The Landcover Impact on the Aspect/Slope Accuracy Dependence of the SRTM-1 Elevation Data for the Humboldt Range
نویسنده
چکیده
The U.S. National Landcover Dataset (NLCD) and the U.S National Elevation Dataset (NED) (bare earth elevations) were used in an attempt to assess to what extent the directional and slope dependency of the Shuttle Radar Topography Mission (SRTM) finished digital elevation model is affected by landcover. Four landcover classes: forest, shrubs, grass and snow cover, were included in the study area (Humboldt Range in NW portion of Nevada, USA). Statistics, rose diagrams, and frequency distributions of the elevation differences (NED-SRTM) per landcover class per geographic direction were used. The decomposition of elevation differences on the basis of aspect and slope terrain classes identifies a) over-estimation of elevation by the SRTM instrument along E, NE and N directions (negative elevation difference that decreases linearly with slope) while b) underestimation is evident towards W, SW and S directions (positive elevation difference increasing with slope). The aspect/slope/landcover elevation differences modelling overcome the systematic errors evident in the SRTM dataset and revealed vegetation height information and the snow penetration capability of the SRTM instrument. The linear regression lines per landcover class might provide means of correcting the systematic error (aspect/slope dependency) evident in SRTM dataset.
منابع مشابه
Effects of Digital Elevation Models (DEM) Spatial Resolution on Hydrological Simulation
Digital Elevation Model is one of the most important data for watershed modeling whit hydrological models that it has a significant impact on hydrological processes simulation. Several studies by the Soil and Water Assessment Tool (SWAT) as useful Tool have indicated that the simulation results of this model is very sensitive to the quality of topographic data. The aim of this study is evaluati...
متن کاملAccuracy assessment of the processed SRTM-based elevation data by CGIAR using field data from USA and Thailand and its relation to the terrain characteristics
Shuttle radar topographic mission (SRTM) has created an unparalleled data set of global elevations that is freely available for modeling and environmental applications. The global availability (almost 80% of the Earth surface) of SRTM data provides baseline information for many types of the worldwide research. The processed SRTM 90 m digital elevation model (DEM) for the entire globe was compil...
متن کاملHighlighting the Importance of the Vegetation Variable on Distributed Land surface temperature on different land use/land cover in Javanrud city range
In environmental models, Vegetations are considered as an important part in controlling environmental changes. To determine the importance of vegetation on land surface temperature (LST), preliminary preprocessing was performed on Landsat 8 image and a split window procedure was used to determine surface temperature. Temperature difference with the surrounding synoptic stations was estimated to...
متن کاملAccuracy Comparison of the Srtm, Aster, Ned, Nextmap® Usa Digital Terrain Model over Several Usa Study Sites
Accurate digital terrain models (DTMs) are necessary for a wide variety applications. National-scale mediumresolution elevation data have been acquired for the conterminous United States under the USGS National Elevation Data (NED; 10 m and 30 m), the Shuttle Radar Topographic Mapping (SRTM; 30 m), and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER; 30 m) programs. In...
متن کاملLandforms identification using neural network-self organizing map and SRTM data
During an 11 days mission in February 2000 the Shuttle Radar Topography Mission (SRTM) collected data over 80% of the Earth's land surface, for all areas between 60 degrees N and 56 degrees S latitude. Since SRTM data became available, many studies utilized them for application in topography and morphometric landscape analysis. Exploiting SRTM data for recognition and extraction of topographic ...
متن کامل