Abstract
Water availability and high soil fertility make inland valley landscapes suitable for sustainable rice-based cropping. In this study, Random Forests statistical analysis was used on a database of 499 surveyed inland valleys in four study zones in three West African countries. The goal of the study was to assess parameters that
indicate (are predictors for) high potential for development of rice-based systems in inland valleys. These parameters are related to the biophysical (hydrology, soil, climate, and topography) and socio-economic (demography, accessibility, and markets) environments. Farmer group surveys and secondary data from existing
publicly available spatial data sets were used.
The analysis revealed that, across the four research areas, the following parameters were relevant predictors for rice development: (1) distance from the inland valley to the nearest market; (2) distance from the inland valley to the nearest rice mill; (3) population density in the immediate environment of the inland valley; (4) total nitrogen in the top 20 cm of the soil profile; (5) land elevation; and (6) soil texture on the upper slope of the inland valley. Several predictors were highly important for specific research areas, but not for all, thus showing the diversity in the studied agricultural landscapes. These predictors included soil fertility management, source of irrigation water, and the percentage of female farmers in the inland valley. The identified relevant predictors
will be used to map the potential rice production development of the inland valleys. This will help development agencies to assess their zones based on quantitative analysis for inland valley potential development.
indicate (are predictors for) high potential for development of rice-based systems in inland valleys. These parameters are related to the biophysical (hydrology, soil, climate, and topography) and socio-economic (demography, accessibility, and markets) environments. Farmer group surveys and secondary data from existing
publicly available spatial data sets were used.
The analysis revealed that, across the four research areas, the following parameters were relevant predictors for rice development: (1) distance from the inland valley to the nearest market; (2) distance from the inland valley to the nearest rice mill; (3) population density in the immediate environment of the inland valley; (4) total nitrogen in the top 20 cm of the soil profile; (5) land elevation; and (6) soil texture on the upper slope of the inland valley. Several predictors were highly important for specific research areas, but not for all, thus showing the diversity in the studied agricultural landscapes. These predictors included soil fertility management, source of irrigation water, and the percentage of female farmers in the inland valley. The identified relevant predictors
will be used to map the potential rice production development of the inland valleys. This will help development agencies to assess their zones based on quantitative analysis for inland valley potential development.
Original language | English |
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Pages (from-to) | 86-97 |
Number of pages | 12 |
Journal | Applied geography |
Volume | 96 |
Early online date | 26 May 2018 |
DOIs | |
Publication status | Published - 1 Jul 2018 |
Keywords
- ITC-ISI-JOURNAL-ARTICLE
- n/a OA procedure