Geostatistical Analysis of the Relationships between Land Use and Geodiversity Index in the Água Branca Watershed, Itirapina (SP)

• Grant number: 25/15578-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2025
• End date: September 30, 2026
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Denise Balestrero Menezes
• Grantee: Matilde Eira-Velha Rodrigues
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Changes in land use and occupation, driven by urban growth and the advancement of productive activities, have caused significant environmental challenges, such as the degradation of natural areas and the contamination of water resources. These dynamics intensify socio-environmental conflicts and modify the characteristics of the physical environment, highlighting the need to understand the relationships between land use and geodiversity. Geodiversity, understood as the natural variety of geological, geomorphological, pedological, and hydrological components, plays an essential role in environmental conservation, although it has been threatened by human interventions. Given this scenario, it is essential to analyse how changes in land use affect and are conditioned by the physical characteristics of the territory, with a view to guiding more sustainable territorial planning strategies. Therefore, this study takes a research area in the Água Branca Stream watershed, located in Itirapina/SP. The watershed has a variety of land uses, including urban, rural, industrial, and environmental conservation areas, within the Cerrado biome, which is quite fragmented at present. The proposed methodology involves collecting cartographic data, calculating the Geodiversity Index (GI) and mapping land use, in addition to applying the Land Use Diversity Index (LUDI). Geographic Information System (GIS) tools and spatial interpolation will be used, while geostatistical analysis, using Pearson's correlation, will enable the identification of critical areas and potential socio-environmental conflicts. The results aim to support geoconservation and land use planning strategies, aligned with the Sustainable Development Goals, which will be systematised in a doctoral project.