Full text: Technical Commission VII (B7)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
    
SPECTRAL ANALYSIS OF DIFFERENT VEGETATION COVER USING THE 
HYPERION SENSOR - A CASE STUDY IN THE STATE OF RIO DE JANEIRO - BRAZIL 
E. M. F. R. de Souza ??, , R. S. Vicens *, A. E. P. Rosa *, C. B. M. Cruz? 
a UFF, Dept. of Geography, Federal University Fluminense, Brazil, Niteroi - (elizabethmfr, rsvicens, 
anely2509)@gmail.com 
b UFRJ, Dept. of Geography, Federal University of Rio de Janeiro, Brazil, Rio de Janeiro, (carlamad@gmail.com) 
Commission VII/3 
KEY WORDS: Hyperespectral, Vegetation cover, Landscape, Remote Sensing, Atlantic Forest. 
ABSTRACT: 
The knowledge about of land use and current status of vegetation represent important steps in understanding the spatial dynamics in 
areas with increased removal of vegetation and human disturbance. This feature is very common in its Brazil considering the 
biophysical diversity observed. In this sense, interest in patterns and processes that lead to environmental changes has been receiving 
great support from geoprocessing and remote sensing for monitoring, environmental and planning of natural resources. Following 
this trend, the study uses products from hyperspectral geotechnology to identify new methods of analysis of the landscape, in areas 
with vegetation remnants of Atlantic Forest in the State of the Rio de Janeiro. 
1. INTRODUCTION 
1.1 Relevance of the Research 
This study seeks to determine the classification targets that 
represent the vegetation Atlantic Forest using hyperspectral 
remote sensing. Actions focused on environmental management 
and control of deforestation will be benefited with the results. 
In this context is important to note that the use of 
geotechnologies, especially the remote sensing techniques 
already were adopted in studies of different vegetation covers 
during the '40s through the use of the aerial photographs. The 
results obtained by RADAM Brazil represent an important 
milestone for the application of this tool. This aspect is 
important because show the beginning to specific applications 
in landscape and the classification of images or photos for the 
generation of thematic maps. 
According Ponzoni and Shimabukuro (2007) during the 80 
begin the activities for the classification of different vegetation 
cover with an emphasis on qualitative analysis. The context 
begins to change from the 90's. In this moment arise new 
studies with remote sensing to explore the quantitative aspects, 
from the study of correlation between the biophysical and 
geophysical parameters of the environment, and radiometric 
data extracted from the images. 
1.2 Objectives and Study Area 
The aim of this study is to explore a geotechnology still little 
known among specialists in geosciences, especially geography, 
in order to identify the stages of vegetative conservation, 
considering the different spectral responses of vegetation in a 
section with the availability of hyperspectral images, in the 
State of Rio de Janeiro - Brazil. They are specifics objectives: 
Analysis of hyperspectral images and spectral responses for the 
different types surface, highlighting the spectral responses 
obtained for the structures of forest fragments in approximate. 
scale of 1:100,000, using the samples and analysis of resulting 
graphs. 
The study area covers the cities of Paraíba do Sul, Areal, 
Petrópolis and Duque de Caxias, in the Rio de Janeiro state. 
The Figure 1 highlights the study area. 
  
  
Figure 1. Study area 
According to Souza (2009) the knowledge about the spectral 
behavior of vegetation is essential for the correct extraction of 
different classes from the images. 
According to Goel (1988), the radiation detected by the sensors 
is a function of parameters of the radiation source, the 
atmosphere, canopy of the trees, soil, parameters of the sensor. 
So what is actually measured by a remote sensor come from a 
  
	        
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