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Article detail · 2005 · article

Digital elevation model DEM generation and accuracy assessment from ASTER stereo data

YÖKSİS OpenAlex SJR Q1 JCR Q2
Year2005
Citations68OpenAlex
Percentile%82.2
FWCI1.671.00 = world average
Scopus (SJR)Q1
WoS (JCR)Q2

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venueInternational Journal of Remote Sensing
  • Catalog match (ISSN)International Journal of Remote Sensing
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex English

Digital elevation models (DEM) are the indispensable quantitative environmental variable in most of the research studies in remote sensing. The improvement of sensor and satellite imaging technologies enabled the researchers to generate DEM using remotely sensed data. These data can be started to use as not only the two-dimensional (2-D) but also three-dimensional (3-D) information sources with usage of the DEM. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of the sensor systems capable of DEM generation and during the study, ASTER level 1A (L1A) data were used. Due to presence of many geological features and different landcover types, the test site is selected as the watershed of Asarsuyu River, located in north-western Anatolia in between Duzce and Bolu plains. The aim of this study is to check the best effort of 15 m spatial resolution DEM generation from ASTER L1A data by collecting different numbers of ground control points (GCP) (30, 45, and 60) and tie points (TP). During the study, three different techniques—spatial correlation, image differencing and profiling—were used for both planimetric and vertical accuracy assessment. The obtained results from both of the techniques show that the accuracy of the DEM increases by increasing the number of GCP. However, there is an only slight difference between the result of 45 GCPs and 60 GCPs.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

68citationsOpenAlex · cited_by_count (cache / database)

8 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. 2014 An evaluation of SVM using polygon based random sampling in landslide susceptibility mapping the Candir catchment area western Antalya TurkeyCitations 105 · OpenAlex
  2. 2018 Comparison of machine-learning techniques for landslide susceptibility mapping using two-level random sampling (2LRS) in Alakir catchment area, Antalya, TurkeyCitations 84 · OpenAlex
  3. 2012 An assessment on the use of Terra ASTER L3A data in landslide susceptibility mappingCitations 56 · OpenAlex
  4. 2012 An assessment on the use of Terra ASTER L3A data in landslide susceptibility mappingCitations 56 · OpenAlex
  5. 2022 Data Integration for Lithological Mapping Using Machine Learning AlgorithmsCitations 29 · OpenAlex
  6. 2023 The effect of DEM resolution on Topographic Wetness Index calculation and visualization: An insight to the hidden danger unraveled in Bozkurt in August, 2021Citations 21 · OpenAlex
  7. 2014 Flooding and Earthquake Risk Interpretation for Kutahya Province Turkey Using ASTER DEMCitations 2 · OpenAlex
  8. 2022 Yükselen ve Alçalan Yörüngeye Ait TerraSAR-X Görüntülerinden Üretilen Sayısal Yükseklik Modellerinin Doğruluk KarşılaştırmasıCitations 0 · OpenAlex

Authors

2
  1. BEKİR TANER SAN 1
  2. MEHMET LÜTFİ SÜZEN ORTA DOĞU TEKNİK ÜNİVERSİTESİ 2