Specials Environment

Updated April 1999

Special: Remote Sensing for Decision-makers

Forest management

Pilot study in Morocco

Introduction | Aquaculture | Forest management | Rangeland assessment | Groundwater exploration | Forest fire management | Forest decline assessment | Crop information systems | Inventory and monitoring of shrimp farms

The use and management of forest resources need to be based on the mapping and inventory of the forestry environment. In addition to these static data, the changing state of the forest, as a result of natural or human-induced causes (felling, clearing, fire, reforestation, decline, regeneration, etc.), also needs to be monitored. Remote sensing and geographic information systems (GIS)2 provide for the continuous monitoring of forest developments by detecting changes and for the integration of the results into existing databases.

High-resolution satellite imagery

The operational availability of high-resolution satellite imagery, namely Landsat Thematic Mapper, SPOT, Soyouz and ERS-SAR, opens up new possibilities for investigating and monitoring forest resources. Compared with information acquired by traditional methods, these data offer a number of advantages:

Case study in Morocco: Monitoring and management of Maâmora National Forest

Maâmora National Forest, covering about 150 000 ha, lies along the Atlantic coast to the northwest of Rabat. It is mainly made up of a native species (cork oak) and certain introduced species (eucalyptus, pine, acacia). The forest is divided into five cantons, 33 groups and 460 forest plots. Its management plan has just been revised and its cartographic documents digitized (plot plans, types of stand).

A study was conducted on the changing state of Maâmora Forest, using remote sensing techniques and GIS, to supplement the static data and improve its management. The changing forest situation (felling, reforestation) was mapped by applying the differences method and by supervised classification of the SPOT multispectral images of 1989 and 1991. The results of this multidate study and existing data (plot plan, topography, etc.) were collated and fed into a GIS.

Changes in Maâmora Forest from 1989 to 1991

SPOT images 1989 (left) and 1991 (right)

Left: Image difference produced by subtraction of SPOT images 1989 and 1991
Right: Map of forest felling obtained by classification of image difference (C: felling, F: forest, NF: non-forest)

Remote sensing and GIS: decision-making aids

The multidate study of Maâmora Forest from SPOT images and additional data (existing documents, ground surveys) provided forest managers and developers with:

Map of changes in Maâmora Forest (1989-1991, integrated with existing baseline data

Evaluation and recommendations

Costs and delivery times

 Costs (US$/km2)Time (months)
Acquisition of satellite data3.51.0
Image processing and interpretation6.03.0
Ground survey1.51.0
GIS and databases4.02.0
Map preparation1.01.0

The evaluation of costs and delivery times is based on the overall implementation of the study through a combination of national expertise and minimal international assistance. The cost can be seen to be relatively high. However, total cost and delivery time will then almost halve at operational mode, for the following reasons:

A cost-effective technique

The multidate use of satellite imagery has provided access to synoptic and up-to-date information for the mapping, illustration and modelling of natural and human-induced events, such as regular felling, illicit felling, forest fires, reforestation and regeneration. This technique helps decision-making for the enhanced management and development of forest resources. The building of a database provides for the statistical and spatial analysis of data for the improved planning of future actions.


The methodology developed has led to the implementation of a GIS-based forest monitoring system that will be entirely operational once all the conventional data have been digitized and integrated (plot plan, topographic map, map of types of stand, management operations). The database can be updated on a regular basis (two to three years for example) depending on the scale and frequency of change in the forestry environment. As Maâmora is a representative Mediterranean forest, this methodology can be used in other countries of the Mediterranean basin to support forest management, subject to the availability of reliable databases and the necessary expertise.

This project was carried out by the Royal Centre of Spatial Remote Sensing and the Ministry of Agriculture and Agricultural Development of Morocco (MAMVA/AEFCS).

  • Adapted from FAO Remote Sensing for Decision-makers Series, No. 15, "Satellite imagery to assist forest management - Pilot study in Morocco". For a full list of issues available in the Series, see FAO Publications on Remote Sensing

    The designations employed and the presentation of material in this brochure do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations concerning the legal status of any country, territory, city or area or of its authority, or concerning the delimitation of its frontiers or boundaries.

    Remote sensing Introduction | Aquaculture | Forest management | Rangeland assessment | Groundwater exploration | Forest fire management | Forest decline assessment | Crop information systems | Inventory and monitoring of shrimp farms

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