Satellite Imagery Solution for Social Good | White Paper by Gramener



[White Paper] - Using Satellite Imagery and
Deep Learning to Predict Quality of Life

Download the white paper to discover a novel approach to calculating Quality of Life in the U.S. at county level. We obtain data using open-access satellite images and leverage Deep Learning.  

Throughout the white paper you will learn:

  • How we can capture metrics like vegetation index and water index at county level in the United States using open-access satellite data  
  • A novel approach for assigning weights and calculating Quality of Life in these locations using satellite and other data 
  • How to interpret the results and assign a QoL metric for each county


 Throughout history, the presence of water bodies, agricultural land, and the surplus of food have led to the beginnings of society and civilization. This foundation has been fortified by factors such as population density, expansion of urban areas, and industrial areas. Quality of life (QoL) shows the standard of living, health, and happiness of people in the society. There can be several factors that decide the QoL of a region. For urban areas, the factors could be: • Education • Employment • Healthcare facilities • Transportation • Industrialization In rural areas, significant factors could be: • Availability of agricultural land • Water bodies The need for measuring QoL QoL changes with several factors, including urbanization, industrialization, population density, wealth, and employment. These factors have greatly influenced the lives of people in terms of migration to different cities, economic distribution, and government decisions in providing facilities. Let’s take an example. • In 2019, 70% of people moved out of Illinois due to high property taxes (2.37%) and moved to states such as South Carolina and Texas with lower property taxes. • A high percentage of people moved out of Arkansas, Alabama, Mississippi, and Missouri, where job opportunities were less, to states such as Washington, California, and Texas, where they could find employment more easily and the economic situation is better. Thus, there is a need for accurate, up-to-date, and periodical QoL measurements to develop efficient decision-making mechanisms to manage and plan cities or counties effectively. Evolution of Satellite Imagery To get the overall dynamics of a county/city, it is essential to visit every region and capture parameters pertaining to QoL, but this is painstaking, and it involves a lot of manual effort and time. Also, the collected data may not have covered all the regions and time stamps and are prone to errors. To avoid this, we propose an alternative approach that can solve the problem more efficiently with minimal human effort.