View Spat. Interp. Comparison 1997 (public)

2011-01-04 17:11 by cong | Version 1 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Overall (based on 0 votes)
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Interesting
Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star Documentation

Spatial Interpolation Comparison 97, a geostatistical data set.

comparison geostatistics interpolation spatial statistics
Attribute Types
zip (564.8 KB)

Files are converted on demand and the process can take up to a minute. Please wait until download begins.

Completeness of this item currently: 100%.
You can edit this item to add more meta information and make use of the site's premium features.
Original Data Format
Version mldata
Data (first 10 data points)
    ZIP archive surfdem.grd, demstd.grd, sic_full.dat, sic_obs.dat, borders.dxf, SIC97_Readme.pdf

The data sets used for SIC97 (Spatial Interpolation Comparison 97).

Mapping daily rainfall/wet deposited radioactivity in the environment.

The whole report on this international statistical exercise can be found in the "Events" section of AI-GEOSTATS.

Excerpt from description:

Spatial interpolation is an essential feature of many Geographic Information Systems, or GIS. It is a procedure for estimating values of a variable at unsampled locations. A map with isolines is usually the visual output of such a process and plays a crucial role in decision making. Based on Tobler’s Law of Geography, which stipulates that observations close together in space are more likely to be similar than those farther apart, the development of models attempting to represent the way close observations are related can sometimes be very problematic. The approaches can be divergent and may therefore lead to very different results. As a consequence, an understanding of the initial assumptions and methods used is the key to the spatial interpolation process.

    Data Source
    The journal of Geographic Information and Decision Analysis (GIDA) published the accepted papers in a special issue (Vol. 2, No. 2). See - link is broken, will be checked soon A hardcopy version has been published in 2003 as a European Report and includes selected papers published online as well as unpublished material written by invited authors. Hardcopies of the report (if still available) can be obtained from the publication office of the European Commission. Reference: Mapping radioactivity in the environment. Spatial Interpolation Comparison 1997. EUR 20667 EN, EC, Dubois G., Malczewski J. and De Cort M. (Eds.), Office for Official Publications of the European Communities, Luxembourg, 268 p., May 2003.
    Measurement Details
    1. DESCRIPTION OF THE DATA 3.1. Observed rainfall data The data distributed to the SIC97 participants were 100 daily rainfall measurements made in Switzerland on the 8th of May 1986 which were randomly extracted from a dataset of 467 measurements. The participants had to estimate the rainfall at the 367 remaining locations. The measurements were in units of 1/10th of a mm, but values ranging from 1 to 10 were often observed due to air condensation. Figure 1 shows the locations of the 367 measurements for which the values had to be estimated (diamonds) while those of the 100 measurements used for the estimation are presented with proportional symbols (filled circles).

    3.2. Digital elevation model and country borders A digital elevation model (DEM) with a resolution of around 1 km x 1 km was provided as secondary information so as country borders used to define the area under study (Figure 3).

    3.3. Description of the data to be estimated The co-ordinates of the sampling locations of the remaining 367 daily rainfall measurements were distributed to the participants in order that estimates could be made. The observed rainfall values for these locations were made available only after reception of the estimations of all the participants. The statistics of the 367 measurements are given below (Figure 4).

    3.4. Description of the full data set Figure 5 presents the complete 467 rainfall data in terms of proportional symbols and summarised with their statistics and associated histogram (Figure 6).

    1. SOURCES OF THE SIC97 DATA SETS The gathering of the rainfall data, provided by Giovanni Graziani from the Environment Institute of the Joint Research Centre (Ispra, Italy), has been undertaken, under JRC-Ispra funding, by the Air pollution Group at Imperial College, London.

    The Digital Elevation Model has been provided by EROS Data Centre from the U.S. Geological Survey (USGS). The country borders are extracted from ESRI's Digital Chart of the World (DCW) provided by ESRI.

    Usage Scenario

    If you wish to test your methods and experience on the same case study, the data have been made available on this web site (see the “Data” section of aigeostats). The point data set correspond to a simple ASCII file with, for each measurement, an identifier given as an integer, the co-ordinates X and Y in meters and the rainfall measurement given in 1/10th of a mm. The data have been projected with a Lambert azimuthal projection system. Country borders of Switzerland are available as an Autocad Interchange Drawing file (.dxf), the DEM is provided as an ASCII grid projected in order to match with the point data sets and the country borders.

    revision 1
    by cong on 2011-01-04 17:11

    No one has posted any comments yet. Perhaps you would like to be the first?

    Leave a comment

    To post a comment, please sign in.

    This item was downloaded 1519 times and viewed 625 times.

    No Tasks yet on dataset Spat. Interp. Comparison 1997

    Submit a new Task for this Data item


    Sort by


    We are acting in good faith to make datasets submitted for the use of the scientific community available to everybody, but if you are a copyright holder and would like us to remove a dataset please inform us and we will do it as soon as possible.

    Data | Task | Method | Challenge


    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
    PASCAL Logo