GIS Review Back Issues


GIS Review is a periodic column by Roger Longhorn, GIS Consultant, Luxembourg
Back Issues
GIS Review No 4
( June 1998) Miscellaneous issues
GIS Review No 3
(22 June 1998) The CAP and you; The MARS Programme
GIS Review No 2
(14 April 1997): Preamble, Surfing for better crops
GIS Review No 1
(2 Apr 1997): GI/GIS defined; Farmsense; Remote Sensing News/crop yields.

GIS (Geographical Information Systems)Applications in Agriculture:
Paper presented by Roger Longhorn at the ISITA Conference, 1997
GIS (Geographic Information Systems) applied to Agriculture
June 1998 Update by R A Longhorn
Introduction.
Agricultural applications have been much in evidence in the general GI/GIS press of late, partly due to the arrival of high-resolution space imagery and the effect this is having on "precision farming" packages in the USA. Until now, most space imagery used for agricultural, forestry and similar land use applications has consisted of pixels (picture elements) with a resolution of from 20 metres to 200 metres. This resolution was good for (and is still used for) wide area monitoring of land use. However, for small(er) farmers, who might hope to one day monitor and manage their croplands, vineyards, tree nurseries or other small area, income-generating plots of land - this resolution is insufficient. An entire 20 ha. field or orchard might appear as only a small cluster of very few pixels - certainly insufficient to identify specific problem areas within the small plot.

Certain technologies are converging which will soon (not yet, unfortunately!) permit real-time monitoring of field conditions at large scale (i.e. greater detail in small plots). These are:
* the rapidly falling cost of highly accurate GPS (Global Positioning System) receivers, which can maintain an accuracy to with 30 cm today, across most of the developed world, using differential GPS services, and which are ideal for recording actual field conditions with high accuracy,
* the arrival (real soon, now!) of high resolution space imagery, both multispectral (colour) and panchromatic (black and white) at prices which small enterprises can afford, and
* ever decreasing price/performance of desktop PCs and software packages which can use these two technologies in combination.
To see some more examples of GIS applications in agriculture which are available across Europe and the USA, "point your browser" (as they say in the Internet trade!) to the following Web sites.

Ag/GIS Web sites to visit.
ChartWrite AB (Sweden)
http://www.chartwrite.se/
This Web site offers the usual info about ChartWrite's product line, demo software with examples and free maps, plus an order form for the company's AgriMapper 1.1 for Windows 95 product. The package purports to help farmers manage their crops and land, using raster-based soil mapping (i.e. images). According to the blurb "by combining it with Data-on-the-Map 3.0, you can create your own farm maps (a demo can be downloaded)". Manuals for the products are available from the Web site.

Trimble Precision Agriculture Products
http://www.trimble.com/precise/agri/index.htm
Trimble are one of the world leaders in GPS hardware and software. They also produce a range of products and systems for applications which use or require precise navigation/location information - such as precision agriculture. Visit their site above to see some useful information about GPS use in agriculture, via the "Frequently Asked Questions" links.

Farmer's Software Association (USA)
http://www.farmsoft.com/maintext.html
This site presents the US-based Farmers Software Association whose mission is "to provide the best agricultural software and hardware products available to the agricultural community". Despite its obvious US focus, there are links to various GIS-related software systems, such as FarmHMS (Harvest Mapping System), FarmGPS, GPS Server and Grid Sampler, all of which run on Windows PCs using the MapInfo GIS mapping system from MapInfo Corporation (which just happens to be 25% owned by Microsoft, Inc.!).

GeoFocus, Inc.
http://www.gfocus.com/
Another firm which uses ESRI's ArcView GIS product is GeoFocus, whose AgTrac product claims to be an agricultural management system combining GIS and GPS (see introductory note above). AgTrac "enables farmers to build databases of field boundaries and crop locations from digital aerial photos and overlays of other spatial data layers such as soils, elevation and temperature". There is a downloadable demo of AgTrac for Windows 3.x and 95 systems.

Agriculture Research Service (ARS ? whoa!) of the US Dept. of Agriculture
http://www.tucson.ars.ag.gov/research/modeling.html
This is an interesting "case study" site showing how GIS is used in agricultural applications. According to the review of this site in Mapping Awareness magazine, prepared by David Green, Stephen King and Grant Massie of University of Aberdeen, the site "has good data and map examples with details on the soils, vegetation and geology of the area (a case study of the Walnut Gulch Experimental Watershed), a Digital Elevation Model, and some example orthophotos (orthographically corrected aerial photos)." These case studies are an excellent way for the novice to begin to understand how the various elements of imagery, vector data, attribute data, DEMs, etc. are combined in a typical non-trivial example.

GIAS Project
http://www.crpa.it/gias.net/
The EUNITA mailing list mentioned the GIAS project site last month. It is certainly worth a visit for those who have not yet bothered. Full text (Italian and English versions), diagrams and photos are available describing this most interesting project, which uses GIS for the "Farm Layout" module.

GIAS is the result of a two-year-long project involving a few private public authorities of the Emilia Romagna Region in Italy under the co-ordination of the Regional Department on Food and Agriculture Development System. GIAS is a services and software integrated system designed to provide farms and extension workers with all the necessary information concerning a proper farm management and implementation of EU agricultural regulations. We have tried to meet farmers' main needs on the basis of our long-standing experience: namely to provide them with all the information necessary for decision-making, always trying to do so in a prompt and clear way. GIAS stands for GLOBAL Information Agricultural System. It includes two separate but fully integrated systems: a personal Computer-based system, called GIAS-PC and an Internet-based system, called GIAS-NET. GIAS-PC will be available for all farmers and extension workers for its utilisation on a Personal Computer. GIAS-NET will be available to anybody who is connected with the Internet.

AgroExpert Disease Forecasting System from Adcon Telemetry, (A)
http://www.adcon.com
The EC's Innovation and Technology Transfer Newsletter 3/98 (May 1998) contained an interesting description of Adcon Telemetry GmbH's AgroExpert forecasting system, which has been used in northern Europe for the past five years. The system uses a network of solar-powered weather stations to monitor rainfall, temperature, humidity, wind speed and other factors over a range of up to 100 km. The data is transmitted by radio to a PC base station every 15 minutes, compared to a mathematical model of the conditions which favour attack by specific diseases. The system then issues recommendations to spray at the precise moment when the chemical will be most effective.

There are installations in Germany, France, the UK and Austria. Farmers who have clubbed together to invest in the monitoring system spray less frequently than their neighbours, saving considerable money, yet maintaining disease vines and vegetable crops. Models have been developed for grapes, apples, tomatoes, potatoes and sugar beets. In German vineyards, over three years, the system recommended spraying five times during the season to protect against the mildew Peronospara, while the manufacturers recommendation would have been eight times. Not only are costs lower, but "quality and yield are always maximised, at minimised cost, giving farmers a big competitive advantage".

EC funding was involved via the project "TOCAP South", coordinated by Adcon, which hopes to transfer the technology from northern European experience to southern European farmers. In the test regions in Spain and Sicily, plot sizes are small, ranging from 1 - 5 hectares. The 2-year technology transfer project was initiated in June 1996 and operated during the 1997 growing season. In Sicily, even in the first year, small savings on chemicals were achieved and "the farmers were delighted". Adcon has provided the local technology relay centres involved in the pilot with software that will endable them to develop and maintain their own crop models. Information from Bernd Hartman of Adcon on info@adcon.at.


Events.
7th ICCTA International Congress for Computer Technology in Agriculture
"Computer Technology in Agricultural Management and Risk Prevention"
15-18 November 1998 - Palazzo degli Affari, Piazza Adua 8, Florence, Italy
http://www.iata.fi.cnr.it/convegni/iccta98.html (have patience! the link does work!)

Following-up on an announcement on the ITC (NL) ILWIS mailing list, it would appear that GIS applications, or use of GIS in modelling for risk and land resources management, will be much in evidence at this three-day conference in Florence in November this year. Sessions already planned include:

Prediction and Management of Environmental Hazards
Modelling for Land Resources Management
Computer Aided Techniques for Agriculture
Economic Aspects of Precision Farming and Involvement in Agricultural Practises
Session keynote speakers and chairpersons come from Spain, Italy, UK, France and Germany. Conference language is English. Have a look at the conference Web site mentioned above.


That is about all for the June 1998 "GIS in Agriculture" update.

I am sure that there is probably much more to report on, but time (as always!) is too limited. Don't forget to visit the EC's Joint Research Centre (JRC), Centre for Earth Observation's European Wide Service Exchange Case Studies page and click on "Agriculture", for access to many real life Case Studies relating to use of remote sensing data and GIS in agriculture.


GIS Review No 2 (14 April 1997): Preamble, Surfing for better crops

Contents:


Preamble to this topic
Surfing for better crops


Preamble
Below is a short piece from this week's New Scientist"Surfing for better crops" with an interesting Web site (http://climate.usu.edu/science) where you can download TIFF (small) or GIF (large) files related to crop cover world wide, etc. (read the full article) and/or you can go to their full World Atlas site (http://atlas.usu.edu/) to view their world atlas (but you need to download 1.9 Mega viewer - took me 11.5 minutes, not bad!).

Also, from April 1997 issue of Mapping Awareness mag (Vol 11, No. 3) comes the following (p.10 - "What grows in Europe's fields?" - 'A consortium led by the UK's National Remote Sensing Centre (NRSC) Ltd has won a European Commission contract to develop active microwave satellite remote sensing technology to estimate the area of agricultural crops in winter and spring. The other consortium members on this pilot project are Synoptics in the Netherlands and the French company Sotema'. Also, p. 11 "The EC's Directorate General for Agriculture has awarded a contract to NRSC Ltd.
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Surfing grows better crops
by Kurt Kleiner, New Scientist correspondent, Washington, DC

"From July, farmers around the world will be able to call on the World Wide Web to help them describe which crops are most likely to prosper in their fields.
"The World Water and Climate Atlas contains temperature and precipitation data for the entire Earth’s surface, based on 30 years of observations from some 56 000 weather stations. When the atlas goes online in July, farmers will be able to see what the weather is like on any 1.6 km square on the globe.
"The atlas is intended to help farmers decide what crops to plant, and to help governments decide where to build new irrigation projects. ‘This tool will be of tremendous use to decision makers, allowing them to see what works and what doesn’t work,’ says Ismail Serageldin, chairman of the Consultative Group on International Agricultural Research (CGIAR).
"The program’s graphical presentation of weather data shows patterns that might not otherwise be evident, says Serageldin. In one site along the River Indus, for instance, the map shows that the Indian side typically gets heavier rainfall than the Pakistani side. Though small, the difference is enough to affect the best time for farmers to plant crops and the optimum time to irrigate them, says Serageldin.
"One of the biggest tasks in developing the atlas was checking the accuracy of the data, says Donald Jensen, director of the Utah Climate Center, which developed the atlas along with CGIAR. Many weather stations, for example, are in cities or at airports, which tend to be hotter than the surrounding countryside. So figures from these weather stations either had to be adjusted or discarded.
"Some early images from the atlas can be found on the Utah Climate Center’s Web site at http://climate.usu.edu/science/" in New Scientist

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Roger Longhorn, Luxembourg (longhorn@club.innet.lu


GIS Review No 1 (2 Apr 1997): GI/GIS defined; Farmsense; Remote Sensing News/crop yields.
Contents No 1: GI/GIS defined
Farmsense
Remote Sensing News
Remote Sensing and Crop Yields

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Geographic Information
(GI) and Geographic Information System (GIS)
Defined

Geographic Information is “information which can be related to a location on the Earth, particularly information on natural phenomena, cultural and human resources”*.

In the past such information has been expressed in the form of paper maps showing locations, boundaries and relationships. Over the centuries maps have been very important in the development of the nation state, as aids to territorial conquest, sovereignty and defence, and for governing and managing territory in times of peace. Maps are still a valuable tool for scientists, astronomers and explorers to understand and control the natural world.

But the term “geographic information” also includes many other types of information which can be “related to a location”. Examples of geographic information are address data, market research data, census data, postcodes, health data, data on environment and natural resources, descriptions of transport and utility networks, information on flows of goods, cadaster and land registration information and satellite imagery. The time dimension is an important attribute of geographic information because our world is constantly changing.

Today, the information traditionally held on maps, as well as other forms of geographic information, can be stored in digital form, enabling it to be handled by computers.

Geographic Information Systems (GIS) enable different kinds of digital geographic information to be linked, so users can extract and analyse geographic information to support political, economic and scientific decision-making, for example, for managing growth in less favoured areas, understanding the impact of set-aside on agricultural production and rural ecology, or the interaction between industrial activities and environment.

* “GIS Dictionary” - A Standards Committee Publication of the Association for Geographic Information (AGI), UK, Version no. 1.1, STA/06/91, published January 1991.
Contents Review 1
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Farmsense - from Geographic Information, The Newsletter of the Association for Geographic Information (UK)

Vol. 7, No. 1, January 1997

ERDAS IMAGINE is being used by a precision farming project, Farmsense, to show farmers the extent of crop variability in their fields which can help fertiliser application using a GPS controlled spreader.

John Fukker, director of Galaxy PrecisionAG Services, states that ‘satellite imagery has been used to monitor agriculture for a while, but it is only recently that Imaging GIS (Geographic Information Systems) has become more affordable and accessible so that we can allow the individual farmers to share in the benefits.’ The image processing functions built into the ERDAS IMAGINE software allow Galaxy PrecisionAG Services to enhance multispectral imagery to highlight the subtle differences in crop performance which exist in every field. The reflective variations within the image are used to create accurate Farmsense enhanced satellite maps highlighting the variations in crop performance. These maps provide the farmer the opportunity to correct every feature within a field, for example, they may indicate stress conditions caused by poor soil conditions which can be corrected by dispensing fertiliser in the exact quantities and location.

You can find out more from the ERDAS Web site at http://www.erdas.com. This is a well laid out site, very easy to navigate, no fancy frames, etc., to confuse Web newcomers. In their Fall 1995 on-line Newsletter, “Monitor”, you will find an informative article on “GIS and Agrometerology: Today’s Farmer’s Almanac” - and in the Products and Services section, introductory info (simple, one-page explanations, for the non-technical remote sensing person) on “Why Imaging GIS?” and an introduction to their MapSheets, including Frequently Asked Questions (FAQs).

So...give it a go.

***
On the global front, why not have a look at the United Nations Environment Programme site for CGIAR - Use of Geographic Information Systems in Agricultural Research - located at http://www.grida.no/prog/global/cgiar/. Here you will find out how GIS is being used in projects around the world in agricultural research, including remote sensing projects and land use monitoring, etc. in developed and developing nations. A quite comprehensive site, maintained by UNEP-GRID at Arendal, Norway.
Contents Review 1
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Remote Sensing News: Mapping Awareness September 1996

Eye in the sky for Euro farm policy

Scott Wilson Kirkpatrick, Remote Sensing Applications Consultants and Earth Observation Sciences were awarded the UK contract to monitor the 'set-aside' and arable area payment schemes of the common agricultural policy. The schemes are designed to reduce overproduction in certain markets by paying farmers to use their lands for specific crops or to leave them uncultivated for a year. Checks are needed to detect erroneous and fraudulent claims for subsidies. The consortium will use Cropins, a customised version of Laser-Scan's IGIS software, to process the images and integrate land information with images from the SPOT (F) and Landsat (USA) satellites to determine crop area, type and eligibility. The data is then compared with farmers' declarations, and any anomalies are reported to the Ministry of Agriculture, Fisheries and Food. The system incorporates use of radar images, enabling the identification of crops even under cloudy conditions.
Contents Review 1
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“Getting to the root of crop yields
Estimating crop yields is a potentially lucrative application for GIS. Once natural variables like the weather and water supply have been accounted for, sophisticated and accurate yield prediction models97Äbased on satellite data—become feasible. It's already a reality for sugar beet.

Being able to predict likely sugar beet yields helps producers plan and cost their resources at an operational factory level. It also helps them to establish appropriate storage and distribution facilities. In an industry regulated by an EC quota system, it should help ensure that marketing efforts are directed towards the most profitable sectors.

An article in Mapping Awareness (February 1995) reported on a three-year project to predict sugar beet yields up to four months ahead of harvest for British Sugar, using satellite-based earth observation data integrated in a GIS. The project, sponsored by the British National Space Centre, is being carried out by a consortium, led by Logica UK and including British Sugar, Broom's Barn Experimental Station and the University of Nottingham.

The sugar beet project aimed to predict UK yields to within 0.75 tonnes per hectare for each factory catchment area during May, June, July and August for each year. In conjunction with Broom’s Barn Experimental Station, British Sugar had previously managed to predict the entire UK crop to within 1.0 tonnes of sugar per hectare, using a helicopter survey and numerical modelling. The consortium's new yield prediction system is based around Intergraph GIS and image processing technology.

Logica (UK) is also working for the Potato Marketing Board (PMB) to evaluate how satellite observation data might be useful in managing the UK potato crop. Both these projects highlight the role of remote sensing in implementing commercial operational systems and assisting the decision-making process in agricultural business.

The PMB needed a cost-effective way of monitoring the crop which, depending on the state of the market, can be the most profitable of all crops on an arable farm. Every potato grower in the UK has a defined quota which can be sold, leased or used by the owner to grow the crop. The PMB can fine those who grow more than their allocated amount; but if a grower does not use the quota in full, the PMB can reduce it for the next year.

SPOT (F) and Landsat (USA) satellite data have been the main sources of information for both the sugar beet and potato projects. University of Nottingham is investigating whether information about the status of the sugar beet crop can be derived from ERS SAR (Synthetic Aperture Radar) data, which is weather independent, i.e. permits satellite imaging through cloud cover.

The weather is the most important element in determining the yield of sugar beet, with sunshine and rain in the right amounts needed at specific points in the crop life cycle. A big problem in trying to forecast the yield model accurately early in the 1994 growing season was water stress experienced by much of the crop in Eastern England during July. When suffering from water stress, less carbon dioxide is available for the plants to photosynthesise. In a severe water shortage, photosynthesis stops completely. This proved significant in drought conditions experienced in July and August 1995. The sugar beet yield model developed for the project takes specific account of soil moisture and crop water uptake, to help identify periods when the crop is stressed and potential yield is reduced.

The consortium project team made sugar beet yield predictions for all eight of British Sugar's factory catchment areas, in both 1994 and 1995. The 1994 results exceeded the stated project objective, giving a prediction to within 0.1 tonnes per hectare nationally, using the satellite-based system. For most factory catchments, we guaranteed a figure of plus or minus 0.5 tonnes per hectare.

The results of our work on potato yields this year were output as plastic transparent overlays, which PMB field workers could use in conjunction with Ordnance Survey map sheets to check the accuracy of classification maps over a number of test areas. In general, more than 90 per cent accuracy was achieved in identifying potato fields.

“These two projects highlight the role satellite data can play in modern agri-business. The sugar beet yield prediction project has proved that an operational, commercially viable yield prediction system can be successfully implemented, and the work for the Potato Marketing Board underlines how valuable Earth observation data can be in accurately monitoring national land use.”

“Applications like these emphasise the power of data synergy, harnessed by the functionality of integrated data management in a GIS. Satellite information should no longer be seen as the preserve of the university academic; it is a cost-effective managerial tool that can potentially save millions of pounds.”

(extracted from an article by CLARE PRYOR, in Mapping Awareness, September 1996)
Contents Review 1
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GIS Review No 3 - 23 July 1997 - Roger Longhorn.


Contents:


The CAP and you -Big Brother is watching - or is he?

The Man from MARS (Monitoring Agriculture with Remote Sensing)


The CAP and you - Big Brother is watching - or is he?
Can GIS and remote sensing be effectively used to police the EU's programme of agricultural subsidies? Recent articles in the popular science press (by Mark Ward in New Scientist, No. 2082, 17 May 1997, p. 6) seem to indicate not. Under the current EU CAP (Common Agricultural Policy), large subsidies are paid to some farmers who grow certain crops. The scheme has been open to fraud, by claiming a higher subsidy than applies to the alleged crop in question, or even claiming subsidies when no crop is being grown at all.

To help combat this form of potential fraud, the Commission began a project in which remote sensing images from the SPOT satellites would be used to check actual crop coverage. Two problems emerge - (1) the SPOT images are expensive (about 75 - 80 ECU per square kilometre), which means that only sampling is possible, not complete coverage and (2) the underlying strategy, because of limited sampling, is flawed in regard to possible losses or gains to farmers for incorrect reporting.

Because of the high cost of remotely sensed images, and the post processing needed to make the raw images useful for crop analysis, fewer than 5% of applications for subsidies are checked by the Commission to see if they are authentic. Even for these applications, images are used to check only 3% of the farmland claimed. According to modern game theory analysis, which is used to assess likely gains to a farmer for an erroneous claim versus the cost to the Commission of checking claims, the Commission should be checking a much higher percentage of applications, if not all applications. This is according to Jean-Pierre Florens of the Social Science University in Toulouse, France. Florens goes so far (in the New Scientist article) as to say "The policy of the EU in trying to control fraud is totally stupid" because "the level of fines is very low and the number of images they use is low".

The Commission's response to an enquiry from New Scientist was that 'there are plans to increase the use of satellite photographs in policing agricultural subsidies'.

Interestingly enough, the CAP monitoring initiative was also discussed in a paper on "Decision-Analytic Interpretation of Remotely Sensed Data" (see reference below). One point made in the paper is that remotely sensed data is being more heavily used, via geographic information systems, to make major decisions, e.g. is a farmer engaged in fraudulent claims under the CAP. However, the degree of post processing needed to turn a raw, space-based image into something meaningful varies tremendously, depending upon the application and decision to be made. The paper looks at ways of "exploiting concepts from the mathematical framework of decision analysis for integrating (such) uncertainties and preferences".

In the case of fraud detection, the paper's authors (B.G.H. Gorte, L. C. van der Gaag and F.J.M. van der Wel) point out that the main objective is to detect illegal declarations of subsidised crops, using the remotely sensed images of crops on various parcels of land, hopefully to avoid waste of public resources. Thus, the number of illegal claims should be maximised. Yet pursuing a claim thought to be fraudulent, which turns out to be quite valid, is also to be avoided, as it is expensive (and thus a waste of "public resources") and because the policing authority loses face. (The paper is available in Advances in GIS Research II - Proceedings 7th International Symposium on Spatial Data Handling, Volume II, editors M. J. Kraak and M. Molenaar, International Geographical Union, published by Faculty of Geodetic Engineering, Delft University of Technology, Thijsseweg 11, NL-2629 JA Delft, the Netherlands).

So, to really maximise best use of CAP resources, an equitable balance must be found between the sampling rate (how many applications are actually checked), how many images need to be purchased (at 75 - 80 ECU per sq. km.) to check on any one claim, and how much time is needed in post processing of the raw image (another cost) in order to allow or disallow the claim.

The Man from MARS.

Claims for farm crop subsidies under the CAP are monitored at national level and by the Commission, where various Directorates General interact. The "new" DG - Joint Research Centre, in Ispra, Italy, via the Space Applications Institute (SAI) and its Agricultural Information Systems (AIS) Unit, operating in conjunction with DG VI (Agriculture) and Eurostat (Office of Statistics), execute the MARS Programme - Monitoring Agriculture with Remote Sensing, which was created by Council Decision 88/503/EEC reached in September 1988.

MARS was not initially concerned with any "policing" activity in regard to CAP subsidy claims, but rather focused (and still does today) on data collection, modelling, decision analysis, etc. for many areas of agricultural policy making. These include regional inventories, vegetation condition and yield indicators (see next month's article on the Vegetation programme and its associated new remote sensing satellite to be launched soon), models for yield protection, rapid estimates of European crop areas and potential yield, etc. The first phase of MARS extended from 1989 to 1994.

MARS was then extended in 1994 (from 1995 - 1998) for Phase II, by Council Decision L299 of November 1994. In Phase II, Activity F was started - "Control with Remote Sensing". As the Commission puts it on their MARS introductory documents (at URL http://aisws6.jrc.it:2001/ais.html ) "This activity uses multi-date (data), in order to verify, without any contact with the farmer, its declaration for Area aids. This first checking enables to sort the declarations, and to concentrate field control on the non-conform(ing) or suspicious dossiers and parcels". So, the question is - how does the JRC/SIA/AIS Unit assist DG VI in determining what is "suspicious or non-conforming"?

MARS tries to determine what crop cover is on any parcel of land at any one time using a combination of images from SPOT, TM and ERS1 satellites, and numerous image analysis techniques. For those of you not familiar with how much "post processing" of a raw image is required - which leads to questionability of the final "interpreted" result - take a look at the GIF file at URL http://aisws6.jrc.it:2001/ar96/figs/fig4c1-2.gif which is from the MARS 1996 Annual Report. Starting with a raw image file, the following "correction steps" take place: missing data and high scan angle rejection occurs; scan angle correction is made; cloud screening; sharp variation rejection; then weighted sliding average smoothing; then time interpolation and finally "smoothed data". In fact, the data may be so "smoothed" that the results are open to question!

From the main AIS Unit site referenced above, you can scan (and download, section by section - if you are VERY persistent!) the 1995 and 1996 Annual Reports of the AIS Unit, which are comprised 85% of MARS activities. They make quite interesting reading - even if you only look at Section 7 of each annual report, where work on "Control with Remote Sensing of Arable Land Subsidies" is reviewed each year.

In 1995, the report claims that 107 "sites" were imaged, using 72 satellite and 35 aerial photographs, in 13 countries, covering 100 168 applications for subsidy affecting 3 470 361 hectares. This represents 3.45% of the total number of "Area Aid Applications" (AAA) received, against an IACS (Integrated Administration and Control System) regulatory minimum target of 5%, whether checked remotely or on the ground. In Ireland, in 1995, two "sites" were imaged by satellite, covering 1 803 applications and 94 513 ha. In 1995, quality control was found to need more work, especially in conjunction with National Administrations who must coordinate checking on the ground.

Interestingly enough, the 1996 Annual Report contains no such detailed breakdown of coverage achieved, etc., except to note that "the MARS-CAP project is particularly involved in contributing to the technical management of large area projects (60 000 sq. km and upwards) in Ireland, Portugal and Greece. However, the technical management ultimately remains in the hands of the national administrations concerned."

So, the "Man from MARS" may be looking down on your fields at this very minute! But the chances of this happening are only about 1 in 30 - so don't lose too much sleep over it. And if your AAA claim IS challenged - why not hire a decision analysis specialist with image analysis background to refute the administrator's adjudication on the grounds that, after all that data "smoothing" - you could be growing pumpkins by the hectare and the "CAP space policeman" would mistake the crop for wheat!

Next issue: More on MARS and geographic information systems used in conjunction with remote sensing data, both at home here in Europe and "abroad".

GIS Reporter - R A Longhorn, Principal Consultant, GI/GIS, IDG Limited, EC Projects Office, Neihaff, L-9161 Ingeldorf
e-mail: ral@alum.mit.edu


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Roger Longhorn, Luxembourg ral@alum.mit.edu