Santhosh Seelan

Detection of Leafy Spurge (Euphorbia esula) Using Multidate High-Resolution Satellite Imagery1

Leafy spurge is a deep-rooted perennial weed that displaces native rangeland vegetation and replaces forage for cattle and other forages used by vertebrate herbivores. Strategic planning to control this weed requires monitoring its distribution and spread. Classical monitoring techniques, which often involve extensive ground survey efforts, can be aided by the synoptic nature of remotely sensed imagery. This research addresses the use of Space Imagings 4-m multispectral Ikonos imagery for the survey and detection of leafy spurge infestations. Survey data were collected at a site in western North Dakota and used to produce supervised classifications of leafy surge infestations with Ikonos imagery. Multiple image dates per year were combined with each other to assess the added accuracy afforded by multitemporal imagery. Finally, individual patches of leafy spurge were analyzed to determine the minimum patch size and percent cover that were detectable with supervised classification of Ikonos imagery. Under some circumstances, the imagery was effective at detecting leafy spurge, but in areas with a higher forb component, the classification was not as effective. Multidate imagery provided increased accuracy, but improvements were not consistently significant. Leafy spurge infestations of <30% cover and 200 m2 were not reliably detected. Nomenclature: Leafy spurge, Euphorbia esula L. #3 EPHES. Additional index words: Accuracy assessment, digital photography, EPHES, global positioning system, Ikonos, image analysis. Abbreviations: GPS, global positioning system; RMS, root-mean-square.

Digital Northern Great Plains: A Web-Based System Delivering Near Real Time Remote Sensing Data for Precision Agriculture

The US Northern Great Plains is one of the world’s most agriculturally productive areas. Growers in the region are eager to adopt modern technology to improve productivity and income. Use of information derived from remote sensing satellites to better manage farms and rangelands while reducing environmental impacts has gained popularity in recent years. However, prohibitive costs and non-availability of near real time remote sensing imagery has slowed the adoption of this technology for in-field decision making. Digital Northern Great Plains (DNGP), a web based remote sensing data dissemination system, was developed to address these drawbacks. It provides end users easy and free access to a variety of imagery and products in near real time. With delivery of archived and current data, DNGP has helped farmers and ranchers reduce operational costs and increase productivity through a variety of innovative applications. Moreover, negative environmental impacts were lessened.

Empowering farmers with remote sensing knowledge: A success story from the US Upper Midwest

Satellite imagery has proven potential in farm level applications, especially in the US Upper Midwest where the farm sizes are large enough to be studied using high and medium resolutions. In order for farmers to use this technology to improve their productivity and income, it is imperative that they be sufficiently exposed to the technology so that they are able to take full advantage of it. Training of farmers and ranchers in satellite imagery use started at the University of North Dakota in 2000 and has been refined over time. The basic ‘hands on’ training involves downloading imagery from the Upper Midwest Aerospace Consortium (UMAC) website, downloading and use of free visualization software programs available on the web and an introduction to the various application possibilities. Advanced training, which involves more complex extraction of useful information from digital images, is also available to those who complete the basic training. Over 500 farmers, ranchers, crop consultants and other end users have been trained through this programme and the results are beginning to show through the success stories of cost savings and environmental benefits that have emerged.

Precision farming management via information dissemination

In the Northern Great Plains of the United States, growing seasons are short (80-120 days) but extremely productive. Farms and ranches are large (>1000 acres), so many of precision agricultures early adopters reside in the region. Management optimization depends on decisions taken based on past as well as in-season information. Spatial data is an ideal tool to answer both the long term and the short-term needs.

Near real-time high-resolution airborne camera, AEROCam, for precision agriculture

Precision agriculture often relies on high-resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require high-resolution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration between several departments at the University of North Dakota, including the Upper Midwest Aerospace Consortium (UMAC), the School of Engineering and Mines, and flight operations at the John D. Odegard School of Aerospace Sciences. AEROCam consists of a Redlake MS4100 area-scan multi-spectral digital camera that features a 1920 × 1080 CCD array (7.4-μm detector) with 8-bit quantization. When operated at ∼2 km above ground level, multispectral images with four bands in the visible and near infrared have a ground sample distance of 1 m with a horizontal extent of just over 1.6 km. Depending on the applications, flying at different altitudes can adjust the spatial resolution from 0.25 to 2 m. Rigorous spectral and radiometric calibrations allow AEROCam to be used in a variety of applications, qualitative and quantitative. Equipped with an inertial measurement unit (IMU) system, the images acquired can be geo-referenced automatically and delivered to end users near real time through our Digital Northern Great Plains system (DNGP). The images are also available to zone mapping application for precision farming (ZoneMAP), an online decision support tool for creating management zones from remote sensing imagery and data from other sources. Operational since 2004, AEROCam has flown over 250 sorties and delivered over 150,000 images to the users in the Northern Great Plains region, resulting in numerous applications in precision agriculture and resource management.

Helping farmers and ranchers to use remote sensing as a basic management tool: a development of an interactive remote sensing and image processing teaching process

The management of agro-ecosystems is an everyday challenge for farmers, ranchers, and land managers. Four main benefits arise from proper management: 1) increased yields, 2) reduced costs, 3) reduced environmental pollution, 4) maintenance of a quantitative history of field productivity. Satellite data can greatly assist management by providing spatial information on vegetation. Despite its enormous potential, remote sensing data and its derived products are still used on a regular basis by less than 5% of users in the farming and ranching community. The teaching process is essential in helping to grow a true interest in remote sensing data by end-users. Web-based interactive tutorials and training sessions, associated with efficient data acquisition and distribution system together with basic viewers, with simple manipulation capability, can bring end-users from simple spectators to involved actors.

Applications of remote sensing to precision agriculture with dual economic and environmental benefits

In the U.S. Northern Great Plains, growing seasons are short but extremely productive. Farms and ranches are large, so many of precision agricultures early adopters reside in the region. Crop yield maps at seasons end reveal sizable variations across fields. Farm management relying upon uniform chemical applications is ineffective and wasteful. We provided information about crop and range status in near- real-time, so that in-season decisions could be made to optimize final yields and minimize environmental degradation. We created learning communities, in which information is shared among scientists, farmers, ranchers, and data providers. The new information for agricultural producers was satellite and aerial imagery. Value-added information was derived from ETM+, AVHRR, IKONOS, and MIDOS sensors. The emphasis was on reducing the time between acquisition of data by a satellite and delivery of value-added products to farmers and ranchers. To distribute large spatial data sets in short times to rural users we relied upon satellite transmission (Direct PC). Results include: (1) management zone delineation, (2) variable-rate fertilizer applications, (3) weed detection, (4) irrigation efficiency determination, (5) detection of insect infestation, (6) specification of crop damage due to inadvertent chemical application, and (7) determination of livestock carrying capabilities on rangelands.

TECHNOLOGICAL INNOVATIONS BRINGING SPATIAL TECHNOLOGY TO PRECISION AGRICULTURE IN THE NORTHERN GREAT PLAINS

Increasing demand on global food supply, while bringing improved economic returns for the agricultural industry, has driven up input costs, which, in turn, has increased risk associated with food production systems (8,21). To lower risk, increase energy efficiency, enhance productivity, and improve profit ability, agricultural producers increasingly adopt the use of information technologies to aid their decision-making processes (5,6). In addition to land, labor, and capital, which have long been agriculture’s traditional assets, information management has become the fourth asset of increasing importance and has come to be known as precision agriculture (5). According to the National Research Council, “precision agriculture is a management strategy that uses information technologies to bring data from multiple sources to bear on decisions associated with crop production” (9). Information of both spatial and temporal dimensions is required for precision agriculture. Remote sensing imagery acquired from satellites and aircrafts TeChNOlOgICal INNOvaTIONs BRINgINg spaTIal TeChNOlOgy TO pReCIsION agRICUlTURe IN The NORTheRN gReaT plaINs

crop and range alert system in the U.S. northern Great Plains

The Upper Midwest Aerospace Consortium has developed a crop and range alert system to provide farmers, ranchers, land managers from the Native American Community, government agencies and non-governmental organizations with frequent and near real time remote sensing data to enable decisions that both maximize the producers income and protect the environment. The project, started in 1999, includes the establishment of a learning community network of end users, fast delivery of data to remote locations, applications development and training. More than a hundred and fifty end users and research scientists participated in this learning group in which information is shared in all directions. Over fifty end users were connected via high-bandwidth satellite link to a central distribution system at the University of North Dakota. They received and shared products derived from AVHRR, MODIS, Landsat, IKONOS and aerial platforms. A number of practical applications were developed for precision farming, such as zone-based nitrogen management, stress detection, spray drift detection, and for rangeland management, such as weed detection, livestock carrying capacity, and livestock field rotations. Several instances of cost savings and higher earnings occurred. More importantly, the imagery use resulted in lesser use of chemicals in farming and ranching, leading to environmental benefits.