“Bring Back the Land”—A Call to Refocus on the Spatial Dimension of Zimbabwe’s Land Reform

In this article, we argue that research on land reform in the nation of Zimbabwe has overlooked possibilities of integrating geospatial methods into analyses and, at the same time, geographers have not adequately developed techniques for this application. Scholars have generally been captured within the debate focused on the success or failure of the Zimbabwean land reform program, and have neglected to analyze what has occurred where during the process of “fast-track land reform”. To date, no extensive national dataset of land ownership change, and the effect of this change on land use planning strategies, has been developed within the scientific community. As a result, most publications, even very detailed and thorough ones, have been based on regional case studies, broad estimates, or on outdated, cross-referenced statistics. To overcome the lack of spatio-temporal data, we propose an analytic framework to map Zimbabwe’s fast-track land reform and its country-wide effects. It emphasizes the potential of geographic information systems and satellite remote sensing to provide an objective basis for future studies of the subject

“Bring Back the Land”—A Call to Refocus on the Spatial Dimension of Zimbabwe’s Land Reform

In this article, we argue that research on land reform in the nation of Zimbabwe has overlooked possibilities of integrating geospatial methods into analyses and, at the same time, geographers have not adequately developed techniques for this application. Scholars have generally been captured within the debate focused on the success or failure of the Zimbabwean land reform program, and have neglected to analyze what has occurred where during the process of “fast-track land reform”. To date, no extensive national dataset of land ownership change, and the effect of this change on land use planning strategies, has been developed within the scientific community. As a result, most publications, even very detailed and thorough ones, have been based on regional case studies, broad estimates, or on outdated, cross-referenced statistics. To overcome the lack of spatio-temporal data, we propose an analytic framework to map Zimbabwe’s fast-track land reform and its country-wide effects. It emphasizes the potential of geographic information systems and satellite remote sensing to provide an objective basis for future studies of the subject

Evaluating Crop Area Mapping from MODIS Time-Series as an Assessment Tool for Zimbabwe's "Fast Track Land Reform Programme".

Moderate Resolution Imaging Spectroradiometer (MODIS) data forms the basis for numerous land use and land cover (LULC) mapping and analysis frameworks at regional scale. Compared to other satellite sensors, the spatial, temporal and spectral specifications of MODIS are considered as highly suitable for LULC classifications which support many different aspects of social, environmental and developmental research. The LULC mapping of this study was carried out in the context of the development of an evaluation approach for Zimbabwe's land reform program. Within the discourse about the success of this program, a lack of spatially explicit methods to produce objective data, such as on the extent of agricultural area, is apparent. We therefore assessed the suitability of moderate spatial and high temporal resolution imagery and phenological parameters to retrieve regional figures about the extent of cropland area in former freehold tenure in a series of 13 years from 2001-2013. Time-series data was processed with TIMESAT and was stratified according to agro-ecological potential zoning of Zimbabwe. Random Forest (RF) classifications were used to produce annual binary crop/non crop maps which were evaluated with high spatial resolution data from other satellite sensors. We assessed the cropland products in former freehold tenure in terms of classification accuracy, inter-annual comparability and heterogeneity. Although general LULC patterns were depicted in classification results and an overall accuracy of over 80% was achieved, user accuracies for rainfed agriculture were limited to below 65%. We conclude that phenological analysis has to be treated with caution when rainfed agriculture and grassland in semi-humid tropical regions have to be separated based on MODIS spectral data and phenological parameters. Because classification results significantly underestimate redistributed commercial farmland in Zimbabwe, we argue that the method cannot be used to produce spatial information on land-use which could be linked to tenure change. Hence capabilities of moderate resolution data are limited to assess Zimbabwe's land reform. To make use of the unquestionable potential of MODIS time-series analysis, we propose an analysis of plant productivity which allows to link annual growth and production of vegetation to ownership after Zimbabwe's land reform

RMSE of cropland area comparing different land cover products to national¹ FAO statistics [42].

<p>RMSE of cropland area comparing different land cover products to national<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156630#t001fn001" target="_blank">¹</a> FAO statistics [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156630#pone.0156630.ref042" target="_blank">42</a>].</p

Exemplary visualization of an original and a filtered NDVI-curve, as well as 11 Seasonal Parameters.

<p>Adapted from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156630#pone.0156630.ref059" target="_blank">59</a>].</p

MODIS and Landsat tiles used in this study.

<p>Landsat tile used for the creation of agro-ecological stratified endmembers is highlighted. The rectangular NDVI dataset represents the extent of the NDVI dataset.</p

Accuracy report for NDVI+SP,+NIR+RED, 2004/2005.

<p>Accuracy report for NDVI+SP,+NIR+RED, 2004/2005.</p

Accuracy report for NDVI+SP, 2004/2005.

<p>Accuracy report for NDVI+SP, 2004/2005.</p