scholarly journals Assessment of open source digital elevation models (SRTM-30, ASTER, ALOS) for erosion processes modeling

2019 ◽  
Vol 28 (1) ◽  
pp. 95-105 ◽  
Author(s):  
I. P. Kovalchuk ◽  
K. A. Lukianchuk ◽  
V. A. Bogdanets
Keyword(s):  
Open Source ◽  
Correlation Coefficient ◽  
Root Mean Square ◽  
Digital Elevation Models ◽  
Mean Square ◽  
Erosion Processes ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Vertical Accuracy ◽  
Mean Square Errors

The relief has a major impact on the landscape`s hydrological, geomorphological and biological processes. Many geographic information systems used elevation data as the primary data for analysis, modeling, etc. A digital elevation model (DEM) is a modern representation of the continuous variations of relief over space in digital form. Digital Elevation Models (DEMs) are important source for prediction of soil erosion parameters. The potential of global open source DEMs (SRTM, ASTER, ALOS) and their suitability for using in modeling of erosion processes are assessed in this study. Shumsky district of Ternopil region, which is located in the Western part of Ukraine, is the area of our study. The soils of Shumsky district are adverselyaffected by erosion processes. The analysis was performed on the basis of the characteristics of the hydrological network and relief. The reference DEM was generated from the hypsographic data(contours) on the 1:50000 topographical map series compiled by production units of the Main Department of Geodesy and Cartography under the Council of Ministers. The differences between the reference DEM and open source DEMs (SRTM, ASTER and ALOS) are examined. Methods of visual detection of DEM defects, profiling, correlation, and statistics were used in the comparative analysis. This research included the analysis oferrors that occurred during the generation of DEM. The vertical accuracy of these DEMs, root mean square error (RMSE), absolute and relative errors, maximum deviation, and correlation coefficient have been calculated. Vertical accuracy of DEMs has been assessed using actual heights of the sample points. The analysis shows that SRTM and ALOS DEMs are more reliable and accurate than ASTER GDEM. The results indicate that vertical accuracy of DEMs is 7,02m, 7,12 m, 7,60 mand 8,71 m for ALOS, SRTM 30, SRTM 90 and ASTER DEMs respectively. ASTER GDEM had the highest absolute, relative and root mean square errors, the highest maximum positive and negative deviation, a large difference with reference heights, and the lowest correlation coefficient. Therefore, ASTER GDEM is the least acceptable for studying the intensity and development of erosion processes. The use of global open source DEMs, compared with the vectorization of topographic maps,greatly simplifies and accelerates the modeling of erosion processes and the assessment of the erosion risk in the administrative district.

scholarly journals Avaliação da Acurácia Vertical dos Modelos Digitais de Elevação SRTM, ALOS World 3D e ASTER GDEM: Um Estudo de Caso no Vale dos Vinhedos, RS – Brasil

2020 ◽  
Vol 13 (5) ◽  
pp. 2255
Author(s):  
Jorge Antônio Viel ◽  
Kátia Kellem da Rosa ◽  
Cláudio Wilson Mendes Junior
Keyword(s):  
Spatial Resolution ◽  
Digital Elevation Models ◽  
Pearson Correlation ◽  
Mean Square ◽  
Class A ◽  
Aster Gdem ◽  
Digital Elevation ◽  
The Mean ◽  
Vertical Accuracy

Este estudo tem como objetivo avaliar a acurácia vertical dos Modelos Digitais de Elevação (MDEs) SRTM v.3, ALOS World 3D e ASTER GDEM v.2 na região da denominação de origem Vale dos Vinhedos, RS. Para tanto, os dados desses MDEs, com resolução espacial de 30 m, foram comparados com os de um MDE fotogramétrico com resolução espacial de 5 m no terreno, por meio de análises de regressão e correlação linear, e de perfis topográficos derivados desses modelos. O Padrão de Exatidão Cartográfica dos Produtos Cartográficos Digitais (PEC-PCD) de cada MDE foi analisado, para identificar a escala máxima de seu uso em estudos morfométricos, nas escalas 1:25.000, 1:50.000 e 1:100.000, por meio de cálculos da Tolerância Vertical e do Erro Médio Quadrático (EMQ). Os MDEs SRTM v.3 e ASTER GDEM v.2 atenderam o PEC-PCD altimétrico classe A na escala 1:100.000. Diferentemente do MDE ALOS World 3D que enquadrou-se na classe B para a escala de 1:100.000. Todos os modelos, na escala 1:50.000, enquadraram-se na classe D, enquanto que na escala 1:25.000 não houve enquadramento. O MDE SRTM v.3 foi o que apresentou melhores resultados morfométricos e o maior coeficiente de correlação de Pearson (r=0,995). Todos os MDEs avaliados neste estudo apresentaram morfologia próxima a do MDE fotogramétrico. Portanto, recomenda-se o uso de todos os MDEs analisados em estudos morfométricos da área de estudo, sendo necessário observar o objetivo do trabalho, bem como a escala de análise e a apresentação desses dados. Evaluation of the Vertical Acuracy of Digital Elevation Models SRTM, ALOS WORLD 3D and ASTER GDEM: a case study in Vale dos Vinhedos, RS - Brazil A B S T R A C TThis work aims to evaluate the vertical accuracy of the digital elevation models (DEMs) SRTM v.3, Alos World 3D and ASTER GDEM v.2 in Vale dos Vinhedos designation of origin (DO) region, RS. Thus, the DEM data with 30 m of the spatial resolution were compared with photogrammetric DEM data with 5 m of the spatial resolution by linear regression and correlation analyzes, and also, topographic profiles carried out with these models. The Cartographic Accuracy Standard (PEC) of each DEM was analyzed to identify the maximum scale for morphometric application, in scales 1:25.000, 1:50.000 and 1:100.000, by calculations of Vertical Tolerance and the Mean Square Error (MSE). All DEMs. All the models studied were classified in class A for the 1:100,000 scale, and for the 1:50,000 scale the analyzed models were classified in class C, while in 1:25.000 scale doesn´t have application. The DEM SRTM v.3 presented smaller altimetry errors compared to ASTER GDEM and Alos World 3D, as for mophometric analysis and Pearson correlation coefficient (r=0,995). It is worth mentioning that all models analyzed are statistically and morphologically close. Therefore, they can be used to conduct several studies, however it is necessary to have in mind the goal of the work, and the scale of analysis and presentation.Keywords: Vertical accuracy, SRTM v.3, Alos World 3D, ASTER GDEM

scholarly journals Validation of Global Digital Elevation Models in Lagos State, Nigeria

2018 ◽  
Vol 2 (1) ◽  
pp. 78-88
Author(s):  
I. D. Arungwa ◽  
E. O. Obarafo ◽  
C. J. Okolie
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Thermal Emission ◽  
Survey Methods ◽  
Digital Elevation Models ◽  
Shuttle Radar Topography Mission ◽  
Mean Square ◽  
Digital Elevation ◽  
Vertical Accuracy

Satellite-derived Digital Elevation Models (DEM) are fast replacing the classical method of elevation data acquisition by ground survey methods. The availability of free and easily accessible DEMs is no doubt of great significance and importance, and a valuable resource in the quest to accurately model the earth's surface topography. However, the suitability of Digital Elevation Models in simulating the topography of the earth at micro, local and regional scales is still an active area of research. The accuracy of Digital Elevation Models vary from one location to another. As such, it is important to conduct local and regional assessments to inform the global user community on the relative performance of these DEMs. This study evaluates the accuracy of the 30-metre Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Models version 2, the 1-kilometre GTOPO30, the 90-metre Shuttle Radar Topography Mission v4 and the 1-kilometre Shuttle Radar Topography Missionv2.1 Digital Elevation Models by validating with highly accurate GPS check-points over Lagos, Nigeria. With a Root Mean Square Error of 3.75m, the results show that Shuttle Radar Topography Mission v4 has the highest vertical accuracy followed by Shuttle Radar Topography Mission v2.1 (Root Mean Square Error: 5.73m), Advanced Spaceborne Thermal Emission and Reflection Radiometer (Root Mean Square Error: 21.70m), and GTOPO30 which shows the lowest vertical accuracy (Root Mean Square Error: 29.41m). By conducting the accuracy assessment of these products in Lagos, this study informs efforts directed at the exploitation of these Digital Elevation Models for topographic mapping and other scientific and environmental application.

scholarly journals Comparison of Vertical Accuracy of Open-Source Global Digital Elevation Models: A Case Study of Adama City, Ethiopia

2021 ◽  
Vol 12 (4) ◽  
pp. 1731-1744
Author(s):  
Hailu Zewde Abili
Keyword(s):  
Open Source ◽  
Thermal Emission ◽  
Accuracy Assessment ◽  
Shuttle Radar Topography Mission ◽  
Surface Model ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Wide Range ◽  
Vertical Accuracy ◽  
Elevation Model

DEM can be generated from a wide range of sources including land surveys, Photogrammetry, and Remote sensing satellites. SRTM 30m DEM by The Shuttle Radar Topography Mission (SRTM), the Global Digital Elevation Model by Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER GDEM) and a global surface model called ALOS Worldview 3D 30 meter (AW3D30) by Advanced Land Observing Satellite (ALOS) are satellite-based global DEMs open-source DEM datasets. This study aims to assess the vertical accuracy of ASTER GDEM2, SRTM 30m, and ALOS (AW3D30) global DEMs over Ethiopia in the study area-Adama by using DGPS points and available accurate reference DEM data. The method used to evaluate the vertical accuracy of those DEMs ranges from simple visual comparison to relative and absolute comparisons providing quantitative assessment (Statistical) that used the elevation differences between DEM datasets and reference datasets. The result of this assessment showed better accuracy of SRTM 30m DEM (having RMSE of ± 4.63 m) and closely followed by ALOS (AW3D30) DEM which scored RMSE of ± 5.25 m respectively. ASTER GDEM 2 showed the least accuracy by scoring RMSE of ± 11.18 m in the study area. The second accuracy assessment was done by the analysis of derived products such as slope and drainage networks. This also resulted in a better quality of DEM derived products for SRTM than ALOS DEM and ASTER GDEM.

scholarly journals Assessment of vertical accuracy of open source 30m resolution space-borne digital elevation models

2021 ◽  
Vol 12 (1) ◽  
pp. 939-960
Author(s):  
Rocky Talchabhadel ◽  
Hajime Nakagawa ◽  
Kenji Kawaike ◽  
Kazuki Yamanoi ◽  
Bhesh Raj Thapa
Keyword(s):  
Open Source ◽  
Digital Elevation Models ◽  
Digital Elevation ◽  
Vertical Accuracy

VERTICAL ACCURACY ASSESSMENT FOR SRTM V.4 AND ASTER GLOBAL DIGITAL ELEVATION MODELS V.2: A CASE STUDY OF PADANG REGENCY, WEST SUMATERA

2018 ◽  
Vol 2 ◽  
pp. 399
Author(s):  
Sahid Sahid
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Accuracy Assessment ◽  
Likelihood Method ◽  
Project Assessment ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Reference Map ◽  
Vertical Accuracy ◽  
Mean Square Errors

<p>Digital elevation model (DEM) is an important element used to represent surface of The Earth. Generally, DEM has been utilized in many geographic science, for instance cartography, hydrology, geology, and remote sensing. It has been widely used since the advanced of technology in remote sensing. This research concerned to assess the vertical accuracy of SRTM v.4 and ASTER GDEM v.2. Topographic or also known as RBI map of Padang City, West Sumatera which has scale 1:10.000 was used as a reference map. RBI has 2.5 m vertical accuracy and 0.5 mm horizontal accuracy. Moreover, to gain the bias value, root mean square errors (RMSE) assessment was used to calculate the different value between them.  Point height would be obtained through sampling method based on the distribution of land-use, slope, and relief. Land-use was classified digitally using maximum likelihood method from SPOT 6 imagery, slope and relief that were derived based on the reference map. Vertical accuracy assessment for both DEM was necessary in order to know the bias elevation prior to using them in a research or project. Assessment of DEM vertical accuracy also could help to generate contour in global region which should be used after the bias vertical was applied.</p>Keywords: SRTM v.2, ASTER GDEM v.2, DEM Generation, Accuracy Assessment, RBI Map

Using direct transformation approach as an alternative technique to fuse global digital elevation models with GPS/levelling measurements in Egypt

2019 ◽  
Vol 13 (3) ◽  
pp. 159-177
Author(s):  
Hossam Talaat Elshambaky
Keyword(s):  
Least Squares ◽  
Root Mean Square ◽  
Digital Elevation Models ◽  
Support Vector ◽  
Surface Model ◽  
Mean Square ◽  
Transformation Technique ◽  
Raw Data ◽  
Direct Transformation ◽  
Digital Elevation

Abstract Open global digital elevation models (GDEMs) represent a free and important source of information that is available to any country. Fusion processing between global and national digital elevation models is neither easy nor inexpensive. Hence, an alternative solution to fuse a GDEM (GTOPO30 or SRTM 1) with national GPS/levelling measurements is adopted. Herein, a transformation process between the GDEMs and national GPS/levelling measurements is applied using parametric and non-parametric equations. Two solutions are implemented before and after the filtration of raw data from outliers to assess the ability of the generated corrector surface model to absorb the effect of the outliers’ existence. In addition, a reliability analysis is conducted to select the most suitable transformation technique. We found that when both the fitting and prediction properties have equal priority, least-squares collocation integrated with a least-squares support vector machine inherited with a linear or polynomial kernel function exhibits the most accurate behavior. For the GTOPO30 model, before filtration of the raw data, there is an improvement in the mean and root mean square of errors by 39.31 % and 68.67 %, respectively. For the SRTM 1 model, the improvement in mean and root mean square values reached 86.88 % and 75.55 %, respectively. Subsequently, after the filtration process, these values became 3.48 % and 36.53 % for GTOPO30 and 85.18 % and 47.90 % for SRTM 1. Furthermore, it is found that using a suitable mathematical transformation technique can help increase the precision of classic GDEMs, such as GTOPO30, making them to be equal or more accurate than newer models, such as SRTM 1, which are supported by more advanced technologies. This can help overcome the limitation of shortage of technology or restricted data, particularly in developed countries. Henceforth, the proposed direct transformation technique represents an alternative faster and more economical way to utilize unfiltered measurements of GDEMs to estimate national digital elevations in areas with limited data.

Apport de la technique du krigeage avec dérive externe pour une cartographie raisonnée de l'équivalent en eau de la neige : Application aux bassins de la rivière Gatineau

2005 ◽  
Vol 32 (1) ◽  
pp. 289-297 ◽  
Author(s):  
Dominique Tapsoba ◽  
Vincent Fortin ◽  
François Anctil ◽  
Mario Haché
Keyword(s):  
Root Mean Square ◽  
Digital Elevation Model ◽  
Snow Water Equivalent ◽  
Mean Square ◽  
Kriging With External Drift ◽  
Digital Elevation ◽  
Snow Water ◽  
Elevation Model ◽  
Mean Square Errors ◽  
External Drift

The geostatistical algorithm of kriging with external drift (KED) is applied to the spatial estimation of snow water equivalent measured at single points. A digital elevation model with a 10-km resolution is used as external drift. Over the dense network of the period of interest (mid-March 1982), which corresponds to the maximum snow accumulation and the beginning of the snow melt in the Gatineau River basin, the KED technique is compared to the univariate ordinary kriging (OK). The results indicate a significant estimation precision improvement when the KED technique is used, notably in the under-sampled and extrapolated zones. A quantitative performance barometer — the root-mean-square (RMS) error — of this method with regards to the various degradation levels of the snow depth measurement network is proposed.Key words: snow water equivalent, kriging with external drift, root-mean-square errors, digital elevation model.[Journal translation]

scholarly journals Evaluations of Machine Learning-Based CYGNSS Soil Moisture Estimates against SMAP Observations

2020 ◽  
Vol 12 (21) ◽  
pp. 3503 ◽  
Author(s):  
Volkan Senyurek ◽  
Fangni Lei ◽  
Dylan Boyd ◽  
Ali Cafer Gurbuz ◽  
Mehmet Kurum ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Correlation Coefficient ◽  
Root Mean Square ◽  
Temporal Resolution ◽  
Mean Square ◽  
In Situ Observations ◽  
Spatio Temporal ◽  
Mean Square Errors

This paper presents a machine learning (ML) framework to derive a quasi-global soil moisture (SM) product by direct use of the Cyclone Global Navigation Satellite System (CYGNSS)’s high spatio-temporal resolution observations over the tropics (within ±38° latitudes) at L-band. The learning model is trained by using in-situ SM data from the International Soil Moisture Network (ISMN) sites and various space-borne ancillary data. The approach produces daily SM retrievals that are gridded to 3 km and 9 km within the CYGNSS spatial coverage. The performance of the model is independently evaluated at various temporal scales (daily, 3-day, weekly, and monthly) against Soil Moisture Active Passive (SMAP) mission’s enhanced SM products at a resolution of 9 km × 9 km. The mean unbiased root-mean-square difference (ubRMSD) between concurrent (same calendar day) CYGNSS and SMAP SM retrievals for about three years (from 2017 to 2019) is 0.044 cm3 cm−3 with a correlation coefficient of 0.66 over SMAP recommended grids. The performance gradually improves with temporal averaging and degrades over regions regularly flagged by SMAP such as dense forest, high topography, and coastlines. Furthermore, CYGNSS and SMAP retrievals are evaluated against 170 ISMN in-situ observations that result in mean unbiased root-mean-square errors (ubRMSE) of 0.055 cm3 cm−3 and 0.054 cm3 cm−3, respectively, and a higher correlation coefficient with CYGNSS retrievals. It is important to note that the proposed approach is trained over limited in-situ observations and is independent of SMAP observations in its training. The retrieval performance indicates current applicability and future growth potential of GNSS-R-based, directly measured spaceborne SM products that can provide improved spatio-temporal resolution than currently available datasets.

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