Gridded multi-crop suitability mapping using public domain soil and related thematic data

Eleventh amendment of Land Act, 1964 (2010) of Nepal bases classification of land for scientific "on, inter alia, the nature and fertility of soil, geographical situation, environment and climate of the country." Current study uses publicly available thematic soil (percentage Nitrogen content and absolute pH value) and elevation layers data, all of which are publicly available, to generate rank based for crop suitability map. Thresholding parameter ranges for each thematic variable were the optimal ranges of Nitrogen, pH and elevation for individual crops as specified in any standard literature. On each pass, single decision criterion/variabl...  more

Eleventh amendment of Land Act, 1964 (2010) of Nepal bases classification of land for scientific "on, inter alia, the nature and fertility of soil, geographical situation, environment and climate of the country." Current study uses publicly available thematic soil (percentage Nitrogen content and absolute pH value) and elevation layers data, all of which are publicly available, to generate rank based for crop suitability map. Thresholding parameter ranges for each thematic variable were the optimal ranges of Nitrogen, pH and elevation for individual crops as specified in any standard literature. On each pass, single decision criterion/variable was analysed at grid resolution of 250m x 250m for thresholding for a single crop, thus allowing construction of binary layer maps for all set of crops. This map layer was subject to 3 x 3 rolling grid aggregation for obtaining frequency based weights. Finally, a lower resolution grid map was constructed by superimposing several crop layers with grid values populated by their occurance frequency. This discrete information was then presented as images of the crop with various mapping aesthetics to display suitability information. Current approach to is flexible with respect to the number of thematic variables that may be composited to obtain suitability ranking of individual crops, although its strictly required for them to be of same resolution; with respect to the number of crops for mapping as long as thresholding parameters are agreeably defined in literature. The method can also be scaled-up for any larger grid size for aggregation mapping as it relies on a simple rank based statistic. Information value of such maps can be extended by adding crop seasonality information, and by adding first-pass agro-climatological variables such as temperature and precipitation, as they are more readily available.