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Replication Data for: Mixed-Method Land Characterizations: Remote Sensing and LULC Survey Data of Malawi

Domain:

agriculturegeospatial

Record type:

dataset
Creator:
PetMes
Editor:
Pet
Publisher:
Har
Host:avatar
This document contains a crop cover assessment of 200 sites across Malawi and includes responses to inquiries regarding the primary drivers limiting agricultural productivity (based on interviews held with extension planning area officials). The document also contains a discussion on the importance of mixed-method land characterizations, linking social science with remote sensing.

This material is associated with an Accepted Manuscript of an article published by Taylor & Francis in Annals of the American Association of Geographers on 18 January 2018, available online at doi.org. Reference: Peter, B.G., Messina, J.P. and Snapp, S.S., 2018. A Multiscalar Approach to Mapping Marginal Agri-cultural Land: Smallholder Agriculture in Malawi. Annals of the American Association of Geographers, 108(4), pp.989-1005. The contents of this document have also been accepted by ProQuest for publication in a dissertation entitled, Integrated remote sensing and crop system modeling for precision agriculture across spatial and temporal scales, by Brad G. Peter.

This content is made possible by the support of the American People provided to the Feed the Future Innovation Lab for Sustainable Intensification through the United States Agency for International Development (USAID). The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government. Program activities are funded by USAID under Cooperative Agreement No. AID-OAA-L-14-00006.

Visit

doi.orgdataverse.harvard.edu

Tags

Agricultural SciencesEarth and Environmental SciencesSocial Sciences

Licenses

info:eu-repo/semantics/openAccessCustom terms specific to this datasethttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7910/DVN/IEKP6Z

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