Improving the Latin America and Caribbean Soil Information System (SISLAC) database enhances its usability and scalability.

Spatial soil databases can help model complex phenomena in which soils are a decisive factor – for example, evaluating agricultural potential or estimating carbon storage capacity. The Latin America and Caribbean Soil Information System, SISLAC, is a regional initiative promoted by the Food and Agriculture Organization’s (FAO) Latin America and the Caribbean Soil Partnership to contribute to sustainable management of soil. SISLAC includes data from 49 084 soil profiles distributed unevenly across the continent, making it the region’s largest soil database. In addition, there are other soil databases in the region with about 40 000 soil profiles that can be integrated into SISLAC and improve it. However, some problems hinder its usages, such as the quality of the data and their high dimensionality. The objective of this research is evaluate the quality of the SISLAC data and the other available soil databases to generate a new improved version that meets the minimum quality requirements to be used for different purposes or practical applications. The results show that 15 % of the existing soil profiles had an inaccurate description of the diagnostic horizons and 17 % of the additional profiles already existed in SISLAC; therefore, a total of 32 % of profiles were excluded for these two reasons. Further correction of an additional 4.5 % of existing inconsistencies improved overall data quality. The improved database consists of 66 746 profiles and is available for public use at https://doi.org/10.5281/zenodo.7876731 (Díaz-Guadarrama and Guevara, 2023). This revised version of SISLAC data offers the opportunity to generate information that helps decision-making on issues in which soils are a decisive factor. It can also be used to plan future soil surveys in areas with low density or where updated information is required

Assessment of Land Cover and Land Use Change Dynamics in Kibwezi Watershed, Kenya

Land use and land cover (LULC) parameters influence the hydrological and ecological processes taking place in a watershed. Understanding the changes in LULC is essential in the planning and development of management strategies for water resources. The purpose of the study was to detect changes in LULC in the Kibwezi watershed in Kenya, using geospatial approaches. Supervised and unsupervised classification techniques using remote sensing (RS) and geographical information system (GIS) were used to process Landsat imagery for 1999, 2009, and 2019 while ERDAS IMAGINE™ 14 and MS Excel software were used to derive change detection, and the Soil and Water Assessment Tool (SWAT) model was used to delineate the watershed using an in-built watershed delineation tool. The watershed was classified into ten major LULC classes, namely cropland (rainfed), cropland (irrigated), cropland (perennial), crop and shrubs/trees, closed shrublands, open shrubland, shrub grasslands, wooded shrublands, riverine woodlands, and built-up land. The results showed that LULC under shrub grassland, urban areas, and crops and shrubs increased drastically by 552.5%, 366.2%, and 357.1% respectively between 1999 and 2019 with an annual increase of 35.55%, 35.38%, and 33.86% per annum. The area under open shrubland and closed shrubland declined by73.7%, and 30.4% annually. These LULC transformations pose a negative impact on the watershed resources. There is therefore a need for proper management of the watershed for sustainable socio-economic development of the Kibwezi area

Harmonization service and global library of models to support country-driven global information on salt-affected soils

Abstract Global distribution of salt-affected soils (SAS) has remained at about 1 billion hectares in the literature over the years despite changes in climate, sea levels, and land use patterns which influence the distribution. Lack of periodic update of input soil data, data gaps, and inconsistency are part of the reasons for constant SAS distribution in the literature. This paper proposes harmonization as a suitable alternative for managing inconsistent data and minimizing data gaps. It developed a new harmonization service for supporting country-driven global SAS information update. The service contains a global library of harmonization models for harmonizing inconsistent soil data. It also contains models for identifying gaps in SAS database and for showing global distribution where harmonization of available data is needed. The service can be used by countries to develop national SAS information and update global SAS distribution. Its data availability index is useful in identifying countries without SAS data in the global database, which is a convenient way to identify countries to mobilize when updating global SAS information. Its application in 27 countries showed that the countries have more SAS data than they currently share with the global databases and that most of their data require SAS harmonization