IT Geostat Population Grid 2011
Raffaella Chiocchini – Stefano Mugnoli
Istat – Italian National Institute of Statistic
Luca Congedo – Michele Munafò
ISPRA - Italian National Institute for Environmental
Protection and Research
Wien - November 11th 2015
Seek simplicity but distrust it
Introduction
The final product represents very worthwhile collaboration between two
Italian National Research Institutes that permitted a successful synthesis
among many geographic datasets, in particular two of them:
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- Copernicus Degree of Imperviousness HR Layer at 20m of resolution;
- ISTAT 2011 Census cartography and data;
Starting from the bond between ISTAT geographic datasets and ISPRA
Imperviousness Layer, we could estimate with a really good approximation
which are the residential zones. Moreover, the resolution of the Copernicus
satellites ensures very precise estimations
R. Chiocchini, S. Mugnoli, L. Congedo, M. Munafò – Wien - November 11th 2015
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Only by acceptance of the past, can you alter it
- Census Data 2001
- EUROSTAT Elaboration
- Disaggregation Algorithm
- GMES degree of soil-sealing
- CORINE LC/LU
R. Chiocchini, S. Mugnoli, L. Congedo, M. Munafò – Wien - November 11th 2015
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A friend is someone who knows all about you and still loves you
BT ISTAT
R. Chiocchini, S. Mugnoli, L. Congedo, M. Munafò – Wien - November 11th 2015
Copernicus HRLs
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A satellite has no conscience
Copernicus HRLs
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European initiative for land cover
monitoring
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High Resolution Layers:
– Degree of Imperviousness
– Forest
– Grassland
– Wetland
– Water Bodies
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Referred to 2012
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Rasters with spatial resolution 20m
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The nation that destroys its soil destroys itself
Degree of Imperviousness
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Estimation of built-up areas
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Product derived from the classification of multispectral remote
sensing images
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It represents the percentage of soil sealing inside the pixel area
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It includes the following elements:
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•
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Housing areas
Industrial, commercial areas, factories
Traffic areas (airports, harbors, railway yards, parking lots)
Amusement parks (excluding the pure green areas
associated with them)
Construction sites with discernible evolving built-up
structures
Single (farm) houses (where possible to identify)
Other sealed surfaces that are part of fuzzy categories,
such as e.g. allotment gardens, cemeteries, sport areas,
camp sites, excluding green areas associated with them.
Roads and railways associated to other impervious
surfaces
Water edges with paved borders
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Give a man a mask and he will tell you the truth
Masking the Degree of Imperviousness
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Isolate only residential zones from built-up areas, excluding:
– Streets
– Airports
– Railway stations and transport network
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Thematic digital cartographies: Land cover and use Maps, Road Networks, etc.
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Result: raster of mainly residential areas used as input for population distribution
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If you don't know what you want, you end up with a lot you don't
Population distribution inside each 400mq pixel
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Every man is surrounded by a neighborhood of voluntary spies
Zonal Statistics ARCGis 10.1
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Big results require big ambitions
Cell Geostat aggregation (sum)
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It is a capital mistake to theorize before one has data
310.980 cells 1Km2
59.429.359
Vs
59.433.744
138.764 uninhabited cells
28.762 cells with 3 o less units
34.151 the most populated cell
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We are all cells in the same body of humanity
Why grid statistics?
When studying such phenomena, a system of grids with equalsize grid cells has many advantages:
- grid cells all have the same size allowing for easy
comparison;
- grids are stable over time;
- grids integrate easily with other scientific data (e.g.
meteorological information);
- grid systems can be constructed hierarchically in terms of cell
size thus matching the study area;
- grid cells can be assembled to form areas reflecting a specific
purpose and study area (mountain regions, water catchments).
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The city is not a concrete jungle, it is a human zoo
Possibility to do statistics inside cell grids with a smaller area
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I'm not bad. I'm just drawn that way
Better delimitation of the enumeration areas
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A great city is not to be confounded with a populous one
Degree of Urbanisation (DEGURBA) - Local Administrative Units
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Prediction is very difficult, especially about the future
Future developments
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Estimate resident population not only inside ‘conventional’ boundaries’
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Drawing population nets with small mesh sizes, best suited for urban areas;
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Third dimension, to distribute resident population not only on the base of the HRL
Imperviousness classification, but also in relation to buildings characteristics;
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Assessment of other relevant environmental statistic data such as those related
to biomass in forest or agriculture;
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Frequent production process will be very useful to update the estimation of
population distribution inside census area;
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Data collected at this resolution can also be used to upgrade DEGURBA
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We're all working together; that's the secret
Thank You
Raffaella Chiocchini ([email protected])
Stefano Mugnoli ([email protected])
Istat – Italian National Institute of Statistics
Luca Congedo ([email protected])
Michele Munafò ([email protected])
ISPRA - Italian National Institute for Environmental
Protection and Research