**Author details**

Janvier Fotsing *Corresponding Author University of Buea, Faculty of Science/Department of Physics, Cameroon* 

Emmanuel Tonye *University of Yaounde I, National Advanced School of Engineering, Department of Electrical and Telecommunications Engineering, Cameroon* 

Bernard Essimbi Zobo *University of Yaounde I, Faculty of Science, Department of Physics, Cameroon* 

Narcisse Talla Tankam *University of Dschang, Fotso Victor Institute of Technology, Department of Computer Sciences, Cameroon* 

Jean-Paul Rudant *University of Marne-La-Vallée, Institut Francilien des Géosciences, France* 

### **Acknowledgement**

This work was supported by the LETS laboratory of the National Advanced School of Engineering of the University of Yaoundé I. We are also grateful unto the European Spatial Agency (ESA) for the grant of SAR ERS-1 image used in this study.

#### **7. References**


Akono, A.; Talla Tankam, N.; Tonyé E.; Ndi Nyoungui, A.; Dipanda, A. (2006). High Order Textural Classification of two SAR ERS images on Mount Cameroon. *Geocarto International*, vol. 21, n° 3, pp.1-16.

224 Cartography – A Tool for Spatial Analysis

extrema.

**Author details** 

Emmanuel Tonye

Bernard Essimbi Zobo

Narcisse Talla Tankam

**Acknowledgement** 

Jean-Paul Rudant

**7. References** 

pp. 1957-1967.

*Cameroon* 

Janvier Fotsing *Corresponding Author* 

least square method. The operation of the histogram and the signature of the texture image can facilitate the detection of classification thresholds. The main interest of the proposed approach is that we have results that are approaching the best of the reality field; it also does not require a serial multi-date SAR data for the realization of satellite image maps. The method was successfully tested on two satellite images from two different sensors: one from the ESAR program obtained at the resolution 6m and one other from the ERS-1 sensor of resolution 25 m. A limitation of the classification approach lies at the empirical detection of local extrema. A perspective would then be to automate the detection of the number of classes and local

*University of Buea, Faculty of Science/Department of Physics, Cameroon* 

*University of Yaounde I, Faculty of Science, Department of Physics, Cameroon* 

*University of Marne-La-Vallée, Institut Francilien des Géosciences, France* 

Agency (ESA) for the grant of SAR ERS-1 image used in this study.

*University of Dschang, Fotso Victor Institute of Technology, Department of Computer Sciences,* 

This work was supported by the LETS laboratory of the National Advanced School of Engineering of the University of Yaoundé I. We are also grateful unto the European Spatial

Akono, A.; Tonyé, E.; Ndi Nyoungui, A. (2003). Nouvelle méthodologie d'évaluation des paramètres de texture d'ordre trois. *Internationnal Journal of Remote Sensing*, vol.24, n°9,

Akono, A.; Talla Tankam, N.; Tonyé, E.; Dzepa, C. (2005). Nouvel algorithme d'évaluation des paramètres de texture d'ordre n sur la classification de l'occupation des sols de la région volcanique du Mont Cameroun. *Télédétection*, vol. 5, n° 1-2-3, pp. 227-244, Avril 2005.

*University of Yaounde I, National Advanced School of Engineering, Department of Electrical and Telecommunications Engineering, Cameroon* 


*Thèse présentée à l'Université de Nice- Sophia Antipolis pour obtenir le titre de Docteur en Sciences Spécialité Sciences de l'Ingénieur*. 162 pages.

**Chapter 10** 

© 2012 De Las Heras et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2012 De Las Heras et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Cartography of Landscape Dynamics in** 

Ecological and spatial analysis helps us to characterize the territory and know the spatiotemporal relationship between different components of the landscape. Landscape ecology has developed several methods of assessment and analysis of indicators by using Geographical Information Systems [1-4]. Such methods allow characterization of changes in land structure and land uses, as well as the interpretation of the ecological consequences of these dynamics [5]. They also facilitate analysis of the territory, trying to recognize and compare different spatial configurations, using patches of different shapes, numbers,

Several authors have carried out research attempting to integrate the study of territorial dynamics, from an ecological perspective, using Geographic Information Systems [9, 10]. The landscape is influenced by natural and anthropic processes, and the effects of both factors are expressed either at local or regional scale on the territory, showing changes in their structure and composition [11]. Clearly, the landscape appears to us as a complex of many different elements that can reach a great diversity [12]. In Mediterranean areas, the landscape is characterized by a heterogeneous mosaic of land uses and vegetation, where natural subsystems coexist adjacent to other systems at different degrees of perturbation due to human intervention and, therefore, with different degree of ecological maturity, separated by clear boundaries [13, 14]. The intense dynamic of land use changes occurred in these areas over recent decades has caused important changes in the structure of the landscape, as a result of fragmentation processes [14-19]. This influences various ecological processes, including those relating to the matter and energy flows between patches, by altering the composition and distribution of communities, the survival and coexistence of

N. López-Estébanez, F. Allende, P. Fernández-Sañudo,

M.J. Roldán Martín and P. De Las Heras

Additional information is available at the end of the chapter

**Central Spain** 

http://dx.doi.org/10.5772/47841

**1. Introduction** 

classes, etc. [6-8].

species, and species diversity [20-25].

