Analysis of optimal thresholds for identification of open water using MODIS-derived spectral indices for two coastal wetland systems in Mexico
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René R. Colditz | Rainer Ressl | Carlos Troche Souza | Berenice Vazquez | Albertus J. Wickel | R. Colditz | R. Ressl | A. J. Wickel | Berenice Vazquez | Carlos Souza
[1] S. K. McFeeters. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .
[2] Robert E. Wolfe,et al. A Landsat surface reflectance dataset for North America, 1990-2000 , 2006, IEEE Geoscience and Remote Sensing Letters.
[3] B. Wylie,et al. Analysis of Dynamic Thresholds for the Normalized Difference Water Index , 2009 .
[4] W. Cohen,et al. MODIS tasselled cap: land cover characteristics expressed through transformed MODIS data , 2007 .
[5] A. Huete,et al. A Modified Soil Adjusted Vegetation Index , 1994 .
[6] René R. Colditz,et al. Detecting Change Areas in Mexico Between 2005 and 2010 Using 250 m MODIS Images , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[7] ByoungChul Ko,et al. Classification of Potential Water Bodies Using Landsat 8 OLI and a Combination of Two Boosted Random Forest Classifiers , 2015, Sensors.
[8] Alan H. Strahler,et al. MODIS tasseled cap transformation and its utility , 2002, IEEE International Geoscience and Remote Sensing Symposium.
[9] C. J. Tucker,et al. A comparison of satellite sensor bands for vegetation monitoring , 1978 .
[10] Guy Byrne,et al. MODIS-based standing water detection for flood and large reservoir mapping: Algorithm development and applications for the Australian continent , 2011 .
[11] A. Huete. A soil-adjusted vegetation index (SAVI) , 1988 .
[12] Claudia Kuenzer,et al. Detection of inland water bodies with high temporal resolution - assessing dynamic threshold approaches , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[13] A. Huete,et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .
[14] S. Sader,et al. Detection of forest harvest type using multiple dates of Landsat TM imagery , 2002 .
[15] S. Flasse,et al. Analysis of the conflict between omission and commission in low spatial resolution dichotomic thematic products: The Pareto Boundary , 2004 .
[16] Pierre Defourny,et al. Where can pixel counting area estimates meet user-defined accuracy requirements? , 2017, Int. J. Appl. Earth Obs. Geoinformation.
[17] C. Ticehurst,et al. An Evaluation of MODIS Daily and 8-day Composite Products for Floodplain and Wetland Inundation Mapping , 2013, Wetlands.
[18] C. Verpoorter,et al. A global inventory of lakes based on high‐resolution satellite imagery , 2014 .
[19] Mark A. Trigg,et al. Development of a global ~90m water body map using multi-temporal Landsat images , 2015, Remote Sensing of Environment.
[20] Yun Chen,et al. The Strengths and Limitations in Using the Daily MODIS Open Water Likelihood Algorithm for Identifying Flood Events , 2014, Remote. Sens..
[21] J. Gallant,et al. A multiresolution index of valley bottom flatness for mapping depositional areas , 2003 .
[22] Tom Fawcett,et al. An introduction to ROC analysis , 2006, Pattern Recognit. Lett..
[23] Min Feng,et al. A global, high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm , 2016, Int. J. Digit. Earth.
[24] Rainer Ressl,et al. Potential effects in multi-resolution post-classification change detection , 2012 .
[25] René R. Colditz,et al. Flood delineation in a large and complex alluvial valley, lower Pánuco basin, Mexico , 2003 .
[26] Hanqiu Xu. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .
[27] A. K. Lohani,et al. Delineation of Flood-Prone Areas Using Remote Sensing Techniques , 2005 .
[28] N. C. Strugnell,et al. First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .
[29] S. Wofsy,et al. Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data , 2004 .
[30] Hannes Taubenböck,et al. How good is the map? A multi-scale cross-comparison framework for global settlement layers: Evidence from Central Europe , 2016 .
[31] C. Verpoorter,et al. Automated mapping of water bodies using Landsat multispectral data , 2012 .
[32] Zhiqi Yang,et al. Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors , 2017 .
[33] J. Pekel,et al. High-resolution mapping of global surface water and its long-term changes , 2016, Nature.
[34] P. Döll,et al. Development and validation of a global database of lakes, reservoirs and wetlands , 2004 .
[35] Tong Xiao,et al. An Automated Method for Extracting Rivers and Lakes from Landsat Imagery , 2014, Remote. Sens..
[36] J. Ryu,et al. Waterline extraction from Landsat TM data in a tidal flat: a case study in Gomso Bay, Korea , 2002 .
[37] B. Gao. NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .
[38] Ali Selamat,et al. Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery , 2014, Remote. Sens..
[39] J. Downing,et al. The global abundance and size distribution of lakes, ponds, and impoundments , 2006 .