Identifying large-scale land acquisitions and their agro-ecological consequences : a remote sensing based study in Ghana

Sammanfattning: Today there are more than 45 million hectares (ha) of concluded large-scale land acquisitions (LSLAs) in the low- and middle- income countries around the globe. Whether LSLA is referred to as land grabbing or land investment, LSLA means that the right to utilise land is moved from the local people to investors. Few studies investigate agro-ecological consequences and water use of LSLAs. Hence, this study aims to (1) identify LSLAs and their previous land use in Ghana, and (2) investigate the suitability of the current crops choice of LSLAs and compare with the previous crop choice of residents. The identification of LSLAs and previous land use is based on interpretation of satellite images and additional literature and statistics on land use and land covers of Ghana, whereas the results of agro-ecological suitability are generated from a global agro-ecological zoning (GAEZ) model. Eventually 20 LSLAs was identified, however their locations were confirmed with different levels of certainty. The previous land use was then determined and four different land use classes were found: small-scale farming, multifunctional land use, commercial forestry and large-scale cultivation. A crop suitability index (CSI) was generated for previous and current crops and the results showed that the CSI had increased significantly (p < 0.05) due to the LSLAs. The identification of LSLAs and the determination of previous land use using remote sensing were time consuming and field observations is needed to fully assess the certainty and the significance of the method. The increasing CSI indicate that either current crop choice or management are more suitable for the areas than previous crop choice or management. However, a combination of agro-ecological suitability and socio-economic suitability is required to obtain a holistic view of the consequences of LSLAs. Nevertheless, this study managed to identify LSLAs with open access data and remote sensing as well as assessing the agro-ecological suitability of the crops of the LSLAs.