Manual-Based Improvement Method for the ASTER Global Water Body Data Base

A water body detection technique is an essential part of digital elevation model (DEM) generation to delineate land–water boundaries and to set flattened elevations. The initial tile-based water body data that are created during production of the Advanced Spaceborne Thermal Emission and Reflection r...

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Published in:Remote Sensing
Main Authors: Hiroyuki Fujisada, Minoru Urai, Akira Iwasaki
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/rs12203373
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/20/3373/ 2023-08-20T04:09:47+02:00 Manual-Based Improvement Method for the ASTER Global Water Body Data Base Hiroyuki Fujisada Minoru Urai Akira Iwasaki 2020-10-15 application/pdf https://doi.org/10.3390/rs12203373 EN eng Multidisciplinary Digital Publishing Institute Earth Observation Data https://dx.doi.org/10.3390/rs12203373 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 20; Pages: 3373 ASTER optical sensor digital elevation model global data base water body data base Text 2020 ftmdpi https://doi.org/10.3390/rs12203373 2023-08-01T00:16:54Z A water body detection technique is an essential part of digital elevation model (DEM) generation to delineate land–water boundaries and to set flattened elevations. The initial tile-based water body data that are created during production of the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) GDEM, as a by-product, are incorporated into ASTER GDEM V3 to improve the quality. At the same time as ASTER GDEM V3, the Global Water Body Data Base (ASTWBD) Version 1 is also released to the public. The ASTWBD generation consists of two parts: separation from land area, and classification into three categories: sea, lake, and river. Sea water bodies have zero elevation. Lake water bodies have flattened elevations. River water bodies have a gradual step-down from upstream to downstream with a step of one meter. The separation process from land area is carried out automatically using an algorithm, except for sea-ice removal, to delineate the real seashore lines in the high latitude areas; almost all of the water bodies are created through this process. The classification process into three categories, i.e., sea, river, and lake, is carried out, and incorporated into ASTER GDEM V3. For inland water bodies, it is not possible to perfectly detect all water bodies using reflectance and spectral index, which are the only available parameters for optical sensors. The only way available to identify the undetected inland water bodies is to manually copy them with visual inspection from the earth’s surface images, like Landsat images. GeoCover2000 images are the main part of the object images. Color–Land ASTER MosaicS (CLAMS) images are used to cover the deficiency of the GeoCover2000 images. This kind of time-consuming, unsophisticated way is inevitable as it is a manual-based method to improve the quality of the ASTWBD. This paper describes the manual-based improvement method; specifically, how deficient water body images are efficiently copied as rasterized images from the earth’s surface images to obtain ... Text Sea ice MDPI Open Access Publishing Remote Sensing 12 20 3373
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic ASTER
optical sensor
digital elevation model
global data base
water body data base
spellingShingle ASTER
optical sensor
digital elevation model
global data base
water body data base
Hiroyuki Fujisada
Minoru Urai
Akira Iwasaki
Manual-Based Improvement Method for the ASTER Global Water Body Data Base
topic_facet ASTER
optical sensor
digital elevation model
global data base
water body data base
description A water body detection technique is an essential part of digital elevation model (DEM) generation to delineate land–water boundaries and to set flattened elevations. The initial tile-based water body data that are created during production of the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) GDEM, as a by-product, are incorporated into ASTER GDEM V3 to improve the quality. At the same time as ASTER GDEM V3, the Global Water Body Data Base (ASTWBD) Version 1 is also released to the public. The ASTWBD generation consists of two parts: separation from land area, and classification into three categories: sea, lake, and river. Sea water bodies have zero elevation. Lake water bodies have flattened elevations. River water bodies have a gradual step-down from upstream to downstream with a step of one meter. The separation process from land area is carried out automatically using an algorithm, except for sea-ice removal, to delineate the real seashore lines in the high latitude areas; almost all of the water bodies are created through this process. The classification process into three categories, i.e., sea, river, and lake, is carried out, and incorporated into ASTER GDEM V3. For inland water bodies, it is not possible to perfectly detect all water bodies using reflectance and spectral index, which are the only available parameters for optical sensors. The only way available to identify the undetected inland water bodies is to manually copy them with visual inspection from the earth’s surface images, like Landsat images. GeoCover2000 images are the main part of the object images. Color–Land ASTER MosaicS (CLAMS) images are used to cover the deficiency of the GeoCover2000 images. This kind of time-consuming, unsophisticated way is inevitable as it is a manual-based method to improve the quality of the ASTWBD. This paper describes the manual-based improvement method; specifically, how deficient water body images are efficiently copied as rasterized images from the earth’s surface images to obtain ...
format Text
author Hiroyuki Fujisada
Minoru Urai
Akira Iwasaki
author_facet Hiroyuki Fujisada
Minoru Urai
Akira Iwasaki
author_sort Hiroyuki Fujisada
title Manual-Based Improvement Method for the ASTER Global Water Body Data Base
title_short Manual-Based Improvement Method for the ASTER Global Water Body Data Base
title_full Manual-Based Improvement Method for the ASTER Global Water Body Data Base
title_fullStr Manual-Based Improvement Method for the ASTER Global Water Body Data Base
title_full_unstemmed Manual-Based Improvement Method for the ASTER Global Water Body Data Base
title_sort manual-based improvement method for the aster global water body data base
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12203373
genre Sea ice
genre_facet Sea ice
op_source Remote Sensing; Volume 12; Issue 20; Pages: 3373
op_relation Earth Observation Data
https://dx.doi.org/10.3390/rs12203373
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12203373
container_title Remote Sensing
container_volume 12
container_issue 20
container_start_page 3373
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