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Page 1: The Forest Fire of Parnitha Mountain, Greece

The forest fire of Parnitha mountain , Attica, Greece on June 28th 2007 Christos Kastrisios

GEOG 652 – Final Project

Introduction The main objective of this project is to

identify and measure the area burned and need to

be reforested and evaluate in what extent the

place of exceptional natural beauty (NATURA)

was affected. Additionally I will evaluate the

current condition of the burned area; several

public and private reforestation efforts have been

performed and I indent to find the area that

remains destroyed although the reforestation and

the natural recovery of the forest.

References Jensen, J., “Introductory Digital Image Processing”(2005)

http://www.parnitha-np.gr/index.htm

http://www.parnitha-np.gr/glk_master.pdf

Abstract Mount Parnitha is the highest mountain in

Attica (one of the 13 administrative regions of

Greece) with an elevation of 1,413 m, located

20km northwest of the capital city of Athens.

Parnitha is a densely forested mountain with

pretty rich flora and fauna (the flora of Parnitha

comprises of 1.100 taxa; that is equal to the taxa

of whole Scandinavia). Parnitha is part of the

ecological network Natura 2000 with a national

park and a place of exceptional natural beauty.

On June 28th 2007 a massive forest fire

broke out which within three days claimed a

large proportion of the rare Greek Fir and Aleppo

Pine forest, birds and rare animal species.

According to scientists it would take about a

century for the ecosystem to recover without

intense reforestation efforts.

Data The study area and period are limited by the

fire. The time frame is before and after the fire in

2007 as well as the condition in 2011. The fire

started on June 28th but due to the temporal

resolution of Landsat 5 the imagery used was

acquired on May and July 2007. For 2011 I will

use an August L5 image. Imagery data were

downloaded from http://glovis.usgs.gov/. For

classification purposes additional L7 images

were also utilized. GIS data (administrative areas

and Natura datasets) acquired from the Greek

http://www.geodata.gov.gr. Finally ENVI,

ArcMap, ArcGlobe and Google earth were used

as well as yahoo. maps web site.

Methodology In the flowchart diagram we can see the

procedures implemented in the study. After the

acquisition of data, the images were preprocessed in

ENVI. The atmospheric error was corrected by

calibrating the images and then a subtraction of the

minimum value in each band accounted for the Dark

Object correction. After having stacked bands,

1,2,3,4,5 and 7, the images were spatially subseted to

the area of study using custom ROIs as EVF.

The NDVI transformation couldn‟t be utilized to

determine the burnt area size due to the nearby quarry

area (SW) which reflectance values were similar to

the burnt forest (Fig. 4 and Fig.11 for NDVI values).

Similarly the significance change in agricultural areas

(NW) reflectance characteristics from May to July,

raised difficulties in utilizing the NDVI results for

Change Detection analysis (CD) (Fig. 5 and Fig.11).

Therefore the best delineation of the study area

was achieved using supervised classification methods

(ISODATA created a fuzzy result with regards to the

May image). After classifying the May and July

(Figure 6) images, I ran clumping and combining

classes functions, in order to give spatial coherence to

and bring out the Burnt Area class (Figure 6). Then by

utilizing the higher resolution images (L7) as well as

Google Earth and yahoo.maps applications, the

necessary for the accuracy assessment ground truth

ROIs were created. The overall accuracy of the July

classification was 95.2489% and Khat 0.9445. The

Producer and user accuracies are shown in Figure 9.

Similar accuracies achieved for May and August.

The final step was assessing the Land Cover

change from July 2007 to August 2011 for the

destroyed area. Figure 8 is an ArcGlobe export

showing the CD map superimposed above the August

image. In Fig.11 we can see the NDVI values for

random pixels before, after the fire and in August „11.

Data Acquisition

Pre-Processing

Image Subsetting

Stacking

Calibration

Image Exploration

Image Classification

Change Detection

GIS data and results Utilization

May to July 2007

Accuracy Assesment

Combine Classes

Clumping Function

Classificat.

Transfor- mations

Enhance- ment

July 07 to Aug 2011

ArcGlobe utilization

ArcMap utilization

Re-project GIS Data

GIS data

Landsat L7

Landsat L5

Results and discussion The CD analysis revealed that 46.783.900 m2

(18.1 sq.miles) were destroyed from the fire. That is

approximately one third of Parnitha‟s Natura Area (57

sq.mi.) (Figure 10). Most of the burnt areas where

densely forested (50%), while 37% was medium

dense forest and 13% was classified as sparse/fields.

The 2011 imagery analysis revealed that, due to

reforestation and natural processes, 9.6 sq.mi. had

increased vegetation existence in comparison to July

2007 (yet, only 1 sq.mi. could be considered as dense

forest). Unfortunately about half of the previously

forestall areas are now mostly fields and bare soil.

Fig.11

NDVI

Values

Dense

Forest

(reforested)

Medium

Forest

(Refor.)

Sparse

Vegetat.

Agricult.

common

values

Agricult.

extreme

value

Quarry

Previously

Dense ‘11

destroyed

May 07 0.60 0.47 0.39 0.27 0.36 0.08 0.64

July 07 0.06 0.08 0.09 0.33 0.19 0.08 0.07

Aug 11 0.50 0.42 0.25 0.33 0.31 0.08 0.15

Agriculture

Quarry

Fig.1 – May 2007

Fig.2 – July 2007 Fig.3 – Aug 2011

Fig.8 – CD ‘07-’11

Fig.7 – CD Forest Fire

Fig.4 – July NDVI

Fig.10 – Burnt and NATURA areas

Fig.5 – NDVI Ch.Detection

Agriculture change

Fig.9 – July Accuracies

Fig.6 –Classification

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