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.
Where to find GIS data
GIS data can be available commercially and publicly. For instance, USDA’s online web soil survey tool 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 provides GIS data that shows crop statistic information and acreage estimates based on different crop 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.
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.
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 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 fields can be depicted from space?
Furthermore, satellite data in tandem with ground-based sensors and UAVs (unmanned aerial vehicles) 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.
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. 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 can better understand crop resiliency toward heat stress and soil moisture in response to our changing climatic conditions.
Brush management
One recent example 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. UAVs are used 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.
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 and crop disease surveillance. — Noble Research Institute
