High-Level Project Summary
In the world food chain agriculture arguably plays the biggest role, therefore, we must make agriculture more sustainable. According to the UN, more than 600 million people worldwide are underfed. Therefore, there is a need to develop technology to help farmers and food producers.TECH-AGRO is a service aimed at government and food producers, which allows you to analyze and manage agricultural fields in particular as well as country agricultural sector using geospatial data and Satellite Data, in order to support farmers’ decisions by improving resource use efficiency, productivity, quality, profitability and sustainability of agricultural production;
Link to Final Project
Link to Project "Demo"
Detailed Project Description
TECH-AGRO is a web geographic information system (GIS) app in a form of an interactive Dashboard. It displays agricultural data on a MAP as well as graphs of the data that are being visualised.
It uses open-source satellite data such as ESA Sentinel 2 and NASA LandSat 8,9 to calculate vegetation and biophysical indicators. In addition, open source Food and Agriculture Organisation (FAO) data, as well as country census data, are also provided;
The main data are as follows:
As we have Angola as a case study, the app shows data about the 4 Crops produced in Angola: Corn, Banana, Rice, and Coffee. Using the app it is possible to know the quantity of each crop in each province of Angola, as well as analyze how the production has changed over time. The website is very interactive and easy to use, this will allow anyone to be able to use the App and interpret country-level Agricultural data. Since the data used was open source anyone can use the data available in the app.
Data Displayed
TECH-AGRO monitors vegetation health, using satellite images that measure multiple regions of the electromagnetic spectrum (EM). The vegetation health is monitored using the Normalized Difference Vegetation Index(NDVI) and other radiometric indexes. Those indexes are obtained from the satellite image using band arithmetic (combining multiple satellite images measuring different regions of the EM.
By plotting the Crop production in each province with the crop produced each year, the app user is able to have insight into which province does not have enough food.
TECH-AGRO give many indicators such as Land Use, nationwide, this will allow the user to know how the land use is changing, in addition, it gives indicators such as what is the percentage of urban areas, vegetation or Crop Land. Other indicators include Soil Moisture and country population by province per year.
TECH-AGRO use open source data to provide the following information:
- Vegetation Health
- Land Use
- Crop Produce in each Province
- Crop yield in Each Province
Future
We plan to keep developing TECH-AGRO so that it can be used by everyone involved in Agriculture Production. From Government to the farmers.
We plan firstly to make TECH AGRO a tool that can answer 3 main questions at the country level. What is Produce, How much is produce and Where is Produced. This will be achieved by using satellite data mainly Sentinel 2 and Landsat 8 data, as well as machine learning algorithms and this information, will be more useful for governments.
As far as producers are concerned, we plan to develop the app so that it can monitor crop growth by giving vegetation indicators as well as biophysical indicators. One of the main challenges is to provide yield estimation, to help plan the harvest. Other indicators that we plan to include are field productivity in other to create prescription maps, and digital elevation model to better plan for irrigation.
Space Agency Data
The data used are as follow:
- NASALandsat: To calculate vegetation index, to monitor crops.
- Sentinel 2 Images: To extract Land Use, using machine Learning
- FAO crop data: To present the crop produced in each provinces.
Hackathon Journey
Participating in this hackathon has been a great experience, we had to work under pressure as we only learned about the hackathon one week prior. As in Angola, we have our own challenges we decided to participate In this category so that we can solve a problem close to our heart.
Even though it was challenging, we took advantage of open-source tools to create our app. Usually in those project data acquisition is one of the most difficult aspects, therefore, we found that using NASA satellite data as well as other space agency data was really helpful, and we are happy to have created and finalised our first prototype.
References
NASA LandSat 8
ESA Sentinel 2
FAO (Food and Agriculture Organization)
Tags
#TECH-AGRO,#Agriculture, #Satellite, #Angola, #GGPEN, #Space,#Spaceapps