Improving AfriPop dataset with settlement extents extracted from RapidEye for the border region comprising South-Africa, Swaziland and Mozambique
Submitted: 25 February 2015
Accepted: 25 February 2015
Published: 4 November 2015
Accepted: 25 February 2015
Abstract Views: 2240
PDF: 914
HTML: 1092
HTML: 1092
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Similar Articles
- David Gikungu, Jacob Wakhungu, Donald Siamba, Edward Neyole, Richard Muita, Bernard Bett, Dynamic risk model for Rift Valley fever outbreaks in Kenya based on climate and disease outbreak data , Geospatial Health: Vol. 11 No. 2 (2016)
- Robert Bergquist, Anna-Sofie Stensgaard, Laura Rinaldi, Vector-borne diseases in a warmer world: Will they stay or will they go? , Geospatial Health: Vol. 13 No. 1 (2018)
You may also start an advanced similarity search for this article.