There are types of technologies built to advance knowledge and practices in agricultural research and operations. Geographic Information System or Geospatial Information Technology (GIS) is one of the prominent technologies used in the agriculture realm. It is an integrated system comprising computer software, hardware, data, analytics and the users themselves, who help to address real-world problems with location-based information.
GIS Helps Maximize Returns
In agriculture, a primary goal of producers is to maximize their return on investment (ROI). So exactly how does GIS impact agriculture to maximize returns? Well, using spatial extent and location of agricultural fields, GIS tools and applications help to capture, analyze, and interpret pertinent data and information anywhere at any given time.
For instance, by gathering historical and current conditions of farmland, such as temperature, crop health and soil moisture, producers can come up with future yield capacity or risk of their farm.
With the visual representations of GIS data in the form of imagery, field survey maps and tabular data, producers can quickly make decisions such as how to address nutrient deficiencies and fertilizer treatments, crop health, weed control, etc.
Example of Sensors Noble is Employing in Producers’ Fields
Noble’s DJI Matrice 600 (shown here) has six propellors to make the 600 capable of carrying a 13-pound payload. This payload allows for multiple sensors to be carried at the same time. Listed below are some of the sensors that the GIS team at Noble uses for research and data collection.
1 DJI Zenmuse X5
RGB camera capable of shooting 4K quality video and imagery a few centimeter.
2 Velodyne Lidar Puck
3D modeling sensor that can detect height and surface area.
3 GPS Compass Pro
Provides satelite-based location data.
4 RTK-GNSS
A satelite navigation system that provides geospatial positioning.
Where to Find GIS Data
GIS data can be available commercially and publicly. For instance, USDA’s online web soil survey tool (bit.ly/usdasoilsurvey) hosts soil information, GIS maps and data that can be accessed and used at your fingertips. Similarly, interactive web applications such as USDA’s CropScape (bit.ly/usdacropscape) provides GIS data that shows crop statistic information and acreage estimates based on different crops types.
While there are commercial and publicly available software and platforms that can perform our mapping needs, custom GIS web applications and online tools can perform similar tasks on-the-fly. One example is the Noble Research Institute’s agricultural database mapping tool. This web tool allows a consultant to map a producer’s property boundaries and footprints using ESRI cloud imagery and platform. In addition, to better leverage our consultation efforts, the tool also allows us to store cooperator information and provides decision-making abilities for producers. For example, it can calculate a producer’s stocking rate and carrying capacity at the same time.
Obtaining Agriculture Information from the Sky
GIS data, maps and imageries can be obtained from several platforms such as ground-based devices like GPS, airborne platforms like manned and unmanned aerial vehicles (drones), and space-borne platforms like commercial satellites.
These tools and technologies allow users to sense and collect data remotely — hence they are called remote sensing tools — at different heights from the ground. Ground-based sensors allow researchers to efficiently capture multispectral, laser and ultrasonic data, which ultimately provides forage quality and biomass yield information.
While most cutting-edge geospatial and remote sensing technologies were developed for other markets, the agriculture industry is now being transformed into a new frontier. With that perspective, we launched a UAV-based remote sensing program to empower scientists, consultants and stakeholders to tackle current agricultural challenges through advance research and technologies.
Looking at the technological pieces, we have several UAV fleets. These UAVs are paired with sensors and cameras including Global Navigation Satellite System (GNSS) as well as flight plan and processing software. This makes the fleet resemble a whole technological system, which is why it is called an unmanned aerial system or UAS.
During the data collection mission, UAV operations are conducted under Federal Aviation Administration (FAA) rules and regulations. Furthermore, survey flights are performed autonomously — the system can take off, scan the area and return home in autopilot fashion.
The Future of Smart Agriculture
Agricultural technologies are growing faster than ever before, which leads us to think about future technologic opportunities and challenges that can bring agricultural research and operation to the next level.
With the rise of Internet of Things (IOT), big data and innovative geospatial technologies, smart agriculture or smart farming practices have been implemented in many parts of the world. IOT-powered smart farming can eradicate inefficient farming practices and perform actions that require physical labor such as farm irrigation, crop scouting and weed control, and plant and soil health assessment. On the flip side, smart agriculture is challenging due to its integration on so many variables such as smart field devices, real-time data and analytics, wireless network, and so on. In addition to these, producers want very easy-to-use, cost-effective tools, and these are often difficult to find.
Smart agriculture requires several types of real-time data digestion from multiple sources. One source is the satellite data services. Sensors onboard the satellite platforms offer large fields of view, enabling researchers and farmers to see land surfaces at macro levels.
In addition, with multitudinous bandwidth and frequent earth visit, satellite data allows many possibilities to maximize efficiency in agriculture through yield modeling, monitoring of soil moisture and drought conditions, and detecting crop stress over large-scale farms.
While there are openly available satellite data with low resolution from government entities like NASA, commercially available satellites from Digital Globe, Planet Lab and Astro Digital offer better resolution (below sub-meter) with higher quality.
In the coming years, researchers here will work on satellite data services to understand forage dynamics and biomass health across its farms. Wouldn’t it be interesting to understand what additional information of our fields can be depicted from space?
Furthermore, satellite data in tandem with ground-based sensors and UAVs enable us to capture biomass and crop information at three altitudinal gradients. This combination of three-tier platforms allows citizen scientists, consultants and producers to intersect diverse sets of information and make data-driven decisions pertaining to agriculture and biomass productivity.
This will certainly help tackle our common agricultural interests and challenges leading to smart agriculture practices across the Great Plains.
UAV uses in Ag
Wildlife Management
UAVs have significantly helped researchers in wildlife management conduct surveys using thermal infrared remote sensing technology. In the past, thermal sensors were largely deployed in satellite systems and ground optical devices, but with the rapid advancement of robotics and automated systems, thermal sensors such as FLIR can be mounted onto UAVs. They are capable of identifying and tracking livestock and wildlife animals during the day and night based on heat signature patterns emitted from their bodies.
Pasture and Rangeland Health
UAVs have been proven useful to agricultural producers, allowing them to understand the health status of their pastures and rangeland. With visual and multispectral sensors, we can easily obtain crucial plant health information such as plant greenness, chlorophyll and nitrogen content. This metric is commonly known as Normalized Difference Vegetation Index (NDVI). Using this metric, healthy and diseased areas can be isolated, allowing producers to view area conditions that are otherwise invisible to the human eye.
Crop Resiliency
While the human eye doesn’t have the ability to detect subtle temperature differences, thermal sensors are can better understand crop resiliency toward heat stress and soil moisture in response to our changing climatic conditions.
Cotton Root Rot
One example is mapping of the cotton root rot disease, also called Texas root rot — a fungus that originated from cotton plants and spreads out on the roots of other plants, killing them off gradually. This disease causes huge economic loss to producers annually. UAVs have obtained high quality images and prescription maps to identify and track disease movement, which allows consultants and producers to adequately plan and make treatment decisions during the disease progression.
Brush Management
One recent examples is brush management work. As we all know, eastern redcedar is a nuisance to agricultural lands and pastures of the Great Plains. It not only competes with the growth of desirable biomass but also threatens the wildlife habitat and degradation of rangelands quality. We use UAVs to identify hotspots of cedar trees using high resolution visual and infrared imagery that can easily isolate cedar trees from the other tree species. This helps producers decide the best option to treat areas with invasive trees.
Pecan Orchard Surveys
Similarly, we observed that UAVs are a key tool for surveying pecan orchards. During the last couple of years, we’ve been monitoring pecan orchards using Lidar sensors mounted to the UAV fleet. It shoots pulse waves to the ground and measures height of any object based on the calculation of time the pulse wave return. Lidar scanning techniques are frequently and widely used to obtain digital elevation models (DEM) and surface models (DSM) with greater precision.
What Ag Sensors can Measure
Sensors mounted on the UAVs are able to inexpensively capture very high resolution data at just a few centimeters. These high resolution images provide useful information, including:
- Vegetation growth
- Surface 3D elevation and volumetric analysis
- Soil erosion mapping
- Wildlife surveys
- Fence line inspection
- Crop disease surveillance
Compare Drones, Sensors and Prices Online
Aerial Scanning Drone Sensor Options
Each sensor has its own specific functions depending on what it can achieve from aerial scanning, so it is important to understand and evaluate the drone based on what you need in your business or operation. Since sensors capture actual data, the cost of UAVs are determined by the sensor types embedded in it. Some available sensors include:
- High Resolution
- Visual Band (RGB),
- Multispectral (Infrared),
- Lidar (Light Detection and Ranging)
- Thermal
