Post fire natural regeneration monitoring with the integrated use of high resolution remotely sensed images: the case study of the Pineta di Castel Fusano
Author(s)
Date Issued
2008
Type
Article
Abstract
Stone pine stand of Castel Fusano (Rome) burnt on July the 4th 2000 during a huge wildfire.
As a consequence of the fire an intensive natural sexual and asexual regeneration
began. In order to monitor such a regeneration field surveys were carried out in 2003 and
2006 in sample plots. Remotely sensed high resolution images from Ikonos and Quick Bird
were acquired for the same years. The purpose of this work is to test different methodologies
for modeling existing relationships between remotely sensed images and ground
collected data in order to estimate and to map both sexual and asexual regeneration. For
such a purpose different methodologies were tested: step-wise Muliple Linear Regression,
Neural Networks (Relevance-Vector-Machine and the Multi-Layered-Perceptron) and the
k-Nearest-Neighbors. These activities were carried out within the framework of the GRINFOMED-
MEDIFIRE also developing a specific software named Spatial Forest Modeler
(SFM) able to analyze existing relationships between remotely sensed variables and data
collected in the field in order to identify the best available models to map and estimate the
studied variables acquired on the basis of a field sampling design. The present paper presents
data collected in the field, analysis and modeling methods and achieved results. The
SFM software is also presented.
Citation
Chirici, G. 2008. Post fire natural regeneration monitoring with the integrated use of high resolution remotely sensed images: the case study of the Pineta di Castel Fusano. "Italian Journal of Remote Sensing" 40 (1): 107-122.
File(s)![Thumbnail Image]()
Name
AIT_CHIRICI_ET_AL.pdf
Size
1.59 MB
Format
Adobe PDF
Checksum (MD5)
07ff28b308c3e0ccb129ce2d28f8ad0b