Abstract

This special session introduces an exploratory approach combining Earth Observations (EO) and Artificial Intelligence (AI) to enhance our understanding of socio-economic trends across various geographic regions. This integrative method provides a new perspective on the interconnections between economic activities, agriculture, and environmental changes, moving beyond conventional income classifications.

The session will encompass three focused talks:

- Quick and Reliable Socio-Economic Assessments from Remote Sensing and Machine Learning: This talk will discuss the potential of remote sensing and AI in conducting socio-economic assessments.

- Estimating Economic Activity Indicators at the Municipal Level in Mexico Using Nighttime Lights: This presentation will share preliminary insights into using nighttime light data for economic activity estimation at a local level in Mexico.

- Identification of Agricultural Land Use through Remote Sensing and Machine Learning Techniques: It will explore initial findings on the use of these technologies for agricultural land use identification.

Attendees will be invited to consider the emerging role of EO and AI in socio-economic analysis, particularly in relation to Sustainable Development Goals (SDG). The session aims to foster a discussion on the opportunities and challenges in this field, providing a platform for sharing knowledge and experiences in integrating EO and AI for socio-economic and environmental research.