Applications of Low Altitude Remote Sensing in Agriculture

Applications of Low Altitude Remote Sensing in Agriculture

In a study by Chunhua Zhang et. al., on “Applications of Low Altitude Remote Sensing in Agriculture upon Farmers’ Requests– A Case Study in Northeastern Ontario, Canada” reveals the importance and practical application of low altitude remote sensing (LARS).

With the growth of the low altitude remote sensing (LARS) industry in recent years, their practical application in precision agriculture seems all the more possible. The purpose of this study is to showcase actual requests by farmers to monitor crop conditions in their fields using an unmanned aerial vehicle (UAV). In this study optical and near-infrared imagery was used to monitor fertilizer trials, conduct crop scouting and map field tile drainage.

Mosaicked image map based on UAV images of a soybean field in Sturgeon Falls, ON, Canada (79°56′51″E, 46°20′14″N) taken on July 12, 2013.

Mosaicked image map based on UAV images of a soybean field in Sturgeon Falls, ON, Canada (79°56′51″E, 46°20′14″N) taken on July 12, 2013.
The image map on the left is a mosaicked infrared color composite image (NIR, red, green-no enhancement applied) and the image map on the right a mosaicked NDVI image. The A, B, and C represent treatment areas of organic only, organic and chemical fertilizer and chemical fertilizer only applications, respectively. D indicates a fertilizer application error.

With the primary objective of matching agricultural practice with crop and soil conditions, the use of Precision Agriculture technologies is considered one of the key directions in modern agriculture development. Some of the perceived benefits of Precision Agriculture include increasing crop yield and efficiency by lowering the costs associated with fertilizer, pesticides, herbicides, and fungicides. An additional socio-economic benefit of Precision Agriculture is reducing the transport of agriculture inputs on the air, soil and water.

Remotely sensed imagery obtained during the growing season could be utilized to extract crop condition information for management purposes in a timely fashion. In particular, high spatial resolution satellite imagery can provide crop and soil condition information for management adjustment. However, satellite image availability is highly restricted to weather condition and the satellites’ poor temporal resolution. Moreover, the spatial resolution of these satellite images is limited with the highest resolution for commercial satellite data (WorldView-2 and GeoEye-1) at approximately 50 cm for the panchromatic band. Although quite good, this spatial resolution along with the limited spectral resolution of the panchromatic band might be not sufficient for examining within-field variations of crop condition and yield.

With finer spatial resolution and real-time monitoring capability, airborne multispectral and hyperspectral sensors had been applied to monitor crop conditions and yield. Aerial imagery has been shown to be as effective as high resolution satellite imagery in monitoring spatial variation of crop condition and yield.

The top image is a mosaicked infrared color composite map (NIR, red, green-no enhancement) of a wheat field located in Verner, ON, Canada (80°5′50″E, 46°22′35″N) that was stricken by army worms and lodging taken on July 31, 2013. The bottom image is the corresponding NDVI derived map. The A indicates a healthy non-infested alfalfa field, the B indicates a section of the wheat crop hit by army worms, the C shows an area of lodging and D indicates a rock outcrop.

The top image is a mosaicked infrared color composite map (NIR, red, green-no enhancement) of a wheat field located in Verner, ON, Canada (80°5′50″E, 46°22′35″N) that was stricken by army worms and lodging taken on July 31, 2013.
The bottom image is the corresponding NDVI derived map. The A indicates a healthy non-infested alfalfa field, the B indicates a section of the wheat crop hit by army worms, the C shows an area of lodging and D indicates a rock outcrop.

The rapid development of Low Altitude Remote Sensing Systems (LARS) over the past decade makes its application for Precision Agriculture possible. The study demonstrates that LARS imagery has many practical applications.  The results from their study showed that it might be plausible to apply Low Altitude Remote Sensing Systems images in studying crop biological parameters. More recently, research scientists at the US Department of Agriculture have been conducting experiments using a fixed wing UAV to monitor various crop characteristics.

While a number of sensors/cameras are available for LARS, optical or infrared are the most commonly used for crop monitoring. Thermal infrared sensors have been shown to be useful for monitoring soil moisture or stress and, most recently, hyperspectral sensors on board a UAV were used to examine leaf carotenoid content.

The studies to date demonstrate the scientific feasibility of LARS applications for monitoring crops. LARS appears capable of resolving the spatial resolution restrictions of satellite imagery. However, there are several key limitations apparent in such studies including the small spatial coverage and the image processing of the LARS data.

Study Area

This research takes place in the clay belt area within in the West Nipissing District of northeastern Ontario, Canada. The main cash crops grown in this region are soybean (Glycine max), wheat (Triticum spp.), barley (Hordeum vulgare), oat (Avena sativa) and canola (Brassica napus).

Equipment and Methods

For this study, the UAV system, developed by Aeryon Labs Inc., Canada, consisted of a graphical, touch-screen control station (Figure 1), an aerial vehicle (Aeryon Scout) (Figure 2), and a radio repeater station to extend the control station’s transmission range. This aerial vehicle is a commercially available quadrocopter UAV that can be equipped with both an optical and infrared camera.

The touch-screen control station for the Aeryon Scout UAV.

Figure 1: The touch-screen control station for the Aeryon Scout UAV.

Figure 2. The Aeryon Scout quadrocopter.

Figure 2. The Aeryon Scout quadrocopter.

Optical images were captured using the Photo3S optical camera (Aeryon Labs Inc., Canada) and near infrared images using an ADC-lite camera (Tetracam, United States) that affix to the Aeryon Scout.

Ground Control Points (GCP) were set up to help in the orthorectification and georeferencing of the final mosaic images.

Results:

The application of UAV imagery to assess fertilizer treatments

There have been several studies demonstrating the benefits of organic manure on soil quality and crop production. The three distinct fertilizer treatments were observed in the field. The producer had applied only organic fertilizer (9.37 L/ha or 1 gallon/acre) in section A of the field, whereas in section C a conventional chemical fertilizer (3–14–45, 371.25 kg/ha or 330 lb/acre) was applied. Section B (i.e. middle strip) was treated with a mix of organic (9.37 L/ha or 1 gallon/acre) and chemical fertilizer (185.53 kg/ha or 165 lb/acre). The research team flew his soybean field on a clear day (July 12, 2013) 42 days after seeding. The crop height was approximately 30 cm at the time image acquisition. The mosaicked image shows a large contrast between the organic treatment and chemical fertilizer treatment. The section treated with only organic fertilizer had the weakest vegetation vigor and consequently appears much darker in the infrared image.

The application of UAV images in identifying area of lodging and insect infestation

Fall armyworm is an agricultural pest more typical of tropical and subtropical regions. However, a cool, wet spring followed by warm, humid weather and heavy rainfall favor the propagation of fall armyworm in more temperate regions. For many crops, including wheat, the fall armyworms tend to consume only the succulent parts of the leaves with the main midribs intact following the infestation. As a result the leaf area of the field or parts of the field drops significantly in a relatively short period of time. Given this type of damage it is believed that armyworm movement/impacts could be assessed using high resolution remotely sensed imagery. For areas infested within a wheat field, the reflectance in the NIR band should decrease whereas that of the red band should increase due to the loss of flag leaves and increased exposure of the soil surface and shadows.

A comparison of the result of an armyworm attack. The arrows indicate the difference in the flag leaf of the infested (left) versus the healthy (right) wheat plants. Only the mid-rib of the flag leaves remains on the infested plants.

A comparison of the result of an armyworm attack.
The arrows indicate the difference in the flag leaf of the infested (left) versus the healthy (right) wheat plants. Only the mid-rib of the flag leaves remains on the infested plants.

Weather conditions and UAV image acquisition

Weather conditions are critical for remote sensing acquisitions and unfortunately the growing seasons are typically the rainy seasons for many parts of the world.

In comparison to satellite and high altitude aerial remote sensing, LARS has a higher degree of flexibility with regards to image acquisition. Although it is best to take imagery during a cloud free period, LARS images were successfully collected under full cloud cover. However, the impacts of varying solar radiation on the image should be considered for each task particularly when creating large mosaics based on hundreds of individual images.

Conclusion

This paper examined the feasibility of applying UAV acquired images for monitoring crop conditions based on the actual requests from producers. The results suggest that it is plausible to obtain images and process them in a timely fashion for Precision Agriculture applications. However, due to current costs and operational logistics the application is still in its infancy stage. At present one of the major factors impeding the adoption of LARS is the cost. Currently it is expensive to own LARS equipment with the flyers alone costing between US$20,000 and US$70,000.  Besides the requirement of short image processing, certain skills in image interpretation or classification are also necessary for effective use of a LARS for Precision Agriculture. Most producers would require image interpretation training. The collection and processing of UAV images in a timely fashion is a key obstacle for their practical application. A fast adoption of UAV systems should occur as the costs of LARS decrease and more experienced personnel, possibly a service industry, are available to acquire and process these data in a timely fashion.

Categories: Remote Sensing

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Comments

  1. shop4leica
    shop4leica 14 April, 2015, 19:15

    Interesting agricultural implementation. However, the costs seem to outnumber the benefits, at least for now.

    Reply this comment

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