Assessment of the impact of forest fires (1)

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Report of Case Study: Thasos island, NE Greece 1

Assessment of the impact of forest fires and

marble quarries on the environment of Thasos island

Ioannis Gitas, George Mouflis, George Mitri, Hara Minakou, Stavroula Iliadou, Spiros Tsakalidis

PP02-WP3: Implementation of best practice models in the development of case-studies through an interactive assessment procedure.

Laboratory of Forest Management and Remote Sensing, Faculty of Forestry & Natural Environment,

Aristotle University of Thessaloniki, Greece

This manuscript describes the research work carried out by the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki (ISOTEIA project partner 02) for WP3.5.

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List of Figures

Figure 1: Location of the study area ... 7

Figure 2: Pre-fire landcover types on the island of Thasos ... 11

Figure 3: Topographic relief of Thasos island... 11

Figure 4: Pre-fire area of different landcover types on Thasos ... 11

Figure 5: Landcover types amalgamation into 5 zones of vegetation cover... 12

Figure 6: Comparison of area of 5 landcover zones of functional interest... 12

Figure 7: Flowchart of methodology ... 14

Figure 8: Burned areas statistics ... 16

Figure 9: Multitemporal extent of fire damage on Thasos island ... 16

Figure 10: Total area burnt by landcover class in ha, and as percentages of original class area... 18

Figure 11: Burned landcover types by the fires of 1984, 1985, 1989 and 2000 ... 18

Figure 12: Percentages of area burned by landcover class ... 18

Figure 13: Burned vegetation per zone ... 18

Figure 14: Percentages of burned landcover types in 1984 Figure 15: Percentages of burned landcover types in 1985 Figure 16: Percentages of burned landcover types in 1989 ... 20

Figure 17: Percentages of burned landcover types in 2000 ... 20

Figure 18: Contribution of each landcover type to the area burned in each fire ... 20

Figure 19: Applied indices on the Landsat image of Thasos... 22

Figure 20: Landsat ETM+ image (R: band 4, G: band 3, B: band 2) along with all the (62) field data points from 1997 and 2004 ... 22

Figure 21: MSAVI thresholding ... 24

Figure 22: Year percentages of areas with unsuccessful and successful regeneration by MSAVI=0.51 thresholding ... 25

Figure 23: Applications of MSAVI threshold on the burned area of each fire... 25

Figure 24: Burned area of all years and areas below and above the chosen MSAVI threshold... 25

Figure 25: Regeneration assessment per landcover zone by MSAVI thresholding... 27

Figure 26: Post-fire vegetation recovery per zone of initial landcover ... 27

Figure 27: Vegetation recovery success (MSAVI threshold) per landcover type in ascending order ... 29

Figure 28: Regeneration assessment per zone of vegetation cover ... 29

Figure 29: Image differencing of band 4. The derivative image with the absolute values. ... 31

Figure 30: Highlight image of the image differencing of band 4. The areas in green are increased values and the areas in red are decreased values. ... 31

Figure 31: Marble quarry expansion in the northeast part of Thasos. ... 32

Figure 32: Classification of the 1984 image. Right: Classification of the 2000 image. Water (blue), land (red) and marble quarries (yellow) ... 32

Figure 33: Points taken with the GPS and extracted area of the quarries for the year 2000. ... 33

Figure 34: Comparison of the areas of quarry expansion mapped with each technique .. 34

Figure 35: Area of quarries to the total area of the island ... 35

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Figure 38: Area of quarries over total coniferous area ... 35

Figure 39: Land cover type of the area taken over by marble quarry expansion (1984-2000). ... 36

Figure 40: Quarry locations, viewshed extent and spatial variation in intensity of visual impact in 1984 Figure 41: Quarry locations, viewshed extent and spatial variation in intensity of visual impact in 2000 ... 40

Figure 42 (left): Quarry Viewshed expansion Figure 43 (right): Level of visual impact change between 1984 and 2000 ... 40

Figure 44 (below): Quantification of level of visual impact change with moving average trendline... 40

List of Tables

Table 1: Data used in the development of the case study ... 9

Table 2: Landcover types amalgamated into 5 zones of vegetation ... 12

Table 3: Statistics of extent of burned areas ... 16

Table 4: Vegetation indices evaluation with the use of % vegetation cover from field data... 23

Table 5: Error matrix for the classified image of 2000... 33

Table 6: Areas of change detected from each method ... 34

Table 7: Landscape metrics of marble quarries in the island of Thasos in years 1984 and 2000 ... 37

Table 8: Expansion of viewshed of marble quarries between years 1984 and 2000 in Thasos island... 39

Table 9: Landcover classes burned by all fires as percentages of total area burned and original area of classes ... 45

Table 10: Application of MSAVI thresholding to each burned area. ... 45

Table 11: Percentages of areas below and above the selected MSAVI threshold ... 46

Table 12: Selected vegetation indices... 46

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1. Introduction

It has been well established in the literature that natural fires are an integral part of many terrestrial ecosystems such as boreal forests, temperate forests, Mediterranean ecosystems, savannas and grasslands among others. However, from the 1960s until today, the general trend in the number of fires and surface burnings in the European Mediterranean areas has increased exponentially (Moreno 1998). This increase is mainly due to: (a) changes in traditional land uses, the consequence of which is higher fuel accumulation, and (b) global climatic warming (Gitas 1999). Forest fires have an impact on humans, wildlife, hydrology and soil among others.

The ecological effects of fire vary enormously according to the time of the year; the quantity, condition, and distribution of fuel; the prevailing climatic conditions; and the duration and intensity of the fire (Trabaud 1994). The climatic conditions and the recent changes in landscape structure in the European Mediterranean countries favoured a new fire regime, characterized by frequent, extensive and high intensity fires occurring in the summer and early autumn. In general, the ecological consequences of this new fire regime can be summarised as follows:

• Effects on soil: high-intensity fires destroy the soil structure and reduce the bulk density and porosity of soil, which in turn results in a decrease in infiltration and an increase in runoff and erosion (DeBano et al. 1998) which can result in site degradation.

• Effects on nutrient cycle: Runoff and erosion can carry the minerals in the ash and soil downstream (DeBano et al. 1977), therefore decreasing the levels of nitrogen, calcium, magnesium and potassium (Kutiel & Shaviv 1989). Nitrogen loss can further take place in high-intensity fires by means of volatilisation (Knight 1966).

• Effects on biodiversity: Large fires that produce a greater number of intensely burned patches can favour the colonization of invasive, fire tolerant species at the expense of rare/endemic species less tolerant to post-fire conditions.

• Effects on landscape structure: large fires that produce a greater number of intensely burned patches can be a driving force in landscape homogenisation.

• Effect on fire frequency: burned areas in which flammable shrublands expand can have a greater likelihood of reburning than neighbouring unburned areas.

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Report of Case Study: Thasos island, NE Greece 6 from as long ago as in ancient Rome (Drew et al. 2002).

Marble extraction is an economically important and widespread activity in modern Greece and other Mediterranean countries. The extraction takes place by open-pit quarries in hill slopes. The original landform is permanently altered and the original vegetation cover is destroyed. The visual impact of the quarries extends over larger areas as noticeable scars of high colour contrast, reducing the aesthetic appeal of the landscape and deteriorating the scenic quality of areas where tourism often is a major constituent of income.

Environmental Impact Assessment (EIA) is a requisite for sustainable development and EU has adopted this policy in Directives 1985/337 and 2001/42 which aim to provide for a high level of protection of the environment. These directives stipulate that EIA or Strategic Environmental Assessments are required during the planning or scoping stage of all projects and plans likely to have significant environmental impacts. There are various reporting frameworks for EIAs or conceptual models to develop effective strategies that achieve tangible conservation results (Stem et al. 2005), such as the 5S (Systems, Stresses, Sources of Stress, Strategies, Success Measures) (Anonymous 2000), or the DPSIR framework used in ISOTEIA which identifies the driving forces (D) and pressures (P) on the environment, indicators for the state (S) of the environment, the impacts (I), and the responses (R) to redress the balance in terms of environmental impacts (Bürgi et al. 2004; E.E.A. 1999).

Geographical Information Systems (GIS), Remote Sensing and landscape analysis are useful tools in measuring environmental impacts, especially when large areas are involved. These tools can be used for the identification and monitoring of areas in need of special or intense management after a forest fire event (Gitas 1999; Jakubauskas 1988; Jakubauskas et al. 1990) or landscape changes brought about by quarrying activities over large areas and long time-spans (Latifovic et al. 2005; Rigina 2002).

The aim of this case study was to assess the impact of forest fires and marble quarries on the environment of Thasos by employing GIS, Remote Sensing and landscape analysis. The specific objectives were:

1. To accurately map the burned areas and to estimate the ecological impact of fires. 2. To assess vegetation recovery following forest fires.

3. To map the quarries and their expansion using multi-temporal satellite data.

4. To assess the ecological and visual impact of quarries and describe their landscape dynamics.

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2. Background information and case-study development

Before moving into the results and discussion, some background information about the study area, conservation designations, relevant legislation and a description of data and methods are necessary.

2.1 Study area

The study area was the island of Thasos which is Greece's most northerly island (Figure 1) extending from 24o30’ to 24o48’ East and 40o33’ to 40o49’ North. Its surface area is 383 sq. km while its perimeter is approximately 128 km. Elevation ranges from 0 to 1200 m (Figure 3, p.11) while slopes range from 0 to 80 degrees.

The climate of Thasos is cool and humid Mediterranean according to the Emberger bioclimatic classification (Gitas 1999), characterised by a relatively high mean yearly precipitation (742.3 mm) and a xerothermic period that starts in May and lasts through September (Spanos et al. 2000). According to the formula of Emberger, the pluviothermic quotient Q for Thasos is 87.4 and the Mediterranean-type climate of the island can be further classified to the cold and subhumid variant (Spanos et al. 2000).

Surface geology and soil depth: Approximately 65% of Thasos, the highland areas, is composed of metamorphic gneisses (gneiss of Maries). To the east of the island, there is a series of metamorphic rocks – the oldest, Potamia series – primarily composed of dolomites that constitute approximately 25% of the island’s total area. Quaternary deposits of clay, sand and gravel around the coastline, particularly in the areas of gentle slopes, make up the remaining 10%. The soil depth varies widely depending on surface geology, relief and vegetation density. Shallow soils (5-10 cm) prevail due to steep slopes, grazing, and repeated forest fires. Almost 50% of the island’s surface is covered with shallow soils, 35% with deep soils, while the remaining 15% is bare.

The landcover and vegetation description is described in 2.3.1. Pre-fire Landcover types and zones), p.9.

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Report of Case Study: Thasos island, NE Greece 8 In this section there is a summary of legislation pertaining to the study area and the environmental pressures analysed in this report, namely forest fires and marble quarries.

Special Areas for Conservation on Thasos island

With respect to the EU Directive (92/43/EEC) on the conservation of natural habitats & of wild fauna and flora (1992), to date Greece has identified mainly three candidate Special Areas for Conservation (cSACs) on Thasos. These are: Akrotirio Prinou-Pachy, Limenaria-Akrotirio Kefalas, Ormos Potamias. These three special areas have been chosen for their marine habitats, reefs and Poseidon oceanica beds.

European Legislation for Environmental Impact Assessments

Council Directive 97/11/EC of 3 March 1997 amending Directive 85/337/EEC on the assessment of the effects of certain public and private projects on the environment. In Annex 1, case 19, quarries and open-cast mining where the surface of the site exceeds 25 hectares, or peat extraction, where the surface of the site exceeds 150 hectares, are subject to ARTICLE 4 (1) (requirement for an environmental impact assessment). In Annex 2, Quarries, open-cast mining and peat extraction (with an area <25ha projects not included in Annex I), are subject to ARTICLE 4 (2) (requirement for an EIA depending on the specific project and thresholds and criteria set by Member States).

National Legislation for the protection of forests and forest fires

The national legislative framework for the protection of forests is Law 998/1979. This law stipulates that land-use change of public or private forest and forest areas is not permitted and no buildings of any sort can be constructed. Exceptions are provided for reasons of national security and defence, construction of public roads, energy lines and aqueducts. Denuded forests or forest areas (as a result of fire, clear felling, landslide, pathogen attack etc.) do not lose the protection afforded by this law but their protection is strengthened by their automatic designation within 3 months into “regeneration status”. In this status grazing is not allowed. Felling or any attempt to convert part of the area into agriculture or housing is severely prosecuted.

National Legislation for marble extraction and quarries

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2.3 Dataset description

The data used in this case study consisted of satellite images (QuickBird, Ikonos and Landsat TM and ETM+), a Digital Elevation Model, digital maps of pre-fire landcover (Figure 2 with their area in ha) produced from ortho-photos at a scale of 1:20,000 (Forest Service – Greek Ministry of Agriculture) and data collected in the field. All data are listed in Table 1 while the landcover is discussed in more detail below.

Table 1: Data used in the development of the case study

Type of Data Name/date of product Characteristics

Satellite image Quickbird (2003) multispectral 2.5 m and panchromatic 0.6 m - orthorectified

Satellite image Ikonos 1 m spatial resolution –

geometric and atmospheric corrections

Satellite image Landsat TM and ETM+ (1984-1985-1989-2000)

30 m spatial resolution – geometric and atmospheric corrections

Ancillary data Topographic map 1 : 50 000

Ancillary data Digital Elevation Model 10 m resolution

Ancillary data Landcover map Produced from orthophotos Field data Vegetation regeneration

plots (1997-2003-2004-2005)

GPS measurements

Field data Digital photographs Coded photos

Data derived from remote sensing analysis

Quarries and fire perimeters Object-oriented image analysis

2.3.1. Pre-fire Landcover types and zones

Before the forest fire of 1984, forest and forested lands covered 47.5% of the island, making forests the dominant landcover type at the time. After the fires of 1984 and 1985, forests and forested lands covered 37.95% of the island. Today, as a result of fires, illegal logging, intensive grazing and bad management, the remaining forest has a spatial extent of about 2000 ha in the Northern and Eastern parts of the island. Pinus brutia was the dominant species of the forests at elevations ranging from sea level up to 800 m, while Pinus nigra was the dominant species of the forests found in the mountainous areas of the island (Giakoumakis et al. 2002; Gitas 1999). Other types of Mediterranean vegetation present on the island are maquis and garigue.

The pre-fire landcover was composed of the following 14 classes: Pinus brutia forest,

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Abies borisii-regis mixed forest (Figure 2). The area of each landcover type is shown in a graph form in Figure 4, p.11. The landscape was characterized by the dominant landcover of coniferous forest, agricultural land and shrubland in this order.

It was decided to amalgamate these landcover classes into fewer, namely 5 ecologically related classes or zones of specific functional interest for the purposes of deriving and presenting zonal area statistics. Table 2, p.12 and Figure 5, p.12 show which landcover types make up the 5 landcover zones.

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andcover Figure 2: Pre-fire l

types on the island of Thasos

Figure 3: Topographic relief of Thasos island

Figure 4:Pre-fire area of different landcover types on Thasos

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Report of Case Study: Thasos island, NE Greece

Table 2: Landcover types amalgamated into 5 zones of vegetation

Landcover type Landcover type Area (ha) Landcover group (zone) Zone area (ha)

Abandoned farmland 54.8

Arable land _7825.6 Agriculture / Abandoned Farmland 7880.4

Bare land 440.9

Settlement 358.2 Settlement / Bare Land 799.1

Castanea 41.4

Platanus 49.9 Deciduous 91.4

Grassland 457.0

Quercus 14.3

Shrubland 5038.6

Other Vegetation 5510.0

Pinus brutia 19207.8

Pinus brutia - Pinus nigra 981.5

Pinus brutia - Platanus 46.6

Pinus nigra 3691.5

Pinus nigra - Abies 23.8

Conifers 23951.2

PINUS BRUTIA - PINUS NIGRA

PINUS BRUTIA - PLATANUS ABANDONED FARMLAND

PINUS NIGRA - ABIES ARABLE LAND

Figure 5: Landcover types amalgamation into 5 zones of vegetation cover

OTHER

Grouping of 14 landcover types (inner

circle / legend) into 5 zones (outer circle)

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2.4 Methods

A brief description of the main steps followed for the completion of the four objectives of this case study is given below and summarised schematically in Figure 7, p.14.

1. Mapping of burned areas and ecological impact assessment: The burned areas were located and mapped by employing object-oriented classification. Burned areas were then intersected with pre-fire landcover. This allowed the assessment of the ecological impact by means of area burned per landcover class and as percentages to the initial area of each landcover type as well as to the total surface of the island.

2. Post-fire regeneration assessment: A number of vegetation indices were calculated and then evaluated with regard to their efficiency to indicate density of vegetation cover (%). For the evaluation of the indices a field survey was conducted. Thresholds were then applied to MSAVI which was the best-performing vegetation index, in order to separate the areas of successful vegetation recovery. A comparison was then made of the vegetation recovery percentage per initial landcover class.

3. Mapping the quarries and their expansion since 1984: Quarries were delineated using image differencing and post classification comparison. Their extent was compared to the total area covered by coniferous forest and the total surface of the island.

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Mapping of quarries

Multi-temporal LandSat, QuickBird and Ikonos

sattelite images

Quarries Ecological Impact Assessment

Landscape and Visual Impact Assessment Forest fires Ecological

Impact Assessment

Environmental Impact Assessment

Regeneration

Forest fires Marble quarries

Object-based (VIs) from post-fire

satellite imagery

Accuracy assessment of VIs with the use of data from

field surveys

Selection of MSAVI as the best index

Maps produced from MSAVI thresholding

Extraction of area statistics from pre-fire landcover

LandSat 1984, 2000

Object-based classification

Mapping of quarries expansion

Extraction of area statistics from pre-fire

landcover

Maps of quarries 1984, 2000

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3. Results and discussion

In this section the results of the analyses of the data are presented and discussed. The numbering of the subsections is in correspondence with the numbering of the four objectives. The methodology followed for each objective is elaborated in more detail where necessary.

3.1. Mapping of burned areas and ecological impact assessment

Remote sensing was used to specify what areas were burned in the four major fires of 1984, 1985, 1989 and 2000. The assessment of the impact was made by comparison with the pre-fire land cover.

Object-based classification procedure for burned area mapping

Digital maps of burned areas have been produced using LANDSAT-TM and Ikonos images for the years 1984, 1985, 1989 and 2000 in the Greek island of Thasos. Object-oriented image analysis was used to map the burned areas. Object-Object-oriented image analysis, which is based on the fuzzy concept, is an approach that uses not only spectral information, but also spatial information. Fuzzy theory replaces the ‘yes’ or ‘no’ in the binary theory by the continuous (0-1), where 0 means ‘exactly no’ and 1 means ‘exactly yes’, thus all values between 0 and 1 represent a more or less certain status of yes and no. Segmentation, the first step in object-oriented approach, involves merging the pixels in the image into image object primitives called objects or segments with a certain heterogeneous and homogeneous criterion. This step is critical because segmentation generates the objects that will be treated as a whole in the classification. Multiresolution segmentation was firstly applied to the images. Image objects resulting from the segmentation procedure were therefore intended to be rather image object primitives, serving as information carriers and building blocks for further segmentation steps and for the final classification. The results of the classifications were then compared with the fire perimeters provided by the Greek Forest Service in order to assess their accuracy. The overall classification accuracies were estimated to be centred in most cases at approximately 98 %.

Area burned per year

The four major fires that occurred in 1984, 1985, 1989 and 2000 resulted in burning 48% of the island. The areas burned in each fire are shown in the map of Figure 9, p.16.As will be discussed later, 77% of this area was high forest.

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Burned area 1984

Burned area 1985

Burned area 1989

Burned area 2000

1601

8121

8531

197

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

ha

Burned areas (1984-2000)

Figure 8: Burned areas statistics Table 3: Statistics of extent of burned areas

Fires Area in ha % of island

Burned area 1984 1600.87 4.2%

Burned area 1985 8120.72 21.2%

Burned area 1989 8530.51 22.3%

Burned area 2000 197.33 0.5%

Total burned 18449.42 48.2%

Island total area 38250.27 100%

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Report of Case Study: Thasos island, NE Greece 17 The ecological assessment of the damage caused by fires was analysed by deriving area statistics of landcover classes (types) that were affected by all fires and for each fire separately.

In the following section there is an analysis of the damage caused by all fires.

3.1.1. Ecological assessment of all fires

As shown in Figure 10, p.18 and Figure 11, p.18, from the total area burned, the Pinus brutia forest was the single landcover class that contributed most (62%) to the total area burned. In descending order the rest of the area was made up from shrubland (12%), arable land (11%), Pinus nigra (9%) forest and mixed stands of Pinus brutia and Pinus nigra (4%), as well as the other classes (the remaining 2%) with smaller areas.

The mixed stands of P. brutia and P. nigra as well as the abandoned farmland and

Quercus sp. suffered most from the forest fires because a larger proportion of their original resource was burned (Figure 11, p.18). Area statistics and percentages of landcover types burned are listed in Table 9, p.45 of the Annex.

A comparison of the area burned by all fires, classified into the simpler 5 zones of vegetation cover (Figure 13, p.18), reveals that coniferous forest made up 75% of the area burned. Coniferous forest was the major landcover zone impacted. After fire the regeneration can reinstate these areas into forest again or part of this area can revert to lower vegetation types such as shrubland or grassland. Failure of regeneration leaves the soil exposed to erosion and there is a risk of degradation and permanent loss of vegetation. Therefore an assessment of vegetation recovery following the fire events is necessary to assess the post-fire impact. This assessment was carried out and is presented later.

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Burned vegetation per zone

13540.81925

12% coniferous_deciduous

other vegetation agriculture Figure 11: Burned landcover types by the fires of 1984, 1985, 1989 and 2000

Figure 13: Burned vegetation per zone Figure 10: Total area burnt by landcover class in ha, and as percentages of original class area

Figure 12: Percentages of area burned by landcover class in relation to the total burned area by all fires, and as percentages of the original class areas.

Area burned in all fires by original landcover class

11406.

Area burned in ha % of original class

Comparison of area percentages of landcover classes burned by all fires

0%

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3.1.2. Ecological assessment of individual fires

The assessment of landcover types burned in each fire event (Figure 14 - Figure 17, p.20) reveal that Pinus brutia forest contributed most of the area burned, as shown collectively also in Figure 12, p.18. In part this is due to the large initial area of Pinus brutia forest (Figure 4, p.11) but it also expresses the fire-proneness of this forest species.

• In the fire of 1984 (Figure 14) P. brutia accounted for 75% of the area burned, followed by shrubland (20%).

• These two landcover types made up 81% in the fire of 1985 (Figure 15) while 6% was made up from P. nigra and 12% by arable land.

• In the fire of 1989 (Figure 16) the percentage of P. brutia dropped to 55% but because the fire passed on to higher ground it burned mixed stands of P. brutia

and P. nigra (9%) and pure P. nigra stands (14%). The rest was arable land (12%) and shrubland (9%).

• The fire of 2000 (Figure 17) affected only P. brutia (91%) and shrubland (9%).

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Percentages per year of different lancover types burned

0%

1984 1985 1989 2000

%

PINUS BRUTIA

Figure 18: Contribution of each landcover type to the area burned in each fire Figure 14: Percentages of burned landcover types in 1984 Figure 15: Percentages of burned landcover types in 1985 Figure 16: Percentages of burned landcover types in 1989

Burned landcover (1985)

Figure 17: Percentages of burned landcover types in 2000

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Report of Case Study: Thasos island, NE Greece 21 As discussed earlier forest fires provide the starting point for secondary vegetation succession and set the template for a dynamic landscape change. While multi-temporal satellite imagery classification with multi-temporal field surveys can provide detailed landcover trajectories and landuse change matrices, a fundamental concern for an impact assessment is the assessment of post-fire vegetation recovery. Failure of sites to develop and adequate vegetation cover leaves the ground prone to erosion especially in steep sloping ground. For the purposes of this report an assessment of vegetation recovery was made in the year following the last fire event of 2000 by employing remotely sensed vegetation indices. The analyses made are presented in the following section.

3.2 Vegetation recovery assessment

The vegetation recovery assessment revealed that vegetation cover re-established on 2/3 of the area burned. Failure of vegetation recovery in the remaining 1/3 of the burned area may be attributed to adverse conditions for species recolonisation and establishment, soil erosion or grazing pressure during the first years after the fire. Long-term monitoring of the burned areas can be used to identify whether, at places, lack of vegetation recovery is of a temporary or permanent nature.

In the following section there is an evaluation of RS (remotely sensed) vegetation indices which of theoretical and applied interest, and case-specific assessment of vegetation recovery a) for the areas burned in each fire, and b) for the landcover types and zones, which is of theoretical and applied interest, relating to the post-fire response of burned areas depending on the initial landcover type.

3.2.1 Evaluation of vegetation indices for monitoring vegetation regeneration after fire in the case of Thasos

Twenty nine (29) Vegetation Indices were found in the literature. Seven indices out of the 29 were selected for evaluation, accuracy assessment and implementation (Annex, Table 12, p.46). These seven indices are shown below (Figure 19, p.22).

Vegetation indices evaluation for post-fire vegetation recovery assessment

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Figure 20: Landsat ETM+ image (R: band 4, G: band 3, B: band 2) along with all the (62) field data points from 1997 and 2004 LANDSAT ETM+ IMAGE, ALONG WITH (62) FIELD DATA POINTS

¯

0 1 875 3 750 7 500 11 250 15 000

Meters MSR (Modified Simple Ratio)

MSAVI (Modified Soil Adjusted Vegetation Index) MNLI (Modified non-Linear V.I.) NDVI (Normalized Difference Vegetation Index) II (Infrared Index)

GVI (Greenness Vegetation Index) SR (Simple Ratio)

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Report of Case Study: Thasos island, NE Greece 23 Although the field data were collected at different years than the images used, it is assumed that vegetation cover (%) has only slightly changed. This is supported by the field observations carried out. The position of field survey locations is shown in Figure 20, p.22.

The data were imported in SPSS for statistical analysis to define the correlation between the field data and the corresponding pixel data from the vegetation indices. Non-parametric correlation and least square regression method were applied and the correlation found is shown in the following table.

Table 4: Vegetation indices evaluation with the use of % vegetation cover from field data

a/a INDICES

NON-PARAMETRIC CORRELATION SPEARMAN

COEFFICIENTS

LEAST SQUARE

REGRESSION R2 VALUES

1 MSAVI 0,626 0,407

2 NDVI 0,626 0,404

3 II 0,626 0,404

4 MNLI 0,381 0,117

5 GVI 0,442 0,153

6 SR 0,626 0,385

7 MSR 0,626 0,395

Slightly better from II and NDVI proved to be the MSAVI (Modified soil adjusted vegetation index), with Spearman coefficient 0.626 and r2=0.407. MSAVI accounts for the influence of the soil background and it can be used when the vegetation cover has a low density, to minimize the effect of the bare soil (Santos et al. 2000).

3.2.2 Assessment of vegetation recovery by MSAVI thresholding

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Figure 21: MSAVI thresholding

Following the definition of the MSAVI threshold an assessment was made of the proportion of all burned areas and each individual fire above and below the threshold, as well as an analysis of MSAVI values for each landcover zone. The results are presented in the following sections.

3.2.3 Comparison of vegetation recovery for each fire

A comparison of the area below and above the selected MSAVI threshold (0.51), representing unsuccessful and successful post-fire vegetation recovery respectively, revealed that in total, 68% of the area burned showed adequate or abundant vegetation recovery, while the remainder 32% had not at the time of assessment developed an adequate vegetation cover (Figure 22, p.25).

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Fire 1989

27%

73%

MSAVI value <=0.51 MSAVI value >0.51

Fire 2000

60% 40%

Fire 1984

29%

71%

Fire 1985

38%

62%

Regeneration - All years burned areas

32%

68%

Figure 22: Year percentages of areas with unsuccessful and successful regeneration by MSAVI=0.51 thresholding

Figure 23: Applications of MSAVI threshold on the burned area of each fire

Figure 24: Burned area of all years and areas below and above the chosen MSAVI threshold

Tw ice burned area (1985-89)

15%

85%

Regeneration assessment for each fire

74%

1984 1985 1989 2000 Total

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Report of Case Study: Thasos island, NE Greece 26 which may be due to the relatively short time (< 1 year) between the fire event and the satellite image used to assess vegetation recovery. From the other areas burned, the regeneration was relatively low (61%) for the 1985 fire. The other two fires of 1989 and 1984 had successful vegetation recovery in 73% and 74% of their area respectively. The exact area statistics are shown in the Annex, Table 10, p.45.

Figure 24, p.25 shows a map of burned areas with little or no vegetation recovery (problematic areas) and areas where vegetation recovery following fire was adequate according to the applied threshold of the MSAVI index. This map can be used for targeting areas for reafforestation.

3.2.4 Comparison of vegetation recovery of different landcover types and zones

Post-fire vegetation recovery is a crucial element of post-fire site condition. Failure of vegetation recovery leaves the soil vulnerable to erosion which may lead to site degradation and conversion of vegetated land to bare and barren land. Therefore, if the post-fire ecosystem response is taken into account in the Environmental Impact Assessment, the fire impact is exacerbated in burned areas that fail to develop an adequate vegetation cover and ameliorated in areas where vegetation cover redevelops, thereby preventing soil erosion and site degradation.

The vegetation recovery analysis by the employment of the MSAVI threshold in the generalized landcover zones (Figure 26, p.27 and Figure 25, p.27) revealed that post-fire vegetation recovery is very much dependent on the initial landcover type. The exact area statistics of landcover zone percentages above the selected threshold, signifying successful vegetation recovery are shown in the Annex, Table 11, p.46.

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Comparison of vegetation recovery of different zones of vegetation cover

31.6

Percentage above and below MSAVI threshold

Successful recovery

Unsuccessful recove

Legend

MSAVI

threshold ry

Figure 25: Regeneration assessment per landcover zone by MSAVI thresholding

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Quercus sp. (Table 2, p.12 and Figure 5, p.12). This zone was second in the vegetation recovery success spectrum. This landcover zone may represent areas that had been burned in the past and were in secondary succession to forest, areas where grazing kept a low vegetation cover or lastly areas where harsh site conditions (for example wind-exposed, steep areas or shallow infertile soils) could only support a low vegetation cover of grassland or scrub. All these factors may have contributed to the relatively low vegetation recovery percentage of this zone.

Coniferous forest comes next with a 68.4% of its burned area developing an adequate vegetation cover. Depending on the time elapsed since the fire event this may reflect patchy regeneration, localised erosion / degradation or disturbance possibly from grazing. The “agricultural land” zone comes next with 74% vegetation recovery which is not surprising considering that there is no reason why utilisation of private cultivated land for agricultural production should cease after a fire. Annual crops can be planted as usual and tree orchards, vineyards or olive groves can be replanted. Perhaps it is only marginal and/or abandoned agricultural land that may be left unutilised, in which case secondary succession will allow the redevelopment of vegetation cover unless there has been soil erosion and site degradation.

Finally the “deciduous” zone (made up of areas initially covered by chestnut or riparian plane trees - Table 2, p.12) showed the best post-fire vegetation recovery with 95% of its area being above the MSAVI threshold, which may be attributed to fertile site-conditions and absence of water-stress.

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Figure 27: Vegetation recovery success (MSAVI threshold) per landcover type in ascending order

Vegetation recovery by landcover type

BARE LAND

GRASSLAND

SHRUBLAND

PINUS NIGRA

Figure 28: Regeneration assessment per zone of vegetation cover

Agricultural zone (Arable land / Abandoned farmland)

26%

74%

Deciduous zone (Castanea / Platanus)

5%

95%

Bare land and settlement zone

68% 32%

Coniferous zone

32%

68%

Other vegetation zone (Grassland / Shrubland /

Quercus)

41% 59%

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3.3 Mapping the quarries and their expansion since 1984

This section describes the detection of changes in the extent of marble quarries, especially changes from vegetated cover to quarries. Quarry monitoring allowed the assessment of the impacts that the quarries have had on the landscape and the environment of Thasos, where marble extraction has been going on for more than 30 years.

Two techniques were selected and implemented: image differencing and post-classification comparison.

In the following subsections first there is a description of the RS (remote sensing) methodology and procedures used for identifying quarries and their expansion (4.3.1 to 4.3.5) and then the results are presented and discussed in 4.3.6. Two techniques were used: Image differencing (4.3.2) and post-classification comparison (4.3.3). The results obtained by the two techniques are compared in 4.3.4.

3.3.1 Image pre-processing

Before implementing change detection analysis using multi-temporal images, precise registration and radiometric and atmospheric calibration or normalization are required (Lu et al. 2004). The two images for the change detection were acquired in close anniversary dates and both in the summer, which is a phenologically stable period. Although the images were acquired by different sensors, this problem was eliminated by using the six bands in common and especially the red and the near infrared ones that are the most important for the purpose of this study.

The geometric rectification for both images (of 1984 and 2000) has been done using a first order polynomial and nearest neighbour resampling. Average Root Mean Square (RMS) error, as a measure of misregistration, was less than 0.2 pixels for the co-registered images which is satisfactory (Dai & Khorran 1997).

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3.3.2 Image differencing

Figure 29: Image differencing of band 4. The derivative image with the absolute values.

Figure 30: Highlight image of the image differencing of band 4. The areas in green are increased values and the areas in red are decreased values.

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Figure 31: Marble quarry expansion in the northeast part of Thasos.

3.3.3 Post-classification comparison

The following three main categories were extracted: - Water

- Land

- Marble quarries

The final classification results are shown in Figure 32.

Figure 32: Classification of the 1984 image. Right: Classification of the 2000 image. Water (blue), land (red) and marble quarries (yellow)

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3.3.4 Accuracy assessment

The accuracy of the post-classification comparison was assessed for the classified quarries of the 2000 image. For that purpose point data were used that were taken both on the field in the quarries with a GPS and from image interpretation (Figure 33). Accuracy assessment module from Erdas Imagine 8.7 was used and an error matrix was produced (Table 5).

Figure 33: Points taken with the GPS and extracted area of the quarries for the year 2000.

Table 5: Error matrix for the classified image of 2000.

Class name Reference Classified Number Producers Users Totals Totals Correct Accuracy Accuracy Quarries 21 18 18

Other 0 3 0 85.71% 100.00% Totals 21 21 18

Overall Classification Accuracy = 85.71%

There is a difference between the producer’s and the user’s accuracy. The bright areas mentioned above and the fact that the GPS data have a time difference with the image are responsible for the observed difference on the accuracy.

3.3.5 Comparison of the two methods

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Report of Case Study: Thasos island, NE Greece 34 Post-classification comparison

Island's surface (m2)

Image differencing

(m2) Absolute _values

(m2)

Percentage of the island's surface (%)

4/8/1984 382.320.238 - 306.900 0,080273

24/8/2000 382.320.238 - 1.801.800 0,47128

Expansion 1.576.800 1.494.900

0.391 (487% increase over the 1984

area)

149,49 157,68

0,00 20,00 40,00 60,00 80,00 100,00 120,00 140,00 160,00

a re a (ha )

post classification comparison image differencing

Figure 34: Comparison of the areas of quarry expansion mapped with each technique

3.3.6 Quarry expansion

It is obvious that the area of the quarries is bigger in the image of 2000, even from a quick look of the classifications.

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30.7

180.2

0 20 40 60 80 100 120 140 160 180 200

Quarries 1984 Quarries 2000

Quarry total area (ha)

Figure 37: Area of the quarries in the classified images of 1984 and 2000

Figure 38: Area of quarries over total coniferous area Figure 35: Area of quarries to

the total area of the island

Figure 36: Area of quarries over total vegetated area

Area of quarries in 2000

180 ha 0.47%

38232 ha 100%

Quarries 2000 Total island area

37433 ha 100%

180 ha 0.48%

Quarries 2000 Total Vegetated area

23951ha 100%

180 ha 0.75%

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3.4 Landscape change, ecological and visual impact in relation

to the marble quarries

In order to assess the ecological impact of the quarries, it was necessary to identify the land cover on the area where quarry expansion took place after 1984. The results are presented in 4.4.1. Moreover it was necessary to quantify and assess how the landscape changed in relation to the marble quarries between 1984 and 2000. This was performed by deriving landscape metrics of quarry patches. The results of the landscape analysis are presented in 4.4.2.

3.4.1 Ecological assessment

Marble quarry polygons for 1984 and 2000, identified by post-classification comparison, were overlaid and subtracted from each other to derive the area of quarry expansion. Then, the land cover was clipped by the polygons of quarry expansion. The results (Figure 39) revealed that quarry expansion took place mainly in areas previously covered by forest and more specifically semi-natural coniferous forest of Pinus brutia and Pinus nigra that represent the climax forest types on the island. It is worth noting that the area where quarry expansion took place had not been affected by forest fires (Figure 39).

90,59%

8,09%

1,28%

0,04%

AGRICULTURE / ABANDONED FARMLAND SETTLEMENT / BARE LAND

OTHER VEGETATION CONIFERS

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3.4.2 Quantification of landscape metrics of quarry patches in 1984 and 2000

A discussion of the change in landscape metrics of quarry patches between 1984 and 2000, summarised in Table 7 is necessary to describe the characteristics of the landscape change as a result of quarrying activity.

Table 7: Landscape metrics of marble quarries in the island of Thasos in years 1984 and 2000

Attribute of quarries 1984 2000 Difference

% difference

on 1984 levels

Number of patches 28 36 +8 +29 %

Total (class) area (ha) 30.69 180.18 +149.49 +487 % Percent of landscape (%) 0.08 0.47 +0.39 +487.5 % Quarries

Mean elevation (m) 269 267 -2 -0.7 %

Mean patch size (ha) 1.1 5.0 +3.9 +354 %

Median patch size (ha) 0.45 1.08 +0.63 +140 %

Patch size coefficient of variation (%PSSD/MPS)

115.17 169.14 +53.97 +47 %

Largest patch index (% total area of quarries)

15.25 16.78 +1.53 +10 %

Patch

Patch Density (#/100 ha) 0.073 0.094 +0.021 +29 %

Total edge (m) 13260 44340 +31080 +234 %

Mean patch edge (m) 427.74 1055.71 +627.97 +147 % Edge

Edge density (m/ha island) 0.35 1.16 +0.81 +231 % Area weighted Mean Shape

Index

1.39 2.12 +0.73 +53 %

Shape

Area weighted Mean Patch Fractal Dimension

1.06 1.12 +0.06 +6 %

Mean Nearest Neighbour distance: patch centroids (m)

233 296 +64 Clustered

(p<0.01) +28 % Mean Nearest Neighbour

Distance: patch edges (m)

158 116 - 42 -27 %

Nearest Neighbour coefficient of variation (%NNSD/MNN)

105.8 127.6 +21.8 +21 %

Proximity - Aggregation

Mean Proximity Index (area/distance2 of quarry patches)

3.44 41.89 +38.45 +1118 %

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Report of Case Study: Thasos island, NE Greece 38 according to the results of the LANDSAT images interpretation. Therefore the mean quarry size increased from 1.1 ha to 5 ha, although the distribution of the sizes of the quarries is skewed to smaller sizes with a median size that increased from about half a hectare to one hectare and the variability of sizes also increased but this increase was not due to the enlargement of just the largest quarry site since the largest quarry patch only slightly increased to take up 16.78% of the total area of quarries. The observed trend of increasing quarry (patch) sizes in Thasos has been documented also for limestone quarries in Britain by (Cullen et al. 1998; Gunn & Bailey 1993) who note that natural revegetation becomes more precarious as quarries increase in size and they therefore cannot be left to evolve ecologically as hundreds of years would be required while artificial restoration may speed up this process to a decade or less.

The spatial distribution of the marble quarries in Thasos is neither uniform nor random. Spatial pattern analysis (Average Nearest Neighbour Distance) in ArcGIS 9.0 (available only for polygon centroids) revealed that they are clustered in the north-east part of the island at a mean elevation of about 270 m (S.D. 131m in 1984 and 153m in 2000). The creation of the new quarries increased the mean nearest neighbour distance of their centroids from 232m to 296m in 2000. The expected mean distance for randomly or uniformly dispersed patches in 1984 was 1756m and 1509m in 2000 and the ratios of observed to expected distances was 0.13 in 1984 and 0.20 in 2000. These ratios reveal clustering i.e. that the nearest neighbour distance between quarries is highly significantly smaller than a random or uniform distribution. This may reflect that the marble substrate is most pure, abundant and/or accessible in this part of the island but also the proximity to the main port of the island.

At the same time the enlargement of existing quarries reduced the mean nearest neighbour distance measured from their edges from 158m to 116m. This does not contradict the mean nearest neighbour distance calculated from patch centroids because centroid distance is less realistic as a measure of proximity than proximity calculated from patch edges. It indicates that new quarries and enlarged existing quarries tend to coalesce, making their presence more noticeable in NE Thasos.

An even more effective measure of patch proximity and area which combines the influence of all neighbour distances with the area of the patches is the mean proximity index which is defined as the area of a given habitat patch divided by the square of the distance from each patch of the same type. This index increased to 41.89 from 3.44 in 1984, a 1118% increase which reflects that the landscape in 2000 has larger quarries and closer to each other which corroborates the conclusion above.

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Report of Case Study: Thasos island, NE Greece 39 weight to a hectare of quarry as to a hectare of other land cover (be it forest, arable land or seaside beach) are misleading because noone expects that a large proportion of the island can ever turn into a gigantic quarry. In landscape character assessments the character of the landscape changes long before the area extent of obtrusive features becomes comparable to the total area of the landscape especially in areas of scenic beauty. The impact cannot also be properly assessed by just the quantification of the area of forest lost, although this provides an indication of the ecological damage and associated problems. Thasos is a touristic island and the visual impact of the quarries degrades the aesthetic impression of visitors of the island especially because quarries are clustered in the Northeast part of the island where the capital town and main port of the island is. Therefore the analysis of the impact of quarries on the landscape has to take into account the visual impact and how much this increased between 1984 and 2000.

3.4.3 Visual impact assessment and change

The cumulative quarry viewshed in 1984 (Figure 40) and 2000 ( Figure 41) affect the north east part of the island. The viewsheds are contingent on the landform of the island (Figure 3, p.11) and they are bounded by mountain ridges that block visual contact to quarries to areas where the line of sight is not interrupted by the intervening landform.

An initial assessment of the visual impact of quarry expansion in Thasos is the difference in the total area of the viewshed of the quarries that is the area of the island affected by having visual contact with at least one portion of marble quarry (segment of 30m that is the pixel size of quarry boundaries). This is shown in Table 8 and Figure 42 where it is evident that the 31 ha of quarries distributed in 28 patches in 1984 had a visual impact over an area of 4700 ha or 12.29% of the island. In 2000 the area of quarries increased to 180 ha distributed in 36 patches affecting an area of 5180 ha or 13.54% of the island. These percentages of the visually affected landscape of Thasos provide a more realistic quantification than the absolute area of the quarries. The increase of the total area affected is not dramatic reflecting that the new quarries were created in the vicinity of existing quarries.

Table 8: Expansion of viewshed of marble quarries between years 1984 and 2000 in Thasos island.

1984 2000

Viewshed area of

marble quarries (ha) 4699.53 5179.86

Viewshed area as %

of island surface 12.29% 13.54%

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Figure 40: Quarry locations, viewshed extent and spatial variation in intensity of visual impact in 1984 Figure 41: Quarry locations, viewshed extent and spatial variation in intensity of visual impact in 2000

Figure 42 (left): Quarry Viewshed expansion Figure 43 (right): Level of visual impact change between 1984 and 2000

Figure 44 (below): Quantification of level of visual impact change with moving average trendline.

The product of viewshed area difference by no of visible quarry edge pixels

Number of visible quarry perimetre pixels

V

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Report of Case Study: Thasos island, NE Greece 41 The intensity of visual intrusion of marble quarries increased dramatically considering the amount of quarry edge visible in the viewshed of 1984 and 2000 as shown in Figure 44 of the previous page, which is a map of the difference in the number of quarry edge pixels visible.

The maximum value of quarry (perimeter) pixels visible in 1984 was 201 pixels which corresponds to 6030 m of quarry edge (45.5% of the total edge of quarries) while in 2000 the maximum value was 542 pixels which corresponds to 16260 m of quarry edge (36.7% of the total edge of quarries in 2000).

Obviously an increase in viewshed area of pixels with low visibility of quarry edges does not add as much visibility load as the same increase of the viewshed pixels with high visibility of quarry edges.

To quantify visibility load each viewshed pixel (0.09 ha) was multiplied by its visibility score (number of quarry edge pixels visible) to assess the cumulative increase of the visual impact.

The change in the cumulative amount of visual impact between 1984 and 2000 is shown as a graph in Figure 44, p.40 which summarizes the map of Figure 44 in quantitative terms.

The change of visibility load between 1984 and 2000 indicated that the visual impact increased by a factor of 2.52, i.e.

∑

(

)

∑

(

)

.

= ∗ = ∗ = ∗

542

1

201

1 1984

2000 2.52

i j

j j i

i A N A

N

The spatial distribution of areas of the viewshed with high visibility load increase (Figure 44), includes the location of the capital town of the island, main touristic destination and port of the island which can be considered the ‘front yard’ of Thasos island.

This indicates that quarry expansion planning did not take into account the visual effects on the potential of the island to maintain a forested landscape view, uphill from the island capital.

4. Conclusions

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Report of Case Study: Thasos island, NE Greece 42 1. Nearly half the island of Thasos was burned within a period of 16 years

(1984-2000). The mostly affected landcover type was high coniferous forest (77%). Specifically 62% of the burned area was P. brutia forest (60% of its original area), 12% was shrubland (45% of its original area), 11% was arable land, 9% was P. nigra forest (46% of its original area), 4% was mixed P. brutia and P. nigra forest (74% of its original area), while the remainder 2% of the burned area belonged to the rest landcover types.

2. Αn adequate vegetation cover re-established on 2/3 of the burned area. Vegetation recovery success differed greatly between different landcover types with bare land having the worst vegetation recovery (29%) and broadleaved deciduous forest having the best recovery (95%). Grassland and shrubland had relatively low recovery (55%) while for coniferous forest, revegetation was adequate at 68.4% of its area. Vegetation recovery was slightly higher in areas originally covered by

Pinus brutia (66%) than Pinus nigra (69%) forest and worst for their ecotones (59%). Regarding the comparison of the 7 Vegetation Indices evaluated for their efficiency to indicate percentage vegetation cover, MSAVI proved to be the best and NDVI was second-best.

3. Between 1984 and 2000 new quarries were created and existing quarries were enlarged from an average size of 1.1 ha to 5 ha. The total area of the quarries increased c. 500% to occupy 0.5% of the island. Marble quarries are clustered in the north-east part of the island at a mean nearest neighbour distance of 116m. The quarries were created mainly (>90%) in areas covered by coniferous forest that had not been affected by forest fires during the study period. Regarding the comparison between the two methods for quarry expansion monitoring, post-classification comparison gave practically the same results as image differencing. 4. In terms of visual and landscape impact, marble quarries tend to assume a

dominant role in the landscape character of the northern part of Thasos. Viewshed analysis revealed that the visibility load between 1984 and 2000 increased 252% affecting 14% of the island, including areas such as the island’s capital and nearby coasts.

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ANNEX

Table 9: Landcover classes burned by all fires as percentages of total area burned and original area of classes

Landcover Area burned

in ha

PINUS BRUTIA 11406.35 61.90% 19207.78 59.38%

SHRUBLAND 2265.24 12.29% 5038.62 44.96%

ARABLE LAND 2044.73 11.10% 7825.60 26.13%

PINUS NIGRA 1690.23 9.17% 3691.50 45.79%

PINUS BRUTIA - PINUS NIGRA 726.61 3.94% 981.52 74.03%

GRASSLAND 111.43 0.60% 456.99 24.38%

BARE LAND 104.61 0.57% 440.89 23.73%

ABANDONED FARMLAND 43.61 0.24% 54.77 79.62%

CASTANEA 12.88 0.07% 41.44 31.08%

QUERCUS 10.93 0.06% 14.35 76.17%

SETTLEMENT 6.09 0.03% 358.23 1.70%

PLATANUS 4.44 0.02% 49.93 8.90%

PINUS BRUTIA - PLATANUS 0 0.00% 46.64 0.00%

PINUS NIGRA - ABIES 0 0.00% 23.78 0.00%

18427.151 38232.02

Table 10: Application of MSAVI thresholding to each burned area.

MSAVI

VALUE AREA (ha) AREA %

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Table 11: Percentages of areas below and above the selected MSAVI threshold

Zone of vegetation type MSAVI

VALUE AREA (ha) AREA % <=0.51 4453.61 31.6

>0.51 9658.35 68.4 CONIFERS >0.51 1581.46 59.4 OTHER

VEGETATION

SUM 2661.40 100

<=0.51 536.57 25.6 >0.51 1559.79 74.4 AGRICULTURAL >0.51 12852.44 67.6 TOTAL AREA

SUM 18999.08 100

Table 12: Selected vegetation indices

INDEX FORMULA

1 II (Infrared Index) II = (TM4-TM5)/(TM4+TM5)

2 NDVI (Normalized Difference

Vegetation Index)

NDVI=(pNIR-pRED)/(pNIR+pRED)

3 MSR (Modified Simple Ratio)

MSR=((pNIR/pRED)-1))/((pNIR/pRED)1/2+1)

4 MSAVI (Modified Soil Adjusted Vegetation Index)

MSAVI=((2NIR+1-(√(2NIR+1)2-8(NIR-R))) / 2

5 GVI (Greenness Vegetation Index)

GVI= -0.2728(TM1)-0.2174(TM2)-0.5508(TM3)+ 0.7221(TM4)+0.0733(TM5)-0.1648(TM7).

6 SR (Simple Ratio) SR=pNIR/pRED

7 MNLI (Modified non-Linear

Vegetation Index

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Case study references

Full title Full sources Organization Full title

(translated)

Full source (translated)

An examination of a fire-altered Pinus nigra ecosystem on the

Mediterranean island of Thasos

Gitas I.Z., Radoglou K., and Devreux B.J (2001), International conference on Forest research: a challenge for an integrated european approach, systems (GIS) in measuring post-fire natural regeneration of pinus brutia in Thasos

Joint research

programmes between Britain and Greece 1998-2000, Final Cambridge, CB2 3 EN, UK1999. remote sensing in mapping and monitoring fire-altered forest landscapes.

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Report of Case Study: Thasos island, NE Greece 48 of the forests of Pinus

Development of a computer

programme that will simulate the natural evolution of forest ecosystem British council - M. Norman, M.Karteris, L. Illiadis, A.Makras, G. Mallinis and J.Bown

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Report of Case Study: Thasos island, NE Greece 49 A semi-automated

object-oriented model for burned area mapping in the Mediterranean region using Landsat-TM imagery.

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Accelerate Erosion after the forest fires in Greece

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interpraevent 1992 - Bern