Weather and GPS satellites in space support our lives on Earth. Conventionally, a single satellite was deployed to observe Earth for a specific purpose. In recent years, however, constellations of multiple satellites are being set up to create environments for daily observations or even multiple observations a day. Space-oriented businesses based on these technologies are burgeoning. One area of application showing a lot of promise is agriculture. We interviewed Kokusai Kogyo Co., Ltd., a company that offers remote sensing services for a wide range of applications, including urban planning and forestry/environmental protection. Here is what we learned about the utility, specific examples, and future potential of satellite remote sensing for agricultural applications.
Reasons Why Daily Satellite Remote-sensing Imagery is Useful for Agricultur
Today, many farmers check crop growth and predict harvest time and yield by going into the fields and visually inspecting the plants. This approach makes it harder to know the condition of the entire crop for large farmlands, as farmers can only sample-check their crop. Growers are looking to satellite remote-sensing as a potentially very useful solution to this problem.
Remote-sensing is a technology that takes observation images of Earth from aircraft, satellites, and more recently, unmanned aerial vehicles (UAV) to obtain various kinds of information from the data. Advantages of remote-sensing include aerial imagery capturing wider areas in a single shot than ground-level imagery, and the use of infrared and other non-visible wavelengths to detect crop growth and farmland conditions that are invisible to the naked eye or in ordinary photographs.
A pioneer of aerial surveys and a remote-sensing service provider for about 40 years in Japan, Kokusai Kogyo, Co., Ltd. is now offering remote-sensing services based on multiple satellites. In addition to the areas of urban planning, forestry/environmental protection, and disaster prevention/management, the company is now zeroing in on agriculture. About seven years ago, Kokusai Kogyo began a field trail in
"The main reason we chose to focus on agriculture is the launch of observation services based on satellite constellations. In agriculture, the timing and frequency of observation are critical. We saw great opportunities in this regard", says Kunihiko Arai, head of geo-information at the company.
With fewer satellites, the timing and frequency of observation are limited. On the other hand, if an observation system comprised of multiple satellites is built, images can be taken more frequently to satisfy the users' frequency and timing requirement. The costs of purchasing image data have been coming down, resulting in more users and use cases.
"Kokusai Kogyo partners with several companies that own satellites to create systems capable of addressing various customer needs such as observation timing, frequency, types of image data, accuracy, and budget", says Arai.
Pasture Diagnosis Using Image Data
The company's first effort was diagnosing pasture for dairy farming using satellite imagery.
"As in some other industries, lack of successors is a serious issue in the dairy industry, causing a major problem in managing pasture adequately", according to Noritoshi Kamagata, who is working on remote-sensing technology in the company's geospatial infrastructure section within the engineering division. Raising dairy cows on a pasture with overgrown weeds compromises yield and quality of milk due to lack of nutrition. Therefore, dairy farmers give cows feed crops to supplement nutritional deficiencies. As a result, costs increase and profits go down, forcing farmers to close business and leading to a declining number of new farmers. It is a vicious cycle. To resolve this issue, the company came up with the idea of utilizing satellite imagery to diagnose the condition of large pasture areas with the aim of simplifying the work required to bring the pasture back to its optimal condition.
Another advantage of remote-sensing is the ability to use wavelengths of light other than visible light for observation. For example, pasture within a field is not homogeneous due to different growth rates of grass and penetration of weeds. Using near-infrared light, types of grass and growth conditions can be differentiated to diagnose the quality of pasture. JA [Japan Agricultural Cooperatives] and dairy farmers can use this information to efficiently bring their pastures back to optimal conditions.
Kokusai Kogyo performed field tests in large pastures in
Based on these results, the local JA was able to efficiently select the fields to perform pasture renovation, a process to replace the current pastures, and successfully renewed the condition of the whole pastureland in the local co-op to an optimal state. They are gradually seeing positive outcomes of this effort.
Predicting Harvesting Time of Wheat and Rice Based on Protein and Water Contents
Kokusai Kogyo is also conducting field trials of "growth diagnosis" for crops such as wheat, rice, soy and tea.
The quality of wheat and rice heavily depends on protein content. Flour is classified into cake flour, all-purpose flour, and bread flour depending on the amount of proteins. Rice with lower protein content is known to taste better, with fluffier and tenderer texture when cooked. For these reasons, rice and wheat farmers vary the amount and timing of fertilization based on years of experience and educated guesses to adjust the amount of protein.
"Using remote-sensing technology, the protein contained in wheat and rice can be estimated from observation data of the fields", says Kamagata.
Kokusai Kogyo first diagnosed wheat growth at each phase of the growers' agricultural management process. Each time, decisions such as the amount of fertilization and the need for top-dressing were made. For wheat, moisture content was also diagnosed using satellite remote sensing, as this is a critical factor in determining the harvest time. Based on the data, optimal harvesting times were predicted, and which field to harvest first was determined. For rice, protein content was estimated to determine the amount of fertilization and the need for top-dressing.
According to Kamagata, "...soy and tea growth diagnosis is done by observing the color of the leaves. The wavelength of light optimal for a diagnosis and the type of image data needed for it depend on the type of crop... we are still in the field validation phase, but we will be obtaining the most suitable image data for customer needs and budget, and enhancing our image analysis techniques to make this technology commercially viable as soon as possible," Kamagata says. The future with eyes from space helping produce high-quality crops is around the corner.
Contributing to Mitigation of Global Warming and Food Crises Worldwide
"In fact, I believe that satellite remote-sensing in agriculture is more needed and can make a bigger difference in developing and semi-developed countries than in
For this reason, Kokusai Kogyo has a plan to advance efforts in agricultural development and management assistance as well. They expect synergy in these areas, combined with their consulting expertise gained over the years in the areas of land use and water resources that they are deploying overseas.
"In December, 2015, COP21 (UN Framework Convention on Climate Change 21st Session) adopted the 'Paris Agreement'. Part of the CO2 emissions framework was the 'REDD+'. This program offers financial benefits to developing countries for taking action to preserve their forests. Kokusai Kogyo is using satellite remote-sensing to monitor deforestation targeting the REDD+ program. We plan to use remote-sensing to identify regions that have become deforested, while at the same time, recommending which forests should be preserved for the future, and where and what types of crops the local residents should plant and grow", says Kamagata.
Satellite remote-sensing is not only useful in agriculture, but it is also expected to make a major contribution toward solving some of the most urgent challenges facing humanity, such as global warming and food crises.