Multi-criterial analysis for modelling Matengo/Ngolo pits agro-ecological zones using fuzzy logic in Southern Tanzania
Abstract It has known that grain production is declining globally, leading to food insecurity becoming increasingly apparent in tropical countries, particularly in Sub-Saharan Africa. Countries in Sub-Saharan Africa must concentrate on indigenous agricultural methods to mitigate the impact of climate change on grain production while preserving ecological balances and achieving sustainable goals. Matengo/Ngolo pits, practised on steep slopes in the Matengo highlands, southern Tanzania, are indigenous knowledge invented by local communities over the past 300 years. Despite its effectiveness in increasing agricultural productivity, soil moisture retention, and other environmental advantages, Matengo/Ngolo agricultural technique has resulted in severe land cover changes that substantially influence other producing sectors. Understanding the agro-ecological zones is essential for enhancing policy development for the expansion and restrictive of Matengo/Ngolo pits practice that intercepting by decreasing its influence on the shrinkage of other ecological services, achieving sustainable agricultural practice in the Matengo highlands. Therefore, this study employed the multi-criteria parameters under the fuzzy logic algorithm in ArcGIS 10.8 for modelling the Matengo/Ngolo pits agro-ecological zone to realize sustainable land management in Matengo highlands.