Influence of DEM spatial resolution on the susceptibility mapping with SHALSTAB in the Rio Garcia hydrographic basin, municipality of Blumenau/SC / Influência de la resolución espacial del MDE en la cartografía de susceptibilidad con SHALSTAB en la cuenca hidrográfica del Río García, municipio de Blumenau/SC

2021 ◽  
Vol 5 (3) ◽  
pp. 1475-1491
Author(s):  
Gisele Marilha Pereira Reginatto ◽  
Regiane Mara Sbroglia ◽  
Camilo Andrade Carreño ◽  
Bianca Rodrigues Schvartz ◽  
Pâmela Betiatto ◽  
...  

In translational landslide susceptibility analysis with SHALSTAB (Shallow Landsliding Stability Model), the resolution of the digital elevation model (DSM) is determinant for defining the type of mapping generated (preliminary or not). In this study, in order to verify the influence of the SDM scale on the SHALSTAB stability classes, susceptibility maps were prepared at two scales: 1:50,000 and 1:10,000. The study area was the Garcia River watershed, belonging to the municipality of Blumenau, Santa Catarina, affected by landslides in the 2008 catastrophe, which enabled the validation of the simulations with the scars mapped in the field. Thus, the influence of scale on the distribution of the model's stability classes and on its performance was verified. SHALSTAB performed better at the 1:10,000 scale, predicting 70% of the instabilities in a percentage of unstable area approximately three times smaller than at the 1,50,000 scale.

Geosciences ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 360 ◽  
Author(s):  
Sansar Raj ◽  
Thimmaiah

Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.


2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Andrea Lopes Iescheck ◽  
Patricia Andréia Paiola Scalco

<p><strong>Abstract.</strong> This work is part of a research project that aims at the automatic determination of knickpoints and the assessment of morphometric and hypsometric parameters of Mirim Lagoon Hydrographic Basin, using Shuttle Radar Topography Mission digital elevation model (SRTM-DEM) and spatial analyses.</p><p>The analysis of geomorphologic systems is done using computational treatment of data obtained by remote sensing, especially those obtained by SRTM. These data permit the elaboration of a topographic model for the Earth surface and provide a base for studies in several units of geomorphologic analyses (geomorphologic systems), such as hydrographic basins.</p><p>The most usual technique for derivation of relief morphologic attributes is based on digital elevation models (DEMs) and digital hydrographic nets. Computational routines are applied on those data for acquisition of the hydrography and drainage anomalies. The DEMs and the hydrographic nets must have either morphologic or hydrologic consistency to validate the results obtained in the morphometric analyses.</p><p>More specifically, this study aims at describing the method and related results regarding the validation of the vertical accuracy of SRTM-DEM through a kinematic positioning based on the Global Navigation Satellite System (GNSS), in the Mirim Lagoon Hydrographic Basin region. Mirim Lagoon Hydrographic Basin is as cross-border basin located on the Atlantic coast of South America, and covers an area of 58,407.78&amp;thinsp;km<sup>2</sup>, where 47% of this area is in Brazil and 53% in Uruguay.</p><p>Several studies deal with the validation of Digital Elevation Models (DEMs) and SRTM data using different GNSS surveying methods and receivers. The innovation of this work is the methodology developed to achieve the suitable accuracy for the control points coordinates to validate the SRTM-DEM of Mirim Lagoon Hydrographic Basin. The study used the kinematic relative positioning method with a recording rate of 1 second and without reference stations for post-processing with the precise point positioning (PPP) method. This methodology allowed covering a large area with reference stations being very far from the surveyed region and with different geodetic reference systems (two countries).</p><p>The methodology entails the GNSS data acquisition and post-processing, the transformation from geometric heights into orthometric heights, the SRTM-DEM mosaic, the extraction of homologous points in the SRTM-DEM and the statistical analyses for validating the model.</p><p>The study used a GNSS receiver of dual-frequency with recording rate of 1 second to collect a total of 275,916 points with 3D coordinates. Those points were post-processed using the PPP method with the Canadian Spatial Reference System &amp;ndash; Precise Point Positioning (CSRS-PPP), and the ellipsoidal height was converted into orthometric height through the software INTPT geoid. During this work, we used the geopotential model (EGM96) to transform height differences between two countries, Brazil and Uruguay.</p><p>In order to obtain the SRTM-DEM we used 15 SRTM images, version 3, band C, with a spatial resolution of 1 arcsecond (approximately 30&amp;thinsp;m). These images were individually processed to obtain the Digital Elevation Model Hydrologically Consistent (DEMHC) and to treat the inconsistencies. Afterwards, we created a mosaic with the 15 images.</p><p>In the statistical analysis we examined the magnitude of absolute errors in the SRTM data. These errors were named discrepancies between the SRTM heights and the heights of GNSS survey points. After the post-processing and the heights conversion, the GNSS survey points were considered accurate and used as a reference for SRTM-DEM validation. The goal of the statistical analysis was to verify if the absolute vertical precision of the DEM data exceeds 16&amp;thinsp;m, according to the precision specifications of the DEM SRTM.</p><p>Results showed that the vertical mean absolute error of the SRTM-DEM vary from 0.07&amp;thinsp;m to &amp;plusmn;&amp;thinsp;9.9&amp;thinsp;m with average of &amp;minus;0.28&amp;thinsp;m. This vertical accuracy is better than the absolute vertical accuracy value of &amp;plusmn;&amp;thinsp;16&amp;thinsp;m published in the SRTM data specification and validates the SRTM-DEM. Besides that, even considering different slopes and different heights the statistics showed that SRTM-DEM could be validated, in spite of the results for lower and flat area were more accurate than the ones for a higher area with high slope.</p>


2020 ◽  
Vol 13 (2) ◽  
pp. 713
Author(s):  
Danilo Da Silva Dutra ◽  
André Ricardo Furlan ◽  
Luís Eduardo De Souza Robaina

O relevo é a base onde todas as populações vivem e desenvolvem suas atividades, derivando dessa relação vantagens e desvantagens, daí a importância de conhecê-lo através do estudo de suas diferentes formas e elementos. Nesse contexto insere-se a importância de metodologias para o seu estudo, sendo que atualmente vivencia-se a expressividade de dados disponíveis para aplicação de geoprocessamento. A partir das geotecnologias pode-se empreender diversas análises sobre o relevo, destacando-se nesse contexto, a proposta dos geomorphons a qual foi aplicada na bacia hidrográfica do arroio Pantanoso. O objetivo da pesquisa é a identificação e análise dos elementos do relevo definido por geomorphons, quais sejam: 1) Planos, 2) Picos, 3) Cristas, 4) Ressaltos, 5) Crista secundária, 6) Encostas, 7) Escavado, 8) Base de encosta, 9) Vales e 10) Fosso. A determinação dos geomorphons foi a partir do processamento em ambiente SIG do Modelo Digital de Elevação (MDE) do Shuttle Radar Topograph Mission (SRTM) com resolução espacial 3 arcsec (90 metros), “L” Lookup (distância em metros) definiu-se como de 20 pixels (1800 metros) e o “T” Theresholdt (nivelamento em graus) definiu-se em 2º. Para visualização do comportamento dos elementos do relevo na área de estudo realizaram-se trabalhos de campo, o que contribuiu para evidenciar a padronização desses elementos. Os quatro elementos geomorphons mais representativos são encostas, vales, cristas e planos. Subdivision of relief elements through the proposal of geomorphons: river basin of arroio Pantanoso - Canguçu/RS A B S T R A C TRelief is the basis where all populations live and develop their activities, deriving from this relation advantages and disadvantages, hence the importance of knowing it through the study of its different forms and elements. In this context, the importance of methodologies for its study is inserted and geoprocessing application for data available for is currently experienced. From the geotechnologies one can undertake several analyzes on the relief, highlighting in this context, the proposal of the geomorphons which was applied in Pantanoso stream basin. The objective of the research is to identify and analyze the elements of the relief defined by geomorphons, namely: 1) Flats, 2) Peaks, 3) Ridges, 4) Shoulders, 5) Spurs, 6)Slopes, 7) Hollows, 8) Footslope, 9) Valley and 10) Pits. The determination of the geomorphons was based on the GIS environment of the Shuttle Radar Topograph Mission (SRTM) Digital Elevation Model (DEM) with spatial resolution 3 arcsec (90 meters), "L" Lookup (distance in meters) was defined as of 20 pixels (1800 meters) and the "T" Theresholdt (leveling in degrees) was defined in 2º. In order to visualize the behavior of the relief elements in the study area, fieldwork was carried out, which contributed to the standardization of these elements. The four most representative geomorphons, which are: Slopes, Valleys, Ridges and Flat.Keywords: SIG, Geomorphons; Canguçu/RS; relief


Author(s):  
M. Nishio ◽  
M. Mori

These The present study aims to simulate the hydrologic processes of a flood, based on a new, highly accurate Digital Elevation Model (DEM). The DEM is provided by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan, and has a spatial resolution of five meters. It was generated by the new National Project in 2012. The Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS) is used to simulate the hydrologic process of a flood of the Onga River in Iizuka City, Japan. A large flood event in the typhoon season in 2003 caused serious damage around the Iizuka City area. Precise records of rainfall data from the Automated Meteorological Data Acquisition System (AMeDAS) were input into the HEC-HMS. The estimated flood area of the simulation results by HEC-HMS was identical to the observed flood area. A watershed aggregation map is also generated by HEC-HMS around the Onga River.


2019 ◽  
Vol 11 (15) ◽  
pp. 1767 ◽  
Author(s):  
Francesca Pasquetti ◽  
Monica Bini ◽  
Andrea Ciampalini

The aim of this paper is to evaluate the usefulness of TanDEM-X DEM (digital elevation model) for remote geomorphological analysis in Argentinian Patagonia. The use of a DEM with appropriate resolution and coverage might be very helpful and advantageous in vast and hardly accessible areas. TanDEM-X DEM could represent an unprecedented opportunity to identify geomorphological features because of its global coverage, ~12 m spatial resolution and low cost. In this regard, we assessed the vertical accuracy of TanDEM-X DEM through comparison with Differential Global Positioning System (DGPS) datasets collected in two areas of the Patagonia Region during a field survey; we then investigated different types of landforms by creating the elevation profiles. The comparison indicates a high agreement between TanDEM-X DEM and reference values, with a mean absolute vertical error (MAE) of 0.53 m, and a root mean squared error (RMSE) of 0.73 m. The results of landform analysis show an appropriate spatial resolution to detect different features such as beach ridges, which are impossible to delineate with other lower resolution DEMs. For these reasons, TanDEM-X DEM constitutes a useful tool for detailed geomorphological analyses in Argentinian Patagonia.


OSEANA ◽  
2018 ◽  
Vol 43 (4) ◽  
Author(s):  
Marindah Yulia Iswari ◽  
Kasih Anggraini

DEMNAS : NATIONAL DIGITAL ELEVATION MODEL FOR COASTAL APPLICATION. DEM is a digital data which contain information about elevation. In Indonesia, DEM can be generated from elevation points or contours in RBI (Rupabumi Indonesia). DEM can be performed to research of coastal application i.e. inundation or tsunami. DEM can help to analyze vulnerability or evacuation zone for coastal hazards. DEMNAS is one product of BIG (Geospatial Information Agency) which consist of elevation data from remote sensing images. DEMNAS data has not been widely used and is still being developed but DEMNAS has an advantage of spatial resolution. DEMNAS has spatial resolution 0.27 arc-second, which is bigger than the spatial resolution of global DEM.


2021 ◽  
Author(s):  
Jingming Hou ◽  
Xinyi Li ◽  
Zhanpeng Pan ◽  
Junhui Wang ◽  
Ruike Wang

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