Gis applications zm_2

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Modelling sea level change in the Baltic Sea Region

as decision support for regional planning with help of GIS

Reinhard Zölitz-Möller & Bernd RöberInstitute of Geography and Geology, Greifswald University

2

Baltic Sea

3

N

EW

S

Finnland

Schweden

Estland

Polen

Deutschland

SEAREG Partners:

Finland

Sweden

Estonia

Poland

Germany

5

4 global climate change scenarios: HCA2, HCB2, MPIA2, MPIB2

IPCC: CO2 – szenarios (A2, B2)

SMHI: 4 regional climate change scenarios: S1, S2, S3, S4

Local sea level change scenarios for Usedom: (+1), +41, (+82) cm additionally: +24 cm (STIGGE)

6

German contribution to the project:

- Evolution of the outer sea coastReconstruction of coastal evolution during the past 200 years;Calculation of accumulation and abrasion rates by means of coastalevolution models (Rudolphi & Lampe)

- GIS application for the DSFDecision support tool suitable for planners (Röber & Zölitz-Möller)

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Planning region Vorpommern

Island of Usedom

German area of investigation

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Methods for reconstruction of the historical shoreline evolution: maps and aerial photographs:

– scanning– geo-referencing– digitizing of shore lines

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Aerial photos 1937

Historical maps 1885Historical maps 1829

1998193718851829

Aerial photos 1998

Data sources (1 :25.000)

10

180 m

1998193718851829Baltic Sea

Usedom

11

-2,0

-1,5

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

1 2 3

abra

sion

/ ac

cum

ulat

ion

[m/y

]

1829 - 1885 1885 - 1937 1937 - 1998

NW-Usedom Central Usedom SE-Usedom

Result: Changes for 3 sections of the Usedom outer coast

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Morphodynamic sections of Usedom outer coast

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Calculation of accumulation and abrasion rates by means of coastal evolution models

Aims:

- to find a practical method to predict a 100 year evolution of the sea coast

- to be applied flexibly to the data available

14

Total shoreline shift with sea level change [m/100yr] (model of Stephan & Schönfeldt)

coastal evolution up to 2100

-250

-200

-150

-100

-50

0

50

100

150

200

250

4 7 10 13 16 19 22 25 28 31 34 37 40

coastal kilometre

Abr

asio

n / a

ccum

ulat

ion

[m/1

00yr

]

DWD-2100 (HCB2)+1cm DWD-2100 (HCB2)+41cmDWD-2100 (HCB2)+82cm

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Results: areas of risk

Section of accumulationSection of abrasionSection of abrasion, human settlements are located

16 Streckelsberg with wave breakers

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Ückeritz

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How to support regional planners

in order to increase their coping capacity with respect to the expected sea level rise

in their planning region

?

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Elevation model Usedom island

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Sea level rise = 10 cm

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Example theme:biotope types andland use classes

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…overlaid withsea level rise by 10 cm

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26


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How to support regional planners more precisely and convenient?

GIS tool for planners

(as part of the Decision Support Frame of the project)

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Aims:

• To point out several land use planning strategies for the affected areas

• To give not only general, but detailed spatial information about the areas affected by sea level rise

• To offer the possibility of a dynamic adjustment of different sea level change scenarios with help of a digital elevation model, linked to recent economic, social and natural parameters of a target region

• To enable a neutral display of the results for the affected areas

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• open GIS format (shp)• open for different sea level rise scenarios• open for different map themes• open for different areas of interest• open for different geometric resolutions

An open and easy to use GIS Tool

is needed for plannersThis statement is the result of deliberations

with planners in our region

What does “open” mean ?

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1. The user´s choice 2. The pre-processing3. The users decision no. 14. The classification5. The users decision no. 26. The normalising7. The result processing

The general work flow of the GIS tool:

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The user´s choice:

• choose the map theme(s) to be analysed• choose the area of interest (AOI)• choose the predicted sea level scenario• choose the wanted grid resolution

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Example theme 1:biotope types and land use classes

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Example theme 2:ground water protection areas

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Example theme 3:linear infrastructure

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Select the AOI(municipalities)

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Select the predictedsea level (+70 cm)

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1. The choice of the user2. The pre-processing3. The users decision no. 14. The classification5. The users decision no. 26. The normalising7. The result processing

… general application flow

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The steps of pre-processing:

• Step 1: clip a theme with AOI• Step 2: clip result of step 1 with predicted

sea-level• Step 3: generate a raster grid with

selected resolution, which covers the area of step 2

• Step 4 to n: repeat step 1 and 2 for n themes

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clip theme 1with AOI (selected communities)

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clip result of step 1with predicted sea level

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generate raster gridwith selected resolution(250m)for further analysis

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.. general application flow

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The users decision no. 1

For each theme• choose the method of classification• choose the object field for classification• load or define the table of assessment

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Methods of classification

• an absolute classification:each object type gets a value(€/m² or €/ha or €/m)

• a relative classification:each object type gets a relative factor

• a verbal classification:e.g. a choice between “very low”, “low”, “intermediate”, “high”, “very high”

for each objectand a choice between dominate or highestvalue per grid square

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Table of assessment

Object type Value* (€/m²)

Grassland 1.5

Forest 4

Arable fields

2

Object type Factor

Grassland 0.75

Forest 2

Arable fields

1

Object type Value

Grassland very low

Forest low-medium

Arable fields

low

absolute value

relative value

verbal classification

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result raster grid for map theme 1:biotope types and land use classes

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result raster grid for map theme 2:ground water

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result raster grid for map theme 3:lines (roads, cables)

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The users decision no.2

Decisions for normalizing and weighting the single results

For each theme• determine the max of result

(or theoretical max result)• set it 100 (or 50, 25 etc – weighting)• calculate the other values

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result rastersum of all results

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area model

location

risk

data

land use

value

class

climate model elevation modelstatistic data geometric data

Incompatibility between statistical andgeometric data

scale problem

problem

Assessment ofaffected areasdepends on points of view

problem

variable scalingdepending on geographic location

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Digital Elevation Models (DEM) – data availability

DEM 1: STAUN (Staatliches Amt für Umwelt und Natur)(state agency of nature and environment)

DEM 2: Univ. Greifswald (model from former projects)

DEM 3: DGM 50 (state agency of land survey)

DEM 4 GTOPO (USGS – United States Geological Survey)

Point data provided by the „Zweckverband – Peenetal“

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DEM 1: Island of UsedomSTAUN

Elevation model for outer coast of Usedom (4 km coastal zone)horizontal resolution: 25 melevation resolution: unknownProblems:- differences to topographic map 1:10 000- proprietary coordinate system based

on Krassovski (?) ellipsoid- not compatible to national projection standardsusability:-point data valid as raw data for the creation of a new elevation model

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57 Point data ; fit of the model

DEM 1: Island of UsedomSTAUN

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DEM 2: Greifswald LagoonUNIV of Greifswald

horizontal resolution: 50 m proprietary coordinate system

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DEM 3: DGM50state agency of land survey

horizontal resolution: 50 melevation resolution: 5 m

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DEM 4: GTOPO 30USGS

horizontal resolution: 1 kmelevation resolution: ± 30 m

now back ?

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Point data provided by „Zweckverband – Peenetal“

- very high horizontal and elevation resolution- with differences to topographic map 1: 10 000-point data valid as raw data for the creation of a new elevation model 70 km

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Conclusions referring to availabledigital elevation models

set up of a new elevation model was needed

Requirements:consistency of data and modelconsistent map projection horizontal resolution = 10 melevation resolution = 25 cmTasks:Digitizing of elevation information from topographic maps (1:10 000)Modelling

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Required Data

for estimation of the value

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- Land userecentplanned

- Infrastructurerecentplanned

- Tourism- Nature protection

- Drinking water- Population density - Municipal capital- Cost of coastal protection- Cost of drainage- National treasurs- Cultural heritage- Soils and geology

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Available digital geometric data

-BNTK (Biotop- und Nutzungstypen Kartierung)(digital biotope and land use types map)

-ATKIS (Amtliches Topographisches Karten Informations System)(authoritative topographic cartographic information system)

- Digital data from the land use planning authority

- Digital data from the land register

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biotope and land use typesBiopoly.shp

W11 QuellbereichW12 Bach < 3 mW13 Graben < 3 mW14 Fluß > 3 mW15 Kanal > 3 mW21 temporäres Kleingewässer, Tümpel oder LacheW22 permanentes KleingewässerW31 Flachsee < 5 mW32 SeeW41 N iedermoorW42 Hoch- und ÜbergangsmoorW43 SumpfW51 OffenwasserW52 mariner Block- und SteingrundW53 SandbankW54 W indwattW61 OffenwasserW62 mariner Block- und SteingrundW63 SandbankW71 SandhakenW72 StrandW73 StrandseeW74 StrandwallW75 W eißdüneW76 KliffW77 Kliff randdüne

L11 FeuchtgrünlandL12 fr isches GrünlandL13 wechselfeuchtes GrünlandL14 TrockengrünlandL15 SalzgraslandL21 AckerL22 ErwerbsgartenbauL23 BaumschuleL24 Obstbau

T11 ZwergstrauchheideT12 GinsterheideT13 KrähenbeerheideT21 SilikattrockenrasenT22 KalktrockenrasenT31 anstehendes FestgesteinT32 Lesesteinhaufen und -mauerT33 Einzelfindling

B11 LaubwaldB12 Laubwald gemischt (< 10% N adelbäume)B13 Laubmischwald (Verhältnis Laub- zu Nadelbäumen 90/10-70/30)B14 Mischwald (Verhältnis Laub- zu Nadelbäumen 50/50)B15 Nadelmischwald (Verhältnis Nadel- zu Laubbäumen 90/10-70/30)B16 NadelwaldB17 WaldrandB18 KahlschlagB19 Lichtung/SchneiseB21 Feldgehölz (0.5 - 5 ha)B22 Baumgruppe (< 0.5 ha)B23 BaumreiheB24 AlleeB25 dominanter EinzelbaumB26 HeckeB27 Gebüsch, Strauchgruppe

S11 geschlossene BebauungS12 EinzelbebauungS13 Neubaugebiet, undif ferenziertS21 städtisches MischgebietS22 dörfliches MischgebietS23 EinzelgehöftS31 Gewerbe- und Industr iegebietS32 TierproduktionsanlagenS33 MilitärobjektS41 ParkS42 Wildgehege, ZooS43 FreizeitparkS44 SportanlageS45 GolfplatzS46 CampingplatzS47 Kleingartenanlage, Fer ienhäuserS48 DorfangerS49 Fr iedhofS51 PfadS52 Wirtschaftsweg, unbef estigtS53 Wirtschaftsweg, befestigtS54 StraßeS55 Autobahn S56 Bahnanlage / GleisanlageS57 FlugbetriebsgeländeS58 HafenanlageS61 Deich, DammS62 BuhneS63 SteinwallS64 PumpwerkS71 FernwärmeleitungS72 Klärbecken / -anlageS73 Güllebecken

R11 Steinbruch / KreidebruchR12 Sand / KiesgrubeR13 TongrubeR14 Geländeabgrabung undifferenziertR21 D eponieR22 ungeordnete DeponieR23 SpülfeldR24 landwirtschaftliche Lagerfläche (Dungläge, Miete, Silo)

L11 FeuchtgrünlandL12 frisches GrünlandL13 wechselfeuchtes GrünlandL14 TrockengrünlandL15 SalzgraslandL21 AckerL22 ErwerbsgartenbauL23 BaumschuleL24 Obstbau

Available geometric data

2.2 km

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Land use from ATKIS dataDlm_gr_pol.shp

SIEDLUNG (2000)

Baulich geprägte Flächen (2100)2101 Ortslage2111 Wohnbaufläche2112 Industrie- und Gewerbeflaeche2113 Flaeche gemischter Nutzung2114 Flaeche besonderer funktionaler Praegung

Versorgung2121 Bergbaubetrieb2126 Kraftwerk2127 Umspannwerk2128 Förderanlage2131 Ausstellungs-, Messegelände2132 Gärtnerei2133 Heizwerk2134 Wasserwerk

Entsorgung2122 Abfalldeponie2129 Klaeranlage Klaerwerk2135 Abfallbeseitigungsanlage

Siedlungsfreiflächen (2200)2201 Sportanlage2202 Freizeitanlage2211 Freilichttheater2212 Freilichtmuseum2213 Friedhof2221 Stadion2222 Sportplatz2223 Schiesstand2224 Schwimmbad, Freibad2225 Zoo2226 Freizeitpark, Safaripark2227 Grünanlage2228 Campingplatz2230 Golfplatz

Bauwerke/Einrictungen (2300)2301 Tagebau Grube Steinbruch2302 Halde, Aufschüttung2314 Absetzbecken Rieselfeld Schlammteich2345 Schwimmbecken

VERKEHR (3000)

Strassenverkehr (3100)3103 Platz (Rastplatz Parkplatz)

Flugverkehr (3300)3301 Flughafen3302 Flugplatz Landeplatz3303 Rollbahn3304 Vorfeld

Schiffsverkehr (3400)3401 Hafen3402 Hafenbecken

Anlagen und Bauwerke für Verkehr, Transport und Kommunikation (3500)3501 Bahnhofsanlage3502 Raststätte3511 Grenzübergang, Zollanlage3513 Tunnel3514 Brücke, Unterführung, Überführung

VEGETATION (4000)

Vegetationsflächen (4100)4101 Ackerland4102 Gruenland4103 Gartenland4104 Heide4105 Moor4106 Sumpf4107 Wald Forst4108 Gehoelz4109 Sonderkultur4110 Brachland4111 Nasser Boden4120 Vegetationslose Fläche4199 Flaeche z.Zt. unbestimmbar

GEWÄSSER (5000)

Wasserflächen (5100)5101 Strom Fluss Bach5102 Kanal (Schiffahrt)5103 Graben Kanal (Wasserwirtschaft)5111 Meer5112 Binnensee Stausee Teich

Besondere Objekte in Gewässern (5200)5201 Sandbank

Einr ichtungen und Bauwerke an Gewässern (5300)5301 Durchlaß5303 Schleuse5304 Schleusenkammer

GEBIETE (7000)

Geographische Gebietseinheiten (7200)7211 Insel

Schutzgebiete (7300)7301 Nationalpark7302 NSG7304 LSG7305 Naturpark

Gefahrengebiete, sonstige Sperrgebiete (7400)7403 Truppen-, Standortübungsplatz

Siedlungsfreiflächen (2200)2201 Sportanlage2202 Freizeitanlage2211 Freilichttheater2212 Freilichtmuseum2213 Friedhof2221 Stadion2222 Sportplatz2223 Schiesstand2224 Schwimmbad, Freibad2225 Zoo2226 Freizeitpark, Safaripark2227 Grünanlage2228 Campingplatz2230 Golfplatz


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Digital data from the land use planning authority


e.g.:- Harbours- Airports- Other technical

infrastructure- National treasures

Minor priority areas for:- Nature protection- Mineral resourcesHigh priority areas for:- Nature protection- Mineral resources

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Digital data from the planning register (ROK)


-Protection zones for drinking water- Power plants- Waterworks- Sewage plants- Waste treatment sites- Roads- Residential areas- Industrial areas- Hybrid areas- Nature protection areas- Pipelines and cable (power, oil, water)

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from the state office for statistics

- Population- No. of employed people- Education- Social contributions- Housing- Land use- Agriculture- Industry- Trade & Tourism- Taxes

Regions:- State- District- Municipality

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Available statistic data

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Macro-Scale: for baltic sea region or larger parts of it:

not sufficient for planners

Meso-Scale:for districts and parishes

statistic data available useful for regional planners

Micro-Scale: Landregister areas

no data (data protection) too expensive to raise data too much time to calculate useful for local planners (municipalities)

How useful are different scalesfor a regional DSS?

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Decision in Greifswald for meso-scale approach

Problem: incompatibility of geometric and statistic data

Option A) The area will be subdivided into small squares and each square gets the information about its dominant land use According to this land use information the value is assigned to the grid square

Option B) The same land use areas from one parish will be summarised and will get the same value .Each patch gets the proportional value corresponding to the size of it´s area

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Var. A)

- It might be that the land use information has to be weighted by it´s importance. After this, the grid square get it´s “dominant” land use information (“the winner takes it all”)- According to the land use information the square gets its value

A*0,5

A*2?

50m

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Var. B)- Each land use type from one parish gets a value- The multipart polygon will be simplified into single part polygons- proportional value corresponding to the single area

Multipartpolygon

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Value classification

The assigned value may depend on the observer´s viewpoint

high

low

medium

F1 residential area

F2 pasture land

F3 forest

F4 agriculture

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F1 residential area

F3 forest

F4 agriculture

F2 pasture land

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Risk classification

high

low

medium

Elevation of the areaThe relative position

to the coast

0,0 m

1,0m

2,0m

3,0 m

4,0 m

5,0 m

General floodingareas

Areas with risk for storm tideand flood

0 km

10 km

20 km

30 km

40 km

50 km

Attention: all borderlines are dynamic,they may change

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Areas with risk for storm tideand flood

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Final classification

riskvalue

result

Current state

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Example 1 for visualization of results

Recent land use of NW Usedom islandThe appearance of this island after sea level rise 1 m?

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Conflicts betweencurrent plans and sea level rise Wohnbauflaeche

Wohnbauflaeche

Tourismus

Gewerbliche Bauflaeche

Housing area

Housing areaHousing area

Tourism

Industrial area

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Options for recommendations:- conserve, protection areas (1)- renaturation areas (2)- lesser and higher priority areas for flood (3)

(1)

(2)

(3)


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Usedom 2100 (?)

Size of flood-prone areas on Usedom

Area below sea levelArea above sea level

13%

+ 25 cm = 46 km²

16%+ 40 cm = 58 km²

28%

+ 80cm = 102 km²

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Usedom at slr of +80 cm

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Industry 0,69 %

Area of Ecological

Interest 15,66 %

Agriculture 71,13 %

Other Areas 11,90 %

Human Settlement

0,62 %

Areas of different land use, affected at slr of +80 cm

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Object price area total price

grassland 0.5 €/m²

housing area

70 €/m²

72 km²

0.63 km² 44 mio €

36 mio €

Values endangered at slr of +80 cm

84

Impact assessment:

Object area[km²]

total price[€/area]

grasslandimpact

72 km²high impact

36 mio €medium impact

housing areaimpact

0.63 km²low impact

44 mio €high impact

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Part 2

Workflow of the GIS-tool in details

86

Requirements

- GIS

PresettingBasic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

• ArcView

• Elevation layers each 5 cm

• A polygon theme for the Area of Interest (AOI)

• Input themes with consistent map projection

• .

87

Presetting

Load the themewhich holds theArea of Interest

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

88

The two selected municipalities are the AOI

for this example

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

89

Load the themeswhich should be

analysed

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

90

The example datasetsare

roads

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

91

Ground waterprotection areas

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

92

Land use types

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

93

data from theAuthoritative Topographic Cartographic Information

System (ATKIS)

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

94

And now we can run the script

Presetting

- GIS


Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

95

Basic settings

Set the neededdirectories

- GIS

Presetting

Basic settingsInitialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

96

Choose thesea level rise(in 5cm steps)

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

97

Choose thegrid resolution

(grid cell size in m)

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

98

Choose the themewhich holds the AOI

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

99

Choose a themewhich should be

analysed

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

100

Choose the fieldwhich holds

the object types

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

101

Validate the choice with“all object types” or

“only affected”

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

102

Repeat these steps untilall necessary themes

are listed in the table below

Basic settings

- GIS

Presetting


S.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

103

Initialisation

- GIS

Presetting

Basic settings

InitialisationS.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

In this step an empty grid with the selected resolution will be generated over the affected areaand …

104

Initialisation roads

groundwater

ATKIS

land use

… the themes will be cut with the AOI and the selected sea level

This is the first result of the tool: the affected objects

- GIS

Presetting

Basic settings

InitialisationS.f. assessment

Classification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

105

Settings for assessment

Choose atheme …

- GIS

Presetting

Basic settings

Initialisation

S.f. assessmentClassification

S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

106

… and a method.(absolute, relative or nominal)


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

107

(relative or absolute)for each object type …


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

108

(relative or absolute)… set a value …


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

109

(relative or absolute)… or load a prepared table.


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

110

(nominal)Choose the number of

possible classes and …


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

111

(nominal)…set for each object type …


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

112

(nominal)…a value …


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

113

(nominal)…or load a prepared table


- GIS

Presetting

Basic settings

Initialisation


S.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

114

Classification

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

ClassificationS.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

roads

groundwater

ATKIS

land use

For each grid cell the affected objects will be summarized in relation to its area or length

This is the second result of the tool: the affected evaluated grids foreach theme

115

Classification

low

high

By the nominal classification the user has to decide which value should be used for each grid cell: the dominant (in the example “low”)or the highest (in the example “high”)

medium

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

ClassificationS.f. normalisation

Normalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

116

Settings for normalisation

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f.

normalisationNormalisation

Result processing

- Modelling

-Vulnerability

-Conclusions

For each theme …

117

Settings for normalisation …set a value which should correspond with the highest

value or …- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f.


Result processing

- Modelling

-Vulnerability

-Conclusions

118

Settings for normalisation … if all values in all themes

are absolute set the check box = true- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f.


Result processing

- Modelling

-Vulnerability

-Conclusions

119

Normalisation

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

NormalisationResult processing

- Modelling

-Vulnerability

-Conclusions 0

100

200

300

400

500

600

700

bntk

atkis

norm

1

norm

2

norm

3

road

s

grou

ndwa

ter

highmiddle

low

highmiddle

low

In the example the datasets “ATKIS” and “land use” are

classified as medium important …

120

Normalisation

0

100

200

300

400

500

600

700

bntk

atkis

norm

1

norm

2

norm

3

road

s

grou

ndwa

ter

highmiddle

low

highmiddle

low

…and so they will be normalised to a range between 0 and 100 - GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation


- Modelling

-Vulnerability

-Conclusions

121

Normalisation

0

100

200

300

400

500

600

700

bntk

atkis

norm

1

norm

2

norm

3

road

s

grou

ndwa

ter

highmiddle

low

highmiddle

low

The theme “groundwater protection areas” (nominal classified) is the

most important and … - GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation


- Modelling

-Vulnerability

-Conclusions

122

Normalisation

0

100

200

300

400

500

600

700

bntk

atkis

norm

1

norm

2

norm

3

road

s

grou

ndwa

ter

highmiddle

low

highmiddle

low

… so it will be normalised to a range between 0 and 200- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation


- Modelling

-Vulnerability

-Conclusions

123

Normalisation

0

100

200

300

400

500

600

700

bntk

atkis

norm

1

norm

2

norm

3

road

s

grou

ndwa

ter

highmiddle

low

highmiddle

low

The theme “roads” is the least important and will be normalised to

a range between 0 and 50- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation


- Modelling

-Vulnerability

-Conclusions

124

Result processing

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result

processing- Modelling

-Vulnerability

-Conclusions

The generated result viewcontains the unevaluated objects

per theme …

125

Result processing …the evaluated grids per theme …

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result


-Vulnerability

-Conclusions

126

Result processing …and the aggregated result gridwhich is the third result of the tool

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result


-Vulnerability

-Conclusions

127

Result processing

All user settings are written in a text file

“analysis_parameter.txt” for reproducibility

- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result


-Vulnerability

-Conclusions

128

Result example for Pärnu (Estonia)

Pärnu- GIS

Presetting

Basic settings

Initialisation

S.f. assessment

Classification

S.f. normalisation

Normalisation

Result


-Vulnerability

-Conclusions

129

Thank you for your attention.

Gis applications zm_2

Technology

Transcript of Gis applications zm_2