Importance of the mapping unit on the land suitability assessment for agriculture

Land suitability assessment (LSA) provides geospatial information about growing crops where they are best suited and can play a crucial role in addressing contemporary challenges such as feeding 9 billion people by 2050, coping with climate change, and enabling sustainable production. Despite the known limitations of the current mapping units (conventional soil map units) used for LSA, alternative methods to objectively delineate mapping units, such as geographic object-based image analysis (GEOBIA) or geomorphons have never been tested for LSA. The objective of this work is to quantitatively assess the effects of different polygon-based mapping units on LSA for agriculture: 1) conventional soil map units; 2) units delineated semi-automatically using GEOBIA; 3) geomorphons. In addition, the three delineation procedures will be compared with the pixel-based LSA conducted as a benchmark. LSA is conducted within the framework of the existing Romanian rating methodology for land suitability, which was developed based on FAO guidelines for land evaluation. We use georeferenced soil profiles with field-measured soil properties and digital terrain models to digitally map 17 eco-pedological indicators (e.g. soil pH, soil texture, soil porosity, gleization, carbonate content, humus content). Based on several lookup tables, these maps are transformed into digital maps with suitability ratings for 14 crops, 7 fruit trees, and 2 land-use types, ranging from 0 (not suitable) to 1 (maximum suitability). The product (multiplication) of the 17 maps with LSA ratings is the final suitability map for each crop and land use. Overall, the best maps were obtained when the LSA was conducted using the GEOBIA units (similar accuracy to the pixel -based approach), whereas geomorphons and conventional soil map units resulted in much poorer maps. GEOBIA is much more suitable for LSA than the conventional soil map units and geomorphons, showing a much higher accuracy and internal homogeneity. Another conclusion is that the LSA based on conventional soil map units recorded the poorest accuracies by far. Our results show that the GEOBIA-based units or pixel-based approach are the right choices when conducting LSA, however, if the map user (eg. farmer, land manager) needs delineated units as semi-permanent and stable regions to manage them as stable spatial entities then GEOBIA technique should be used for LSA.

Automated summary

Land suitability assessment (LSA) is crucial in addressing challenges like food security and climate change. This study compared different mapping units for LSA and found that GEOBIA units performed the best, while geomorphons and conventional soil map units resulted in poorer maps.