GREES - Space Apps Challenge

GREES| Sustaining Our Planet for Future Generations

Awards & Nominations

GREES has received the following awards and nominations. Way to go!

Local Peoples' Choice Winner

Global Nominee

Sustaining Our Planet for Future Generations

There is concern worldwide that environmental issues we face today will have an impact on future generations. Your challenge is to create a way to communicate the importance of environmental responsibility to people of all ages.

FoodMap App

Summary

The FoodMap project uses different databases to characterize the scenario of agricultural production in the world, in order to propose a solution to the scarcity of food. It identifies anthropized areas in the current production scenario, creates an ideal scenario based on agronomic criteria, and separates the locations for optimizing production by defining the suitability for use with perennial, annual or pasture crops.The difference is to map land use,highlighting the unused areas on the planet, to propose productive use without increasing deforestation and burning,since the use of anthropized areas will promote an efficient and sustainable production for the current and future generation.

How We Addressed This Challenge

The prototype of a land use and land mapping application was developed. The great importance is that this application correlates different databases about land use and occupation at different work scales. It integrates data, generating production deficit maps by area, indicating the best use for the analyzed location. It is expected that the application recognizes patterns of occupation, integrates and recommends the appropriate use of the soil, in addition to obtaining maps with good accuracy that help decision making, reducing possible underutilization of areas. As a final result, we want to increase food production, which meets the growing demand of the expanding population, without deforesting new areas, preserving the environment for future generations.

How We Developed This Project

Our team is made up of students and teachers of agronomy and environmental management, and there is no challenge more present in our daily lives as professionals whose object is work with nature and its resources. Our approach was based on the recurring concern with the global population increase and how it accelerates deforestation in the search for new areas to produce food, and we know that there is a way to increase the productivity of the areas in use in a way that meets the demand without the need for deforestation. The project was developed using the Marvel App application to create the application screens, which can be seen at the link https://marvelapp.com/prototype/f6211je.

The JavaScript language on the Google Earth Engine (GEE) platform was used to develop the initial scripts needed for the application frontend. The QGIS 3.10 software was useful for the initial processing of the classification of land use and cover obtained from the Mapbiomas project.

Our team found it difficult to not have people from different areas of knowledge, formed only by two students with some experience in algorithm development. We didn't know how to split up so that it would pay off during Friday and part of Saturday. One of the participants passed almost the entire challenge without electricity and three other students were without it.

Our team was able to understand the initial idea proposed by a participant in order to be replicable, we developed the flowchart for creating the algorithm and wrote part of the algorithm, we were able to prototype for the first time through a friendly interface application. We were able to deliver everything that was proposed as the 1st hackathon for most of the members.

How We Used Space Agency Data in This Project

In summary, the Clima Hazards Group InfraRed Precipitation with Station data (CHIRPS) data sets with spatial resolution of 0.05 ° of arc, Shuttle Radar Topography Mission (SRTM) with resolution of 30 m, provided by NASA JPL with resolution of 1 second of arc, and the Mapbiomas project.

For prototyping, a 2019 land use and land cover classification obtained from the Mapbiomas project was used as a reference for anthropized areas. These areas became limits for filtering the CHIRPS data set from which precipitation was obtained to characterize the areas' annual rainfall regime. In the same way, they also served to filter SRTM data, which was used to obtain the elevation information of the areas. And through the association of these two information (degree of elevation and precipitation), our intention was to define the ideal agricultural use of the areas.

Project Demo

In this video we demonstrate in 30 seconds, the central idea of our challenge.

https://youtu.be/6qj9GTYeHXg

In this video we demonstrate in a few minutes, the central idea of the challenge, detailing the data used, the objectives and expectations of results to be achieved.

https://youtu.be/9Hh9YAS3nlI