Mark Ryder

Mark Ryder

Ever increasing world population, global price pressures, and a greater acceptance of environmental responsibilities demands an improved management of the world’s agricultural resources. Remote sensing (RS) technologies will play an integral part in the collection, analysis and application of agricultural resource data.

Ever since the industrial revolution, management within agriculture, particularly within the developed countries, has favoured the continued growth in size of machinery and application of chemicals and fertiliser. To its credit, these practices have enabled agricultural resources to support the continued growth of the human population.

Society, however, can only be described as naive if it continues to fulfil the growing food needs through this damaging approach. Just some of the damaging implications which would result and increase include soil erosion and salinisation, reduction in soil fertility, compaction of subsoils and soil and water pollution.

RS is part of a new technological age sweeping the agricultural industry. Simply, it is the collection and analysis of information from a distance using technology which does not require physical contact with the target object. RS makes up only one element feeding into the concept of precision agriculture (PA).

Other key elements include Geographical Information System (GIS), Global Positioning System (GPS), computer modelling, variable rate technology (VRT) and advanced information processing. PA is dramatically changing the way people farm and with development in RS technology, PA as a concept will continue to evolve and deliver benefits including profitability, sustainability, environmental protection and food safety.

Within the fresh produce industry specifically, RS is starting to shape future agricultural practises. Pre-seeding, airborne photos can be used to translate differing levels of reflectance from both visible and near infrared light to allow for targeted soil sampling thus enabling whole field spatial coverage. This spatially referenced data quantifies site factors which may in turn affect, for example, iceberg lettuce growth resulting in reduced field/ head uniformity, leaf density and colour, head weight and thus final saleable yield.

Soil texture, nutrient level, salinity and organic matter are some of the attributes which can be measured. Post seeding, regular RS and the use of Normalised Difference Vegetation Index (NDVI) allows for the monitoring of the variable site factors and their effect of crop growth supplying the relevant information required for VRT. Keeping to the example of iceberg lettuce, monitoring areas of adjusted chemical application will allow for an increased understanding of crop requirements for different soil types.

Thus, building towards the long term goal in achieving maximum saleable yield through maximising plant genetic potential and minimising stress. This concept is being adopted by leading UK salad producers including G’s and Produce World.

In addition to monitoring growth rates in accordance with soil quality and nutrient availability, RS and NDVI can allow for an earlier detection of either disease, pest or weed pressures. Unexpected variances in light reflectance highlights potential problem areas allowing targeted crop walks to further investigate the concern. In the case of a weed infestation for example sprayers can apply the appropriate flow rate of the necessary herbicide to the affected areas.

As previously mentioned, PA when broken down can be simplified into three basic elements within a continuous cycle; Collection of information, analysis of said information and finally translating this information into management adjustments. This is a continually improving cycle, where volume & accuracy of information will continue to grow allowing for a more intelligent method of crop production facilitated by the use of RS in its ability for non-contact data collection.

Although it is clear RS has the ability to collect vast amounts of useful data, it remains raw data until it can be harnessed into accessible and user friendly information. In order to achieve this, aforementioned technologies including GIS and GPS are essential to successfully implementing PA management practices.

It is also essential for regular revisits to monitor variance throughout crop life cycle. This in itself presents a number of challenges. Current satellite systems able to capture the images instantaneously cannot provide the spatial resolution and therefore the detail required for PA. On the other hand, the use of airborne sensors is somewhat prohibited by cost for many producers with the exception of valuable cash crops or large land owners. In addition these devices, such as Unmanned Aerial Vehicle (UAV’s), cannot currently achieve timely crop coverage. Fortunately however, there are a number of projects in motion devoted to high resolution satellite based imagery for both PA and other high resolution applications.

Technical developments alone will be insufficient to facilitate the potential benefits RS and PA can deliver. A supporting, recognised and trusted, structure will be required to amalgamate both archived and incoming data in a comprehensive user friendly and timely fashion. The Canadian government recognised this and launched an initiative called CEONet with the aim to help solve this very issue with an end goal to provide readily available RS data sets on the internet.

As it stands PA and RS as a commercial management practice is still in its infancy; a member of the NASA Landsat 7 science team, Susan Moran, states “Precision crop management is still in its experimental phase”. The development of RS and PA for the future requires buy in from a vast range of sectors, with each taking on different responsibilities. This includes universities and academic institutes contributing to longer term research and technology, and the private sector building the commercial and market presence/ credibility. Finally, an effective affordable training programme will be required to facilitate the broad range acceptance of RS and PA.

RS has huge potential within the agricultural industry to deliver the accuracy and quantitative data required to facilitate precision agriculture and together bring it to the forefront of technological innovation where it belongs. Moreover negating the need for universal application of fertilisers and chemicals and reversing the trend of increasing size of machinery. There are, however, a number of limitations and hypothetical threats challenging the progression of this technology and so considerable commitment and investment is required to ensure its success.