Nemani RR, Huete AR, Dickinson RE, Knyazikhin Y, Didan K, Fu R, Negrón Juárez RI, Saatchi SS, Hashimoto H, Ichii K, Shabanov NV, Tan B, Ratana P, ... ... Friedl MA, et al. Large seasonal swings in leaf area of Amazon rainforests. Proceedings of the National Academy of Sciences of the United States of America. 104: 4820-3. PMID 17360360 DOI: 10.1073/Pnas.0611338104 |
0.478 |
|
| 2007 |
Baccini A, Friedl MA, Woodcock CE, Zhu Z. Scaling field data to calibrate and validate moderate spatial resolution remote sensing models Photogrammetric Engineering and Remote Sensing. 73: 945-954. DOI: 10.14358/Pers.73.8.945 |
0.713 |
|
| 2007 |
Santanello JA, Friedl MA, Ek MB. Convective planetary boundary layer interactions with the land surface at diurnal time scales: Diagnostics and feedbacks Journal of Hydrometeorology. 8: 1082-1097. DOI: 10.1175/Jhm614.1 |
0.724 |
|
| 2007 |
Santanello JA, Friedl MA. Estimation of convective planetary boundary layer evolution and land-atmosphere interactions from MODIS and AIRS 87th Ams Annual Meeting. |
0.635 |
|
| 2006 |
Zhang X, Friedl MA, Schaaf CB. Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements Journal of Geophysical Research: Biogeosciences. 111. DOI: 10.1029/2006Jg000217 |
0.578 |
|
| 2005 |
Santanello JA, Friedl MA, Kustas WP. An empirical investigation of convective planetary boundary layer evolution and its relationship with the land surface Journal of Applied Meteorology. 44: 917-932. DOI: 10.1175/Jam2240.1 |
0.718 |
|
| 2005 |
Zhang X, Friedl MA, Schaaf CB, Strahler AH, Liu Z. Monitoring the response of vegetation phenology to precipitation in Africa by coupling MODIS and TRMM instruments Journal of Geophysical Research D: Atmospheres. 110: 1-14. DOI: 10.1029/2004Jd005263 |
0.505 |
|
| 2005 |
Lotsch A, Friedl MA, Anderson BT, Tucker CJ. Response of terrestrial ecosystems to recent Northern Hemispheric drought Geophysical Research Letters. 32: 1-5. DOI: 10.1029/2004Gl022043 |
0.811 |
|
| 2004 |
Zhang X, Friedl MA, Schaaf CB, Strahler AH. Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data Global Change Biology. 10: 1133-1145. DOI: 10.1111/J.1529-8817.2003.00784.X |
0.559 |
|
| 2004 |
Zhang X, Friedl MA, Schaaf CB, Strahler AH, Schneider A. The footprint of urban climates on vegetation phenology Geophysical Research Letters. 31. DOI: 10.1029/2004Gl020137 |
0.496 |
|
| 2004 |
Baccini A, Friedl MA, Woodcock CE, Warbington R. Forest biomass estimation over regional scales using multisource data Geophysical Research Letters. 31: L10501 1-4. DOI: 10.1029/2004Gl019782 |
0.768 |
|
| 2004 |
Tian Y, Dickinson RE, Zhou L, Myneni RB, Friedl M, Schaaf CB, Carroll M, Gao F. Land boundary conditions from MODIS data and consequences for the albedo of a climate model Geophysical Research Letters. 31: n/a-n/a. DOI: 10.1029/2003Gl019104 |
0.529 |
|
| 2004 |
Santanello JA, Friedl MA. Convective planetary boundary layer evolution and land surface energy balance Bulletin of the American Meteorological Society. 3599-3603. |
0.678 |
|
| 2003 |
Schneider A, Friedl MA, Woodcock CE. Mapping Urban Areas by Fusing Multiple Sources of Coarse Resolution Remotely Sensed Data International Geoscience and Remote Sensing Symposium (Igarss). 4: 2623-2625. DOI: 10.14358/Pers.69.12.1377 |
0.517 |
|
| 2003 |
Santanello JA, Friedl MA. Diurnal covariation in soil heat flux and net radiation Journal of Applied Meteorology. 42: 851-862. DOI: 10.1175/1520-0450(2003)042<0851:Dcishf>2.0.Co;2 |
0.648 |
|
| 2003 |
Lotsch A, Friedl MA, Pinzón J. Spatio-temporal deconvolution of NDVI image sequences using independent component analysis Ieee Transactions On Geoscience and Remote Sensing. 41: 2938-2942. DOI: 10.1109/Tgrs.2003.819868 |
0.785 |
|
| 2003 |
Lotsch A, Tian Y, Friedl MA, Myneni RB. Land cover mapping in support of LAI and FPAR retrievals from EOS-MODIS and MISR: Classification methods and sensitivities to errors International Journal of Remote Sensing. 24: 1997-2016. DOI: 10.1080/01431160210154858 |
0.83 |
|
| 2003 |
Lotsch A, Friedl MA, Anderson BT, Tucker CJ. Coupled vegetation-precipitation variability observed from satellite and climate records Geophysical Research Letters. 30. DOI: 10.1029/2003Gl017506 |
0.821 |
|
| 2003 |
Yang R, Friedl MA. Modeling the effects of three-dimensional vegetation structure on surface radiation and energy balance in boreal forests Journal of Geophysical Research D: Atmospheres. 108. DOI: 10.1029/2002Jd003109 |
0.602 |
|
| 2003 |
Yang R, Friedl MA. Determination of roughness lengths for heat and momentum over boreal forests Boundary-Layer Meteorology. 107: 581-603. DOI: 10.1023/A:1022880530523 |
0.597 |
|
| 2003 |
Zhang X, Friedl MA, Schaaf CB, Strahler AH, Hodges JCF, Gao F, Reed BC, Huete A. Monitoring vegetation phenology using MODIS Remote Sensing of Environment. 84: 471-475. DOI: 10.1016/S0034-4257(02)00135-9 |
0.546 |
|
| 2002 |
Friedl MA, McIver DK, Hodges JCF, Zhang XY, Muchoney D, Strahler AH, Woodcock CE, Gopal S, Schneider A, Cooper A, Baccini A, Gao F, Schaaf C. Global land cover mapping from MODIS: Algorithms and early results Remote Sensing of Environment. 83: 287-302. DOI: 10.1016/S0034-4257(02)00078-0 |
0.842 |
|
| 2002 |
Myneni RB, Hoffman S, Knyazikhin Y, Privette JL, Glassy J, Tian Y, Wang Y, Song X, Zhang Y, Smith GR, Lotsch A, Friedl M, Morisette JT, Votava P, Nemani RR, et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data Remote Sensing of Environment. 83: 214-231. DOI: 10.1016/S0034-4257(02)00074-3 |
0.798 |
|
| 2002 |
McIver DK, Friedl MA. Using prior probabilities in decision-tree classification of remotely sensed data Remote Sensing of Environment. 81: 253-261. DOI: 10.1016/S0034-4257(02)00003-2 |
0.826 |
|
| 2002 |
Friedl MA. Forward and inverse modeling of land surface energy balance using surface temperature measurements Remote Sensing of Environment. 79: 344-354. DOI: 10.1016/S0034-4257(01)00284-X |
0.379 |
|
| 2002 |
Friedl MA, McIver DK, Brodley CE. Integration of domain knowledge in the form of ancillary map data into supervised classification of remotely sensed data International Geoscience and Remote Sensing Symposium (Igarss). 2: 1038-1040. |
0.825 |
|
| 2002 |
Zhang X, Friedl MA, Schaaf CB, Strahler AH, Hodges JCF, Gao F. Using MODIS data to study the relation between climatic spatial variability and vegetation phenology in northern high latitudes International Geoscience and Remote Sensing Symposium (Igarss). 2: 1149-1151. |
0.37 |
|
| 2001 |
Schneider A, McIver DK, Friedl MA, Woodcock CE. Mapping urban areas using coarse resolution remotely sensed data Ieee/Isprs Joint Workshop On Remote Sensing and Data Fusion Over Urban Areas, Dfua 2001. 136-140. DOI: 10.1109/DFUA.2001.985750 |
0.835 |
|
| 2001 |
McIver DK, Friedl MA. Estimating pixel-scale land cover classification confidence using nonparametric machine learning methods Ieee Transactions On Geoscience and Remote Sensing. 39: 1959-1968. DOI: 10.1109/36.951086 |
0.821 |
|
| 2001 |
Yan G, Friedl M, Li X, Wang J, Zhu C, Strahler AH. Modeling directional effects from nonisothermal land surfaces in wideband thermal infrared measurements Ieee Transactions On Geoscience and Remote Sensing. 39: 1095-1099. DOI: 10.1109/36.921427 |
0.339 |
|
| 2001 |
Yang R, Friedl MA, Ni W. Parameterization of shortwave radiation fluxes for nonuniform vegetation canopies in land surface models Journal of Geophysical Research Atmospheres. 106: 14275-14286. DOI: 10.1029/2001Jd900180 |
0.608 |
|
| 2001 |
Schneider A, McIver DK, Friedl MA, Strahler AH. Classification of urban areas at continental scales using remotely sensed data International Geoscience and Remote Sensing Symposium (Igarss). 5: 2146-2148. |
0.834 |
|
| 2001 |
Zhang X, Hodges JCF, Schaaf CB, Friedl MA, Strahler AH, Gao F. Global vegetation phenology from AVHRR and MODIS data International Geoscience and Remote Sensing Symposium (Igarss). 5: 2262-2264. |
0.331 |
|
| 2001 |
Friedl MA, McIver DK, Zhang XY, Hodges JCF, Schnieder A, Bacinni A, Strahler AH, Cooper A, Gao F, Schaaf C, Liu W. Global land cover classification results from MODIS International Geoscience and Remote Sensing Symposium (Igarss). 2: 733-735. |
0.843 |
|
| 2000 |
Friedl MA, Woodcock C, Gopal S, Muchoney D, Strahler AH, Barker-Schaaf C. A note on procedures used for accuracy assessment in land cover maps derived from AVHRR data International Journal of Remote Sensing. 21: 1073-1077. DOI: 10.1080/014311600210434 |
0.486 |
|
| 2000 |
Muchoney D, Borak J, Chi H, Friedl M, Gopal S, Hodges J, Morrow N, Strahler A. Application of the MODIS global supervised classification model to vegetation and land cover mapping of Central America International Journal of Remote Sensing. 21: 1115-1138. DOI: 10.1080/014311600210100 |
0.539 |
|
| 2000 |
Friedl MA, Muchoney D, McIver D, Gao F, Hodges JCF, Strahler AH. Characterization of North American land cover from NOAA-AVHRR data using the EOS MODIS Land Cover Classification Algorithm Geophysical Research Letters. 27: 977-980. DOI: 10.1029/1999Gl011010 |
0.545 |
|
| 2000 |
Friedl MA, Gopal S, Muchoney D, Strahler AH. Global land cover mapping from MODIS: Algorithm design and preliminary results International Geoscience and Remote Sensing Symposium (Igarss). 2: 527-529. |
0.341 |
|
| 2000 |
Friedl MA, Woodcock C, Gopal S, Muchoney D, Strahler AH, Barker-Schaaf C. A note on procedures used for accuracy assessment in land cover maps derived from AVHRR data International Journal of Remote Sensing. 21: 1073-1077. |
0.386 |
|
| 1999 |
Brodley CE, Friedl MA. Identifying Mislabeled Training Data Journal of Artificial Intelligence Research. 11: 131-167. DOI: 10.1613/Jair.606 |
0.303 |
|
| 1999 |
Friedl MA, Brodley CE, Strahler AH. Maximizing land cover classification accuracies produced by decision trees at continental to global scales Ieee Transactions On Geoscience and Remote Sensing. 37: 969-977. DOI: 10.1109/36.752215 |
0.494 |
|
| 1998 |
Morrow N, Friedl MA. Modeling biophysical controls on land surface temperature and reflectance in grasslands Agricultural and Forest Meteorology. 92: 147-161. DOI: 10.1016/S0168-1923(98)00098-7 |
0.401 |
|
| 1997 |
Brodley CE, Friedl MA. Decision tree classification of land cover from remotely sensed data Remote Sensing of Environment. 61: 399-409. DOI: 10.1016/S0034-4257(97)00049-7 |
0.386 |
|
| 1996 |
Friedl MA. Relationships among remotely sensed data, surface energy balance, and area-averaged fluxes over partially vegetated land surfaces Journal of Applied Meteorology. 35: 2091-2103. DOI: 10.1175/1520-0450(1996)035<2091:Rarsds>2.0.Co;2 |
0.488 |
|
| 1996 |
Friedl MA. Modeling area-averaged fluxes over partially vegetated land surfaces using aircraft and in-situ thermal data International Geoscience and Remote Sensing Symposium (Igarss). 4: 2152-2154. |
0.388 |
|
| 1995 |
Friedl MA. Modeling land surface fluxes using a sparse canopy model and radiometric surface temperature measurements Journal of Geophysical Research. 100. DOI: 10.1029/95Jd00723 |
0.383 |
|
| 1995 |
Friedl MA, Davis FW, Michaelsen J, Moritz MA. Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables: An analysis using a scene simulation model and data from FIFE Remote Sensing of Environment. 54: 233-246. DOI: 10.1016/0034-4257(95)00156-5 |
0.448 |
|
| 1994 |
Michaelsen J, Schimel DS, Friedl MA, Davis FW, Dubayah RC. Regression tree analysis of satellite and terrain data to guide vegetation sampling and surveys Journal of Vegetation Science. 5: 673-686. DOI: 10.2307/3235882 |
0.543 |
|
| 1994 |
Friedl MA, Michaelsen J, Davis FW, Walker H, Schimel DS. Estimating grassland biomass and leaf area index using ground and satellite data International Journal of Remote Sensing. 15: 1401-1420. DOI: 10.1080/01431169408954174 |
0.512 |
|
| 1994 |
Friedl MA, Davis FW. Sources of variation in radiometric surface temperature over a tallgrass prairie Remote Sensing of Environment. 48: 1-17. DOI: 10.1016/0034-4257(94)90109-0 |
0.392 |
|
| 1994 |
Friedl MA, Davis FW, Michaelsen J, Moritz M. Modeling sources of uncertainty in satellite-based estimates of leaf area index using a scene simulation model International Geoscience and Remote Sensing Symposium (Igarss). 3: 1826-1828. |
0.362 |
|
| 1992 |
Davis FW, Schimel DS, Friedl MA, Michaelsen JC, Kittel TGF, Dubayah R, Dozier J. Covariance of biophysical data with digital topographic and land use maps over the FIFE site Journal of Geophysical Research. 97: 19009. DOI: 10.1029/92Jd01345 |
0.544 |
|
| 1989 |
Friedl MA, McGwire KC, Star JL. MAPWD: An interactive mapping tool for accessing geo-referenced data sets Computers and Geosciences. 15: 1203-1219. DOI: 10.1016/0098-3004(89)90087-3 |
0.316 |
|
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