Dataset
Replication Data for: Mapping land suitability for agriculture in Malawi
Harvard Dataverse
2020
Abstract
This remote sensing-based model characterizes land suitability for agriculture in Malawi using a collection of terrain and soil characteristics, including slope, precipitation/runoff/erosion, drainage, sand/silt/clay fraction, soil organic carbon, Ph in H 2 O, and cation exchange capacity. The raster structure data set depicts agricultural land suitability in Malawi. The resulting classifications are [1] Marginally not suitable (N1), [2] Marginally suitable (S3), [3] Moderately suitable (S2), [4] Highly suitable (S1), and [5] Permanently not suitable (N2) or Unavailable (protected, settlement, or water).
The study was partially supported by the Zhejiang A & F University’s Research and Development Fund (2013FR052)and by the Project “Perennial Grain Crops for African Smallholder Farming Systems” (grant number OPP1076311), which was funded by Bill & Melinda Gates Foundation through the support of the United States Agency for International Development (AID-OAA-A-13-00006). The opinions expressed herein are those of the authors and do not necessarily reflect the views of the US Agency for International Development or the US Government.
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Details
- Title
- Replication Data for: Mapping land suitability for agriculture in Malawi
- Creators
- G. Li - Michigan State UniversityJ. P. Messina - University of AlabamaB. G. Peter - University of AlabamaS. S. Snapp - Michigan State University
- Academic Unit
- College of Agricultural, Human, and Natural Resource Sciences
- Publisher
- Harvard Dataverse
- Identifiers
- 99901398991101842
- Language
- English
- Resource Type
- Dataset