scholarly journals Using Selective Drainage Methods to Extract Continuous Surface Flow from 1-Meter Lidar-Derived Digital Elevation Data

2010 ◽  
Author(s):  
Sandra K. Poppenga ◽  
Bruce B. Worstell ◽  
Jason M. Stoker ◽  
Susan K. Greenlee
Keyword(s):  
Surface Flow ◽  
Digital Elevation ◽  
Elevation Data ◽  
Continuous Surface ◽  
Digital Elevation Data

scholarly journals Landslides across the USA: occurrence, susceptibility, and data limitations

Landslides ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. 2271-2285 ◽  
Author(s):  
Benjamin B. Mirus ◽  
Eric S. Jones ◽  
Rex L. Baum ◽  
Jonathan W. Godt ◽  
Stephen Slaughter ◽  
...  
Keyword(s):  
The United States ◽  
National Scale ◽  
Landslide Occurrence ◽  
Process Understanding ◽  
Digital Elevation ◽  
Data Limitations ◽  
Elevation Data ◽  
The Usa ◽  
Digital Elevation Data ◽  
Landslide Mapping

Abstract Detailed information about landslide occurrence is the foundation for advancing process understanding, susceptibility mapping, and risk reduction. Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.

scholarly journals Environmental classification of administrative units of the Ukrainian Carpathians

2014 ◽  
pp. 245-253
Author(s):  
Ivan Kruhlov
Keyword(s):  
Cluster Analysis ◽  
Standard Deviation ◽  
Satellite Images ◽  
Environmental Classification ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Administrative Units ◽  
Elevation Model

Boundaries of 43 administrative units (raions and oblast towns) were digitized and manually rectified using official schemes and satellite images. SRTM digital elevation data were used to calculate mean relative elevation and its standard deviation for each unit, as well as to delineate altitudinal bioclimatic belts and their portions within the units. These parameters were used to classify the units via agglomerative cluster analysis into nine environmental classes. Key words: cluster analysis, digital elevation model, geoecosystem, geo-spatial analysis.

scholarly journals Retrieval of similar topographic areas.

2016 ◽  
Vol 47 (1) ◽  
pp. 275
Author(s):  
E. Kokinou ◽  
C. Panagiotakis ◽  
Th. Kinigopoulos
Keyword(s):  
Image Processing ◽  
High Efficiency ◽  
Automatic Extraction ◽  
Local Minima ◽  
Initial Model ◽  
Area Of Interest ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Step Number

Image processing and understanding and further pattern recognition comprises a precious tool for the automatic extraction of information using digital topography. The aim of this work is the retrieval of areas with similar topography using digital elevation data. It can be applied to geomorphology, forestry, regional and urban planning, and many other applications for analyzing and managing natural resources. In specifics, the user selects the area of interest, navigating overhead a high resolution elevation image and determines two (3) parameters (step, number of local minima and display scale). Furthermore the regions with similar relief to the initial model are determined. Experimental results show high efficiency of the proposed scheme.

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