Vegetation mapping in the Parque Nacional, Brasilia (Brazil) area using advanced spaceborne thermal emission and reflection radiometer(ASTER) data and spectral identification method (SIM)

Osmar Abílio de Carvalho Júnior; Renato Fontes Guimarães; Ana Paula Ferreira de Carvalho; Nilton Correia da Silva; Eder de Souza Martins; Roberto Arnaldo Trancoso Gomes

doi:10.1117/12.627749

31 October 2005 Vegetation mapping in the Parque Nacional, Brasilia (Brazil) area using advanced spaceborne thermal emission and reflection radiometer (ASTER) data and spectral identification method (SIM)

Osmar Abílio de Carvalho Júnior, Renato Fontes Guimarães, Ana Paula Ferreira de Carvalho, Nilton Correia da Silva, Eder de Souza Martins, Roberto Arnaldo Trancoso Gomes

Author Affiliations +

Proceedings Volume 5983, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology V; 598307 (2005) https://doi.org/10.1117/12.627749
Event: SPIE Remote Sensing, 2005, Bruges, Belgium

Abstract

The spectral classifiers allow a good estimate for the mapping of the materials from the similarity between the reference curve and the image. Initially the spectral classifiers had been developed for hyperspectral images analysis. However, some works demonstrate good results for the application of these techniques in multispectral images. The present work aims to evaluate the spectral classifier Spectral Identification Method (SIM) in ASTER image. The Spectral Identification Method (SIM) is proposed to establish a new similarity index and three estimates according to the significance of regression (5%, 10% and 15%) of the materials. This method is based on two statistical procedures: ANOVA and Spectral Correlation Mapper (SCM) coefficient. This information can be used to evaluate the degree of correlation among the materials in analysis. The advantage of this method is to validate according to significance of regression most probable areas of the sought material. The method was applied to ASTER image at the Parque Nacional (DF - Brazil). The images were acquired with atmosphere correction. The pixels size from the SWIR image was duplicated in order to join the VNIR and SWIR images. Endmembers were detected in three steps: a) spectral reduction by the Minimum Noise Fraction (MNF), b) spatial reduction by the Pixel Purity Index (PPI) and c) manual identification of the endmembers using the N-dimensional visualizer. The classification was made from the endmembers of nonphotosynthetic vegetation (NPV), photosynthetic vegetation (PV) and soil. These procedures allowed identifying the main scenarios in the study area.

Citation Download Citation

Osmar Abílio de Carvalho Júnior, Renato Fontes Guimarães, Ana Paula Ferreira de Carvalho, Nilton Correia da Silva, Eder de Souza Martins, and Roberto Arnaldo Trancoso Gomes "Vegetation mapping in the Parque Nacional, Brasilia (Brazil) area using advanced spaceborne thermal emission and reflection radiometer (ASTER) data and spectral identification method (SIM)", Proc. SPIE 5983, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology V, 598307 (31 October 2005); https://doi.org/10.1117/12.627749

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Vegetation

Short wave infrared radiation

Atmospheric corrections

Reflectivity

Holmium

Particle filters

Multispectral imaging

Show All Keywords

Keywords/Phrases

Search In:

Publication Years