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Data Set ID:

SMEX02 Land Surface Information: Geolocation, Surface Roughness, and Photographs, Version 1

This data set combines various ancillary data (geolocation, surface roughness, and photographs) collected for the Iowa Soil Moisture Experiment 2002 (SMEX02) study region.

Geographic Coverage

Spatial Coverage:
  • N: 42.66, S: 41.7, E: -93.2, W: -93.8

Spatial Resolution: Not Specified
Temporal Coverage:
  • 22 June 2002 to 12 July 2002
Temporal Resolution: Not specified
  • Topography > Surface Roughness
Sensor(s): CAMERAS, ETM+, GPS, TM
Data Format(s):
  • JPEG
  • ASCII Text
Version: V1
Data Contributor(s): Thomas Jackson, Michael Cosh

Data Citation

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.

Jackson, T., M. Cosh, W. P. Dulaney, and L. McKee. 2004. SMEX02 Land Surface Information: Geolocation, Surface Roughness, and Photographs, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/R9AA6FC58HES. [Date Accessed].

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Detailed Data Description

This data set combines various ancillary data (geolocation, surface roughness, and photographs) collected for the Iowa Soil Moisture Experiment 2002 (SMEX02) study region.


Geolocation data are in 14 ASCII text files, including 13 tab-delimited (row/column) data files and one text document that describes the study areas and bounding boxes.

Surface roughness data are provided in two ASCII files.

Photographs are provided as JPEG image files.

Table 1 describes the variables used in the column headings for the surface roughness data files.

Table 1. Variables Used in Column Headings for Roughness Data Files
Heading Description
file name Name of the original file. Includes: site ID (for example, WC08) location in the field (A, B, C, or D)
1 for in-row pictures
2 for cross-row pictures
np Number of points
sigma rms height
L Correlation length
adj. sigma Slope-corrected (adjusted) rms height
Exp. The power coefficient of the autocorrelation function

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File and Directory Structure

Data are available on the FTP site in the ftp://sidads.colorado.edu/DATASETS/AVDM/data/soil_moisture/SMEX02/ancillary_data/ directory. Within this directory therer are five folders: geolocation_information, landuse_classification, photographs, soils_database, and surface_roughness.

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File Naming Convention

This section explains the file naming convention used for this product with an example.

Geolocation Data Files

These files are named for the locations around the study site as shown in Table 2.

Table 2. File Naming Convention Used for Geolocation Data Files
File Name Description
ASOS_Stations.txt Automated Surface Observing System (ASOS) stations
AWOS_Stations.txt Automated Weather Observing System (AWOS) stations
Bounding_Boxes.txt SMEX02 study areas and bounding boxes (this is a text document)
IA_Field_Boundaries.txt Iowa regional field boundaries
IA_Sites.txt Iowa regional sampling sites
ISUW_Stations.txt Iowa Agriculture Climate Network - Iowa State University (ISU) Crop, Soil, and Environmental Sciences
KCCI_Stations.txt School Network for KCCI-TV in Des Moines, Iowa
Vegetation_Sites.txt Walnut Creek vegetation sampling sites
WC_Basin.txt Walnut Creek watershed boundary
WC_Field_Boundaries_V2.txt Walnut Creek field boundaries
WC_Flux_Towers.txt Flux tower locations
WC_Raingages.txt Walnut Creek rain gages
WC_Sites.txt Walnut Creek sampling sites
WC_Streamgages.txt Walnut Creek stream gages

Surface Roughness 

These data files are named for the type of scanning.

Example File Names
Grid: grid_scanning.txt
Slope: slope_scanning.txt.


Example File Name: IA13_03_062902.jpg is from the Iowa regional area, field 13, index 03, and was taken on 29 June 2002.


Variable Description
Table 3. File Naming Convention Used for Photograph Files
IA Indicates the the Iowa Regional study region and WC indicates the Walnut Creek watershed.
ff The field number in which the photograph was taken.
nn The picture index number for that field.
mmddyy The date (month, day, and year).

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File Size

Geolocation: Range from approximately 1 KB to 51 KB (102 KB total) 
Surface Roughness: 17.2 KB and 18.5 KB
Photographs: Range from 240 KB to 2,000 KB (53.1 MB total)

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Total volume of all files is approximately 54 MB.

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Spatial Coverage

Southernmost Latitude: 41.7° N
Northernmost Latitude: 42.66° N 
Westernmost Longitude: 93.8° W
Easternmost Longitude: 93.2° W

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Temporal Coverage

Data were collected from 22 June 2002 through 12 July 2002.

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Parameter or Variable

Parameter Description

Geolocation data are provided as latitude and longitude coordinates, in decimal degrees, and in UTM coordinates, in meters.

Surface roughness data include root-mean-square height in centimeters and correlation length in centimeters.

Photographs of the study area are also provided.

Sample Data Records

The following geolocation sample is taken from the file IA_sites.txt.

Site_ID	Latitude Longitude	Easting	Northing
IA01	42.6599	-93.7174	441207	4723296
IA02	42.5872	-93.7058	442086	4715215
IA03	42.5066	-93.7192	440911	4706278
IA04	42.4122	-93.7280	440099	4695803
IA05	42.3417	-93.7287	439977	4687974

The following surface roughness sample is from the file grid_scanning.txt.

               <------------- surface output ------------------><---Scorelat --->                
 		            grid scanning (1 cm)     					                         
 file name          np      sigma     L       adj.sigma	 Exp.		Exp          
 wc01a1            101     0.778     4.079     0.772	 1     	        
 wc01a2            101     2.142    14.838     2.137	 1.75  	        
 wc01b1            101     0.557     3.734     0.557	 1     	        
 wc01b2            101     1.855     9.744     1.850	 1.5		1.3    
 wc01c1            101     0.467     5.107     0.467	 1    
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Software and Tools

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Data Acquisition and Processing


Geolocation data are provided in both latitude and longitude (decimal degrees) and in UTM coordinates (Zone 15, in meters). Georeferencing is based on the WGS84 ellipsoid. Geolocation data were collected by a variety of methods. Some site locations were determined using Landsat Thematic Mapper (TM) imagery, some by global positioning system (GPS) measurements, some from a combination of aircraft and GPS data, and some by other methods. Table 5 shows the geolocation data sources for the various types of SMEX02 locations.

Table 5. Geolocation Data Sources for the SMEX02 Locations
Georegistration Source
Data Type
Data Points
ASOS Stations Points Unknown Point 15
AWOS Stations Points Unknown Point 33
Bounding Box Boundary TM Image Corners 4
Ground Soil Moisture IA Sites GPS Point 47
WC Sites GPS Clusters 14*31
IA Field Boundaries TM Image Lower Left and Upper Right Corners 47*2
WC Field Boundaries TM Image Lower Left and Upper Right Corners 31*2
Flux Towers Point GPS Point 14
ISUW Sites Point Unknown Point 12
KCCI Sites Point Unknown Point 40
Rain Gages Point GPS Point 22
Stream Gages Point GPS Point 5
Watershed Boundary TM Image Boundary 1465
Vegetation Points GPS Point 31*3*5

Surface Roughness

The surface roughness data were derived from digital photographs, then processed to produce root-mean-square (rms) height, correlation length, and correlation function. Fgure 1 shows the measuring board and how it was used in the field to photograph surface roughness. The commercial program SigmaScan pro 4 was used to digitize the roughness photographs.

Surface roughness measuring board photograph
Figure 1. Measuring Board Used to Photograph Surface Roughness

Before scanning, the dimensions of the board were identified using reference points on the board. The surface was scanned in two ways:

  1. Taking a height measurement at every cm (grid scanning)
  2. Taking a height measurement at every point where the slope of the surface was changing or at least every cm (slope scanning)

The grid scanning method provides a random (or normal) distribution of the surface height, which is required for a correct computation of the rms height. With this method, some variation in the surface height is neglected, which could influence the computation of the correlation length.

The slope method approximates the surface roughness more accurately by taking a height measurement at each point the slope changed, or at a minimum of every centimeter. By increasing the density of the height measurements at points with many slope changes, the sampling of height measurements may be biased. This could influence the correct computation of the rms height. Therefore, two surface height data set were created:

  1. Grid scanning data
  2. Slope scanning data

Roughness parameters were calculated using programs named surface and scorelat. The surface program calculates the rms height and the correlation length and writes the computed autocorrelation curve to a file. This program also corrects for the slope of the roughness board using a least-square fit and calculates an adjusted rms height. The investigators recommended using the adjusted rms height ("adj.sigma" in the data files). The scorelat program was used only to create an autocorrelation curve, but it uses a different algorithm than does the surface program. Both autocorrelation curves of surface and scorelat were used to determine the autocorrelation function. The scorelat program was successfully applied to only some of the digitized surfaces of the grid scanning and the slope scanning data set.


Teams were assigned cameras throughout the experiment. Not all fields were photographed.

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References and Related Publications

Contacts and Acknowledgments

Tom Jackson 
US Department of Agriculture (USDA) Hydrology and Remote Sensing Lab
Beltsville, MD

Mike Cosh
US Department of Agriculture (USDA) Hydrology and Remote Sensing Lab
Beltsville, MD


The investigators thank the Soil Moisture Experiment 2002 Science Team, the National Soil Tilth Laboratory, the National Aeronautics and Space Administration (NASA), NASA Aqua AMSR Terrestrial Hydrology and Global Water Cycle Programs, and all those who collected and analyzed the data, including: Rogier Van der Velde, Ann Hsu, and Laura Kimes. They also want to thank the many graduate students and volunteers who collected field photographs.

Document Information


January 2004


November 2005

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