FLAT: Fine-scale Land Allocation Tool

By Jingyu Song1, Michael S Delgado1, Paul Preckel, Shandian Zhe1, Lan Zhao1, Carol Song1

1. Purdue University

Online FLAT tool to calculate FLAT models and to show crop fractions.

Launch Tool

This tool version is unpublished and cannot be run. If you would like to have this version staged, you can put a request through HUB Support.

Archive Version 1.0
Published on 28 Jun 2016
Latest version: 2.0. All versions

This tool is closed source.

Category

Tools

Published on

Abstract

The Fine-scale Land Allocation Tool, FLAT, is an interface developed based on an econometric framework that uses pixel level (e.g., 5 arc-minute) independent variables (agronomic data in the examples installed with the tool) and aggregate dependent variables (land use statistics at the regional level in the examples) to develop predictions of the dependent variables (cropland allocations in the examples) at the pixel level (Song et al., 2016).

FLAT is an open source tool. Users can upload their own data files of independent and dependent variables and GAMS script that implements an estimation approach, or use the default datasets and scripts. Default datasets include state/province level cropland harvested area data for maize, soybeans, and wheat, and pixel level land attributes data for the Americas. The default models predict cropland area at the 5 arc-minute pixel level for the Americas. All default datasets, programming scripts, and result files can be downloaded. FLAT provides mapping options so that the users can view and download the predicted crop fractions shown on a map by selecting the region and crop of interest.  

This research is supported in part by USDA grant Agreement #58300010058, Purdue grant #105651.

References

Song, J., Delgado, M. S., Preckel, P. V., and Villoria, N. B. (2016). “Pixel Level Cropland Allocation and the Marginal Impacts of Biophysical Factors,” in preparation.

Graphical user interface was created by:

Jingyu Song, Michael S. Delgado, Paul V. Preckel, Shandian Zhe, Ian Campbell, Lan Zhao, Carol Song. (2016). “FLAT in the Cloud,” https://mygeohub..org/resources/flat

Cite this work

Researchers should cite this work as follows:

  • Jingyu Song; Michael S Delgado; Paul Preckel; Shandian Zhe; Lan Zhao; Carol Song (2016), "FLAT: Fine-scale Land Allocation Tool," https://mygeohub.org/resources/flat.

    BibTex | EndNote

Tags

  1. GeoShare
  2. Land Allocation