Abstract:
A study was conducted in Lushoto, District, Tanzania to identify farmers’ perceived agricultural land value determinants to establish determinants for agricultural land valuation across different land use types. Remote sensing and GIS techniques were used to identify dominant agricultural land uses for screening the agricultural land value determinants across the land uses. Household survey, key informant interview, and focus group discussions were used to explore farmers’ criteria. Content analysis was used to transform verbal information into numerical data to examine the agricultural land value determinants. Relative Importance Index was used to determine the relative agricultural land value with respect to land uses, agricultural land value determinants, and land types. Binary logistic regression was used to establish relationships between farmers’ perceived agricultural land value and determinants. Dominant identified agricultural land uses were: agroforestry (41% – 60%), crop cultivation (13% – 43%), woodlots (2% – 8%) on the hills and sloping lands, vegetable cultivation (8% – 12%) in the valley bottoms and, open spaces and settlements (1% – 9%) on the lower slopes. Land under vegetable cultivation was highly valued with Relative Importance Index (RII = 0.76), followed by agroforestry (RII = 0.64), woodlot (RII = 0.6), crop cultivation (RII = 0.59), and Open spaces and settlements (RII = 0.38). Valley bottoms were the most valued lands (RII of 0.853) when compared to other lands. Farmers’ identified physical and social-cultural determinants for valuation of agricultural land were: topography, soil fertility, nearness to water, nearness to road, aesthetic, heritage, and management practice(s). Farmers’ perceived determinants that were significantly higher (p < 0.05) across the land uses were nearness to water, nearness to road, soil fertility, aesthetic, heritage, and management practices. Agricultural land valuation involving farmers is a new paradigm shift in the land valuation process, hence further studies are recommended in diverse agro-ecosystems landscapes.
