QGIS explorations

[pkd2512]

As we go on learning how to work with spatial data in QGIS, drop in your explorations in this thread.

Write a brief description of what your map shows and the data sources used. Post map screenshots from QGIS showing WIP and final results.

Lecture notes

Airports (purple), Ports (blue), Stations (yellow) sized by altitude

Oil pipelines by volume

[8PocketElf]

co- siesmic landslides in sikkim due to dams

data layers - teesta river & its tributaries major road networks hillshade glaciers glacier lake changes exisiting dams proposed dams protected forest area earthquakes since 1990s effected villages due to nepal- india earthquake 2011 landslides cause within 2 days of earthquake

work to be done detailed hillshade layer by layer data reveal poster data narrative, texts & images

[mohnishlandge]

RGB

Airports

Rivers - India

Processing

Earthquakes

Narrative Cartography

[karthikeya-gs07]

QGIS Explorations

Karthikeya GS

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Rule-based sectioning in map

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Assigning colours from CSV file to Countries

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Population Mapping of the World

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GDP Mapping of the World

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Airports of the World - Mapping Elevation as Symbol Area

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India Map Explorations

First Iteration:

Note: Will make India POV soon

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Indian Coastal Water Control

Using reprojection to 44N - for meter projection. Using line buffer with 'difference' to obtain outer boundaries.

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Indian Airports and Connections

Using 'Join by lines (hub lines)' with source and destination airports on separate CSV and common ID values.

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World Gas Pipelines with Volume Encoding

Using WKT file with 'Linestring' for the route.

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World Earthquakes - Last 30 Days (9th Jan - 9th Feb 2023)

World Earthquakes Map

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Pacific Ring of Fire

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Major Countries

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Schematic Cartography

'East Coast' is a schematic map of all the marine accidents that have happened between the years 2000 - 2015 on the east coast of the US. The map highlights the types of ships that met with an accident wrt the geographical landscape. The map also emphasises the Mississippi River, which is the heartline of trade in the US.

An interactive version of the map was also made to derive better insights from the map about types of incidents (accidents), and what geographical landscapes could cause such issues.

Interactive Prototype

Link - https://xd.adobe.com/view/4d2b5909-5139-449a-9477-c56bc6fa1d67-1878/?fullscreen

[amandeep2496]

[ParvathyRaju98]

Homework 1: Rivers of India

Version 1

Feedback

• Outline of the country need not be this thick, demarkation is already obvious
• Fade out the Lat Long lines to make it look like Graph Sheet
• Legend is redundant
• Check Spelling for typo
• River lines & State Lines are overlapping and there is no hierarchy

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Exploration 1: Delhi Pointer

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Exploration 2: Population Density - Choropleth

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Exploration 3: Airports of the World

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Exploration 4: Disputed Lines

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Exploration 5: Airports & Destinations Hub & Spoke Method

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Exploration 6: Airports of India Clip Method

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Exploration 7: Coastal Lines - Nautical Miles

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Exploration 8: Oil and Fuel Pipelines of the World

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[Rucha-ux]

BASICS

RANDOM COLOR

POPULATION ESTIMATE

GDP COMPARISON

RIVERS OF INDIA

AIR ROUTES

OIL-NGL PIPELINES

LAYOUTING

[Rajeshm006]

Rivers_India

Earthquake

Airport_links

tsunami_dataset

Air_pollution

Mapping_my_selected_lake

Checking the Inlet and outlet of the selected lake using altitude:

Cellphone Data

[dmrunal08]

### Task 1: Plotting Rivers of India

Task 2: Earthquakes

Its a WIP

Explorations:

Its a WIP

Scrolly: LINK: https://xd.adobe.com/view/30455bd7-7d69-4ea4-a8f6-bb30d5904abe-6516/?fullscreen

PNG Version:

[geetanjalikhanna98]

QGIS Explorations

Geetanjali Khanna

Filtering in map (using Query Builder)

Choropleth 1: Assigning colors from CSV file to Countries

Choropleth 2: Population Mapping of the World (Mapping population to color using Assistant)

Choropleth 3: GDP Mapping of the World (Mapping GDP to color using Graduated Symbols)

Airports of the World: Mapping Elevation as Symbol Size

Rivers Map of India

A4 - 1.pdf

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Airport Routes

Pipelines

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Narrative Cartography

Interactive Narrative Cartography

[speckx]

Fill Color in World Map

Learnings- Data defined channels like color, stroke color, weight with the help of expression builder

World GDP

Learnings- Graduated symbols Adding Legend Projections

Creating buffer of geographies

Learnings- Reprojections, UTM Processing tool Geoprocessing tool

Gas Lines (based on capacity)- Using Assistant for linking data to channels.

Learnings- Assistant

Flight Routes

Learnings- Expression builder

Particulate Pollution

Learnings- raster data formats and importing raster layer properties- symbology, histogram, no data values manipulating color gradation to suit narrative - here we highlighted extreme pollution by exaggeration and manipulating data classification

DEM files

Learnings- Understanding DEMs Render styles Hill Shade, Scaling

Trees of Banglore

Narrative theme We constantly hear about the dwindling greens of Bengaluru. The consequences of it are well know ; ecological problems, urban heat island effect, loss of public greens etc. There is also a loss of heritage and identity that comes with mistreating the city's trees. The narrative traces back the trees to their origin which wasnt quite natural.

Questions

How did a geographically arid and dry land turn into a lush urban forest ? why were these trees/ groves made and who was responsible? At what rate are we losing our greens ?

Concept

Illustrations of Bengaluru in 1700s Lalbagh

Nandi Hills

How a barren land turned into lush forest The trees were a result of a cultural / political agent rather than a natural process

1. The sacred groves planted near banks of Arkavati river
2. The trees imported by Deccan Sultanate
3. The botanical experiments during colonial period

This book maps groves, trees and avenues of historical prominence

But in the last 3 decades, the green cover Bengaluru has come down from 63% to 7 %

It is interesting to note that greens of cultural and heritage value managed to survive the urbanization

Narrative sketch

NDVI index map calculated using raster processing from Landsat 8 images

Tree density - trees per person - 2014

[ankita360]

[kowsie]

[Gagarina1]

Coloured maps -

Population estimation

Understanding Masking

Airport routes

Floods of India