Manual-Based Improvement Method for the ASTER Global Water Body Data Base
"> Figure 1
<p>Typical examples of GeoCover and CLAMS images to grasp the feature for water bodies. The corresponding water body are shown as green density slice images. Tile size: 1° latitude by 1° longitude: (<b>a</b>) Images of the N61W100 tiles; (<b>b</b>) Images of the N63W106 tiles; (<b>c</b>) Images of the N69E158 tiles; (<b>d</b>) Images of the N74E107 tile.</p> "> Figure 2
<p>The improvement process of undetected water body areas using a GeoCover image as the reference: (<b>a</b>) original GeoCover image; (<b>b</b>) undetected water body areas filled with green on original the GeoCover image; (<b>c</b>) original GWBD image; (<b>d</b>) improved GWBD image. The GWBD images are shown as green density slice images.</p> "> Figure 3
<p>The improvement process of undetected water body areas using a CLAMS image as the reference: (<b>a</b>) original CLAMS image; (<b>b</b>) undetected water body areas filled with green on the original CLAMS image; (<b>c</b>) original GWBD image; (<b>d</b>) improved GWBD image. The GWBD images are shown as green density slice images.</p> "> Figure 4
<p>Four typical examples of improvement using GeoCover images (<b>a</b>,<b>b</b>) or CLAMS images (<b>c</b>,<b>d</b>). For each example, the lower and the upper images show the entire tile images and partially expanded sub-area images with 600 by 400 pixels, respectively. The expanded sub-area in each entire tile image is shown by the rectangular red line. Tile size: 1° latitude by 1° longitude: (<b>a</b>) Images of the N60W076 tiles; (<b>b</b>) Images of the N71E127 tiles; (<b>c</b>) Images of the N71E143 tiles; (<b>d</b>) Images of the N72E141 tiles.</p> "> Figure 4 Cont.
<p>Four typical examples of improvement using GeoCover images (<b>a</b>,<b>b</b>) or CLAMS images (<b>c</b>,<b>d</b>). For each example, the lower and the upper images show the entire tile images and partially expanded sub-area images with 600 by 400 pixels, respectively. The expanded sub-area in each entire tile image is shown by the rectangular red line. Tile size: 1° latitude by 1° longitude: (<b>a</b>) Images of the N60W076 tiles; (<b>b</b>) Images of the N71E127 tiles; (<b>c</b>) Images of the N71E143 tiles; (<b>d</b>) Images of the N72E141 tiles.</p> "> Figure 5
<p>Effect of improved GWBD to the corresponding GDEM. The two upper images are the original and improved shaded-relief GDEM images. The two lower images are the corresponding original and improved color density slice images. The green color denotes a lake water body, and the red color denotes a river water body: (<b>a</b>) a part of N60W076 tile images; (<b>b</b>) a part of N71E127 tile images; (<b>c</b>) a part of N71E143 tile images; (<b>d</b>) a part of N71E141 tile images.</p> "> Figure 5 Cont.
<p>Effect of improved GWBD to the corresponding GDEM. The two upper images are the original and improved shaded-relief GDEM images. The two lower images are the corresponding original and improved color density slice images. The green color denotes a lake water body, and the red color denotes a river water body: (<b>a</b>) a part of N60W076 tile images; (<b>b</b>) a part of N71E127 tile images; (<b>c</b>) a part of N71E143 tile images; (<b>d</b>) a part of N71E141 tile images.</p> "> Figure 6
<p>Global color density slice images of the improvement effect for the inland water body occupancy ratios. Large yellow-color areas denote sea areas. An inland water body means a lake or river: (<b>a</b>) Original occupancy ratio image; (<b>b</b>) Improved occupancy ratio image; (<b>c</b>) Increased occupancy ratio image.</p> "> Figure 6 Cont.
<p>Global color density slice images of the improvement effect for the inland water body occupancy ratios. Large yellow-color areas denote sea areas. An inland water body means a lake or river: (<b>a</b>) Original occupancy ratio image; (<b>b</b>) Improved occupancy ratio image; (<b>c</b>) Increased occupancy ratio image.</p> ">
Abstract
:1. Introduction
2. Improvement by GeoCover or CLAMS Images
2.1. Features of the GeoCover and CLAMS Images
2.2. How the Improved ASTWBD Was Created
- (1)
- (2)
- The undetected water body areas are filled in green on the GeoCover image as shown in Figure 2b using the support tool “ROI”. The green color areas correspond to the undetected areas.
- (3)
- The undetected areas on the GeoCover image are imported to the GWBD image and saved as a GeoTIFF file using the support tool “Masking” function.
- (4)
- The final improved GWBD image is shown in Figure 2d.
2.3. Typical Examples of Improvements
3. Discussion
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Fujisada, H.; Sakuma, F.; Ono, A.; Kudos, M. Design and preflight performance of ASTER instrument protoflight model. IEEE Trans. Geosci. Remote Sens. 1999, 36, 1152–1160. [Google Scholar] [CrossRef]
- Fujisada, H. ASTER Level-1 data processing algorithm. IEEE Trans. Geosci. Remote Sens. 1998, 36, 1101–1112. [Google Scholar] [CrossRef]
- Fujisada, H.; Bailey, G.B.; Kelly, G.G.; Hara, S.; Abrams, M.J. ASTER DEM performance. IEEE Trans. Geosci. Remote Sens. 2005, 43, 2707–2714. [Google Scholar] [CrossRef]
- Fujisada, H.; Iwasaki, A.; Hara, S. ASTER stereo system performance. Proc. SPIE 2001, 4540, 39–49. [Google Scholar]
- Fujisada, H.; Urai, M.; Iwasaki, A. Advanced methodology for ASTER DEM generation. IEEE Trans. Geosci. Remote Sens. 2011, 49, 5080–5091. [Google Scholar] [CrossRef]
- Fujisada, H.; Urai, M.; Iwasaki, A. Technical methodology for ASTER Global Water Body Data Base. Remote Sens. 2018, 10, 1860. [Google Scholar] [CrossRef] [Green Version]
- GeoCover. Available online: http://www.cr.chiba-u.jp/databases/GeoCover/TM_mosaic.html (accessed on 10 October 2020).
- Gonzalez, L.; Valerie, V.; Yamamoto, H. Global 15-Meter Mosaic from Simulated True-Color ASTER Imagery. Remote Sens. 2019, 11, 441. [Google Scholar] [CrossRef] [Green Version]
- Nelson, G.C.; Robertson, R.D. Comparing the GLC2000 and GeoCover LC land cover datasets for use in economic modelling of land use. Int. J. Remote Sens. 2007, 28, 4243–4266. [Google Scholar] [CrossRef]
- Rajagopalan, R.; Aparajithan, S.; James, S.; Michael, C. Validation of Geometric Accuracy of Global Land Survey (GLS) 2000 Data. Photogrametric Eng. Remote Sens. 2015, 81, 131–141. [Google Scholar]
- NASA JPL. NASA Shuttle Radar Topography Mission Water Body Data Shapefiles & Raster Files; NASA EOSDISL and Processes DAAC: Sioux Falls, SD, USA, 2013. [Google Scholar]
- Abrams, M.; Crippen, R.; Fujisada, H. ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD). Remote Sens. 2020, 12, 1156. [Google Scholar] [CrossRef] [Green Version]
Tile Name | Type of Images | Sea Occupancy (%) | River Occupancy (%) | Lake Occupancy (%) |
---|---|---|---|---|
N60W076 | Original image | 0 | 0 | 6.56163 |
Improved image | 0 | 0 | 18.36819 | |
N71E127 | Original image | 0 | 8.55893 | 2.52542 |
Improved image | 0 | 8.81181 | 0.60127 | |
N71E143 | Original image | 0 | 0 | 4.83586 |
Improved image | 0 | 0 | 14.03497 | |
N72E141 | Original image | 22.28395 | 0 | 0.38985 |
Improved image | 22.28395 | 0 | 6.48122 |
Tile Name | Location | Ratio (%) | Tile Name | Location | Ratio (%) | Tile Name | Location | Ratio (%) |
---|---|---|---|---|---|---|---|---|
N60E007 | Norway | 5.25127 | N64W095 | Canada | 6.79022 | N68W097 | Canada | 9.95321 |
N61W098 | Canada | 5.28094 | N68E145 | Russia | 6.81613 | N71W109 | Canada | 10.13983 |
N71E141 | Russia | 5.33550 | N65W097 | Canada | 6.87522 | N69W105 | Canada | 10.19871 |
N72E097 | Russia | 5.39406 | N70W112 | Canada | 6.91013 | N61W164 | USA (Alaska) | 10.24639 |
N60W100 | Canada | 5.40833 | N71W111 | Canada | 6.91214 | N70W111 | Canada | 10.55154 |
N75E112 | Russia | 5.41753 | N69W125 | Canada | 6.92857 | N65W114 | Canada | 10.56258 |
N72E142 | Russia | 5.45569 | N63W099 | Canada | 7.04038 | N66W098 | Canada | 10.64937 |
N71E080 | Russia | 5.46514 | N68W090 | Canada | 7.06019 | N70W157 | USA (Alaska) | 10.67472 |
N66W105 | Canada | 5.50322 | N71E140 | Russia | 7.16263 | N63W106 | Canada | 10.79045 |
N70E078 | Russia | 5.52684 | N64W098 | Canada | 7.19305 | N70W154 | USA (Alaska) | 10.94286 |
N69W098 | Canada | 5.54657 | N61W165 | USA (Alaska) | 7.28413 | N64W114 | Canada | 10.95453 |
N67W115 | Canada | 5.56222 | N62W108 | Canada | 7.32367 | N63W097 | Canada | 11.10577 |
N72W108 | Canada | 5.59931 | N63W118 | Canada | 7.38103 | N60W164 | USA (Alaska) | 11.20842 |
N60W074 | Canada | 5.62596 | N61W099 | Canada | 7.43363 | N70E158 | USA (Alaska) | 11.25973 |
N63W095 | Canada | 5.63278 | N67W126 | Canada | 7.62890 | N62W102 | Canada | 11.31035 |
N60W165 | Russia | 5.63698 | N64W115 | Canada | 7.73903 | N62W101 | Canada | 11.33130 |
N65W105 | Canada | 5.65309 | N71E096 | Russia | 7.76664 | N62W096 | Canada | 11.36850 |
N61E008 | Norway | 5.67248 | N63W110 | Canada | 7.83731 | N64W108 | N64W108 | 11.47643 |
N69W104 | Canada | 5.71586 | N62W109 | Canada | 7.95232 | N64W117 | N64W117 | 11.49349 |
N69E124 | Russia | 5.76290 | N70W105 | Canada | 7.97608 | N68E154 | N68E154 | 11.64781 |
N65W108 | Canada | 5.85980 | N62W104 | Canada | 8.03119 | N60W076 | N60W076 | 11.80715 |
N70E079 | Russia | 5.87961 | N69E156 | Russia | 8.08248 | N70W156 | N70W156 | 12.06289 |
N71E095 | Russia | 5.94174 | N70E159 | Russia | 8.08720 | N65W099 | N65W099 | 12.13787 |
N61W075 | Canada | 5.94803 | N68W128 | Canada | 8.10427 | N69W113 | N69W113 | 12.33947 |
N64W093 | Canada | 5.94889 | N63W096 | Canada | 8.13296 | N65W116 | N65W116 | 12.63866 |
N70W106 | Canada | 5.95411 | N61W096 | Canada | 8.14558 | N63W109 | N63W109 | 12.69144 |
N70W088 | Canada | 6.00687 | N65W115 | Canada | 8.22398 | N65W113 | N65W113 | 12.88074 |
N70E150 | Russia | 6.02750 | N64W113 | Canada | 8.25485 | N65W117 | N65W117 | 13.15168 |
N72E141 | Russia | 6.09137 | N67W105 | Canada | 8.51486 | N66W104 | N66W104 | 13.47813 |
N63W094 | Canada | 6.09459 | N69E155 | Russia | 8.53566 | N72W107 | N72W107 | 13.65664 |
N70E153 | Russia | 6.18505 | N72W106 | Canada | 8.75356 | N61W111 | N61W111 | 14.22826 |
N61W139 | Canada | 6.22052 | N70W110 | Canada | 8.80408 | N61W101 | N61W101 | 14.36880 |
N64E029 | Finland | 6.25783 | N68E071 | Russia | 8.83583 | N62W095 | N62W095 | 14.62151 |
N65W104 | Canada | 6.27058 | N68W133 | Canada | 8.96451 | N61W104 | Canada | 14.89520 |
N71W110 | Canada | 6.35164 | N67W107 | Canada | 8.98649 | N69W112 | Canada | 15.19103 |
N64W096 | Canada | 6.41225 | N70W155 | USA (Alaska) | 9.00188 | N64W118 | Canada | 15.41963 |
N61W095 | Canada | 6.44154 | N68E155 | Russia | 9.02434 | N62W100 | Canada | 15.48538 |
N67W102 | Canada | 6.48683 | N70W153 | USA (Alaska) | 9.09714 | N65W100 | Canada | 15.50255 |
N63W101 | Canada | 6.52677 | N67W104 | Canada | 9.14772 | N62W103 | Canada | 15.55613 |
N69W111 | Canada | 6.57954 | N68E070 | Russia | 9.19645 | N66W103 | Canada | 16.04481 |
N70W113 | Canada | 6.58299 | N71E143 | Russia | 9.19910 | N61W100 | Canada | 16.81194 |
N64W109 | Canada | 6.59901 | N65W111 | Canada | 9.23940 | N61W103 | Canada | 17.00779 |
N67W098 | Canada | 6.65046 | N74E107 | Russia | 9.33596 | N63W107 | Canada | 17.57145 |
N65W098 | Canada | 6.65231 | N69E159 | Russia | 9.40438 | N66W099 | Canada | 17.66327 |
N70W158 | USA (Alaska) | 6.69218 | N69E158 | Russia | 9.52341 | N60W075 | Canada | 18.45545 |
N69E146 | USA (Alaska) | 6.70507 | N64W107 | Canada | 9.61353 | N63W108 | Canada | 18.94309 |
N66W115 | Canada | 6.70820 | N67W106 | Canada | 9.67472 | N62W107 | Canada | 21.11334 |
N65W157 | USA (Alaska) | 6.74008 | N67W103 | Canada | 9.82968 | N75E142 | Russia | 33.45049 |
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Fujisada, H.; Urai, M.; Iwasaki, A. Manual-Based Improvement Method for the ASTER Global Water Body Data Base. Remote Sens. 2020, 12, 3373. https://doi.org/10.3390/rs12203373
Fujisada H, Urai M, Iwasaki A. Manual-Based Improvement Method for the ASTER Global Water Body Data Base. Remote Sensing. 2020; 12(20):3373. https://doi.org/10.3390/rs12203373
Chicago/Turabian StyleFujisada, Hiroyuki, Minoru Urai, and Akira Iwasaki. 2020. "Manual-Based Improvement Method for the ASTER Global Water Body Data Base" Remote Sensing 12, no. 20: 3373. https://doi.org/10.3390/rs12203373