Next Article in Journal
Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data
Next Article in Special Issue
Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX)
Previous Article in Journal
A Review of Swidden Agriculture in Southeast Asia
Previous Article in Special Issue
Long-Term Satellite Detection of Post-Fire Vegetation Trends in Boreal Forests of China
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2014, 6(2), 1684-1704; doi:10.3390/rs6021684

A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape

1
Department of Forestry and Management of the Environment and Natural Resources, School of Agricultural Sciences and Forestry, Democritus University of Thrace, Orestiada 68200, Greece
2
Forestry and Natural Environment, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
*
Author to whom correspondence should be addressed.
Received: 31 December 2013 / Revised: 8 February 2014 / Accepted: 13 February 2014 / Published: 20 February 2014
(This article belongs to the Special Issue Quantifying the Environmental Impact of Forest Fires)
View Full-Text   |   Download PDF [1135 KB, uploaded 19 June 2014]   |  

Abstract

Forest fires constitute a natural disturbance factor and an agent of environmental change with local to global impacts on Earth’s processes and functions. Accurate knowledge of forest fuel extent and properties can be an effective component for assessing the impacts of possible future wildfires on ecosystem services. Our study aims to evaluate and compare the spectral and spatial information inherent in the EO-1 Hyperion, Quickbird and Landsat TM imagery. The analysis was based on a support vector machine classification approach in order to discriminate and map Mediterranean fuel types. The fuel classification scheme followed a site-specific fuel model within the study area, which is suitable for fire behavior prediction and spatial simulation. The overall accuracy of the Quickbird-based fuel type mapping was higher than 74% with a quantity disagreement of 9% and an allocation disagreement of 17%. Both classifications from the Hyperion and Landsat TM fuel type maps presented approximately 70% overall accuracy and 16% allocation disagreement. The McNemar’s test indicated that the overall accuracy differences between the three produced fuel type maps were not significant (p < 0.05). Based on both overall and individual higher accuracies obtained with the use of the Quickbird image, this study suggests that the high spatial resolution might be more decisive than the high spectral resolution in Mediterranean fuel type mapping.
Keywords: SVMs; high spatial resolution; high spectral resolution; fuel type mapping; fire risk; fire impact; object-based; pixel-based SVMs; high spatial resolution; high spectral resolution; fuel type mapping; fire risk; fire impact; object-based; pixel-based
Figures

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Mallinis, G.; Galidaki, G.; Gitas, I. A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape. Remote Sens. 2014, 6, 1684-1704.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top