Scipediacontent at 14:00, 21 January 2021

2021-01-21T14:00:19Z

Scipediacontent: Scipediacontent moved page Draft Content 326315571 to Antos et al 2016a

2020-10-14T13:51:59Z

Scipediacontent moved page Draft Content 326315571 to Antos et al 2016a

Scipediacontent: Created page with " == Abstract == This paper illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large Afr..."

2020-10-14T13:51:56Z

Created page with " == Abstract == This paper illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large Afr..."

New page

== Abstract ==

This paper illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large African cities (Addis Ababa, Nairobi, Kigali, Dar es Salaam, and Dakar). To allow for comparability across very diverse cities, this work looks at the above mentioned cities through the lens of several spatial indicators and relies heavily on data derived from satellite imagery. First, it focuses on understanding the distribution of population across the city, and more specifically how the variations in population density could be linked to transportation. Second, it takes a closer look at the land cover in each city using a semi-automated texture based land cover classification that identifies neighborhoods that appear more regular or irregularly planned. Lastly, for the higher resolution images, this work studies the changes in the land cover classes as one moves from the city core to the periphery. This work also explored the classification of slightly coarser resolution imagery which allowed analysis of a broader number of cities, sixteen, provided the lower cost.

Document type: Book

== Full document ==
<pdf>Media:Draft_Content_326315571-beopen882-4169-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://documents.worldbank.org/curated/en/502451481312733719/pdf/WPS7911.pdf http://documents.worldbank.org/curated/en/502451481312733719/pdf/WPS7911.pdf]

@@ Line 2: / Line 2: @@
 == Abstract ==
-This paper illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large African cities (Addis Ababa, Nairobi, Kigali, Dar es Salaam, and Dakar). To allow for comparability across very diverse cities, this work looks at the above mentioned cities through the lens of several spatial indicators and relies heavily on data derived from satellite imagery. First, it focuses on understanding the distribution of population across the city, and more specifically how the variations in population density could be linked to transportation. Second, it takes a closer look at the land cover in each city using a semi-automated texture based land cover classification that identifies neighborhoods that appear more regular or irregularly planned. Lastly, for the higher resolution images, this work studies the changes in the land cover classes as one moves from the city core to the periphery. This work also explored the classification of slightly coarser resolution imagery which allowed analysis of a broader number of cities, sixteen, provided the lower cost.
+This paper illustrates how the             capabilities of GIS and satellite imagery can be harnessed             to explore and better understand the urban form of several             large African cities (Addis Ababa, Nairobi, Kigali, Dar es             Salaam, and Dakar). To allow for comparability across very             diverse cities, this work looks at the above mentioned             cities through the lens of several spatial indicators and             relies heavily on data derived from satellite imagery.             First, it focuses on understanding the distribution of             population across the city, and more specifically how the             variations in population density could be linked to             transportation. Second, it takes a closer look at the land             cover in each city using a semi-automated texture based land             cover classification that identifies neighborhoods that             appear more regular or irregularly planned. Lastly, for the             higher resolution images, this work studies the changes in             the land cover classes as one moves from the city core to             the periphery. This work also explored the classification of             slightly coarser resolution imagery which allowed analysis             of a broader number of cities, sixteen, provided the lower cost.
 Document type: Book
 == Full document ==
-<pdf>Media:Draft_Content_326315571-beopen882-4169-document.pdf</pdf>
+<pdf>Media:Antos_et_al_2016a-beopen619-9241-document.pdf</pdf>
@@ Line 15: / Line 15: @@
 * [http://documents.worldbank.org/curated/en/502451481312733719/pdf/WPS7911.pdf http://documents.worldbank.org/curated/en/502451481312733719/pdf/WPS7911.pdf]

← Older revision	Revision as of 13:51, 14 October 2020
(No difference)

Antos et al 2016a - Revision history

Scipediacontent at 14:00, 21 January 2021

Scipediacontent: Scipediacontent moved page Draft Content 326315571 to Antos et al 2016a

Scipediacontent: Created page with " == Abstract == This paper illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large Afr..."