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Publications Citing LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code

The following 20 publications cited the product LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code.

Year Citation
2022 Park, E., H. Loc Ho, D. Van Binh, S. Kantoush, D. Poh, E. Alcantara, S. Try, and Y.N. Lin. 2022. Impacts of agricultural expansion on floodplain water and sediment budgets in the Mekong River. Journal of Hydrology. 605:127296. https://doi.org/10.1016/j.jhydrol.2021.127296
2018 Chen, B., X. Xiao, H. Ye, J. Ma, R. Doughty, X. Li, B. Zhao, Z. Wu, R. Sun, J. Dong, Y. Qin, and G. Xie. 2018. Mapping Forest and Their Spatial-Temporal Changes From 2007 to 2015 in Tropical Hainan Island by Integrating ALOS/ALOS-2 L-Band SAR and Landsat Optical Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(3):852-867. https://doi.org/10.1109/JSTARS.2018.2795595
2018 Heimhuber, V., M.G. Tulbure, and M. Broich. 2018. Addressing spatio-temporal resolution constraints in Landsat and MODIS-based mapping of large-scale floodplain inundation dynamics. Remote Sensing of Environment. 211:307-320. https://doi.org/10.1016/j.rse.2018.04.016
2017 Bullock, E.L., S. Fagherazzi, W. Nardin, P. Vo-Luong, P. Nguyen, and C.E. Woodcock. 2017. Temporal patterns in species zonation in a mangrove forest in the Mekong Delta, Vietnam, using a time series of Landsat imagery. Continental Shelf Research. 147:144-154. https://doi.org/10.1016/j.csr.2017.07.007
2017 Chernetskiy, M., N. Gobron, J. Gmez?Dans, P. Lewis and C.C. Schmullius2017. Earth Observation Land Data Assimilation System (EO?LDAS) Regularization Constraints over Barrax Site. Earth Observation for Land and Emergency Monitoring.
2017 Hofmann, S., J. Everaars, O. Schweiger, M. Frenzel, L. Bannehr, and A.F. Cord. 2017. Modelling patterns of pollinator species richness and diversity using satellite image texture. PLOS ONE. 12(10):e0185591. https://doi.org/10.1371/journal.pone.0185591
2017 Khare, S., S.K. Ghosh, H. Latifi, S. Vijay, and T. Dahms. 2017. Seasonal-based analysis of vegetation response to environmental variables in the mountainous forests of Western Himalaya using Landsat 8 data. International Journal of Remote Sensing. 38(15):4418-4442. https://doi.org/10.1080/01431161.2017.1320450
2017 Martinez, S., E. Chuvieco, I. Aguado, and J. Salas. 2017. Burn severity and regeneration in large forest fires: an analysis from Landsat time series. Revista de Teledeteccion. 17. https://doi.org/10.4995/raet.2017.7182
2016 Hamzeh, S., A.A. Naseri, S.K. AlaviPanah, H. Bartholomeus, and M. Herold. 2016. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and Quantitative mapping of salinity stress in sugarcane fields. International Journal of Applied Earth Observation and Geoinformation. 52:412-421. https://doi.org/10.1016/j.jag.2016.06.024
2016 MILES, E.S., I.C. WILLIS, N.S. ARNOLD, J. STEINER, and F. PELLICCIOTTI. 2016. Spatial, seasonal and interannual variability of supraglacial ponds in the Langtang Valley of Nepal, 1999-2013. Journal of Glaciology. 63(237):88-105. https://doi.org/10.1017/jog.2016.120
2016 Molina, J., P. Lugo, J. Arias, J. Guaje, H. Castro, C. Costa, E. Cabrera, and M. Sanabria. 2016. Atmospheric correction matching to theoretical forest signature applied to different colombian regions. 1-7. https://doi.org/10.1109/STSIVA.2016.7743313
2016 Valencia, G.M., J.A. Anaya, and F.J. Caro-Lopera. 2016. Implementacion y evaluacion del modelo Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS): estudio de caso en los Andes colombianos. Revista de Teledeteccion. 83. https://doi.org/10.4995/raet.2016.3582
2016 Zipper, S.C., J. Schatz, A. Singh, C.J. Kucharik, P.A. Townsend, and S.P. Loheide. 2016. Urban heat island impacts on plant phenology: intra-urban variability and response to land cover. Environmental Research Letters. 11(5):054023. https://doi.org/10.1088/1748-9326/11/5/054023
2015 Camarero, J., M. Franquesa, and G. Sanguesa-Barreda. 2015. Timing of Drought Triggers Distinct Growth Responses in Holm Oak: Implications to Predict Warming-Induced Forest Defoliation and Growth Decline. Forests. 6(12):1576-1597. https://doi.org/10.3390/f6051576
2015 Dihkan, M., F. Karsli, A. Guneroglu, and N. Guneroglu. 2015. Evaluation of surface urban heat island (SUHI) effect on coastal zone: The case of Istanbul Megacity. Ocean & Coastal Management. 118:309-316. https://doi.org/10.1016/j.ocecoaman.2015.03.008
2015 Gartner, P. and B. Kleinschmit. 2015. Monitoring forest recovery with change metrics derived from Landsat time series stacks. 1-3. https://doi.org/10.1109/Multi-Temp.2015.7245807
2015 Gebhardt, S., P. Maeda, T. Wehrmann, J. Argumedo Espinoza, and M. Schmidt. 2015. A proper Land Cover and Forest Type Classification Scheme for Mexico. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XL-7/W3:383-390. https://doi.org/10.5194/isprsarchives-XL-7-W3-383-2015
2015 Guneroglu, A. 2015. Coastal changes and land use alteration on Northeastern part of Turkey. Ocean & Coastal Management. 118:225-233. https://doi.org/10.1016/j.ocecoaman.2015.06.019
2013 Laurent, O., J. Wu, L. Li, and C. Milesi. 2013. Green spaces and pregnancy outcomes in Southern California. Health & Place. 24:190-195. https://doi.org/10.1016/j.healthplace.2013.09.016
2013 Wilson C.R. (2013) Evaluating Satellite-Observed Changes in Impervious Surface Cover in Relation to Economic Changes and Spatially Variable Socioeconomic Conditions in Census Data in Southeastern Michigan. University of Michigan, Department of Natural Resources and Environment.