Satellite and aerial imagery play a significant role in modern day agricultural production and forest related activities. Advances in image sensors help to identify and delineate landscape level food production not only in different ways, but more quickly and effectively than before – and at higher resolutions. Image processing software supports these sensors, providing greater analytical capabilities, thus improved knowledge, than was previously possible.
Satellite and aerial imagery play a significant role in modern day agricultural production and forest related activities. Advances in image sensors help to identify and delineate landscape level food production not only in different ways, but more quickly and effectively than before – and at higher resolutions. Image processing software supports these sensors, providing greater analytical capabilities, thus improved knowledge, than was previously possible.
The top ten per cent of agricultural producers use imagery in their operations, and modern day forest operations depend upon imagery for forest management purposes. If we strip away all of the talk and zero in on the primary value of satellite and airborne imagery to agriculture and forestry, the answer is two-fold. Firstly, imagery provides valuable information that is useful for planning and managing the potential crop output, in a sustainable way. Imagery results in more sustainable food production. 
Secondly, imagery enables the gathering of knowledge about agriculture and forestry through local to regional to global scales. That knowledge enables a better understanding of overall production factors, but also contributes toward risk management decisions and supports predictive modeling of food supply and consumption. If we know what the world’s crops and forests are doing, then we can adapt for stable or unstable outlooks.
Map support vs. active geo-operability
To understand the changes involving maps issued once a year as compared to near real-time, based on remotely sensed imagery today, it is important to realise that re-visitation frequency (time a sensor makes an image of the same place till the next time) has decreased considerably.
There are more satellites and digital cameras in space / air than any other previous time. This means they revisit places more frequently – providing updated imagery (and processed results) more often. Additionally, the above frequency now includes more high resolutions (each pixel has more detail and extractable value). The per pixel cost /value has changed markedly – meaning more information per unit cost. What this results in is a shift to more frequent use of remotely sensed data to drive information and details, not only about seasonal cropping or yearly forest growth, but to act as a means for in-crop and current forest operational planning and operations. What does that really mean?
It means that a forest fire happening right now can be flown and remotely sensed images will deliver information about it’s size, the types of forests it covers, where to orient resources tomorrow and so on. It means that a disease infestation within a current crop can be seen across a region, enabling decisions to be made about how to respond to it right away – mitigating impacts. It means that decision making surrounding adequate storage and transport of higher yielding crops can be made today, in time for harvest at a later date – within reason.
For example, the European Space Agency (ESA) published an interesting map this week that shows a comparison across Europe of the current dry soil conditions as compared to last year. “The animation, derived from data from SMOS, shows the difference in soil moisture in France between April 2010 and April 2011. The yellow colours indicate drier and the blue show wetter soils.” (See here – rolling mouse over map).
Crop and forest growth and health
While soil moisture is an important aspect to growing forests and producing foods. Other remotely sensed data can be used to determine Leaf Area Index (LAI) – a measure of crop health. Other satellite imagery is used for broader agricultural planning, which leads toward the development of precision agriculture and precision forest operations.
But this information is not only available through the use of satellites, aerial imagery gathered from airplanes carrying digital aerial cameras, often produce the highest quality imagery available. And digital airborne cameras have been investigated for their contributions toward managing water upon landscapes, for agriculture and forestry. Also, residing close to imagery related services is LiDAR which has been used in Indonesia for monitoring forests in that country.
Image analysis and processing
No talk about remotely sensed imagery for agriculture and forestry is complete without reference to the software that processes the imagery. This is an integral aspect of the production of valuable information. Whereas it used to be primarily handled on an individual basis, that is not the case today. Satellite data providers and aerial image producers alike are now capable of providing extended image processing services.
These agencies can process large quantities of imagery in an automatic fashion, delivering results back to users and other third party’s providing image related services. This has important implications for users who need results, but do not wish to know all the technical details for processing imagery themselves. Another new approach finds image processing software residing inside GIS software. And this configuration can be used on a server through Cloud computing, meaning that the entire image analysis to map making end is handled automatically.
Digital imagery, policy and governance
Perhaps one of the most interesting aspects to all of this imagery goodness lies in the pursuit of new policies, regulations and governance surrounding the uses and applications for imagery related activities, that has been gathered remotely. As standardised procedures and methodologies for handling and working with remotely sensed imagery in agriculture and forestry become more pervasive, policies and management of the spatial data need to be developed. Simple questions like archiving, processing extended geography and ownership issues are all hotbeds of activity with many government agencies attempting to develop open vs. closed strategies (or in between), new taxing capabilities and strategies for issues of privacy.
Obviously I have not covered all activities relating to imagery here, there are so many. But hopefully this column points to the notion that farmers and agriculture producers gain values, geospatial service producers gain advantages and governments also benefit through better management of their agricultural and forest bases. Activites across many downstream industries and sectors are only beginning to be exposed.
The whole area of regional energy management, watershed management, ecological services and transport are similarly impacted by remotely sensed images – and link to agriculture and forestry. We now have the opportunity to see more, and to act more appropriately with this resources – hopefully these technologies cause that result.
