nach oben

Earth Science Informatics

Erschienen in:

04.11.2021 | Research Article

Accuracy evaluation and improvement of common DEM in Hubei Region based on ICESat/GLAS data

verfasst von: Mengjie Hu, Shen Ji

Erschienen in: Earth Science Informatics | Ausgabe 1/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Based on Geoscience Laser Altimeter System onboard the Ice, Cloud, and land Elevation Satellite (ICESat/GLAS) data, this paper analyzes the vertical accuracy of four kinds of digital elevation model (DEM)dataset in Hubei Province, and discusses the influence of the geographical factors (slope, aspect, geomorphic and land-use types) on DEM data accuracy. The results show that: (1) Among the four kinds of DEM data in Hubei Province, the ALOS World 3D -30 m (AW3D30) offers the highest data accuracy; (2) High slope and vegetation coverage will affect DEM data accuracy, and AW3D30 data accuracy is the least affected by this; (3) No obvious relationship has been found between data accuracy and aspect. In addition, using ICESat/GLAS data as reference, this paper also attempts to improve the vertical accuracy of DEM by employing five machine learning based methods, the results show that each DEM dataset obviously outperform themselves by using the models selected in this paper.

Vorheriger Artikel Identifying the spatial distribution of Prosopis Juliflora using Hyperion imagery

Nächster Artikel Integration of satellite geodetic observations for regional geoid modeling using remove-compute-restore technique

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Abshire JB, Sun XL, Riris H, Sirota JM, McGarry JF, Palm S, Yi DH, Liiva P (2005) Geoscience Laser Altimeter System (GLAS) on the ICESat Mission: On-orbit measurement performance. Geophys Res Lett 32(21). https://doi.org/10.1029/2005GL024028

Bao LL, Qin CZ, Zhu AX, Hu XM (2012) Effect of DEM error on landslide susceptibility mapping models. Prog Geogr 31(10):1326–1333

Bu XQ, Yue P (2016) A scientific workflow approach for hydrologic analysis from digital elevation model. 2016 Fifth International Conference on Agro-geoinformatics. Tianjin, China, 1-5. https://doi.org/10.1109/Agro-Geoinformatics.2016.7577708

Carabajal CC, Harding DJ (2005) ICESat validation of SRTM C-band digital elevation models. Geophys Res Lett 32(22). https://doi.org/10.1029/2005GL023957

Chen CF, Yang SI, Li YY (2020) Accuracy assessment and correction of SRTM DEM Using ICESat/GLAS data under data coregistration. Remote Sens 12(20):3435–3435. https://doi.org/10.3390/rs12203435

Du XP, Guo HD, Fan XT, Zhu JJ, Yan ZZ, Zhan Q (2013) Vertical accuracy assessment of SRTM and ASTER GDEM over typical regions of China using ICESat/GLAS. Earth Sci-J China Univ Geosci 38(4):887–897. https://doi.org/10.3799/dqkx.2013.087CrossRef

Gao ZY, Xie YL, Wang NL, Jiang GX, Zhou P (2019) Response of three global DEM accuracy to different terrain factors in Tibetan Plateau. Bull Soil Water Conserv 39(2):184–191. https://doi.org/10.13961/j.cnki.stbctb.2019.02.030CrossRef

Jafarzadegan K, Merwade V (2017) A DEM-based approach for large-scale floodplain mapping in ungauged watersheds. J Hydrol 550:650–662. https://doi.org/10.1016/j.jhydrol.2017.04.053CrossRef

Jia DX, Tang GA, Wang C, Jia YN (2009) Slope accuracy associated with DEM data error and terrain representation error. J Geo-Inf Sci 11(01):43–49

Jiang GX, Xie YL, Gao ZY, Zhou P (2020) Evaluation on elevation accuracy of commonly used DEM in five typical areas of China. Res Soil Water Conserv 27(05):72–80. https://doi.org/10.13869/j.cnki.rswc.2020.05.011CrossRef

Khromova TE, Dyurgerov MB, Barry RG (2003) Late-twentieth century changes in glacier extent in the Ak-shirak Range, Central Asia, determined from historical data and ASTER imagery. Geophys Res Lett 30(16):1863. https://doi.org/10.1029/2003GL017233CrossRef

Kim DE, Liu J, Liong SY, Gourbesville P, Strunz G (2021) Satellite DEM improvement using multispectral imagery and an artificial neural network. Water 13(11):1551. https://doi.org/10.3390/W13111551CrossRef

Lee H, Hahn M (2020) Point-to-surface matching for dem correction using ICESat data. ISPRS - Int Arch Photogramm Remote Sens Spat Inf Sci XLIII-B4-2020:715–720. https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-715-2020

Shen HF, Liu L, Yue LW, Li XY, Zhang LP (2018) A multi-source DEM fusion method based on elevation difference fitting neural network. Acta Geodaetica Cartogr Sin 47(6):854–863

Su X, Wei WH, Guo WQ, Wang SY, Wang GY, Wu WJ, Ye WL (2017) Analyzing the impact of relief amplitude to loess landslides based on SRTM DEM in Tianshui Prefecture. J Glaciol Geocryol 39(03):616–622

Toutin T (2008) ASTER DEMs for geomatic and geoscientific applications: a review. Int J Remote Sens 29(7):1855–1875. https://doi.org/10.1080/01431160701408477CrossRef

Wang WF, Jiao XH, Li GC (2018) The influence of DEM resolution on the evaluation results of soil erosion in Daxinganling forest area. J Northeast For Univ 46(04):23–28. https://doi.org/10.13759/j.cnki.dlxb.2018.04.005CrossRef

Yu HY, Luo L, Ma HH, Li H (2017) Application appraisal in catchment hydrological analysis based on SRTM 1 Arc-Second DEM. Remote Sens Land Resour 29(2):138–143. https://doi.org/10.6046/gtzyyg.2017.02.20CrossRef

Yu YM, Mu ZX (2016) Influence of DEM resolution on runoff simulation accuracy of Kashi River Basin. Water Resour Power 34(03):19–23

Zhang Q, Yang QK, Wang CM (2016) SRTM error distribution and its associations with landscapes across China. Photogramm Eng Remote Sens 82(2):135–148. https://doi.org/10.14358/PERS.83.2.135CrossRef

Zheng TT, Chen CF, Liu HT (2020) A slope-based weighting method for fusing SRTM and ASTER. Bull Survey Map (4):121–124. https://doi.org/10.13474/j.cnki.11-2246.2020.0124

Titel: Accuracy evaluation and improvement of common DEM in Hubei Region based on ICESat/GLAS data
verfasst von: Mengjie Hu
Shen Ji
Publikationsdatum: 04.11.2021
Verlag: Springer Berlin Heidelberg
Erschienen in: Earth Science Informatics / Ausgabe 1/2022
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-021-00721-3

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2022

Using remote sensing data for geological mapping in semi-arid environment: a machine learning approach

Real time deep learning framework to monitor social distancing using improved single shot detector based on overhead position

Capability of an Elman Recurrent Neural Network for predicting the non-linear behavior of airborne pollutants

Framework for developing IDF curves using satellite precipitation: a case study using GPM-IMERG V6 data

A comparative study of the cost–benefit strategy with the learning ensembles of decision stumps in polymetallic prospectivity modelling

Evaluating quality of surface water resources by ANN and ANFIS networks using Sentinel-2 satellite data

Premium Partner