Quantitative soil mapping in Sudan−a systematic review

Quantitative soil mapping (QSM), including both digital soil mapping (DSM) based on the scorpan concept and approaches that rely on geostatistical approaches (GeoSA), is important to provide information to make informed decisions for sustainable soil management and land use planning, especially in developing countries. This work provides a systematic review of QSM literature focused on Sudan between 2000 and 2024. In the literature search, we identified 27 QSM articles for Sudan, with the largest number of articles published in 2023. The majority of the QSM (16 articles) utilized a GeoSA for prediction and mapping, while the rest (11 articles) applied the DSM-based scorpan concept. Ordinary kriging was the most used GeoSA, while machine learning algorithms coupled with environmental covariates (ECOVs: i.e., remote sensing data and terrain attributes) only appeared in recent years. Most studies targeted the 0–60 cm soil depth interval, and soil pH and salinity/sodicity were the soil properties most commonly mapped across the country. Only 30 % of studies provided uncertainty estimation along with model assessment. QSM studies in Sudan are still at their early stages in terms of predictive models applied, ECOVs utilized, and utilization of DSM information. Several challenges and research gaps were identified in the current literature that should be investigated in future studies. We recommend the establishment of an international team including Sudanese scientists and interested scientists from other countries to collaborate in research projects that would improve QSM in Sudan, specifically reliance on DSM. Meanwhile, the present collaboration between the Agricultural Research Corporation, Sudan, and the United Nations Food and Agriculture Organization could be upgraded to include more advanced technologies to support a national DSM program that would transform the conventional objective of QSM (i.e., map production) into operational goals.