scholarly journals A NEW METHOD TO DETECT REGIONS ENDANGERED BY HIGH WIND SPEEDS

2016 ◽  
Vol XLI-B8 ◽  
pp. 59-63
Author(s):  
P. Fischer ◽  
S. Ehrensperger ◽  
T. Krauß
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Boosted Regression Trees ◽  
Slope Aspect ◽  
Maximum Wind ◽  
Wind Speeds ◽  
Landform Classification ◽  
Area Of Interest ◽  
Land Cover Data ◽  
Digital Elevation ◽  
Elevation Model

In this study we evaluate whether the methodology of Boosted Regression Trees (BRT) suits for accurately predicting maximum wind speeds. As predictors a broad set of parameters derived from a Digital Elevation Model (DEM) acquired within the Shuttle Radar Topography Mission (SRTM) is used. The derived parameters describe the surface by means of quantities (e.g. slope, aspect) and quality (landform classification). Furthermore land cover data from the CORINE dataset is added. The response variable is maximum wind speed, measurements are provided by a network of weather stations. The area of interest is Switzerland, a country which suits perfectly for this study because of its highly dynamic orography and various landforms.

scholarly journals A NEW METHOD TO DETECT REGIONS ENDANGERED BY HIGH WIND SPEEDS

2016 ◽  
Vol XLI-B8 ◽  
pp. 59-63
Author(s):  
P. Fischer ◽  
S. Ehrensperger ◽  
T. Krauß
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Boosted Regression Trees ◽  
Slope Aspect ◽  
Maximum Wind ◽  
Wind Speeds ◽  
Landform Classification ◽  
Area Of Interest ◽  
Land Cover Data ◽  
Digital Elevation ◽  
Elevation Model

In this study we evaluate whether the methodology of Boosted Regression Trees (BRT) suits for accurately predicting maximum wind speeds. As predictors a broad set of parameters derived from a Digital Elevation Model (DEM) acquired within the Shuttle Radar Topography Mission (SRTM) is used. The derived parameters describe the surface by means of quantities (e.g. slope, aspect) and quality (landform classification). Furthermore land cover data from the CORINE dataset is added. The response variable is maximum wind speed, measurements are provided by a network of weather stations. The area of interest is Switzerland, a country which suits perfectly for this study because of its highly dynamic orography and various landforms.

scholarly journals PREDICTION OF WIND SPEEDS BASED ON DIGITAL ELEVATION MODELS USING BOOSTED REGRESSION TREES

2015 ◽  
Vol XL-1-W5 ◽  
pp. 197-202
Author(s):  
P. Fischer ◽  
C. Etienne ◽  
J. Tian ◽  
T. Krauß
Keyword(s):  
Learning Algorithm ◽  
A Priori ◽  
Regression Trees ◽  
Geographic Area ◽  
Boosted Regression Trees ◽  
Maximum Wind ◽  
Wind Speeds ◽  
Area Of Interest ◽  
Digital Elevation ◽  
Depth Analysis

In this paper a new approach is presented to predict maximum wind speeds using Gradient Boosted Regression Trees (GBRT). GBRT are a non-parametric regression technique used in various applications, suitable to make predictions without having an in-depth a-priori knowledge about the functional dependancies between the predictors and the response variables. Our aim is to predict maximum wind speeds based on predictors, which are derived from a digital elevation model (DEM). The predictors describe the orography of the Area-of-Interest (AoI) by various means like first and second order derivatives of the DEM, but also higher sophisticated classifications describing exposure and shelterness of the terrain to wind flux. In order to take the different scales into account which probably influence the streams and turbulences of wind flow over complex terrain, the predictors are computed on different spatial resolutions ranging from 30 m up to 2000 m. The geographic area used for examination of the approach is Switzerland, a mountainious region in the heart of europe, dominated by the alps, but also covering large valleys. The full workflow is described in this paper, which consists of data preparation using image processing techniques, model training using a state-of-the-art machine learning algorithm, in-depth analysis of the trained model, validation of the model and application of the model to generate a wind speed map.

scholarly journals Relationship between landform classification and vegetation (case study: southwest of Fars province, Iran)

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Marzieh Mokarram ◽  
Dinesh Sathyamoorthy
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Tree Height ◽  
Shuttle Radar Topography Mission ◽  
Fars Province ◽  
Visual Interpretation ◽  
Landform Classification ◽  
Digital Elevation ◽  
Position Index ◽  
Elevation Model

AbstractThis study is aimed at investigating the relationship between landform classification and vegetation in the southwest of Fars province, Iran. First, topographic position index (TPI) is used to perform landform classification using a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) with resolution of 30 m. The classification has ten classes; high ridges, midslope ridges, upland drainage, upper slopes, open slopes, plains, valleys, local ridges, midslope drainage and streams. Visual interpretation indicates that for the local, midslope and high ridge landforms, normalized difference vegetation index (NDVI) values and tree heights are higher as compared to the other landforms. In addition, it is found that there are positive and significant correlations betweenNDVI and tree height (

scholarly journals A New Approach to the Quality Control of Slope and Aspect Classes Derived from Digital Elevation Models

2021 ◽  
Vol 13 (11) ◽  
pp. 2069
Author(s):  
M. V. Alba-Fernández ◽  
F. J. Ariza-López ◽  
M. D. Jiménez-Gamero
Keyword(s):  
Quality Control ◽  
Hypothesis Test ◽  
Simulated Data ◽  
Slope Aspect ◽  
New Approach ◽  
Reference Set ◽  
Digital Elevation ◽  
Using Data ◽  
Elevation Model ◽  
Degree Of Similarity

The usefulness of the parameters (e.g., slope, aspect) derived from a Digital Elevation Model (DEM) is limited by its accuracy. In this paper, a thematic-like quality control (class-based) of aspect and slope classes is proposed. A product can be compared against a reference dataset, which provides the quality requirements to be achieved, by comparing the product proportions of each class with those of the reference set. If a distance between the product proportions and the reference proportions is smaller than a small enough positive tolerance, which is fixed by the user, it will be considered that the degree of similarity between the product and the reference set is acceptable, and hence that its quality meets the requirements. A formal statistical procedure, based on a hypothesis test, is developed and its performance is analyzed using simulated data. It uses the Hellinger distance between the proportions. The application to the slope and aspect is illustrated using data derived from a 2×2 m DEM (reference) and 5×5 m DEM in Allo (province of Navarra, Spain).

scholarly journals MORPHOMETRIC CHARACTERIZATION OF THE HYDROGRAPHIC BASIN OF JAUQUARA RIVER IN THE TRANSITION BETWEEN THE CERRADO AND AMAZON BIOMES IN MATO GROSSO-BRAZIL

FLORESTA ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 325
Author(s):  
Gabriel Americo Cassettari ◽  
Tadeu Miranda De Queiroz
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Mato Grosso ◽  
Digital Elevation ◽  
Circularity Index ◽  
Elevation Model ◽  
Basin Area ◽  
Morphometric Characterization ◽  
Effective Water ◽  
Unpublished Information

This study aimed to perform the Jauquara river watershed morphometric characterization. To watershed delimitation was used SRTM 30 type Digital Elevation Model (Shuttle Radar Topography Mission, with spatial resolution of 30 m) provided by USGS Earth Explorer platform. The geographic information system used to watershed delimitation process and maps generation was ArcGIS 10.1 from ESRI®. The morphometric variables calculus was based on classic methodologies of Applied Hydrology. The watershed has an area of 1408,03 km2 and perimeter of 288,43 km with compactness coefficient and circularity index of Kc = 2.15 and Ic = 0.21, respectively, which show an elongated shape. The drainage was classified as 5th order, reinforcing the configuration of the drainage network with a wide hydric distribution. The predominant altitude range is between 368 and 552 m, which corresponds to an area of 478.10 km2. It was observed that there is a predominance of smooth-wavy and undulated reliefs (3-8%, 8-20% slope), which correspond to 38,05% and 23,04% of the total basin area respectively. The morphometric characterization of the basin made it possible to obtain unpublished information that contributes to the decision making regarding the effective water management in the studied area, being this a guiding study for other works

scholarly journals Mapping Post-Earthquake Landslide Susceptibility: A U-Net Like Approach

2020 ◽  
Vol 12 (17) ◽  
pp. 2767
Author(s):  
Yu Chen ◽  
Yongming Wei ◽  
Qinjun Wang ◽  
Fang Chen ◽  
Chunyan Lu ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Environmental Influence ◽  
Landslide Susceptibility Mapping ◽  
Slope Aspect ◽  
Support Vector ◽  
Gis Technology ◽  
2008 Wenchuan Earthquake ◽  
Structure Information ◽  
Digital Elevation ◽  
Elevation Model

A serious earthquake could trigger thousands of landslides and produce some slopes more sensitive to slide in future. Landslides could threaten human’s lives and properties, and thus mapping the post-earthquake landslide susceptibility is very valuable for a rapid response to landslide disasters in terms of relief resource allocation and posterior earthquake reconstruction. Previous researchers have proposed many methods to map landslide susceptibility but seldom considered the spatial structure information of the factors that influence a slide. In this study, we first developed a U-net like model suitable for mapping post-earthquake landslide susceptibility. The post-earthquake high spatial airborne images were used for producing a landslide inventory. Pre-earthquake Landsat TM (Thematic Mapper) images and the influencing factors such as digital elevation model (DEM), slope, aspect, multi-scale topographic position index (mTPI), lithology, fault, road network, streams network, and macroseismic intensity (MI) were prepared as the input layers of the model. Application of the model to the heavy-hit area of the destructive 2008 Wenchuan earthquake resulted in a high validation accuracy (precision 0.77, recall 0.90, F1 score 0.83, and AUC 0.90). The performance of this U-net like model was also compared with those of traditional logistic regression (LR) and support vector machine (SVM) models on both the model area and independent testing area with the former being stronger than the two traditional models. The U-net like model introduced in this paper provides us the inspiration that balancing the environmental influence of a pixel itself and its surrounding pixels to perform a better landslide susceptibility mapping (LSM) task is useful and feasible when using remote sensing and GIS technology.

Landform classification from a digital elevation model and satellite imagery

Geomorphology ◽  
2008 ◽  
Vol 100 (3-4) ◽  
pp. 453-464 ◽  
Author(s):  
Hossein Saadat ◽  
Robert Bonnell ◽  
Forood Sharifi ◽  
Guy Mehuys ◽  
Mohammad Namdar ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Landform Classification ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals The Shuttle Radar Topography Mission Digital Elevation Model as an alternative data source for deriving hydrological characteristics in lowland catchment — Rogożynek catchment case study

2009 ◽  
Vol 41 (1) ◽  
pp. 71-82 ◽  
Author(s):  
Michał Wasilewski ◽  
Jarosław Chormański
Keyword(s):  
Digital Elevation Model ◽  
Shuttle Radar Topography Mission ◽  
Srtm Dem ◽  
Hydrological Characteristics ◽  
Wetspa Model ◽  
Digital Elevation ◽  
Data Source ◽  
Elevation Model ◽  
Topography Data

The Shuttle Radar Topography Mission Digital Elevation Model as an alternative data source for deriving hydrological characteristics in lowland catchment — Rogożynek catchment case study This paper describes possibility of supplementing digital topography data needed for hydrologic modeling (WetSpa model) of lowland catchment with existing, freely available DEM data obtained from Shuttle Radar Topography Mission launched on February 11th, 2000. Rogożynek basin (Upper Biebrza) as case study is given. Authors compared three DEMs: topographic — TOPO DEM 20 (20 m resolution), radar — SRTM DEM 90 (90 m res.) and resampled radar — SRTM DEM 20 (20 m res.). There were several characteristics compared and analyzed like: relative height differences, slopes, generated river network and generated subwatersheds (subbasins).

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