Aerial Mapping of Agricultural Areas Using Drones
The last field survey done in the UAE was in 2005 and since then the Ministry has been relying heavily on statistical data from the 2005 survey, thus creating the need to have a new agricultural survey done with high accuracy, speed, and low cost. A drone-enabled aerial mapping system was used to generate high-resolution highly efficient aerial data over 1100 square kilometre within 12 months, at a cost of less than five times the cost of a field survey, and obtaining 52 parameters statistical data.
Field surveys usually require 36 months to cover all farming areas. Using a drone-enabled aerial mapping system, the project was achieved within 12 months. Moreover, the drone-enabled project requires one fifth of the cost of using the traditional field surveying way. The importance of the project was to identify the numbers and areas of land planted with trees, which represent sustainable crops, or those planted with seasonal crops such as vegetables fruits, as well as all kinds of field crops. This gives a clear picture that helps to predict and study the quantities of production that can be obtained, recognizing the areas planted with forage that represent a necessity for the development of animal production, which in turn also allows the Ministry of Climate Change and Environment to draw up a plan for the possibility of self-sufficiency in some types of feed and start reducing the quantities imported from abroad. This will also help the Ministry to provide the necessary support to increase the productivity and effectiveness of these feed planted areas so as to contribute to boosting animal development in a sustainable manner, and resource efficiency, developing future plans for marketing agricultural products in the local market and determining the extent of their qualification for international accreditation for sustainable agricultural products. This in turn will promote sustainable agricultural practices, and unify the agricultural platform at the federal level, updating it in a manner that raises the results of the country's competitive and international indicators.
Impacts of the project are:
- Achieving the goals of sustainable development by making optimal use of the country's resources and preserving the environment;
- Including the optimal and sustainable use of water and the extent of expansion in applying the concepts of sustainable agriculture and preserving the environment;
- Studying the self-sufficiency in some agricultural products and the possibility of opening their export to foreign markets, thereby improving the country's trade balance;
- Identifying the effect of climate change resulting from agricultural production by estimating the amount of carbon dioxide associated with agriculture, especially forecasting the amount of agricultural waste, which in turn can be recycled and converted into valuable products;
- Establishing contingency and crisis plans for biological security that are closely related to agricultural machinery and animal diseases in a manner that covers all farms across the country;
- Utilizing modern technology in aerial surveying using drones, which places the UAE among the top five countries in the world in terms of area surveyed using unmanned aerial vehicles, and the first to employ this technology to map as many as 50 Statistical statements; and
- Collating more than 12 terabytes of high resolution pictures, which enabled to obtain some important algorithms in the field of census through aerial imagery.
Tools & technology are:
- Fixed wing drones;
- High Resolution RGB orthomap (ground sampling distance 5cm). File format: geo TIFF(.tiff), KML tiles (.png/. Kml). Compatible with: Esri ArcGIS, Global Mapper, QGIS, Autodesk, DraftSight, Geo media, Erdas Imagine, Google Earth and all leading Brands of remote sensing & GIS software; and
- Multispectral Orthomaps (ground sampling distance 15 cm). File format: geo TIFF (, tiff), .shp. Compatible with: SMS (Ag leader), AgPixel, QGIs, Esri ArcGIS, Global Mapper & all leading brands of GIS software. Due to time constraint, if the project was delayed for external reasons, the process could be speeded up by not collecting Multispectral data and focus only on RGB, so the project could be delivered on time. This will only affect vegetation data, but all counts and GIS will not be affected.
- 3D DSM (Digital Surface Model) (ground Sampling Distance 5 cm). File format: wavefront obj. Compatible with: Autodesk, Bentley ccViewer, 3D Reshaper.
- Contour Map: (Ground Sampling distance 5 cm). File format: dxf,.shp. Compatible with: Valcan, I‐site Studio, Autodesk, DraftSight, Esri ArcGIS, Surpac and all leading brands of remote sensing and GIS software.
Future plans include utilising various methods to sustain data updating through several initiatives such as using of high-resolution satellite imagery to identify changes in areas and permanent crops, and using the internet of things to monitor crop health and productivity.
What Makes Your Project Innovative?
The Drone-based Aerial Mapping of Agricultural Areas Survey project undertaken by the Ministry of Climate Change and Environment (MoCCAE) seeks to establish an accurate database of information on farms in the country.
The project surveyed farms to understand their total number and the area of each farm, as well as to identify those classified as agricultural holdings - subdivided into seasonal, year-round, and field crop farms, livestock holdings, and mixed holdings. MoCCAE received benefits such as: Faster turn-around, higher accuracy, higher resolution, additional granularity, distance & volumetric measurements, and compatibility with existing GIS software. Additional benefits include the ability to obtain data in Orthomosaic, 3D Map, Point Clouds, Contour Map, etc,.
The project positioned the UAE among the top five countries in the world in terms of area surveyed using unmanned aerial vehicles, and the first for the number of statistical categories mapped using this technology.
What is the current status of your innovation?
The project is considered to be 100% completed, as aerial photography has been completed, and the data extracted from the pictures have been analysed and uploaded within the prepared geographical platform. In August 2018, MoCCAE launched the pilot phase of the project in Ras Al Khaimah to validate the technology’s operational efficiency and the accuracy of the data collected. Results indicated that drone-based aerial mapping ensuring 90-95 percent accuracy of the data. The pilot phase involved remote sensing and aerial imagery of Wadi Al-aim in Ras Al Khaimah.
Collaborations & Partnerships
This project was conducted with the support of all relevant authorities, from the Ministry of Defence, Civil aviation, urban planning statistical agencies and local authorities responsible for agriculture. These entities have joined forces to obtain a unified ultra-accurate agricultural platform at the federal level accompanied by clear weather images in order to provide decision-makers with accurate data to develop future plans for the country's agricultural sector.
Users, Stakeholders & Beneficiaries
All farmers will benefit from this project, as they will be able to request all agricultural extension services in an efficient manner. It will also enable MoCCAE to define agricultural support programs in a large and productive way so as to determine the necessary agricultural plans for local production in order to boost the economy and support farmers through establishing sales channels for local produce, which in turn enable the farmers to increase their income.
Results, Outcomes & Impacts
Including phase two, the project covered 1,100 square kilometres of agricultural lands across Dubai (188 sq km), Sharjah (276 sq km), Ras Al Khaimah (332 sq km), Ajman (52 sq km), Umm Al Quwain (65 sq km), and Fujairah (135 sq km). By mapping as many as 51 categories of statistical data, the project provided a wealth of information to inform decisions and shape future strategies, as well as develop agricultural extension services for farmers and sales channels for local produce.
The types of data collected through the innovative project include area of windbreaks, infertile land area, area of farm buildings and facilities, number of wells in a farm, and livestock population (camels, cows, sheep, goats, and horses, among others). In addition, data on farm area and geographical boundaries, farm classification (crop farm, animal farm or mixed), area of temporary and permanent crops, number of palm trees and other fruit trees, as well as areas of protected agriculture .
Conditions for Success
The beginning of 21st century witnessed a growing interest in unmanned aircraft in almost all developed countries. There is no question or doubt regarding technical viability or operational utility of UAVs. Success of UAVs in developed countries represents a historic opportunity to exploit transformational capabilities of this leading technology to support life services. There are four major factors which are the symbol of economic growth for any developing country: agriculture, energy, living standard and the ability to mitigate impacts of climate change. UAV can help in many ways to increase and to sustain the development of the agricultural sector in countries. Drones fitted with payloads such as cameras, enable governments to get a comprehensive view of their farming areas by flying at low altitudes. Using much advanced sensors like hyper spectral, Infra-red imaging,
Often referred to as unmanned aerial vehicles, or UAVs, drones were most commonly associated with military or police operations, but with advancement in information technology over the last two decades, cheaper and smaller sensors, better integration and ease-of-use options, this tool has started revolutionising the way geospatial data is collected in many countries. Monitoring large, rugged areas, with the use of photogrammetry, image processing and ground control points, the captured imagery could provide a base for collecting all the 2D and 3D features and data that contribute to solving the problems in modelling and visualizing the desired areas
Among the lessons learned for the future, it is necessary to specify some pre-flight statement, such as farm boundaries, ownership and data of landlords, and the goal of owning them before flying over them, in order to determine the number of documented regular and random farms.
This issue was later remedied in coordination with the agencies responsible for granting, lands and urban planning in the country to compare the results of drone pictures with documented property maps.