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J. Schaefer-Santos & C. Lingnau 2010. Landscapes in Transition – Monitoring in Areas of Landslides
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Landscapes in Transition – Monitoring in Areas of Landslides
Jorgeane Schaefer-Santos * & Christel Lingnau
Curitiba Federal University, Brazil
Abstract
The satellite images have been very effective for monitoring the landscapes dynamics.
Landscapes vulnerable to disasters can be monitored by change detection techniques. We
applied these techniques in areas affected by landslides in November 2008 in Morro do Bau,
Santa Catarina State, which led to material and human losses. The study used four images from
different dates between 1992 and 2009. Vegetation index were developed using bands 7 and 4,
minimizing the atmospheric and radiometric effects. The techniques used were effective to
detect changes caused by the disaster, such as soil exposure and deposition; during the study
period there was no deforestation in the area of landslides; the event had magnitude greater than
the forests protection could promote, mainly high rainfall, combined with the high potential
erosion of these mountains sediments. These landscapes are subject to natural relief
accommodation events that will inevitably be disaster if associated with human occupation.
Keywords: change detection techniques; landslides; environmental disaster; Itajaí Valley;
landscape dynamic.
1. Introduction
The Itajaí Basin covers an area economically very important for the State of Santa Catarina,
southern Brazil. The mountainous relief prints fragility of landslides exacerbated by other
regional environmental problems as water pollution, illegal occupations and sewer without
treatment. Over time, with the rural exodus and urban growth, the region became even more
subject to problems of burial and flooding produced by inadequate occupation of urban land and
silting and contamination results in erosion and lack of rural waste treatment and urban
(Schaefer-Santos, 2003).
All these changes in land cover and land use can be detected through time series of satellite
images with the application of techniques of change detection. The mapping can be
accomplished from the comparison of classified images, subtraction of bands of the same area at
different times, vegetation indices, principal component analysis and neural networks (Carvalho
Jr & Silva, 2007).
Some changes, such as the increase or decrease in forest cover, can be evaluated based on
vegetation index. Caring for the use of vegetation index should be taken, especially the false
changes that may be related to phenological changes, which are those that occur with various
species, such as leaf drop, flowering time, appearance of new leaves in spring (Matínez &
Gilabert, 2009). In a long term, these changes found may be related to climate change and largescale
disturbances antrogênicos (Bradley et al., 2007).
To be chosen images from similar periods of the year, representing the same seasonal cycle of
the forest, the effects of phenological changes are minimized as the effects generated by the
shadow of a region with rugged. Janoth et al. (2007) say that images Landsat–TM and SPOT XI
* Corresponding author. Tel.: 55 41 3360-4218 - Fax: 55 41 3360 4211
Email address: eng_jorgeane@yahoo.com.br
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.