Data Set ID:
SV12STM

SMAPVEX12 Soil Texture Map, Version 1

This data set consists of soil texture classification data derived from field surveys as part of the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12). The soil texture classification map provides information about vegetation present in the study area.

This is the most recent version of these data.

STANDARD Level of Service

Data: Data integrity and usability verified

Documentation: Key metadata and user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools

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Parameter(s):
  • SOILS > SOIL TEXTURE
Data Format(s):
  • ESRI Shapefile
Spatial Coverage:
N: 49.96, 
S: 49.44, 
E: -97.85, 
W: -98.51
Platform(s):FIELD SURVEYS
Spatial Resolution:
  • 316 m x 316 m
Sensor(s):SOIL SAMPLER
Temporal Coverage:
  • 7 June 2012 to 19 July 2012
Version(s):V1
Temporal ResolutionVariesMetadata XML:View Metadata Record
Data Contributor(s):McNairn, H., J. Powers, and G. Wiseman.

Geographic Coverage

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As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

McNairn, H., J. Powers, and G. Wiseman. 2014. SMAPVEX12 Soil Texture Map, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/5694JSVXBA3A. [Date Accessed].

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How To

Programmatic Data Access Guide
Data from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) can be accessed directly from our HTTPS file system or through our Application Programming Interface (API). Our API offers you the ability to order data using specific temporal and spatial filters... read more
Filter and order from a data set web page
Many NSIDC data set web pages provide the ability to search and filter data with spatial and temporal contstraints using a map-based interface. This article outlines how to order NSIDC DAAC data using advanced searching and filtering.  Step 1: Go to a data set web page This article will use the... read more