# How Will Rwandan Land Use/Land Cover Change under High Population Pressure and Changing Climate?
## 3 Results
### Simulation of Future Land Use/Land Cover Pattern  
Driven by the demand for land use in the future, the PLUS model was used to simulate LULC changes in different years. The simulation results are shown in Figure 7. The results indicate that the actual land use in Rwanda in 2015 (Figure 7a) and the simulated land use (Figure 7b) were very similar. The kappa coefficient of the two LULC images was 0.7325, indicating that the two images were highly consistent. The FoM value was 0.3584, which was much higher than the FoM value obtained by [PERSON] et al. (2016) (0.1962), who used the PLUS model to simulate LULC in mainland China. The FoM value obtained herein was also higher than that obtained by [PERSON] et al. (2015) (0.2514), who simulated LULC in Wuhan. This indicated that the simulated LULC pattern was almost the same as the actual pattern, and the simulation results were credible. In terms of temporal evolution, the forest area in Rwanda was projected to decrease gradually from 4326.64 km\({}^{2}\) in 2015 to 2332.72 km\({}^{2}\) in 2050. Both grassland and cropland showed an increasing trend, increasing, respectively by 1180.01 km\({}^{2}\) and 999.09 km\({}^{2}\). Wetlands and water decreased by 343.36 km\({}^{2}\) and 117.66 km\({}^{2}\), respectively, and urban land expanded from 363.29 km\({}^{2}\) in 2015 to 637.97 km\({}^{2}\) in 2050. In this study, the agro-ecological zones proposed by [PERSON] et al. (2015) were used as the standard to calculate the future LULC distribution in Rwanda (Appendix B Figure A1). [PERSON] et al. (2015) divided Rwanda into six eco-agricultural zones, namely the Eastern Savanna (ES), Eastern Plateau (EP), Bubureka Highland (BH), Central Plateau and Collines (CP), Volcanic Highland (VH), and Congo-Nile Crest (CNC). The main LULC types in ES and EP were grassland and cropland, and both regions demonstrated a trend of increasing grassland and decreasing cropland (Figure A2a,b). BH and CP primarily consisted of cropland, which demonstrated an increasing trend in both regions. It is noteworthy that  
Figure 7: Land use maps of Rwanda for the period 2015–2050; (**a**) observed LULC in 2015; (**b**) scheme 2015. (**c**) simulated LULC in 2020; (**d**) simulated LULC in 2030; (**e**) simulated LULC in 2040; (**f**) simulated LULC in 2050.  
the forest land in BH and CP, although not large, exhibited a decreasing trend in both regions (Figure A2c,d). VH mainly consisted of forest and cropland, followed by urban land; the woodland and cropland area in this region decreased, but the urban land area increased significantly (Figure A2e). The main LULC types in CNC were cropland and forest. The forest area showed a decreasing trend, whereas the cropland area exhibited an increasing trend (Figure A2f). To further identify the spatial change characteristics of the main LULC types in the study area, the hotspots of the changes in area for forest, grassland, cropland, and urban land were identified (Figure 8). The regions of change (decrease) in forest land were mainly distributed in the western parts of BH, CNC, and PC. The regions of change (increase) in grassland were mainly distributed in the southern parts of ES and EP. The regions of change (increase) in cultivated land were essentially the same as those of forest land. The changes in urban land use were mainly caused by the expansion of cities, so the regions of change for cities were mainly distributed in the areas surrounding the original cities. The regions of change (decrease) in forest land were mainly distributed in the western parts of BH, CNC, and PC. The regions of change (increase) in grassland were mainly distributed in the southern parts of ES and EP. The regions of change (increase) in cropland were basically the same as those of forest land. The change in urban land was mainly due to the expansion of cities, so the regions of change for cities were mainly distributed in the areas surrounding the original cities.