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Cite as:
Lie&szlig;, M. (2011): <b>digital soil texture maps (resolution 10m ; San Francisco catchment area).</b> <i>Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=1056) from DFG-FOR816dw.</i>

Resource Description

Title: digital soil texture maps (resolution 10m ; San Francisco catchment area)
Short Name: SF soil texture map
FOR816dw ID: 1056
Publication Date: 2011-12-16
Last Update Date: 2012-01-09
License and Usage Rights: FOR816 data user agreement
Temporal Coverage:
Begin: 2007-10-01
End: 2011-07-31
Geographic Coverage:
Geographic Description: catchment of Rio San Francisco (lowest point: Sabanilla)
Bounding Coordinates:
- lon/lat [degrees]
- WGS 84
North: -3.94762° Max: 3260.0 ( meter )
West: -79.1526° East: -79.0573° Elevation
South: -4.03736° Min: 1720.0 ( meter )
Dataset Owner(s):
Individual: Mareike Ließ
Contact:
Associated Person(s):
Individual: David Windhorst
Individual: Felix Altmann
Abstract:
The soil texture of the San Francisco catchment was regionalised by Random Forest methodology. Data from the topsoil of 212 soil profiles was used to supervise the regionalisation process. In addition to the dataset used by Ließ (2011; PhD thesis included in the database: http://www.tropicalmountainforest.org/publications.do?citid=1017 ), additional soil samples were taken by AG Frede (David Windhorst and Felix Altmann) and analysed by AG Huwe in Bayreuth by pipette methodology. The terrain parameters: elevation, aspect, convergence, valley depth, normalised height, Saga Wetness Index, Topographic Ruggedness Index, wind effect and LS Factor were used as predictive parameters. All terrain parameters were calculated from the 10 m resolution digital elevation model (Ungerechts L. (2010): DEM 10m (triangulated from aerial photo - b/w) . Available online (http://www.tropicalmountainforest.org/data_pre.do?citid=901) from DFG-FOR816dw.) by the open source GIS software SAGA . The 50fold texture prediction which was then used to calculate mean and standard deviation was performed based on random 9/10 subsets of the complete dataset. The models were evaluated by the remaining 1/10 test dataset. The prediction of the clay content was evaluated with a median Pearson's rxy of 0.4, the prediction of the sand content was evaluated with a median rxy=0.34. Maximum rxy reached 0.8 for both, clay and sand content. Silt content was predicted as remaining proportion to 100% after subtraction of clay and sand content.
Keywords:
| model output | soil texture | digital soil map |
Associated entities to this dataset:
-------- 1 . spatial raster entity --------
Raster Name: sand mean
Tech. Details ...
Attribute(s) ...
-------- 2 . spatial raster entity --------
Raster Name: silt mean
Tech. Details ...
Attribute(s) ...
-------- 3 . spatial raster entity --------
Raster Name: clay mean
Tech. Details ...
Attribute(s) ...
-------- 1 . other entity --------
Entity name: standard deviation of the modeled sand, silt and clay contents
Entity Description: This entity contains three asc files belonging to the corresponding raster files with mean soil texture contents. Geographical extend and projection are equal.
Tech. Details ...
Attribute(s) ...
Metadata Provider:
Individual: Thomas Lotz
Contact:
Contact Person:
Individual: Mareike Ließ
Contact:
Online Distribution:
Download File: http://www.lcrs.de/data_pre.do?citid=1056
Data Publisher:
Organization: DFG-FOR816 Data Warehouse - University of Marburg, Department of Geography
Contact:


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