Abu Dhabi University| Scanning for Lifeforms

Awards & Nominations

Abu Dhabi University has received the following awards and nominations. Way to go!

Global Nominee

Scanning for Lifeforms

This challenge addresses a pressing global need to track change in biological diversity, which is threatened by human-driven environmental change. Use space agency data to develop innovative ways to detect biological diversity on Earth, track and predict changes over time, and communicate that information to scientists and society.

Vegetation Monitoring using ECOSTRESS Data and Autonomous UAV inspection in the UAE

Summary

Vegetation regions are responsible for protecting biodiversity, sustaining land productivity, and regulating water resources. Urbanization is a leading cause of the generated pressure on these vegetative resources. This, in turn, pushed governments to take action and examine the degradation of these regions over time through traditional and time-consuming methods. In our project, we propose a method for monitoring these regions through the integration of satellite imagery provided by NASA and UAV mission footage. UAVs will be equipped with a camera that can capture high-definition videos of the field. The captured footage is used to construct a mosaic image that represents the area scanned.

How We Addressed This Challenge

In 2017, UAE population witnessed an increase and had reached 9,304,277 people. The income levels and purchasing power had raised, in addition to the growth of the tourism movement. All this had led to increased demand for food. Subsequently, meeting demand, while preserving food quality and safety in unfavorable climatic conditions, is the main driving force for change in the agricultural sector in UAE.

In addition, the pressures and challenges faced by the agricultural sector in the UAE are numerous, and include scarcity of water resources, limited arable land, high production costs, post-harvest losses, agricultural pests, and food safety. However, the limited irrigation water represents the most prominent of these pressures, as the UAE is located in the arid lands, which are characterized by high temperature, increased evaporation rate, less precipitation and scarcity of renewable natural fresh water streams. The increase in agricultural production in light of these two factors, (limited water and agricultural land), this represents the most prominent challenge for the agricultural sector in the UAE.

The project will be implementing a survey of agricultural areas in the country to build a modern and accurate database of agricultural lands. This can be linked with the spatial database of farms and with many other systems, such as the agricultural and veterinary extension system, to ensure the provision of services directed to combat animal epidemics and agricultural pests in more effective ways. The results of the survey will be used to create a database that enables decision-makers to be guided by accurate data to draw and develop policies related to the sector agricultural and food security. 

How We Developed This Project

Vegetation is an aspect of land that needs to be constantly monitored with as much precision and accuracy as possible. It is a vital feature that is responsible for conserving our environment and the ecosystems present in it; and with proper monitoring of vegetation, damaged ecosystems can be gradually restored. With the UAE being a country were mangrove ecosystems are prevalent, it is important to know the significance of theses wide spread plants. Primarily, mangrove forests contain a high level of biodiversity; plentiful species of crabs, birds and fish constitute the mangrove regions in the UAE. More so, mangrove forests affect our lives by protecting costal areas from erosion acting as a buffer zone, and also filtering tidal flows reducing damages and loss of lives caused by potential tsunamis.

Since traditionally, information about green areas required methods that were time-consuming and costly, we decided to automate this process with the help of publicly available data provided by NASA on water stress levels that would significantly decrease the time and money consumption of monitoring green areas.

Initially, a drone is required to be able to carry out missions specified by waypoints. The team settled for a Solo 3DR quadcopter as it can serve that purpose since its autopilot is compatible with the Mission Planner software accessed through the ground station and is used to plan UAV (unmanned ariel missions) autonomous navigation by means of identifying GPS coordinates for the drone to fly to. The drone will fly in a zig-zag manner over the region of interest in order to capture all imagery of the green area by means of an HD visible light camera attached to the gimbal of the drone. The Solo 3DR also has a convenient flight time of around 20 minutes. Finally, we will construct an image mosaic which is defined as a stitched image consisting of non-redundant frames from a captured video. This will allow for easier analysis of the survey image and uncomplicated implementation of image processing techniques. Results from surveys of the same green area at different times can be compared for monitoring purposes. The image mosaicing process will be carried out in a Matlab server.

How We Used Space Agency Data in This Project

For the purpose of this project we are interested in space agency data that allows us to monitor vegetational areas. NASA’s ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer on Space Station) is the instrument which is able to detect the behaviour of plants due to the process of evapotranspiration in which plants release excess water through their leaves. Areas where plants exhibit evapotranspiration are detected by the ECOSTRESS and marked as red areas. The images from the ECOSTRESS database can be extracted, and using a simple color detection algorithm in Matlab, the region of interest can be identified. Furthermore, we can perform morphological operations in order to enhance the quality of our detected regions. With edge detection we can then extract the real-life coordinates of the boundaries of the regions of interest that would allows to plan a flight mission for the drone in a zig-zag manner.

Data & Resources

M. A. Ghazal et al., "Vegetation Cover Estimation Using Convolutional Neural Networks," in IEEE Access, vol. 7, pp. 132563-132576, 2019, doi: 10.1109/ACCESS.2019.2941441.


“ISS: ECOSTRESS,” ISS Utilization: ECOSTRESS - Satellite Missions - eoPortal Directory. [Online]. Available: https://directory.eoportal.org/web/eoportal/satellite-missions/i/iss-ecostress. [Accessed: 2020]. 


L. Burke, “Why the UAE's mangroves are so important - and how to save them,” The National, 16-Jan-2020. [Online]. Available: https://www.thenational.ae/uae/environment/why-the-uae-s-mangroves-are-so-important-and-how-to-save-them-1.848035. [Accessed: 2020]. 

Tags
#biodiversity #nature #vegetation #drone #uav #mosaic #uae
Judging
This project was submitted for consideration during the Space Apps Judging process.