Quality Management in Information Systems for Combating Desertification and Dry Lands Management

  • Mounir Sellami
  • Mohamed Talbi
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

As shown in the Convention to Combat Desertification (UNCCD), as well as in Chapter 12 of Agenda 21, desertification is one of the world's most serious environmental problems, threatening the earth's fertility and population food security.

Desertification is spreading due to climatic causes and human activities, both those performed in a single area and those performed all over the world (climate change). Some measures can only be taken at a general level, but others have to be taken at regional, national or local level. Combating desertification and the tasks to mitigate the effect of droughts requires an integrated treatment of the physical, biological and socio-economic aspects.

Understanding natural, social, cultural, economic and political features of local and national environments, in particular their dynamics and interactions, is considered as one of the basic principles of the Convention to Combat Desertification.

Improvement of the knowledge base is widely considered as a necessary first step for addressing the relevant problems and developing appropriate solutions. Many research and data-collection activities are being implemented worldwide, mainly to better understand the state of the natural resources in dry lands areas.

Such dry lands cover 40% of the world's land surface, and are the habitat and source of livelihood for more than one billion people. Of the 5,200 million hectares of dry lands used for agriculture, more than 70% are suffering from degradation. Africa, Asia, and Latin America are particularly under threat, but some 30 million hectares of European territory, especially those bordering the Mediterranean, are also potentially affected, threatening the livelihoods of over than 16.5 million people.

The mind of partnership as inspired by the UNCCD requires flexibility and simplicity in information circulation to all levels of decision: from local to international, and vice versa.

The assessment of the current status of desertification in a country is a crucial first step for understanding and correcting the problem. National assessment maps are needed for planners and decision-makers to establish priorities for combating desertification. Considered the cost of the environmental damage caused by land degradation and considered the absence of reliable information, sustainable decisions can hardly be made.

Dry land desertification can be remedied or even reversed, if updated information is provided on affected areas; especially concerning land use detection.

Satellite images can highlight relevant land use change along with increased surface reflectivity, temperature, dryness and dustiness; infrared sensors can detect vegetation stress due to environmental shifts.

This satellite data, if combined with in-situ information, processing tools, models, databases management and geo-information systems (GIS), can create standardized and comparable geo-information products, which can also be used to satisfy UNCCD reporting requirements.

Advanced technologies for helping desertification assessment and monitoring, can be of great value: computers, satellite images, GIS and databases management systems have revolutionized natural resource data collection methods. However, these tools do not substitute field studies.

Another problem related to gathering data on arid lands is the diversity of sources, which influences negatively, and sometimes crucially, the GIS and databases quality. As result, the quality of products used in making decisions, can be more or less useful or erroneous. Therefore a quality control of the natural resources management databases in the arid regions becomes a necessity.


Environmental databases desertification information systems data quality arid lands management 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E., 1976, A Land Use and Land Cover Classification System for Use with Remote Sensor Data. U.S. Geological Survey, Professional Paper, Reston, VAGoogle Scholar
  2. Edwards, G., and Lowell, K.E., 1996, Modeling uncertainty in photointerpreted boundaries. Photogrammetric Engineering and Remote Sensing, 62(4), 377–391Google Scholar
  3. Ehlschlaeger, C.R., and Goodchild, M.F., 1994a, Dealing with Uncertainty in Categorical Coverage Maps: Defining, Visualizing, and Managing Errors. Proceedings, Workshop on Geographic Information Systems at the Conference on Information and Knowledge Management, Gaithersburg, MD, 86–91Google Scholar
  4. Ehlschlaeger, C.R., and Goodchild, M.F., 1994b, Uncertainty in Spatial Data: Defining, Visualizing, and Managing Data Errors.Proceedings of GIS/LIS, 246–253Google Scholar
  5. Pang, A., and Furman, J., 1994, Data quality issues in visualization. SPIE Proceedings on Visual Data Exploration and Analysis, 2178, 12–23Google Scholar
  6. Shi, W., 1997, Statistical modeling uncertainties of three-dimensional GIS features. Cartography and Geographic Information Systems, 24(1), 21–26CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media B.V 2009

Authors and Affiliations

  1. 1.Sahara & Sahel Observatory (OSS)Tunisia
  2. 2.Sahara & Sahel Observatory (OSS)Tunisia

Personalised recommendations