The view from space: Building models of the world



ARTEMIS draws upon satellite data to forecast crop production as well as conditions that might favour the buildup of locusts.

The new technologies of remote sensing and Geographic Information Systems (GIS) make it possible to gather, integrate and analyse vast bodies of data that can then be used to tackle complex environmental problems.

Remote sensing involves the collection and interpretation of information about something with which the sensor has no physical contact. Once simply a matter of climbing a hill and observing the lay of the land, it has evolved through black-and-white aerial photography into a complex process, using imaging radar, thermal scanning and satellites.

Modern remote sensing is based on picking up the electromagnetic energy emitted or reflected into space by different features on the earth's surface. This can provide information on geological structures, surface water, land use, soil conditions, vegetation, the oceans and a wide range of other factors relevant to agricultural and natural resource planning.

FAO's comprehensive assessment of the world's forest resources, published in 1995, drew upon remote sensing data and other national statistics. The Organization is now working on a land cover database for Africa. Such activities form part of the Global Environment Monitoring System (GEMS), a worldwide collective effort coordinated by the United Nations Environment Programme.

Two kinds of satellites are used for studying natural resources. Earth resources satellites, such as the United States' Landsat, France's SPOT and Japan's MOS, provide the detailed resolution (between 10 and 80 metres) required for thematic mapping of such things as land cover or erosion. FAO has drawn on data from earth resources satellites for thematic mapping projects in over 70 countries.

Environmental satellites, such as Europe's Meteosat or the United States' NOAA and AVHRR, offer more frequent but less detailed pictures of areas as large as countries or continents. FAO has used them to monitor rainfall and vegetation in Africa and the Near East. This information is processed by the computer system ARTEMIS (the Africa Real Time Environmental Monitoring Information System) and used to predict harvests, drought, locust swarms and food aid requirements.

Information from ARTEMIS is used by FAO's Global Information and Early

Warning System ( GIEWS ) and its Desert Locust Plague Prevention Group.

Remote sensing satellites, 900 kilometres up in space, enable scientists to monitor the conditions for crop production or which might encourage desert locusts to breed in large numbers. Since 1992 early warning of food crises and natural disasters has been transmitted to regional processing centres in Kenya, Ghana and Zimbabwe via the satellite telecommunications system DIANA (the Direct Information Access Network for Africa).

OLIVIA, a satellite environmental monitoring programme for Asia and the Pacific, is currently being developed.


How a remote sensing system works

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Remote sensors record and monitor the earth's surface by measuring the various emissions or reflections of electromagnetic energy from different types of vegetation, soils and other features.


Satellites used for remote sensing

This data is then colour coded to produce an image. Here red represents forest, blue/green, agricultural land, and purple, rocky outcrops

The image is then verified by ground sampling:
Olive groves High land Pasture


How a geographic information system works

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A GIS integrates various types and styles of data which have been collected using a number of different systems. For example, a user could climate, crops and population to establish optimum use of agricultural land for food production.

Resource use planning depends on correlating a vast quantity of data. For instance, a planner trying to locate suitable sites for growing a particular crop must combine information about soils, topography, rainfall, land tenure, transport, infrastructure, labour availability and distance from markets. This involves reconciling maps of different scales and types with tables of statistics and written information.

Until the early 1980s, this was a laborious process, achieved by overlaying transparent maps on light tables. Such manual integration of different soil maps used to prepare FAO's Soil Map of the World, for instance, took an estimated 150 person-years of work.

Introduction of the Geographic Information System (GIS) has transformed the situation. Once the data, often derived from remote sensing, have been entered into the computer system, they can be combined with other data to provide a wide range of outputs, including three-dimensional views, maps and tables. It is even possible to animate events. GIS can also be used to model the effect of a specific process over a period of time for a particular scenario.

FAO is harnessing GIS to help planners in the developing world make a wide range of decisions. It has been used, for example, to identify areas in Africa with potential for different kinds of irrigation, to assess the suitability of land for forestry and to map Kenya's agro-ecological zones. GIS helped Costa Rica to pinpoint the best sites for aquaculture in the Gulf of Nicoya.

GIS can also be a tool for the conservation of genetic resources. When the characteristics of places where samples have been found in the past are merged with maps of unexplored areas, GIS can give collectors an idea of new locations to search for germplasm. It can also provide an inventory of the species, characteristics and environmental conditions of a given area as an aid to in situ conservation.

In 1987, the former International Laboratory for Research on Animal Diseases used GRID, a GIS developed by UNEP, to investigate the environmental factors which limit the range of East Coast Fever, a tick-borne disease which kills many cattle in Africa. Data on climate, vegetation and cattle range were combined to identify high-risk areas where the disease might spread if infected cattle were introduced.


GIS in practice: the example of tsetse fly in Africa

GIS data on the current incidence and distribution of tsetse fly in Africa are used to assess, among other things, where cattle can be safely kept or where they might require protection.

The top map shows the present distribution of the palpalis group. This is a riverine species of tsetse fly which congregates in humid and sub-humid zones.

The bottom map shows cattle distribution superimposed on tsetse infested areas, thus giving an approximate picture of the current encroachment of the tsetse fly on grazing areas. It suggests that around 10 percent of the subcontinent's cattle are being kept within the tsetse-infested area. The dots on the periphery of the red area represent cattle distribution in the tsetse-free drylands.

Two of many electronic maps produced by FAO using GIS for environmental management and planning.
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GIS is used to identify high-risk areas that are then targeted in cattle vaccination programmes.