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F.M. Rabenilalana et al. 2010. Multi-temporal analysis of forest landscape fragmentation in the North East of Madagascar 91 Multi-temporal analysis of forest landscape fragmentation in the North East of Madagascar F.M. Rabenilalana 1 , L.G. Rajoelison 1 , J.P. Sorg 2 , J.L. Pfund 3 & H Rakoto Ratsimba 1 1 Département des Eaux et Forêts, Ecole Supérieure des Sciences Agronomiques, Université d’Antananarivo, Madagascar 2 Swiss Federal Institute of Technology Zurich, Institut of Terrestrial Ecosystems, Groupe de foresterie pour le développement, Zurich. Switzerland 3 CIFOR, Center for International Forestry Research, Bogor, Indonesia Abstract Habitat fragmentation caused by insufficient arable land and rural poverty has become a main concern to tropical forest managers in Madagascar. In order to inform management decisions, the present study aims to provide quantitative information on the fragmentation process and its driving forces in Manompana. Therefore, time series analysis of fragmentation in relation to the spatial distribution of settlements, roads and topographic parameters was done. Results showed that (1) deforestation has been increasing due to expanding upland rice production, thus progressively increasing landscape fragmentation (2) fragmentation dynamic significantly differed with distance to paths, villages and depending on topographic characteristics. In the following these parameters will be used for spatio-temporal modeling of the landscape dynamics to support decision making on sustainable management of natural resources. Keywords: landscape, fragmentation, tropical humid forest, spatial analysis, Madagascar. 1. Introduction Fragmentation refers to breaking a whole into smaller pieces while controlling for changes in the amount of habitat (Forman 1995, Fahrig 2003, Ewers 2006). Deforestation is one driver of habitat fragmentation. Fragmentation often results in the loss of habitat and the isolation of the remaining forest fragments. It creates matrices of human-managed areas, secondary vegetation regrowth, and fragments of primary forest (Benitez-Malvido 2003). The region of Manompana, is a disturbed tropical lowland rainforest,forming a forest corridor between two protected areas with very high levels of endemism: the special reserve Ambatovaky in the South West and Biosphere Reserve of Mananara Nord in the North. In the region of Manompana forest clearing due to slash and burn agriculture and commercial logging are the main drivers of deforestation and thus habitat fragmentation, affecting the landscape structure, the livelihoods and the biodiversity (Forman & Godron 1986, Andren 1992, Reed 1996, Franklin 2001, McGarigal 2002, Kuppfer 2006, Jaeger 2000, Collinge 2009). This paper aims to study spatio-temporal patterns of landscape fragmentation at a regional scale, i.e. the fragmentation of the forest ecosystem in Manompana in order to inform management decisions. Therefore, land cover predictions for future were made using SPOT 5 multispectral, multiband images (V 0,50 -0,59 μm R 0,61 -0,68 μm Near InfraRed or NIR 0,78 -0,89 μm and Mean InfraRed or MIR 1,58 -1,75 μm) with a 10 meters resolution from 2004 and 2009. Furthermore, 1 Corresponding author. Tel.:+2613367162 Email address: rmihajamanana@yahoo Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.) 2010, Instituto Politécnico de Bragança, Bragança, Portugal.
F.M. Rabenilalana et al. 2010. Multi-temporal analysis of forest landscape fragmentation in the North East of Madagascar 92 we focused on identifying the main factors that play a direct role in shaping the spatial variations in forest cover. We will start with a description of the data sources and the process of analysis adopted in the study and finally discuss directions and needs regarding the sustainable management of natural resources. 2. Methodology 2.1 Study area Manompana is situated on the eastern coast of Madagascar (752144 in the East and 1041646 in the north, Laborde Coordinates). This region experiences a warm and humid climate. Rainfall is reliable, and arises throughout the year with a mean annual rainfall of 3677 mm (Weather station at Soanieràna Ivongo, 2009). The wettest months are March and April at the beginning of winter. The temperature lies always above 21°C with a mean annual of 23,7°C (Weather station at Soanieràna Ivongo, 2009). The forest vegetation is typical of tropical lowland rainforest dominated by Anthostema madagascariensis and family of Myristicaceae (Guillaumet and Humbert 1975). 2.1.2 Data processing and classification There are many methods for detecting land cover changes available in the literature such as image differencing and post-classification. In the current study, image differencing was adopted (Singh 2009). This method is used mainly to detect areas with significant land cover changes and does not require atmospheric correction, but requires careful classification of “change / persistence” thresholds. In detail we followed the succeeding steps. First, the study area was extracted from the respective scene. In a second step, the forest components were identified using the classic method of radiometric intervals. The unsupervised classification was done using the application ISODATA (Iterative Self-Organizing Data Analysis Technics), the supervised classification was done using the application Maximum Likelihood in Arc Map 9.2, Arc view 3.2a and ENVI or Environment for Visualizing Images software (Gonzales 1988, Barrett and Curtis 1976). First, ISODATA calculated class means pixels evenly distributed in the data space. Consequently, it iteratively clustered the remaining pixels according to their reflectance (including the diffuse radiation by the atmosphere, the radiation reflected by the pixel and the radiation reflected from neighbouring pixels) using minimum distance techniques. Each iteration recalculated the means and reclassified pixels with respect to the new (class) means. This process continued until the number of pixels in each class changed by less than the selected pixel change threshold or until the maximum number of iterations is reached. Next, Maximum Likelihood methods were applied. This supervised classification assumed that the values for each class in each band are normally distributed and calculated the probability that a given pixel belongs to a specific class. Unless a probability threshold was selected, all pixels were classified. Each pixel was assigned to the class (forest, non forest) that had the highest probability. Finally, the fragmentation index was analyzed by pattern analysis. Fragmentation is a measure of the ecological quality of a habitat. In order to compute it, the following kernel-based formula (1) was used: Fragmentation = (n - l)/(c - 1) (1) where n is the number of different land-cover classes present in a kernel, and c the number of cells considered (Monmonier, 1974). The kernel represents the similarity between two cells defined as dot-product in the new vector space. Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.) 2010, Instituto Politécnico de Bragança, Bragança, Portugal.
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Landscapes Forest and Global Change
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The contributions to this volume ha
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Table of contents Foreword Preface
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Fine-scale mapping of High Nature V
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Characterization of a Maculinea alc
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Urban tree inventory and socio-econ
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xiii Foreword Twenty years ago, Dr.
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Section 1 Scaling in landscape anal
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V. Cortes et al. 2010. Environmenta
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D. S. de Ron et al. 2010. Habitat s
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S.F. Chen et al. 2010. A physiotope
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S. Frank et al. 2010. A regionally
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Section 4 Biodiversity conservation
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Akbarzadeh et al. 2010. Ecotourism
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Akbarzadeh et al. 2010. Ecotourism
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P.A.E. Diogo & J. Aranha 2010. GIS
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Management and conservation of Medi
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IUFRO Unit 8.01.02 Landscape Ecolog
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