Landscapes Forest and Global Change - ESA - Escola Superior ...

F.M. Rabenilalana et al. 2010. Multi-temporal analysis of forest landscape fragmentation in the North East of Madagascar
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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.