This presentation focuses on the application of open-source geospatial technologies for crop monitoring by integrating satellite data and weather parameters in Kolhapur, India. The study utilizes freely available satellite imagery, such as Sentinel data, along with meteorological variables including temperature, rainfall, and humidity to analyze crop health and variability.

Using QGIS, various spatial analysis techniques are applied, including vegetation indices (such as NDVI), temporal analysis, and map visualization to monitor crop conditions over time. The integration of weather data helps in understanding the influence of environmental factors on crop growth and productivity.

The study demonstrates how open-source GIS tools can support agricultural monitoring and decision-making, especially in resource-limited regions. It also highlights the importance of combining remote sensing and GIS for sustainable agriculture and early identification of crop stress.

This work is particularly relevant for researchers, students, and practitioners interested in applying open geospatial technologies in agriculture and environmental studies.