National Administrative Department of Statistics DANE...
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@DANE_Colombia /DANEColombia /DANEColombia
National Administrative Department of Statistics –DANE
Colombia
October 2015
Using satellite images to calculate land use and land cover
statistics
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Background (1)
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Objective
• Explore the usefulness of Big Data from satellite land images for theupdating and improvement of statistic information.
• Calculate an indicator that shows the urban agglomeration degree by usingsatellite images and population data.
• This indicator would provide additional information to the framework forthe implementation of several goals referred to in health and food security.
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Data collection
Changesdetection
Ratescalculation
Indicatorcalculation
Satelliteimagescollection
Populationdata collection
Image pre-processing
Imageclassification
Populationgrowth rate
Urban landconsumptionrate
Ratio of therates
Methodology
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Imagery collection
Landsat 2005 Landsat 2010Landsat 2015
Criteria:
• Availability
• Quality (percentage of cloud cover)
• Acquisitions at the same time of the year
• Spatial coverage
• Similar spectral bands
http://earthexplorer.usgs.gov/
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Imagery pre-processing
Original 2005 Image Pre-processed image
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Semantic net
Rules and operatorsdefinition
Coveragesgeneration
Coverages generation with object-oriented classification
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Coverage map
Water
Urban/Built - Up
Grassland
Barren/Minimal Vegetation
Forest, Shrub and Scrubland
Coverage map 2005Coverage map 2010Coverage map 2015
Map Legend
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Approach to the Land Consumption Rate (ULCR)
)(
)( )(
1
12
tAreaLandUrban
tAreaLandUrbantAreaLandUrbanLCR
10.807
11.288
12.178
2005 2010 2015
Barranquilla Metropolitan Area
Urban hectares
8%4%
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Approach to the Population Growth Rate (PGR)
)(
)()(
1
12
tPopulation
tPopulationtPopulationPGR
1,769,191
1,898,007
2,025,071
2005 2010 2015
Barranquilla Metropolitan Area
Population
7%7%
*Population projections
* *
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Proposed Indicator
RateGrowthPopulation
RatenConsumptioLandIIndicator )(
I=0.642005-2010 I=1.13
2010-2015
* *
* Preliminary data
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• Big Data from satellite imagery is a powerful tool to increase thepotential applications of statistics and to improve the quality ofstatistics data. This integration allows the exploration of newmethodologies and the improvement of those already available.
• The benefits generated by the use of remote sensing, create theopportunity to make the information more traceable and allow thedesign of different types of multitemporal studies.
• This project is a good example for the use of open source software andsatellite images, which are both available on the web for free.
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