Many of us seek methods to optimize crop production by gaining more information from the field. Various technologies are available for grower’s aid electronic devices, sensors, data management applications, and artificial intelligence (AI) technology, to name a few. These trends became more critical in the past decade or so and became a center of research area for many people. For example, Virginia Tech’s College of Agriculture runs a program for Smart Agriculture (Center for Advanced Innovation in Agriculture), which our program and this website are part of.
These technologies can aid growers in accessing information that was not readily available in the past. Some examples of using drones and sensor technology are the survey and monitoring of crops for detection of pests and symptoms associated with biotic (= diseases) or abiotic (= environmental stresses) factor(s). These factors can affect the quality and quantity of the crop and result in long-term negative impacts on the crop or land.
To collect and analyze the data, one must use several software applications. For sUAV, typical requirements are flight planning, mapping, and data analysis. Some software packages can handle all in one interface, and others ask you to obtain different applications. Also, for some systems, you will manage everything (i.e., pick applications and analyze data), and others provide services that will assist you in achieving your goal.
Table
| Mapping Software for Drones | Purpose | Pros | Cons |
|---|---|---|---|
| Photogrammetry | Create 2D and 3D maps, models, and ortho-mosaics by compiling and merging images with the same features and GPS location of the data collected but from different viewpoints recorded during the flight survey. | Gives users an understanding of the health status of the crop and field, such as: Soil quality, irrigation needs, plant nutrition, and pest damage. Can monitor crop growth It can help determine damage after a storm or catastrophic event. | Adverse weather, such as clouds, hazy skies, windy conditions can hinder the quality of the aerial images. Manufactured objects such as bridges or a roof can’t be mapped with photogrammetry. Image quality can vary depending on the season. |
| LiDAR (Light Detection and Ranging) Mapping Software | A laser scanning technology used to collect 3D data to render intricate maps and models. Typically used for sophisticated applications where high-resolution images and very accurate measurements are required. | This sensor has high precision in the land measurements which provides the user with very dependable results. It can discern the details of the smallest of objects and make perfect 3D models of them. The process for scanning images is quite fast so user can scan a large area and get a lot of data in a short amount of time Can collect data in hard to access places, whether its physically hard reach or dense covering one needs to penetrate through from an aerial view. | The user must have a solid understanding of aerial survey procedures such as, taking check shots, operating base stations, and check-ins on benchmarks. LiDAR sensors can be quite expensive. |
| 3D Modeling Software | Creates 3D models of the objects and the environment from image data collected from a drone flight mission. This map type is used for projects that require great precision for measurements and GPS location. | Determine the different sizes of canopy within the field which helps the user make adjustments needed for creating optimal light for the growing environment. Determine water and soil needs for very specific areas within the field, as well as crop stress found within the growing area. The signs of stressors can be manifest to the grower very early on in the season, well before it can be viewed with the naked eye. Allows growers to view their field and crops in high-resolution imagery An ecologically-safe method to increase the crop yield. | There is a learning curve growers must take time to learn how to handle the flight and use the software. Software and applications can be expensive so there is a financial investment to consider. |
References:
Piccoli F, Locatelli SG, Schettini R, Napoletano P. An Open-Source Platform for GIS Data Management and Analytics. Sensors (Basel). 2023 Apr 7;23(8):3788. doi: 10.3390/s23083788. PMID: 37112129; PMCID: PMC10143508.
An Open-Source Platform for GIS Data Management and Analytics
Services: (package that aims for Ag)
Search link for “open source” software agriculture drones 2023
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