Welcome to FastMapping

Tools for univariate analysis:

  • Depuration
    • Global outliers
    • Spatial outliers
    • Border effects
  • Spatial interpolation
    • Variogram fitting
    • Kriging prediction
  • Classification
    • Fuzzy k-means cluster
Example dataset:

Tools for multivariate analysis:

  • Spatial Principal Components
  • Fuzzy k-means on spatial principal components (KM-sPC)
Example dataset:

The User Interface and some other functionalities were changed. If you detect something strange while using the software, please let us know at fastmapping@agro.unc.edu.ar.

FastMapping can read vector data (.gpkg, and .shp, among others). Spatial file format is prefered instead of csv.

We have a new installer (only for windows) you can download it from here

If you have any question please write to fastmapping@agro.unc.edu.ar, brief tutorial is available in this link.

You can create an issue or a bug report at github. Also, you can send us an email.

Citation: Paccioretti, P., Córdoba, M., & Balzarini, M. (2020). FastMapping: Software to create field maps and identify management zones in precision agriculture. In Computers and Electronics in Agriculture (Vol. 175, p. 105556). Elsevier BV. https://doi.org/10.1016/j.compag.2020.105556

Package version: 0.0.0.9005

Data depuration parameters

Select spatial model(s) to fit

Kriging options:

Local neighbourhood selections based on distance as radius (Max.Dist), number of data points (Max, Min), of nearest site of the target point

Fuzzy k-means parameters

152624681014

Spatial PCA parameters

1701214181

Neighborhood network

1,0000 — 350200400800

It seems that you want more distance than 1000 m between neighbours... which value do you want?

No depuration process was made.

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No interpolation process was made.

Variogram Plot
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Key Scale of predicted values
Viridis
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Key Scale of predicted values
Cyan-Magenta

No cluster process was made.

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Statistical Indices
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Cluster plot
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Statistical Indices