Geospatial imagery can be thought of as the production of location-referenced images. Geospatial images typically contain attribute information as well as spatial information about an area.
The acquisition of such images is useful in a wide range of applications across multiple industries. For example, it can be used for remote inspection of high-value assets that would be difficult and costly to inspect otherwise. It can also be used to survey land before it is developed, for example in corridor mapping when upgrading roads.
This article will present an overview of some applications of location-referenced drone imagery. It will also look at the use of the digital medium format camera in such applications.
Applications of Geospatial Imagery
Drones and Agriculture
Drone imagery is being used to fuel precision agriculture and generally to improve agriculture.
The acquisition of high-quality imagery on farms gives useful insights to farmers. They can know which farm areas are dry, which aids in the efficient use of water. In large farms, drone data can be used to facilitate land management. At large-scale, drones are a fast, cost-efficient method of surveying land.
Careful analysis of large farms, enabled by drone data, can be used to implement better seeding prescriptions, based on slope and elevation data. Accurate data helps make better decisions on replanting, thinning, and pruning.
Phenotyping With UAVs and Drones
Drone imaging has proven instrumental in sustainable and precision farming but it’s also being used to improve food production through another way: Phenotyping. Phenotyping involves the study of the extent to which the physical characteristics of a plant depend on its environment and on its genotype.
Agronomists use phenotyping to improve crops, increasing their yield and reducing susceptibility to diseases.
Phenotyping relies on data. Generally, the more data that an agronomist can sustainably access, the better their results will be.
Traditional methods of collecting data are limiting. For example, the longitudinal assessment of a large number of plants is time-consuming.
Using drones to collect data for phenotyping is paving the way for repeated, extensive, and consistent phenotyping, yielding better results. UAV imagery is being used to automate object-based image analysis in plant phenotyping and assess multiple plant traits over extended periods of time.
Digital Twins
A digital twin can be thought of as a high-resolution representation of a physical asset, usually in 3D. Digital twins are useful in a number of ways:
- They allow asset owners to have a reliable picture of the current condition of assets
- The development of digital twins over time helps understand the rate of deterioration and plan for maintenance
- Digital twins of infrastructure such as power lines and telecommunication units inform maintenance
Drones are proving invaluable in the creation of digital twins. Plug-and-play payload solutions for drones have been developed, enabling them to be easily equipped with multi-sensor data collection tools.
A multi-sensor approach is central to the creation of highly-accurate digital twins that have additional information about the assets under inspection. For example, UV radiation from power lines can be a source of valuable information on their state. The multiple forms of data collected are collated, resulting in a full picture of the state of assets.
Drone Imaging Using The Digital Medium Format Camera
The digital medium format camera has multiple advantages when used in areas such as mapping, surveying, and inspection. It has some advantages over the large format camera, such as lower cost in terms of acquisition and operation. It is also uniquely suited for certain applications, such as the mapping of corridors and the development of true orthophotos.
The medium format camera is increasingly being used in partnership with LiDAR systems to inspect infrastructure. Such use of multiple sensors helps come up with 3D representations of real life objects. According to the quality of sensors used, high-reliability digital twins may even be developed.
Digital twins come in handy in multiple scenarios, from artificial intelligence-powered inspection to the tracking of construction progress. In construction, digital twins of buildings can be overlaid on original designs to show progress and ensure that everything is going as planned.
Apart from a significant decrease in operational costs, the medium format camera is small and lightweight, providing for easy installation on small aircraft and unmanned aerial vehicles (UAVs)
In addition, the camera can produce high quality images thanks to interior orientation parameters that are stable and easy to define.
Applications of the Medium Format Camera
Orthophoto and 3D Model Generation
Orthophotos are images of the earth’s surface that are taken vertically and rectified such that they have the same metric properties as maps. The generation of orthophotos from aerial photographs is called orthorectification. This process is important in the use of geospatial imagery in mapping.
3D city models are useful in urban planning and disaster management, among other fields. The generation of high-resolution images using medium format cameras is crucial to this process.
Corridor Mapping
The term “corridor” is usually used to refer to linear infrastructure projects such as roads, railway, and pipelines. Medium format cameras attached to drones can be used to generate high-resolution data on linear-based projects. Such data is essential in mapping and planning for development.
Rapid Response Imaging
When disasters such as earthquakes occur, rapid response is dependent on the rapid acquisition of up-to-date data. The medium format camera enables the capture of high-resolution data, which can be useful in informing evacuation plans and other critical decisions.
Agriculture
The medium format camera enables species identification and phenotyping with UAVs or drones. Moreover, due to the high-quality data acquired, machine learning models can be trained to automatically identify species and aid in the phenotypic improvement of crops.
The medium format camera is also being used in timber value assessment, disease control and monitoring, and precision farming.
Precision farming involves the data-driven and efficient use of farm inputs to promote sustainability and increase farm profitability.
Remote Sensing
Though large-format cameras have traditionally been the go-to option for remote sensing use-cases, including environmental research and coastal zone monitoring, medium-format cameras are emerging as a more affordable alternative.
The geospatial industry has been witnessing significant growth since the past five years and is continuing to do so due to the emergence of new technologies such as Artificial Intelligence (AI), big data, the Internet of Things (IoT), and Machine Learning (ML).
Global studies have shown that geospatial readiness plays a crucial role in the adoption of digital innovation, contributing significantly to world’s Gross Domestic Product (GDP) as well as optimizing efficiency and cost-effectiveness of the economic sectors such as infrastructure, energy, agriculture, financial services, retail and logistics, and climate and environment, among others.Geospatial analytics collects, analyzes, and displays Geographic Information System (GIS) data and imagery, including Global Positioning System (GPS) and satellite photographs.
Geospatial data analytics depend on geographic data points and specific locations such as a zip code or address of service areas.
These data are utilized for developing geographic models and data visualizations for more precise modeling and predictions of trends.
The global population is adopting and is actively using advanced street maps, satellite imagery, and route planners to gain location intelligence and identify the area of choice.
Such intelligence merges with the capabilities of geospatial technologies, data analytics, and artificial intelligence to visualize the geographical patterns, routes, and spatial trends to plan, map, and optimize the positional dimension.The geospatial imagery analytics market is anticipated to have significant growth during the forecast period 2020-2025.
