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ERDAS - Digital Image Classification [Geography 4354 – Remote Sensing]
from cross stitch to object based land cover classification via remote sensing
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from cross s(tch to object based land cover classifica(on via remote sensing for statisticians [email protected] | Istat . Italian national institute of statistics
Transcript of from cross stitch to object based land cover classification via remote sensing
from cross s(tch toobject based land cover classifica(onvia remote sensing
for statisticians
[email protected] | Istat . Italian national institute of statistics
depero . fox . 1923 . tapestry
for the eyessignificant shapesgroups of stitches
for the handsthread softness
external informationround frame
venice . google earth
venice . cross s9tch pa:ern
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1 1 tessuto urbanotessuto urbanotessuto urbanotessuto urbanotessuto urbano
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3 3 attività industrialiattività industrialiattività industrialiattività industrialiattività industriali
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5 5 aree pubblichearee pubblichearee pubblichearee pubblichearee pubbliche
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7 7 strada, ferroviastrada, ferroviastrada, ferroviastrada, ferroviastrada, ferrovia
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9 9 aree portualiaree portualiaree portualiaree portualiaree portuali
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11 11 aree verdiaree verdiaree verdiaree verdiaree verdi
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13 13 canali lagunaricanali lagunaricanali lagunaricanali lagunaricanali lagunari
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15 15 lagunalagunalagunalagunalaguna
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17 17 lidolidolidolidolido
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key elements
image divided in uniform squares . pixelsevery pixel a colourgroups of adjacent pixels . shapes and objects in the map of the city
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1 1 tessuto urbanotessuto urbanotessuto urbanotessuto urbanotessuto urbano
2 2
3 3 attività industrialiattività industrialiattività industrialiattività industrialiattività industriali
4 4
5 5 aree pubblichearee pubblichearee pubblichearee pubblichearee pubbliche
6 6
7 7 strada, ferroviastrada, ferroviastrada, ferroviastrada, ferroviastrada, ferrovia
8 8
9 9 aree portualiaree portualiaree portualiaree portualiaree portuali
10 10
11 11 aree verdiaree verdiaree verdiaree verdiaree verdi
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13 13 canali lagunaricanali lagunaricanali lagunaricanali lagunaricanali lagunari
14 14
15 15 lagunalagunalagunalagunalaguna
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17 17 lidolidolidolidolido
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venice from the satellite . remote sensing
image from WorldView2 satellite
humans have eyes . satellites have sensors
passive sensors register radiation from the earth
radia9ons . different wavelenght
sensors can measure radiations that are not visible
satellite worldview 2 . 8 spectral bands . 2x2m pixel
red
green
blue
near infrared
examples of four spectral bands
different objects on earth
1 pixel =4 measures
Red 59Green 48Blue 21NIR 50
near infrared / red = 50/59 = 0.84values close to 1
green area
different combinations of band values
different objects on earth
near infrared / red = 39/131 = 0.29values far from 1 towards 0
different combinations of band values
1 pixel
Red 131Green 75Blue 65NIR 39
buildings or ar(ficial areas
different objects on earth
high values of blue band
different combinations of band values
water
1 pixel
Red 67Green 58Blue 95NIR 11
objects . adjacent pixels . similar bands’ values
similar bands’ values inside (low variability) &dissimilar bands’ values outside
similarity and dissimilarity evaluated bystatistical mean, variance, texture, ...applied to pixel and objects vectors of band values
pixel grouping.statistical classification methods
ancillary informa9on on land use
administrative maps of land use.public/private areasresidential areastransport routes...
venice . object based land cover
it works with toy building bricks, too
pixel 60x60 m
1 pixel
colorsrepresent classesof land covereg
