Dear Claudia,

I would recommend finding the individual datasets (e.g. altitude or DEM, urbanisation/land-use indices, watercourses etc), set threshold limits for these variables/factors and then rasterise them. You can then conduct a GIS analysis to find areas which possess all of the 'desirable' factors. Raster calculator can be used for this purpose.

Kind regards,

Daniel

That is better to do it step by step.

for example in this address you may have the list of 125 most high density cities:

http://www.citymayors.com/statistics/largest-cities-density-125.html 

then you may search to find out their topography state to extract the desired ones. And so on.

be success

For finding out the topography of a city, you may use a free Gaia software which is able to use free WMS services. There is a free layer which shows all the world contour lines. You may zoom to your selected city location and consider its topography.

be success

Thank you both, Daniel and Ali.

Best regards,

A map of world population distribution will show the unequal spatial pattern of population. Explaining this map demonstrates well the reasons for spatial disparity, and links with the key concept of Physical and Human Processes. Climate, soil, topography are all clearly major factors in human population distribution. The least populated areas are the hottest, driest and coldest. Temperate areas of fertile plains are mostly well populated. People can only live in large numbers where they can produce food or earn enough money to import food. Therefore, areas of high economic output (farms, factories, ports, cities) are areas of population. Societies, nations, cultures have all had key areas where they have lived and flourished. Certain societies have mastered the seas or the deserts, while others have lived successfully in rain forest or treeless plains.

https://www.rgs.org/NR/rdonlyres/.../KS3_CPD_PopulationandMigration_script.doc

Thank you so much, Dr. Krishnan.

Hi Claudia,

I agree with others that the easiest way how to conduct your analysis is to get individual layers and set the threshold / mask based on the requirements you have since that help you identify preliminary areas to focus on.

a) Low topography: you can use some of global DEM data that are available online, e.g. GDEM or SRTM30

http://asterweb.jpl.nasa.gov/gdem.asp

http://www.jspacesystems.or.jp/ersdac/GDEM/E/index.html

b) predominance of urban areas - you can assume that densely populated areas are also the urban areas because the population density is the main indicator of urban areas according to most studies, data e.g.

http://sedac.ciesin.columbia.edu/data/collection/gpw-v3/sets/browse

c) land cover change, data e.g.

http://sedac.ciesin.columbia.edu/theme/land-use/data/sets/browse

d) water, data e.g.

http://landcover.usgs.gov/glc/

e) industrialisation seems like the biggest issue, you probably need to collect the data for areas of interest based on data you already have, from different sources. However, I think that most of industrialised areas are very similar to urban areas again.

f) other resources: e.g. http://www.diva-gis.org/Data

Lukas

Hello Lucas, thank you so much for your inputs. I will check the references as soon as possible. The particular issue in the case of the munciiality I have targeted is about the draining - there are two water streams draining the small territory, it seems more relevant as synergic impact than the river because of the trajectory of each draining. While the rivers sun through the outside part (not urbanised at all), the small streams run through the whole  urbanised and industrialised areas (both are mixed, which means no planning), and in the year of 1990 such water streams were unified in a certain point. This is a very particular situation that entails a significant (synergic) impact every time the rainfall levels are above the annual average. For instance, in 2013 and in 2015, the municipal levels of rainfal were twice the regional ones.