Tell us here what your map’s message is, before you use QGIS to create your map
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To show Ethiopian wolf sighting and distribution in the northern Ethiopia
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The message I want to convey in my maps is the distribution of seahorses (Hippocampus reidi) in the estuary that is my study area, highlighting other aspects such as density, habitat availability, among others.
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I want to show site where rodents were sampled and probably a polygon including the whole region where site were selected.
I’m aiming to create an ecological niche model for a species eventually, so it’s a map that will show continuous climatic data and some thematic data (like vegetation), as well as land features like roads & rivers.
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i would like to create a map that shows Ethiopian wolf habitat sites under threats by humans’ and their livestock encroachments in each of the northern Afroalpine areas of Ethiopia. And as well to show potential places/sites/ for interventions designed to reduce the pressure on these wolf habitat sites.
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Perhaps to show the location of sampling sites and most probably their associated environmental quality.
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I would like to visualise the exact areas within a forest that I collected planarians from by
- using points to denote the abundance of the worms, and
- create a polygon/polygons to denote the exact area/s where we found these planarians within the forest.
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I would like to show the layout of camera traps in relation to the roads and rivers so that I can make an access and service plan for the team to check up on them and change batteries in an efficien manner. Once I know where they all are I can design a route to reach them in a linear fashion … I think
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To look at density of grey squirrels from sightings and management so we know where to focus efforts in the future. I.e. density based points with the larger presence of grey squirrels being larger points to help us visually see and adjust our strategy on the ground over time.
Hi @Glen
just out of interest would there be different species of rodents you’re sampling and would it be worthwhile highlighting these in different colours and possibly associating them with habitat factors in any way to look at why they have that distribution?
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Hi @Mengistu
would you potentially be looking at wolf sighitings in relation to any specific features in the lanscape such as roads or urban areas?
In this module, I will show something a little different.
I want to show maps of multiple sites across a large area (a county in the UK) so I want to create a lot of maps, one for each site (I will use the “Map Atlas” function to be able to do this).
Want I want to show is the detailed site assessment data for each site which has looked at multiple criteria (16 different criteria assessed for each site).
The objective is to show clearly the multiple data used in site evaluation for for each individual site (something that can not be clearly done using a map alone due to the complexity of the underlying data).
So unlike most of the other work in this course, I am switching the emphasis to the data behind the map rather than on the actual geographic map itself (yes, I know this module is about making a map, but as far as GIS goes, then the data lying behind the map is just as important as the map itself).
Really just showing this to give a different aspect on what can be accomplisged in QGIS using it as a geospatial analytical tool as well as a powerful map making tool - just wanted to be different 
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I do not have my own data yet, but I would like to make urban maps about concrete and green areas, calculate distances, heterogeneity, isolation etc. Maps are rather calculation material and not representation. If I represent with them, I am only showing my sampling areas.
Have a look at the OpenStreetaMap data source. As well as using it as a “basemap”, you can also download QGIS data and using its feature attibutes, extract the different land use classifications in urban areas. While it doesnt explicity identify “concrete”, it odes often identify parks and other “un-built” areas.
You can use this as a starting point then sub-divide the classifications further by visual interpretation of the aerial imagery.
Just to clarify - is is actually “concrete” you want to identify explicity ? or are you trying to identitfy “built on” areas in the urban environment (ie. including tarmac, buildings made of brick with metal or tiled roofs etc). Being specific about the actual material used may require an area based survey - or if you are really interested in “Concrete”, use of multispectral image analysis may be able to identify the specific materials you are interested in.
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Thank you, but my group uses European Urban Atlas which has accurate maps about roads, buildings, green spaces with validated values. I am not specifically interested in concrete material, just the “concrete jungle” what interests me and that usually contains lots of other materials like metal and bricks, I know.
Ok - just trying to point you in the direction of some useful data sources seeing as you said you wanted to make urban maps about “concrete and grass”. One of the hardest parts of GIS is working out what the question is . There is an interesting discussion to be had about defining what “urban” actually means and in defining the scope of study.
Hi @MAC ,
Yes, I will be working with different species of rodents. As per advise, I assume grouping species and giving them various colors for each will work.
I am also looking at ecological factors, that can lead to migration of most of these rodents, such as Lemniscomys rosalia, which travels far distances irrespective of food availability, compared to most of the Gerbils caught that relied on certain grass seeds, such as Eragrostis sp during the dry season.
I am also looking at association of seasonal variation to rodent diversity, of which fluctuations can also impact disease prevalence. Example: High rainfall season will equal high disease distribution due to an abundance of food, and and increase in rodent populations.
So, I really have to crack this, as a beginner, to be able to do labelling in all that I have mentioned above, to create not just a very nice map, but with information that makes sense.
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That sounds super interesting @Glen thanks for all the extra info. I’m sure his will really help you figure out all the intricacies of what helps determine their diversity. Good luck with the work.
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@MAC,
I love everything about this project, hence I want to learn GIS more to be able to explain my data.
Thanks