scholarly journals Heat Capacity Mapping Mission (HCMM) thermal surface water mapping and its correlation to Landsat

1980 ◽  
Author(s):  
Alden P. Colvocoresses
Keyword(s):  
Heat Capacity ◽  
Surface Water ◽  
Water Mapping

Analysis of Landsat-8 OLI imagery for land surface water mapping

2014 ◽  
Vol 5 (7) ◽  
pp. 672-681 ◽  
Author(s):  
Zhiqiang Du ◽  
Wenbo Li ◽  
Dongbo Zhou ◽  
Liqiao Tian ◽  
Feng Ling ◽  
...  
Keyword(s):  
Surface Water ◽  
Land Surface ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Land Surface Water ◽  
Water Mapping

scholarly journals Two-Step Urban Water Index (TSUWI): A New Technique for High-Resolution Mapping of Urban Surface Water

2018 ◽  
Vol 10 (11) ◽  
pp. 1704 ◽  
Author(s):  
Wei Wu ◽  
Qiangzi Li ◽  
Yuan Zhang ◽  
Xin Du ◽  
Hongyan Wang
Keyword(s):  
Surface Water ◽  
High Resolution ◽  
Urban Surface ◽  
Mapping Technique ◽  
Support Vector ◽  
Svm Classifier ◽  
P Value ◽  
Urban Water ◽  
Water Index ◽  
Water Mapping

Urban surface water mapping is essential for studying its role in urban ecosystems and local microclimates. However, fast and accurate extraction of urban water remains a great challenge due to the limitations of conventional water indexes and the presence of shadows. Therefore, we proposed a new urban water mapping technique named the Two-Step Urban Water Index (TSUWI), which combines an Urban Water Index (UWI) and an Urban Shadow Index (USI). These two subindexes were established based on spectral analysis and linear Support Vector Machine (SVM) training of pure pixels from eight training sites across China. The performance of the TSUWI was compared with that of the Normalized Difference Water Index (NDWI), High Resolution Water Index (HRWI) and SVM classifier at twelve test sites. The results showed that this method consistently achieved good performance with a mean Kappa Coefficient (KC) of 0.97 and a mean total error (TE) of 2.28%. Overall, classification accuracy of TSUWI was significantly higher than that of the NDWI, HRWI, and SVM (p-value < 0.01). At most test sites, TSUWI improved accuracy by decreasing the TEs by more than 45% compared to NDWI and HRWI, and by more than 15% compared to SVM. In addition, both UWI and USI were shown to have more stable optimal thresholds that are close to 0 and maintain better performance near their optimum thresholds. Therefore, TSUWI can be used as a simple yet robust method for urban water mapping with high accuracy.

scholarly journals A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

2017 ◽  
Vol 6 (5) ◽  
pp. 140 ◽  
Author(s):  
Chang Huang ◽  
Ba Duy Nguyen ◽  
Shiqiang Zhang ◽  
Senmao Cao ◽  
Wolfgang Wagner
Keyword(s):  
Surface Water ◽  
Water Mapping ◽  
Terrain Indices

scholarly journals Automated Subpixel Surface Water Mapping from Heterogeneous Urban Environments Using Landsat 8 OLI Imagery

2016 ◽  
Vol 8 (7) ◽  
pp. 584 ◽  
Author(s):  
Huan Xie ◽  
Xin Luo ◽  
Xiong Xu ◽  
Haiyan Pan ◽  
Xiaohua Tong
Keyword(s):  
Surface Water ◽  
Urban Environments ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Water Mapping

Heat Capacity Studies of Surface Water Confined on Cassiterite (SnO2) Nanoparticles

2012 ◽  
Vol 116 (6) ◽  
pp. 3910-3917 ◽  
Author(s):  
Quan Shi ◽  
Juliana Boerio-Goates ◽  
Kellie Woodfield ◽  
Mckay Rytting ◽  
Katie Pulsipher ◽  
...  
Keyword(s):  
Heat Capacity ◽  
Surface Water ◽  
Sno2 Nanoparticles

scholarly journals Surface Water Mapping from Suomi NPP-VIIRS Imagery at 30 m Resolution via Blending with Landsat Data

2016 ◽  
Vol 8 (8) ◽  
pp. 631 ◽  
Author(s):  
Chang Huang ◽  
Yun Chen ◽  
Shiqiang Zhang ◽  
Linyi Li ◽  
Kaifang Shi ◽  
...  
Keyword(s):  
Surface Water ◽  
Landsat Data ◽  
Water Mapping

scholarly journals Surface Water Mapping by Deep Learning

2017 ◽  
Vol 10 (11) ◽  
pp. 4909-4918 ◽  
Author(s):  
Furkan Isikdogan ◽  
Alan C. Bovik ◽  
Paola Passalacqua
Keyword(s):  
Deep Learning ◽  
Surface Water ◽  
Water Mapping

scholarly journals A Comparison of Land Surface Water Mapping Using the Normalized Difference Water Index from TM, ETM+ and ALI

2013 ◽  
Vol 5 (11) ◽  
pp. 5530-5549 ◽  
Author(s):  
Wenbo Li ◽  
Zhiqiang Du ◽  
Feng Ling ◽  
Dongbo Zhou ◽  
Hailei Wang ◽  
...  
Keyword(s):  
Surface Water ◽  
Land Surface ◽  
Water Index ◽  
Land Surface Water ◽  
Normalized Difference Water Index ◽  
Water Mapping

scholarly journals On the merging of optical and SAR satellite imagery for surface water mapping applications

2018 ◽  
Vol 9 ◽  
pp. 275-277 ◽  
Author(s):  
Kel N. Markert ◽  
Farrukh Chishtie ◽  
Eric R. Anderson ◽  
David Saah ◽  
Robert E. Griffin
Keyword(s):  
Surface Water ◽  
Satellite Imagery ◽  
Water Mapping
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