G E O G R A P H I C I N F O R M A T I O N S Y S T E M S E X E R C I S ES ( V E R S I O N , 19/ S E P / )

G E O G R A P H I C I N F O R M A T I O N S Y S T E M S E X E R C I S E S

( V E R S I O N 1 6 . 1 , 1 9 / S E P / 2 0 1 6 )

A L E X A N D R E G O N Ç A L V E S

D E P A R T A M E N T O D E E N G E N H A R I A C I V I L , A R Q U I T E T U R A E G E O R R E C U R S O S

I N S T I T U T O S U P E R I O R T É C N I C O

2 0 1 6

L A B O R A T O R I E S O F G E O G R A P H I C A L I N F O R M A T I O N S Y S T E M S I 2 0 1 6 - 2 0 1 7

Agenda

Week Weekdays Ex. Theme

1 19 - 23/sep 1,2 Software presentation: introduction to ArcGIS Alphanumeric data; symbology

2 26 - 30/sep 3,4,5 Georeferencing; editing new datasets. Selection by attributes

3 3 - 7/oct 5,6,7 Table join; selection by attributes and by location 4 10 - 14/oct 8,9 exercícios de análise espacial (vetorial)

5 17 - 21/oct 10, 11 continuação da aula anterior 6 24 - 28/oct no GIS classes this week 7 31/oct - 4/nov no GIS classes this week 8 7 - 11/nov rev 1-11 Review of past exercices

9 14 - 18/nov Test 1 (60 minutes)

10 21 - 25/nov 13,14 Raster (raster analysis, DEM and hydrology) 11 28/nov - 2/dec

day TBD (MEAmb)

15, 16 Raster (interpolation and cost surfaces)

12 5 - 9/dec day TBD (MEAmb)

Review of past exercices

13 12 a 16/dez Test 2 (60 minutes)

R E C O M M E N D E D R E F E R E N C E S :

- João Matos: “Fundamentos de Informação Geográfica” – 5.th edition; Ed.

LIDEL; ISBN: 978-972-757-514-5 (in Portuguese, available on the library) - Class slides

G R A D E C A L C U L A T I O N

Theory  70% [exam, minimum grade 9,5 out of 20]

Practice  30% [tests on the 9th and last classes in the computer room, individual or in pairs]

T E A C H I N G B Y :

Alexandre Gonçalves; room: 3.19 (3rd floor); ph: 218418329 (ext.2329);

e-mail: alexandre.goncalves@tecnico.ulisboa.pt; student support: combine by e- mail

G E N E R A L R E M A R K S

The geographical information for the practical classes is on the computer lab server, in a file that will be announced in the board.

Copy the file to drive D in your computer, to a new folder, for example:

D:\gis_meamb\

or

D:\gis_muot\

or

D:\gis_legm\

and unzip its contents to that folder.

There will be a subfolder, initially empty, called exercicios (exercices). It is on this folder that you should save all the results from your exercices along the classes.

Information is organized this as following:

exercicios – folder to store results grids – datasets in raster format images –imagery to use in exercises shapefiles – datasets in vector format tables – tables in dbf format

tins – triangulated irregular networks

 It is strongly recommended to bring your own drive (a pen disk) or use a cloud storage service (ex. Dropbox, Google Drive, etc.) where to copy the results from the folder named exercicios at the end of each lab class.

 Please compress the folder with your results to a ZIP or RAR file

before copying it to your drive.

E X . 1

Open ArcCatalog and note its tools. Verify how vector data is store in the

"shape" folder. Choose one of these geographical datasets and inspect the difference between the tabs named Contents, Preview and Metadata. Use in tab Preview the buttons of the tool bar Geography.

Copy throught this software the information for the classes to your external drive.

Open it with Windows Explorer and observe the copied files.

E X . 2 –

S Y M B O L O G Y

 Open ArcMap. Create a new project, which you will call ex2.mxd.

 Use the button Add Layer to add to the map the layer named concelhos_dt73.shp and the layer of the Portuguese road network (shapefile vias_dt73.shp), both in folder

\shapefiles.

 Switch the layter order (place the line layer "over" the polygon layer). Replace the initial order.

 Open the attribute table of the concelhos_dt73 layer. Note the name of the attribute with the population in 1996.

 Create a thematic map of concelhos (counties, municipalities) by number of inhabitants in 1996. Use 9 classes choosing tour favourite colours and with the break values:

2500, 5000, 10000, 20000, 50000, 100000, 200000, 500000, 600000

 Create a thematic map of the roads by category.

 Create labels on the roads to display the road number.

 Turn the road layer visible only at scales smaller than 1:1000000 (Visible Scale Range).

Answer these questions:

2.1. Are both thematic maps of the same type?

2.2. Would it be possible to see simultaneously two thematic maps of the same polygon layer?

E X . 3 -

G E O R E F E R E N C I N G

 In a new project file (ex_3.mxd) add image 403_dir.jpg which is in D:\...\images e start the georeferencing process following the instructions and verifying the quality of the adjustment. Use these control points (plane coordinates in the Datum Lisboa system, named ArcGIS Lisboa_Hayford_Gauss_IGeoE):

Point XX YY

CALHANDRIZ 119481 217158

MATO DA CRUZ 118128 216132

BOIÇÃO 114978 216524

MOURÃO 117594 218905

The central point in the triangular symbol of geodetic marks should be used.

 Save and cloes the project. Use ArcCatalog to create a copy of the data and project in your personal external drive.

E X . 4 –

C R E A T I N G N E W D A T A S E T S

Open the project of the previous exercice/class, which will have image 403_dir already georeferenced.

 Choose the rectify command to save a new file with a copy of the image in your folder ...\exercicios; choose a spatial resolution of 2 meters, format TIFF, method nearest neighbor.

 Start ArcCatalog to create new shapefiles (define the respective coordinate system and save the data in ...\exercicios) by digitizing:

1 - A line shapefile (polyline) to represent the roads between Santiago dos Velhos and Calhandriz, and from Calhandriz to the geodetic mark named Mato da Cruz. The shapefile should have the following characteristics:

i. Its name is roads_bucelas.shp;

ii. The coordinate system is Lisboa Hayford-Gauss IGeoE (from Projected Coordinate Systems\National Grids\Europe);

iii. There should be an attribute called Name associated with the name of the road (see the red labels in the map);

iv. There should be an attribute called Lenght with the total length of the road segment (double, precision 10, scale 3).

When you finished your editing, choose Stop Editing in the Editor toolbar, and save your edition.

4.1 Calculate the total length of the roads you created (tip: use Calculate Geometry on the Length attribute).

2 - A point shapefile to represent the four geodetic marks in the map. The shapefile should have the following characteristics:

i. Its name should be marks.shp;

ii. The coordinate system is Lisboa Hayford-Gauss IGeoE (from Projected Coordinate Systems\National Grids\Europe);

iii. There should be an attribute called Name associated with the name of the road (see the red labels in the map);

iv. There should be two attributes called X and Y with the x and y coordinates of the mark (double, precision 10, scale 3).

E X . 5 –

Q U E R Y T O A A T T R I B U T E T A B L E

 Start ArcMap. Create a new project, and name it ex5.mxd. Always store your files on the "exercicios" folder in drive D:\...\\exercicios.

 Use button Add Layer to add the "concelhos" layer concelhos_dt73.shp and the road network (shapefile vias_dt73.shp), que both in folder "shape" (same as exercice 2).

 Use the same button to add the table named autarquicas.dbf which is on the

"tables" folder . It contains the winner in each concelho of the local elections in 1997 in Mainland Portugal.

 Join the table with the electoral results to the attribute table of layer concelhos

 Read thouroughly the contents of the window with the title Join Data to understand what joining two tables means.

 Create a thematic map of concelhos by the winner of the local elections in 1997.

Answer these questions:

5.1. For each political party, how many concelhos did it win in 1997?

5.2 What is the total population of the concelhos wher the "PS" party was the winner in 1997?

5.3 Which is the concelho with the lowest number of inhabitants, where "PSD"

political party was the winner in 1997? And what was the largest in the same criteria?

5.4 Point out, amongst the concelhos where "PSD" won, the largest and smallest population change between 1991 and 1996.

5.5 What is the total length of roads in Mainland Portugal for each type of road?

5.6 What is the total length of roads in Mainland Portugal?

5.7 What is the total number of arcs (linear map elements) that are of category IC, independently of being also motorways (AE)? From these, how many have less than 5 km in lenght?

5.8 Calculate the value of Y for each road segment (arc), knowing it is defined by this formula: Y = (speed * number of lanes (num_pistas) + TMD) / length 5.9 Calculate the average value of Y for the motorway (/AE) arcs.

Answers: 5.2: 4410230; 5.3: Vila de Rei / Vila Nova de Gaia; 5.7: 414 / 3

E X . 6 – E

D I T I N G A N D Q U E R Y I N G B Y A T T R I B U T E S

 Create a new project file (ex_6.mxd) and add to it the layer of municipalities (concelhos) named concelhos_dt73.shp.

 In the attribute table create a new numeric field named COMPACT and calculate, for each municipality, its compactness value, given by:

4  x area / perimeter². Answer these questions:

6.1. Which are the municipalities in Mainland Portugal with the largest and the smallest compactness index values?

6.2. Which are the "distritos" of Mainland Portugal Continental with the largest and the smallest average values of the compactenss index?

Right button on the name of the column on the attribute table  Summarize;

then, choose the field(s) to group, the statistic(s) to get and the summarized table where the result will be saved.

Answers: 6.1: Trancoso / Pampilhosa da Serra; 6.2: Viana do Castelo / Évora Don't forget to save the project in your "exercicios" folder.

E X . 7 –

S P A T I A L Q U E R Y

 Create a new project file (ex_7.mxd) and add to it a layer of geodetic marks (shapefile vertices.shp which is in folder "shapefiles").

 Also add the layers distritos.shp (a kind of regions) and vias_dt73.shp.

 Verify the coordinate systems of each layer by inspecting each layer properties:

- layer vertices.shp has no assigned coordinate system

- layer vias_dt73.shp uses Datum_73_Hayford_Gauss_IPCC system - layer distritos.shp uses Lisboa_Hayford_Gauss_IGeoE system

 Assign to the data frame “Layers” the system Datum_73_Hayford_Gauss_IPCC. This operation can be done directly on ArcMap

“copying” the system from another layer that is already using it.

 Assign to shapefile vertices.shp the Lisboa_Hayford_Gauss_IGeoE system. This operation can be done in ArcCatalog by choosing the “Properties” of the shapefile, and selecting the required system in “Projected Coordinate Systems”/”National Grids”. It can also be done in ArcToolbox (ArcToolbox  Data Management Tools

 Projections and Transformations  Define Projection).

Answer these questions:

7.1 How many geodetic marks verify simultaneously these conditions:

 They are in the distrito of Faro;

 They locate up to 1000 m from national roads (national roads have Categoria = ‘EN’).

Layers Properties … Coordinate system Menu: Selection by location

Consider: «select features from» / «select from the currently selected features in»

7.2 Identify the westernmost and northernmost geodetic marks in a area that includes the "distrito" of Évora and a area around this "distrito" with 3500m of radius. Use selection by location.

Menu: Selection by location

Answers: 7.1: 33; 7.2: Almoxarife and Cabecinhas

Don't forget to save the project in your "exercicios" folder.

E X . 8 – V E C T O R S P A T I A L A N A L Y S I S I

 Create a new project (ex_8_9.mxd), on which the data frame (called Layers) uses the coordinate system Lisboa Hayford Gauss IGeoE (from Projected Coordinate Systems\National Grids\Europe);

 Add layers bacias (watersheds), concelhos (municipalities), hidrografia (rivers) and mon_qualidade (water quality measure stations), all of which are in the folder D:\...sig\shapefiles\.

 Based on "concelhos", create a layer of districts, a higher hierarchical subdivision than "concelhos". In Portuguese these are called distritos. Look for the column name in "concelhos" which stores the "distrito" on which each concelho belongs. Save the result in your folder D:\ ...\sig\exercicios\. Choose the adequate "dissolve field". The resulting dataset must have the total population (field "POP1996") and also the area of each district.

Dissolve: ArcToolbox  Data Management Tools  Generalization  Dissolve, or menu Geoprocessing  Dissolve.

Answer the following questions by using the appropriate spatial analysis operation:

8.1 Which is the total area (in hectares) that each distrito has in the Tagus River watershed (note that in Portuguese "Tejo" is the name of the Tagus River). Create a layer with those areas only, with a column called real_area (double, 12, 3), and populate this column.

Export some elements to a new shapefile named "districts_tagus": (right click on layer with selected elements) Data  Export. Save the resulting shapefile in your D:\...\sig\exercicios folder

8.2 How many water quality measure stations are up to 2000 m from the Mondego River? Use the buffer spatial analysis function.

Buffer: ArcToolbox  Analysis Tools  Proximity  Buffer, or menu Geoprocessing  Buffer.

On parameter "dissolve type" choose ALL (compare the result you would obtain with NONE in this parameter)

8.3 Imagining that the Mondego River level will rise and that it is necessary to declare as risk areas all the territory inside a section of 300 m counting from the Mondego River centerline and from each of its important tributaries centerlines (read below). Which are the "concelhos" affected by the risk area? What is the total risk area in each of of these concelhos?

Note: The important tributaries of the Mondego River have a code (check the column "CODRIOS") that starts with '701'. However, this field is numeric (we can see that because numbers are aligned to the right, while textes are aligned to the left), so it will be necessary to create a new text column and copy the contents of CODRIOS to this new column, so then it is possible to build a query using string comparison: newcolumn Like '701%'.

8.4 Use the previous resultado to estimate, for each municipality, the population in the risk area, assuming that in each municipality the population density is constant. Use field POP1996.

Don't forget to save the *.mxd project in your "exercicios" folder.

E X . 9 – V E C T O R S P A T I A L A N A L Y S I S I I

Create in the previous project (exercises_8_9.mxd) a new data frame (Insert  Data Frame). Add layers u_solo_a.shp and u_solo_b.shp, both located in folder D:\...\sig\shapefiles\.

Layer u_solo_a has a field named VALOR_A and layer u_solo_b has a field named VALOR_B (Portuguese for "Value_A" and "Value_B")

9.1 Create a new layer with the union of the two layers, but this new layer must have an attribute named VALUE_UNION, that should:

– contain the value of either "a" or "b" layers where the two layers do not overlay;

– contain the average of VALOR_A and VALUE_B where the two layers overlay.

9.2 Do the identity (u_solo_a id u_solo_b) through an union followed by a selection by attributes.

Union: ArcToolBox  Analysis Tools  Overlay  Union

Identity: ArcToolBox  Analysis Tools  Overlay  Identity (not available in ArcEditor licenses)

E X . 1 0 - V E C T O R S P A T I A L A N A L Y S I S I I I

NOTE: This exercise covers all the themes previousy focused. It includes selection by attributes, selection by location, joining tables, spatial analysis, calculation of columns, etc.

The following layers will be used (all are in D:\...\shapefiles\Lisboa):

 Freguesias.shp – "freguesias" (urban districtics) of Lisbon (for each we know the number of inhabitants and the population density per km²);

 Esp_verde.shp – gardens in Lisbon;

 Rede_viaria.shp – streets of Lisbon;

 Metro.shp – subway stations (year 2000).

10.1 Identify the "freguesia" in Lisbon with the largest total area of gardens.

Present the results as a table with the name of the "freguesia" and its total area of gardens (in m² or hectares).

10.2 Which is the per capita value of gardens per inhabitant, for each "freguesia"

in Lisbon (in m²/inhab)?

10.3 Find the largest garden in Lisbon (it could be only a part of a garden) that verifies these conditions:

 Condition A: Having a part (even a tiny part) up to a distance of 175 m from any road segment of type “estrada” (Port. for "road"). Note that it is required to distinguish between “estradas” and the remaining streets in the city);

 Condition B: Locate entirely less than 500 m from a subway station.

 Condition C: Locate entirely or partially in a "freguesia" that has a population density greater than the average value of population density in the city;

Suggestions: for the conditions that use “partial location”, try to use one of the selection by location options;

On the buffer for condition B, on "dissolve type" choose "ALL".

10.4 Assuming that the population distributes homogeneously in each freguesia (i.e., take a constant population density for each freguesia), how many inhabitants live up to 200 m from subway stations? What would be the result if gardens were excluded from inhabited places?

E X . 1 1 - V E C T O R S P A T I A L A N A L Y S I S I V

Suppose that the Agriculture Ministry wants to locate areas that have suitability for a fruit in the concelho of Trofa, in the north of Portugal. The list of criteria is as follows:

 CR1 = Being in a zone where the soil’s pH >= 5.3 and the use is

“Agricultura” (Agriculture)

 CR2 = Locate more than 1000 m from “Nacional”-type roads

 CR3 = Locate less than 500 m from an water supply point GIVEN DATA, at \...\shapefiles\Trofa

 concelhos_ave.shp – shapefile of concelhos on the Ave River bassin

 solo_trofa.shp – shapefile of soils

 vias_trofa.shp – shapefile of roads

 pontosrega_trofa – shapefile of water supply points

NOTE: From exercise 12 onward a new format of geographical information will be used: the raster format. To copy, move or delete the datasets in this format, you should use ArcCatalog and not Windows Explorer.

You should also activate the extension Spatial Analyst (Costumize Extensions)

E X . 1 2 – I

M A G E C L A S S I F I C A T I O N

In a new project add image 004051Argbx_10.tif (ortophoto of the Tagus river region).

12.1 Make an unsupervised classification of the image in ___ classes. The first step is the productin of a signature file. Use the standart values suggested by the software.

ArcToolbox: Spatial Analyst Tools  Multivariate  Iso Cluster

12.2 Use the signature file produced in the previous step to perform an unsupervised classification using the maximul likelihood classification method.

Use the standart values suggested by the software.

ArcToolbox: Spatial Analyst Tools  Multivariate  Maximum Likelihood Classification

E X . 1 3 – D E M +

R A S T E R S P A T I A L A N A L Y S I S

Consider the DTM_1985 grid (stored at ...\grids) representing digital elevation model (DEM) of a region in Alentejo, southern Portugal (each cell in the DEM has the local elevation).

13.1 What is the total area of the region?

13.2 How many cells have elevation between 250m and 300m?

13.3 What is the average elevation (of the entire DEM)?

13.4 What is the average elevation, but only for the cells with elevation between 250m and 300m?

ArcToolbox: Spatial Analyst Tools  Reclass  Reclassify

ArcToolbox: Spatial Analyst Tools  Map Algebra  Raster Calculator

With the right button of the mouse over the name of a raster layer  Properties

13.5 Make a map with the cells where trees of a given species might be planted, knowing that these should verify simultaneously the following conditions:

 slope is less than 5% (tool slope)

 aspect should be southwest, south or southeast (tool aspect)

 elevation is lower than 285 m

ArcToolbox: Spatial Analyst Tools  Surface  …

13.6 If one adds to exercice 13.5 the following new condition, how many cells does the total possible area for the trees decrease?

 the contiguous area for the trees must have at least 1 hectare (note that 1 ha = 10000 m²)

ArcToolbox: Spatial Analyst Tools  Generalization  Region Group

E X . 1 4 – D E M +

H Y D R O L O G I C A L M O D E L L I N G Consider the DTM_1985 grid used in the previous exercice. Use the functions of hydrological modelling to output the main stream lines, using the criterium of minimum drainage area at 500 cells.

Do not forget that pit filling should be the first step.

ArcToolbox: Spatial Analyst Tools  Hydrology

E X . 1 5 –

C O S T S U R F A C E S

15.1 Consider the DTM_1985 grid used in the previous exercices and the grid

“floresta” (Portuguese for "forest"). Generate a cost surface (a grid that

represents the effort or cost of passing through each cell) based on the following table:

E F F O R T O R C O S T

S L O P E

< 5 % [ 5 % ,^{S L O P E}1 0 % [ > = 1 0 % ^{S L O P E} FO R E S T

T Y P E 1 O R 3 1 3 5

F O R E S T

T Y P E 2 O R 4 2 7 1 2

15.2 Calculate the least-cost path between points A and B (use the shapefile pontosAB.shp to know where points A and B are, or create a new shapefile to use your own points).

Cost Distance: ArcToolBox  Spatial Analyst Tools  Distance  Cost Distance Cost Back Link: ArcToolBox  Spatial Analyst Tools  Distance  Cost Back Link Cost Path: ArcToolBox  Spatial Analyst Tools  Distance  Cost Path

E X . 1 6 –

I N T E R P O L A T I O N

Consider the point dataset pontos.shp (at ....\shapefiles). The attribute named SPOT has the elevation value for each point. Build a new ArcMap project file named ex_15e16.mxd, and add to it pontos.shp and perim_lago.shp. In the project you will make four interpolations to raster layers in order to have a set of four DEM layers with 100 m of spatial resolution, using:

a) IDW, with the 20 closest neighbouring points

b) same as a), but using the dataset perim_lago as a barrier c) IDW, with the 6 closest neighbouring points

d) i same as c), but using the dataset perim_lago as a barrier

Which of the four interpolations results in the DEM with the highest value of average slope? Why?

ArcToolbox: Spatial Analyst Tools  Interpolation

E X . 1 7 –

V I S I B I L I T Y

Following the previous exercice, use one the generated DEMs to estimate the fraction of the surface of the lake (there is a shapefile for the lake named lago.shp in folder ….shape) visible form the highest point in pontos.shp.

ArcToolbox: Spatial Analyst Tools  Surface  Viewshed

E X T R A E X E R C I C E S (

T E X T I N P O R T U G U E S E

)

E X . A -

V E T O R I A L

Todos a informação necessária para a resolução do exercício está em d:\SIG\revisao\dados. A informação produzida no decurso da resolução do exercício deve ser guardada em d:\SIG\revisao\resultados.

1. Suponha que se pretende requalificar o lago grande do jardim do Campo Grande com o intuito de o transformar num parque aquático. Sabendo que a dimensão minima aceitável para o respetivo espelho de água é de 1ha (não dê importância às ilhas), verifique se o lago tem a dimensão necessária. Os pontos de controlo para georreferenciar a imagem têm as seguintes coordenadas:

A: (x,y) = (111000,199500) B: (x,y) = (111500,199500) C: (x,y) = (111000,199000) D: (x,y) = (111500,-199000)

Diga qual o erro médio quadrático encontrado e justifique se este é aceitável.

Grave os pontos de controlo como pcXX.txt.

Defina o sistema de coordenadas respetivo (Projeção de Gauss, Elipsoide de Hayford, Datum Lisboa – Sistema Hayford-Gauss Militar).

Descreva a metodologia utilizada.

2. Com base na imagem anterior construa as seguintes shapefiles:

- Eixos_via_alvalade.shp correspondendo aos seguintes arruamentos:

- Avª da Igreja; Avª do Brasil; Avª de Roma; Campo Grande e Rua envolvente ao Hospital Júlio de Matos.

Estes arrumamentos devem formar apenas três quarteirões e deve garantir a conectividade entre todos os eixos. Calcule a extensão de arrumamentos construída e identifique cada um deles com o respectivo nome.

- Quarteiroes_alvalade.shp correspondendo aos três quarteirões definidos pelos arrumamentos anteriores. Calcule a posição (x,y) para o centroide do Hospital Júlio de Matos

Descreva a metodologia usada.

3. Considere os seguintes dados:

Fregs.shp – delimitação das freguesias de Lisboa; Esp_verde.shp – jardins de Lisboa; e Rede_viaria.shp – ruas de Lisboa;

a) Identifique o maior espaço verde existente na cidade de Lisboa que apresente as seguintes caracteristicas:

 Ter acesso por avenida até 300m (e apenas por avenida);

 Localizar-se mesmo que parcialmente numa freguesia de elevada densidade populacional (densidade superior à média da cidade);

Descreva o método utilizado nos cálculos.

b) Suponha que pretende urbanizar na totalidade o espaço verde identificado na alínea anterior. O novo loteamento prevê um índice de construção de 30 fogos/ha. Calcule a população estimada para essa área admitindo que cada fogo é ocupado por 2,8 habitantes

E X . B -

M A T R I C I A L

Considere as grids DTM_1943 e DTM_1985 localizadas em D:\....\grids\.

Ambas representam modelos digitais de terreno para a mesma zona.

1. Calcule qual o volume de erosão e de depósito na área coberta pelo MDT entre 1943 e 1985.

2. Indique, na zona do MDT anteriormente referido, quais as áreas onde poderá ser implantado uma infra-estrutura de turismo rural tendo em conta as seguintes limitações de implantação:

- declive inferior a 5 % - exposto a sul

- área total superior a 1 ha

- a menos de 6000 mts de uma estrada - cota inferior a 285 mts

T Ó P I C O S A B O R D A D O S N A S A U L A S P R Á T I C A S

I N T R O D U Ç Ã O

Introdução ao ArcGIS 9.x – descrição dos 3 módulos funcionais (ArcMap, ArcCatalog e ArcToolBox)

Principais Funcionalidades do ArcMap:

 Visualização de informação (geográfica e alfanumérica);

 Edição de informação (geográfica e alfanumérica);

 Produção de saídas gráficas (layouts).

Principais Funcionalidades do ArcCatalog:

 Gestão de informação (geográfica e alfanumérica);

 Ligação a base de dados externas;

 Definição de sistemas de coordenadas.

Principais Funcionalidades do ArcToolBox:

 Operações diversas de análise espacial;

 Conversão entre formatos;

Organização e funções básicas do ArcMap:

 Conceitos de data frame; layer; shapefile; entidade; tabela de atributos

 Data view vs layout view;

 Simbologia;

 Zoom, pan, seleção, identificação e procura.

T A B E L A S

 Propriedades das tabelas

 Tabela de layers vs outras tabelas (txt, info, dbf)

 Relações das tabelas com as layers – ligação às entidades

 Criar tabelas a partir de dados existentes o Ficheiros

 Criar uma tabela nova

o Adicionar, definir e apagar campos o Adicionar e apagar registos

 Estado de edição da tabela

 Diferentes formas de edição da tabela o Registo a registo

o Seleção simples e edição conjunta

 Sorting

 Estatísticas sobre campos da tabela (com e sem seleção)

 Seleção / Promote

 Joins(1:1)

o Normal o Spatial

 Entre pontos e linhas equivale a distância mínima

 Entre polígonos e qualquer outro é relação “contido em”

 Links (1:N)

 Summarize

o Generalidades

o Operações de agrupamento o Soma de valores por grupo o Cardinalidade por grupo

o Operadores de agrupamento: mínimo, máximo, média, etc.

 Atenção ao facto de as operações do tipo Spatial Join ou Spatial Summarize não serem de facto operações de Base de Dados mas sim operações de Análise Espacial

Exercícios sobre informação alfanumérica

S E L E Ç Ã O D E I N F O R M A Ç Ã O

Métodos de seleção de entidades: Construção de Querys.

O modo de seleção “Select by attributes” e os diferentes métodos existentes.

Seleção por localização espacial.

O modo de seleção “select by location”.

4 Exercícios sobre Métodos de seleção.

C O O R D E N A D A S

Sistema de coordenadas:

 Elipsoide; Datum; Projeção cartográfica.

O sistema de coordenadas da data frame vs o sistema de coordenadas da layer Transformação de coordenadas e respetivos parâmetros

Procedimentos de georreferenciação (exemplo prático):

 Pontos de controlo;

 Erro médio quadrático;

 Validação.

G E O R R E F E R E N C I A Ç Ã O

Georreferenciação de um raster (extrato de uma folha da carta 1:25000 do IGeoE)

 Sistema de coordenadas da cartografia militar o Sistemas Hayford-Gauss militar e UTM

 Toolbar de georreferenciação

 Pontos de controlo

 Erro médio quadrático

 Correção geométrica

 Definição do sistema de coordenadas do dataset

C R I A Ç Ã O E E D I Ç Ã O D E I N F O R M A Ç Ã O G E O G R Á F I C A V E T O R I A L

 Converter uma layer para uma Shapefile

o Selected – non selected – table attribs

 Criar uma Shapefile nova o XY layers o Point o Line

 Propriedades do snapping

 Split line

 Merge

 Edit vertices

 Shape properties

 Calculo automático de comprimentos o Zooms e Pans dinâmicos

o Polygon

 Propriedades do snapping

 Split poly; Adjacent poly; Donut poly

 Edit vertices

 Edit common line

 Subtract (with ou without shift)

 Intersect

 Shape properties

 Cálculo automático de áreas

 Criação de Shapefiles por digitalização de imagens

A N Á L I S E E S P A C I A L

Análise espacial: Buffer; Dissolve; Merge; Union; Intersect; Clip; Eliminate, etc

A N Á L I S E E S P A C I A L

 As operações de análise espacial, recorrendo a funções de proximidade como a função de buffer ou sobreposição topológica como a função de união, constituem as operações elementares de manipulação de layers que permitem a derivação de novos layers verificando condições expressas sobre a distribuição espacial e/ou atributos.

 A descrição da utilização de operações de análise espacial é apresentada na forma gráfica, e acordo com a notação indicada na que se segue. Esta é uma notação informal, no caso de se pretender uma descrição mais formal sugere- se a utilização de UML com os estereótipos adequados.

 Operadores de análise espacial sobre 1 layer o Buffer e Dissolve

 Operadores de análise espacial sobre 2 layers o Merge; Union; Intersect; Clip

B U F F E R

A operação buffer é aplicável a layers de pontos, linhas ou polígonos e gera um layer de polígonos com o conjunto de pontos do espaço a uma distância dada (constante ou variável em função de atributo) dos elementos do layer original. Na

Conjunto de Dados Geográficos

Operação Espacial

Operação SQL

Sequência de Processo

Indicação de Prioridade no Processo

opção aqui considerada os polígonos de buffer que se intersetam são fundidos. O layer resultante tem como atributo a indicação de interior ou exterior ou buffer.

D I S S O L V E

No layer resultante são agregados todos os polígonos adjacentes que tenham o mesmo valor no atributo designado.

Buffer

< dist >

Tema A

Tema C

Dissolve

<atributo>

Tema A

Tema C

M E R G E

Corresponde à junção das entidades existententes em vários layers, supostamente contíguos.

Merge

Tema A Tema N

Tema C

U N I O N

As entidades dos dois layers são unidas num só, procedendo-se à interseção espacial das entidades quando necessário.

União

Tema A Tema B

Tema C

I N T E R S E C T

Corresponde a uma operação de SQL sobre uma união; só ficam no layer resultantes as entidades que existiam nos dois layers.

C L I P

Esta operação é aplicada a layers de pontos, linhas ou polígonos, tendo como argumento um layer de polígonos cuja forma define a zona a apagar do layer objeto da operação.

Int

Tema A Tema B

Tema C

Corte

Tema A Tema B

Tema C

S I G M A T R I C I A L

E X T E N S Ã O S P A T I A L A N A L Y S T

 Interpretação dos dados – discreto vs contínuo

 Grid properties

 Georreferenciação de grids

 Classificação de imagens

 Grids, suas tabelas e limitações destas

 Histogramas

 Find distance

 Calculate density

 Assign proximity

 Formatos de importação e exportação

 Conversão grid – layer e vice - versa

 Interpolação: IDW / krigagem (fora da matéria)

 Cálculos com grids: Map calculator; Map query; Reclassify (reclassificação)

 Criação de informação derivada (modelação do relevo em matricial): Isolinhas (curvas de nível); Declive; Orientação de encostas