Slides 1: spatial datasets construction and management

PROGRAMME
Introduction to spatial data
analysis
Scuola di Dottorato in Economia, La Sapienza, 2015/2016
Instructors: Filippo Celata, Federico Martellozzo and Luca
Salvati
http://www.memotef.uniroma1.it/node/6524
4) Introduction to spatial statistics with ArcGIS – May 17th
(Celata). Introduction to spatial statistics. Typologies and
specificities of spatial data. Overview of spatial analysis. Local
and global autocorrelation and spatial clustering indexes.
5) Introduction to spatial interpolation – May 26th
(Martellozzo). Introduction to spatial interpolation and the
analysis of aleatory surfaces with ArcGIS. Introduction to
geostatistics: deterministic methods (IDW), probabilistic
methods (Kriging). Huff gravity-based probabilities model.
7) Regression analysis with ArcGIS – June 8th (Salvati).
Introduction to regression analysis of spatial data. Ordinary
least square, geographical weighted regression and
introduction to spatial autoregression methods.
[ Final exam -> June ?, 3 pm (?) ]
1) Introduction to ArcGIS and to the construction of spatial
datasets – May 9th (Celata). Introduction to ArcGIS. The
specificities of spatial data and analysis. Vector and raster
geodata. Sources for spatial data. Georeferencing. Geocoding
services. Table association and mapping (choropleth).
2) Vector data editing and mapping – May 10th (Celata).
Coordinate systems. Table and spatial association. Overview
of geodata processing and editing in ArcGIS. Geodata
conversion tools. Spatial distribution measures, proximity and
accessibility analysis. Kernel density maps.
3) Raster data analysis – May 11th (Martellozzo). Intro to
raster data. How to manage and edit rasters in ArcGIS. Intro to
remote sensing. Raster analysis and map algebra.
Introduction to spatial econometrics – May 17-18-19 (Jayet)
- Spatial linear models: Weight matrices and spatially lagged
variables; Spatial moving average and spatial autoregressive
processes; SSpatial autocorrelation and autoregression
-Estimation of spatial linear models: Maximum likelihood
estimation of spatial linear models; IV and GMM estimation
-Specification of spatial linear models: Moran’s I test;
Specification tests based on ML estimation: Wald, LR, LM
-Panel data and multi-level models: Specification; Estimation
and tests on spatial panel data and spatial multi-level models
- Spatial Limited Dependent Variable models: Specification;
Problems with estimation of LDV models; Methods for
estimating spatial binary models
-> construction, analysis, modelling and
mapping of spatial data in a GIS environment
Introduction to ArcGIS
Introduction to spatial data
Spatial data
Vector
Polygons
Superfici
- Boundaries (municipal, county, district,
provinces, urban areas, neighbourhoods,
census tracks, land parcels)
- Transport (roads, railroads, trails, canals,
etc.).
Points
Lines
Geodati: basemap
Raster
Vector
- Sites, “points of interest” (firms, airports,
schools, etc. etc. etc.)
- Hydrography (surface water, rivers, lakes,
canals, etc.)
- Land cover/use (forest, wetlands, etc,) o
uso del suolo (agriculture, urban,
recreational, etc.).
- Orography (contour map, altimetric map)
Raster
Managing geodata layers
in a GIS
Typologies of geodata
Geodata spatial resolution (vs. Scale / Extent)
Add layers to the workspace
Shapefile (Vector data)
Table
Coordinate system
Spatial index
Spatial index
Vector:
Geometry
Index of geometry
Add data - c/lezgis16/basemap/zoneurbanistiche.shp
Layer file
Add data - c/lezgis16/basemap/…(all)
Add data – c/leggis16/usosuolo/usosuolopc.shp
Raster:
File - Add data - c/lezgis16/raster/raster.tif
[ File – Save as – c/lezgis16/ - (nome) – Save ]
Tool bar
Primary sources: from data to geodata
Primary sources of spatial data:
georeferencing and geocoding
Georeferencing with coordinates (longitudine-latitude, x/y)
Tools - Add XY data: c/lezgis16/AddXY/BBreakfastXY.dbf
- Geocoding services : for georeferencing point data
with nominal information and addresses
Formati numerici delle coordinate
Geographic:
75 59 32.483 W
Decimal:
-7599.2356
75 59.32483’ West -75,992356
75° 59’ 32.483’’ W -75.992356
ID
Via V. Veneto, 72
40390353547731
Excelsior
Via V. Veneto, 125
40390353547723
40390353526305
40390353525546
40390353525522
40390353525516
…
To visualize and export coordinates data:
- Calculate geometry / X/Y coordinates of a point (decimals)
- Write feature to text file (create a text file with ID and
geographic coordinates for all input points)
INDIRIZZO
Regina Hotel Baglioni
40390353547732
40390353525545
Conversion of geographic coordinates to decimal degrees:
DD = (Seconds/3600) + (Minutes/60) + Degrees
[Negativi = - (Seconds/3600) - (Minutes/60) + Degrees]
HOTEL
40390353547738
Marriott Grand Hotel Flora
Ambasciatori Palace
De Russie
Sheraton Roma
Sheraton Golf
Plaza
Parco Dei Principi
…
CAM ERE
151
Via V. Veneto, 191
156
Via V. Veneto, 62
154
Via del Babbuino, 9
327
130
LETT I
310
360
616
366
370
V. le del Pattinaggio, 100
680
1360
Via del Corso, 126
200
547
…
…
V. le Parco de' Medici, 167
Via G. Frescobaldi, 5
…
272
198
addetti
108,72
57,72
235,44
110,88
93,6
M ediaDoppia
495,0
415,0
812,3
425,0
819,0
251,6
570,5
144
598,0
543
100,64
364
142,56
…
…
…
…
…
…
…
…
388,0
…
580,0
…
…
…
…
-Geocoding services :
http://batchgeo.com
- Open
lezgis16/geocode/geocode.xls,
sheet: serv_imp_2 *
- Copy and past in
batchgeo.com
- Settings (address, city,
province, postal code, NAME)
and run
- Save map (+data)
* Istat, Asia archive of firms, 2008,
Rome, Firms owned by foreign
born, Industry: firm services > 2
employed
-Export from google earth (save as .kmz or .kml)
- Save with name and address / Open the KML file in Google Earth
-From google to ArcGIS (kml to shapefile)
Zonums’ Kml2Shp
online:
Right botton /
save place
with name
- Upload / Process /
Export
- Import in ArcGIS over
georeferenced layers
- Export as shapefile:
Right botton / data /
export data (same coord.
syst. as the dataframe)
(Free) geocoding services
(Free) geocoding
services
-From ArcGIS to google (shapefile to .kml)
-Gmap editing and sharing
Zonums’ “shp2kml”
Layers in geographic coordinate system WGS1984 (!)
Georeferencing and
vectorialization
Secondary sources of spatial data
Secondary sources: geodati (free..) / basemap
Fonti di geodati (gratuiti..) / basemap
Administrative (subnational) areas
Administrative areas Europe (NUTS)
Administrative areas: Italy
Sub-municipal areas: Rome
Sistemi locali del lavoro Istat: l’area dei Comuni i cui residenti che si
spostano giornalmente per motivi di lavoro al di fuori del Comune di
residenza, si dirigono per almeno il 75% presso il Comune centrale
Municipi
Postal codes
Sub-municipal areas: Rome
Zone urbanistiche
Sub-municipal areas: Rome
Zone toponomastiche
Census tracks (sezioni di censimento)
Zone OMI (national real estate observatory)
Census tracks
Open (geo)data
Other sources / projects
Table join: to associate external
tables to georeferenced layers
The association of table data to
vector data
Shapefiles’ attribute table:
(right click on the layer / open
attribute table)
Import tables with the right format (DBF IV, .dbf)
Adapt the table in excel: original
Adapt the table in excel: transposed
Adapt the table in excel: summarized
Adapt the table in excel: final
Columns’
names
Only:
az, AZ,
a1
_
Add .xls/final to the wspace, right click to open and
Export as .dbf table (and add to the wspace or to open in excel)
No:
.,!‘“
/&%
etc.
Max
10
digits
Join table data (to
zoneurbanistiche.shp):
-Add lezgis16/tablejoin/str_zurb_15
to the w.space
- Find the two identical columns
(fields) in str_urb_15.dbf and in the
attrib. table of zoneurbanistiche.shp
- Join str_zurb_15.dbf TO the
attribute table of
zoneurbanistiche.shp: right click ON
THE SHP / Join and Relates / Join /
“Join attributes from a table” /
Choose table and fields / OK
- Open the shp table to verify
(problems and clues)
- Export to consolidate: right click on
the shp / data / export data
To edit
tables
- Right click on layer / Edit features / Start editing
-Costumize
/ Toolbars /
Editor /
Stop editing
Mapping the distribution of foreigners in Rome
- Go to VIEW menu / Layout view / Page setup (File / Page setup), Frame
re-size and zoom to the correct extent
Mapping
- Symbolize strangers per square km: right click the polygonal Shp /
Properties / Symbology: choose the format (quantities), set the value
(tot_str15), normalize per square km (Normalization = areakm), choose the
Color ramp (flip or ramp if needed), explore the Classify menu (Quantiles)
- Add and customize legend: Insert / Legend
- Add labels: right click on the layer you want to label / Label Features, and
set the label field and format in the layer’s Properties / Labels
- Export map as image file: (in layour view) File / Export file / Set file
name, format (.tif) and RESOLUTION (min 300 dpi)