it geostat population grid 2011 raffaella chiocchini – stefano mugnoli istat – italian national...
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IT Geostat Population Grid 2011
Raffaella Chiocchini – Stefano MugnoliIstat – Italian National Institute of Statistic
Luca Congedo – Michele MunafòISPRA - Italian National Institute for Environmental Protection and Research
Wien - November 11th 2015
R. Chiocchini, S. Mugnoli, L. Congedo, M. Munafò – Wien - November 11th 2015
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:
• - 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
Seek simplicity but distrust it
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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
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BT ISTAT Copernicus HRLs
A friend is someone who knows all about you and still loves you
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• European initiative for land cover monitoring
• High Resolution Layers:– Degree of Imperviousness– Forest– Grassland– Wetland– Water Bodies
• Referred to 2012
• Rasters with spatial resolution 20m
Copernicus HRLs
A satellite has no conscience
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• Estimation of built-up areas
• Product derived from the classification of multispectral remote sensing images
• It represents the percentage of soil sealing inside the pixel area
• It includes the following elements:• 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
Degree of ImperviousnessThe nation that destroys its soil destroys itself
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Give a man a mask and he will tell you the truth
Masking the Degree of Imperviousness• Isolate only residential zones from built-up areas, excluding:
– Streets– Airports– Railway stations and transport network
• Thematic digital cartographies: Land cover and use Maps, Road Networks, etc.
• 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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Zonal Statistics ARCGis 10.1
Every man is surrounded by a neighborhood of voluntary spies
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Cell Geostat aggregation (sum)
Big results require big ambitions
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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
It is a capital mistake to theorize before one has data
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Why grid statistics?
When studying such phenomena, a system of grids with equal-size 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).
We are all cells in the same body of humanity
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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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Degree of Urbanisation (DEGURBA) - Local Administrative Units
A great city is not to be confounded with a populous one
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R. Chiocchini, S. Mugnoli, L. Congedo, M. Munafò – Wien - November 11th 2015
Future developments
• Estimate resident population not only inside ‘conventional’ boundaries’
• Drawing population nets with small mesh sizes, best suited for urban areas;
• Third dimension, to distribute resident population not only on the base of the HRL Imperviousness classification, but also in relation to buildings characteristics;
• Assessment of other relevant environmental statistic data such as those related to biomass in forest or agriculture;
• Frequent production process will be very useful to update the estimation of population distribution inside census area;
• Data collected at this resolution can also be used to upgrade DEGURBA
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Prediction is very difficult, especially about the future
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
We're all working together; that's the secret