Map narrative

[SudevKiyada]

Use this GitHub issue as the central place to submit your narrative cartography project, including progress updates and your final long‑form webpage or prototype. All submissions should be added as comments below.

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What to Submit

1. Project Progress

Throughout the project, add comments documenting your process. These should include:

• Notes on your narrative concept and structure
• Screenshots or descriptions of your evolving map
• Datasets used, including links and attribution where required

You may add multiple comments as your work progresses.

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2. Final Narrative Cartography Project

Your final submission should be presented as a long‑form, webpage‑like experience. This can be:

• A published webpage
• A prototype built in design tools like Figma, Framer, etc

Your project must include:

• A map as the central element of the story — the map should meaningfully drive the narrative
• Clear, engaging storytelling supported by visuals and data
• Proper crediting of all datasets used
• Thoughtful visual hierarchy and structure, as you would expect in a web‑based long read

[Choy-An]

#Aswanth C

When Rivers Lose Their Source

A narrative cartography project exploring the retreat of the Gangotri Glacier and the shifting origins of the Ganga.

Project Overview

This project investigates how the source of one of South Asia’s most significant rivers is gradually changing. Instead of presenting the glacier as a static point on a map, the story examines the Gangotri Glacier system as a dynamic landscape whose boundaries and snow cover evolve over time.

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Narrative Structure

The story unfolds in several stages:

1. Locating the Source
   The opening sections situate the Gangotri Glacier within the Himalayan landscape and introduce the Bhagirathi river system that ultimately feeds the Ganga.

2. Understanding the Glacier System
   Through maps and imagery, the glacier is presented not as a single body of ice but as a networked system of tributary glaciers and snowfields.

3. Temporal Comparison of Snow Cover
   Satellite imagery from different years is used to visually compare snow and ice coverage.
   An interactive slider allows readers to examine how the extent of snow cover has shifted between 2005 and 2025.

4. Quantifying Glacier Loss
   Estimated mass loss values are translated into an understandable scale through comparative visualization, relating glacier volume loss to the approximate concrete volume of the Statue of Unity.

5. Reflection on River Origins
   The story concludes by reframing the idea of a river’s “source” as something that can slowly move as glaciers retreat.

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Data Sources

The visualizations and maps in this project are based on publicly available remote sensing datasets and geographic data.

Satellite Snow Cover Data

• MODIS Terra Snow Cover (MOD10A1)
  Derived from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS).
  Snow cover is detected using the Normalized Difference Snow Index (NDSI).

  Source:
  https://nsidc.org/data/mod10a1

Glacier and Terrain Context

• Himalayan glacier outlines and reference mapping from global glacier inventories and open geospatial data sources.

Basemap and Geographic Context

• Map imagery and geographic context derived from publicly available satellite imagery and GIS datasets.

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Methods

The project combines several analytical and design methods:

• Remote sensing interpretation using MODIS snow cover datasets
• Temporal comparison of satellite imagery across multiple years
• Spatial visualization through cartographic framing of the glacier system
• Interactive scrollytelling to guide readers through geographic and temporal change
• Comparative volumetric visualization to translate glacier mass loss into a more understandable physical scale

Satellite snow cover maps were processed and visually interpreted to distinguish persistent snow and ice from exposed land and vegetation using NDSI-based classification.

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Tools and Technologies

• SvelteKit for building the interactive web experience
• Static site deployment (Netlify)
• Satellite imagery and GIS processing
• Custom scroll-driven interaction and comparison slider

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https://gangotriglacier.netlify.app/

[Adithee]

The Veerappan Story - How the terrain was advantageous to him

Narrative Concept and Structure

My project explores the 20-year manhunt for India’s most famous outlaw, Veerappan. Instead of a standard true-crime recount, my narrative concept focuses on "The Geography of Neglect." I want to show how Veerappan evaded capture not just because the forest was thick, but because he weaponized bureaucratic loopholes, state borders, and socio-cultural isolation.

Narrative Structure

The story unfolds in several stages:

Establishing the Empire
The opening sections situate the manhunt within a massive 15,000 sq km expanse. Maps are used to establish the sheer physical scale of the terrain and the entangled two-state border of Karnataka and Tamil Nadu.

Locating the Loophole
The narrative zooms in from the macro-landscape to a micro-geographical anomaly: Gopinatham village. It highlights how the Cauvery River was used not just as a physical crossing, but as a jurisdictional wall.

Understanding Terrain Friction
Through geographic contrast, the story explains the logistical nightmare of the Special Task Force confined to paved roads, while the gang utilized ancient, unmapped elephant corridors to remain invisible.

Reflecting on the Human Cost
A deliberate break in the cartographic flow replaces maps with a solid typographic intermission. This section reflects on the socio-cultural vacuum and the tragic story of IFS officer P. Srinivas, proving the true battleground was the people, not just the forest.

The End Game Extraction
The experience transitions from static maps into archival video footage of Operation Cocoon, emphasizing that the 20-year manhunt could only end by luring the subject out of his protective ecosystem and onto an open road.

The Ecological Paradox
The story concludes using Global Forest Watch data to compare tree cover loss before and after his death, presenting the grim irony that his reign of terror inadvertently acted as a brutal conservation mechanism.

Datasets Used (Sources & Attribution)

State Boundaries (Karnataka & Tamil Nadu): OpenStreetMap data queried via Overpass Turbo. Extracted Admin Level 4 boundary relations to establish the rigid jurisdictional lines driving the narrative.

Forest & Protected Areas: OpenStreetMap data extracted directly within QGIS using the QuickOSM plugin. Queried (boundary protected area) across Erode and Chamarajanagar to map the exact polygons for the Sathyamangalam Tiger Reserve, Cauvery Wildlife Sanctuary, and Male Mahadeshwara (MM) Hills. ( https://www.globalforestwatch.org )

River Networks (The Loophole): QuickOSM was used to extract waterway shapefiles, specifically filtering for the Cauvery River to pinpoint Gopinatham village and illustrate the 100-meter jurisdictional wall Veerappan exploited.

Historical Forest Cover: Global Forest Watch. Utilized the "Tree Cover Loss" dataset, filtering for the years 2001–2004 to establish the "before" canopy baseline, and 2005–Present to visualize the ecological aftermath of his death.

Topography & Archival Video: Google Earth was used to navigate the terrain and record the specific video footage illustrating the geographical friction of the 27 hairpin bends at Dhimbham Ghat.

Tools & Technologies

Spatial Processing: QGIS (Vector styling, QuickOSM integration).
Data Extraction: Overpass Turbo, Global Forest Watch.
Frontend Development: Svelte framework, coded in VS Code, utilizing a custom scrollY math function to drive the interactive scrollytelling.
Deployment: Vercel.

Link to Article : https://veerappan-story-d1q7.vercel.app

[kriftsnitch]

Article : https://loader-trial-83680605.figma.site/

Borderline Hacks

1. Narrative Concept

"Borderline Hacks" is a cartographic investigation into the administrative enclaves of Baarle-Hertog and Baarle-Nassau. The project treats the town’s geography as a "Functional Operating System," where a 200-year-old administrative glitch—the 1832 Cadaster—acts as the foundational code for modern-day legal and economic "hacks."
By transitioning from historical parchment to modern vector data, the narrative visualizes Administrative Arbitrage: the practice of using geographical boundaries to bypass national regulations regarding trade, taxation, and personal movement.

2. Narrative Structure

The scrollytelling experience is divided into three thematic "movements" that mirror the evolution of the border:

I. The Blueprint (Historical Origin):
Visual: High-resolution 1832 Minuutplan scans (parchment/ink style).
Context: Establishing the 1832 "Communal Minute," where 5,732 parcels were hand-assigned a nationality, creating the original "jigsaw" DNA.

II. The Jigsaw (Codification):
Visual: Cross-fade from historical TIFF to modern vector linework.
Context: Visualizing the 1995 border settlement. This section highlights how the "Interruption" between border pillars 214 and 215 was finalized, turning historical brushstrokes into definitive digital law.

III. The Arbitrage (The Systematic Hack):
Visual: Interactive zoom into Enclave H1 and residential properties.
Context: Highlighting real-world arbitrage cases, such as the "Front Door Rule" (nationality determined by building entrance) and the "Sulphur Islands" (Belgian fireworks enclaves within the Netherlands).

3. Sources / Attribution

Allmaps Project — Observable: @allmaps/baarle (IIIF georeferencing)
Kaart van de Gemeente Baarle-Nassau — 19th-century cadastral survey
Dutch municipality boundaries — Boonstra (1812)
Treaty of Maastricht (1843) — Belgium-Netherlands boundary

4. Process

Krishnaraj A P | M. Des Information Design 24' | NID

[Mriinmoy-Design]

### Assam–Bhutan Flood Crisis

Article: (https://assamfloods.framer.website/)

Narrative Concept and Structure

This project explores the Assam–Bhutan flood crisis through a map-driven temporal narrative, focusing on how floods evolve across space and time rather than treating them as a static event.

The core idea is to shift the understanding of floods from a singular disaster moment to a dynamic, unfolding geographic process, where water spreads, intensifies, and recedes across districts. The map acts as the primary storytelling device, revealing patterns of inundation and movement.

Narrative Structure

The story unfolds in stages:

1. Locating the Region
   The narrative begins by situating the flood within the larger geography — introducing Assam, Bhutan, and the river systems that connect them.

2. Onset of Flooding
   Initial flood extents are visualized to show how the crisis begins, highlighting early affected regions.

3. Temporal Spread (24–29 June 2023)
   A progression of maps shows how the flood expands over time.
   Instead of a single snapshot, the narrative emphasizes day-by-day change, allowing viewers to observe patterns of spread and intensity.

4. Peak Impact
   The maps reveal the maximum flood extent, making visible the scale and concentration of the disaster across districts.

5. Reflection on Spatial Patterns
   The narrative concludes by encouraging a broader understanding of floods as recurring, spatial phenomena shaped by geography, upstream conditions, and river systems.

Datasets Used (Sources & Attribution)

Flood extent data (time-series): June 24–29, 2023

Geographic boundaries: Assam and surrounding regions

River systems and terrain context: publicly available geospatial datasets

(Note: datasets are visualized as temporal layers to highlight change over time.)

Methods

Temporal mapping of flood extent across multiple days

Spatial comparison to track expansion and concentration

Scrollytelling to guide users through chronological progression

Minimal visual layering to maintain focus on map-based storytelling

Tools and Technologies

Framer (for building the interactive narrative)

Map-based visualization workflows

Scroll-driven storytelling interactions

Reflection

This project uses maps not just as context but as the core narrative interface, allowing users to “see” the flood unfold rather than read about it.

By focusing on temporal change and spatial spread, the work highlights how disasters like floods are not isolated events but continuous geographic processes.

[Srvsh99]

Altitude as a Weapon

How geography determined the outcome of the Kargil War, 1999

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Narrative Concept

This project explores the Kargil War of 1999 not as a military timeline but as a geographic argument. Altitude was not the setting of this war. It was the weapon.

When Pakistani forces occupied the peaks of the Kargil-Drass sector in early 1999, they were exploiting physical laws no numerical superiority could immediately overcome. At 16,000 feet, lungs operate at 60 percent capacity, helicopter rotors lose efficiency, and jet aircraft cannot manoeuvre at combat angles. The Indian Army retook these positions fighting uphill in the most literal and physiological sense possible.

The narrative moves from the macro (the Kargil-Drass sector, the LoC as a fragile boundary through impossible terrain) to the micro (individual peaks and what it cost to retake them) and widens again to the nuclear consequences. The dark visual language and restrained typography are not decorative. They carry the weight of a war fought where supply helicopters could barely function.

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Narrative Structure

The Kargil-Drass Conflict Zone
The opening section situates the reader inside the landscape before any numbers appear. A terrain map on a dark basemap shows the LoC cutting across terrain that makes no concessions to human geometry. Only NH1 and the major towns are labelled, because it was Pakistani fire control over that single road that made the conflict as dangerous as it was.

The Landscape
Two anchor numbers: the elevation of the Drass valley floor and the altitude of the highest contested positions, shown as an elevation cross-section rather than bare figures. The cross-section was generated from SRTM 30m DEM data in QGIS along a transect toward Tiger Hill and rebuilt in Figma. Temperature data for Drass, one of the coldest inhabited places on earth, is layered alongside.

The Heights
Tiger Hill, Tololing, Point 4875, and the Batalik sub-sector mapped against an elevation profile. The argument is precise: a position at 5,000 metres with a direct line of sight to NH1 could interdict the only road supplying Leh. These positions were chosen for fire control geometry, and the maps are designed to make that logic visible.

The Asymmetry
The statistical centrepiece. Roughly 5,000 infiltrators holding entrenched high-ground positions against an Indian Army force of nearly 30,000. The visualisation encodes what that disparity actually meant: the numerically superior side was simultaneously fighting uphill, in thin air, with degraded intelligence in the opening weeks, and constrained from crossing the LoC.

The Cost of Altitude
250,000 shells, rockets, and bombs fired over 74 days. Around 5,000 shells per day at peak intensity from 300 guns. The IAF flew up to 7,631 sorties, the first sustained air campaign at this altitude in history. 527 Indian soldiers killed, 1,363 wounded. The section closes with Indian defence expenditure rising roughly 30 percent in the six years after the war.

Geography as Conclusion
Kargil was the first conventional war between two declared nuclear states. The restraint on both sides was not accidental. It was a mutually understood escalation ceiling. The most inhospitable terrain on the subcontinent became the most dangerous because the nuclear dimension meant the fighting had to stay inside those mountains.

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Datasets Used

SRTM 30m Digital Elevation Model (NASA/USGS)
Terrain relief, hillshade, contours, and elevation cross-section transect in QGIS.
https://earthexplorer.usgs.gov

OpenStreetMap via Overpass Turbo
Admin boundaries for Kargil and Drass tehsils, NH1 road network.
https://overpass-turbo.eu

RAND Corporation Report MR-1450: Limited Conflicts Under the Nuclear Umbrella
Tellis, Fair, Medby (2001). Force size estimates, casualty data, and nuclear escalation analysis.
https://www.rand.org/pubs/monograph_reports/MR1450.html

GlobalSecurity.org: 1999 Kargil Conflict
IAF sortie counts, artillery shell rates, and operational tempo figures.
https://www.globalsecurity.org/military/world/war/kargil-99.htm

SIPRI Military Expenditure Database
India defence spending 1995 to 2006 in constant USD, used for the post-Kargil expenditure chart.
https://www.sipri.org/databases/milex

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Tools and Technologies

QGIS for DEM processing, hillshade, contour extraction, and elevation transects.

Mapbox Studio for the dark basemap and terrain layer.

Figma (Figma Make) for the interactive narrative, scroll-driven layout, and all data visualisation.

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Link to Article

https://www.figma.com/make/RtzKd9rmlkRJY55fQRe59J/Cartography-Narrative?fullscreen=1&t=dKfZjDja8cLzZLlm-1

[gunhachan]

Your Cat's Legacy of World Domination - Their journey from 25 million years ago to our living rooms.

By Hari Chandana G.

Link: https://gunhachan.github.io/cat-evol-scrolly/

Data and process

• Fossil Coordinates: Occurrence data for key fossil discoveries (extracted from the Paleobiology Database / GBIF) were used to plot geographic anchor points.

• Base Maps: Natural Earth
• Pacific-Centered Projection: To prevent the Bering Land Bridge from being split across the map, the vector data was translated by an X-offset of 360 degrees in QGIS to allow for a custom Pacific-centered Robinson projection without clipping the Americas.
• Export: The prepared map layers and geographically accurate fossil markers were exported from QGIS as layered SVG files, which were then decorated on Figma.

Narrative structure

• The story follows a chronological order with some overlaps.
• A limited number of key species were chosen to be characters to follow that had interesting or unexpected stories.
• Other facts that are interesting but not a part of the main narrative are included separately.

Design and aesthetics

• The style evolved from a more vintage/classic look to a cuter, clean aesthetic
• Icons used are from The Noun Project

Planned improvements

• Working on making a more interactive website with more motion and an embedded map and tooltips for the markers.

[neharika-2315]

The Memory of Water -

The relationship between urban flooding & wetland erasure in a visual investigation. How India’s urban rise has systematically dismantled the natural hydrology of its major cities, turning sponges into concrete, that traps water within.

View Here: https://neharika-2315.github.io/cartography-/
(work in progress)

1. Narrative Concept and Structure

A journey through the "memory" of the land and water that reveals how while we can build over a lake, we cannot erase its topography. This reveals the reason behind most urban floods today, that these areas used to be wetlands of some sort once, and hence there is nowhere for rainwater to go

The Structure

• Introduction to wetlands of India
• Ramasar sites and their impact
• Flood prone cities and which cities actually Flood
• Case study of urban metros such as Bangalore, Chennai, etc

All supported by required maps

2. Data Sets and Data Used

• https://indianwetlands.in
• Open Street Map
• data.gov.in
• National Archives of India
• VEDAS (ISRO)
• Bhuvan (NRSC)

3. Technical Platform & Tools

Data Processing: QGIS (for cleaning shapefiles and raster clipping).
Narrative: HTML,CSS,JS developed in VSCode, Deploymed: GitHub Pages
Design Process and Research: Figma / FigJam
Base Map Styles: QGIS (Vector Styles, Custom Maps, Buffer Zones, editing in attributes, etc.)

4. Things to Do:

• Refine and detail out maps to act as a guide to the narrative
• Add city case studies
• Edit narrative structure and design

[Aakash1907]

TITAN — A Narrative Cartography

Link to the article (https://aakash1907.github.io/Titanmap/)

A scroll-driven interactive story of the OceanGate Titan submersible disaster, June 18, 2023.

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What This Project Explores

This project is a narrative cartography — a form of storytelling that uses geographic and spatial data as its primary medium. It traces the final journey of the OceanGate Titan submersible from departure to confirmed loss, using scroll-driven interaction, cinematic animation, and live cartographic data to place the reader inside the event as it unfolded.

The project asks a specific question: can cartography carry human tragedy? Can coordinates, depth readings, and a search perimeter communicate grief, scale, and consequence more powerfully than text alone?

It explores:

• The geography of the expedition — from St. John's Harbour, Newfoundland, across 700 km of open North Atlantic to the Titanic wreck site at 41°44′N 49°56′W
• The spatial scale of the search and rescue operation — 26,000 km² of ocean, comparable in area to the country of Wales
• The physics of what happened at 3,800 metres depth — pressure, material science, and catastrophic implosion
• The human dimension — five individuals, their backgrounds, and the four days the world waited

The work sits at the intersection of cartographic design, interactive journalism, and digital memorialisation.

The video used here is a placeholder, will be replaced by another (rendering in process)

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Project Structure

titan-cartography

Opens with the Event - Shows the tragedy to the viewers. 
About Stockton Rush and Ocean gate - Mission, Vision and History.
The Crew of Dive 88
Map Section showing their start location, path and drop point. Followed by the search area and its gravity.
Timeline of the disaster and how o2 meter was a beacon of hope for days.
Interactive section. - the Game 
Answering why it imploded.
Ending Note - emphasising on the level of uncertainty and unpredictability.

Sections of the site

Section	Description
Intro	Full-screen title with Begin Descent CTA
Cutscene	Scroll-scrubbed video with live depth meter and sea creature markers by depth zone
OceanGate History	Who was Stockton Rush, founding timeline, expedition data
Dive 88	Scroll-zoom typographic sequence — zooming into the number 88
Crew	Five crew members with portraits and biographical descriptions
Map	Mapbox globe — St. John's → animated route → Titanic wreck → search perimeter → Wales overlay
Typewriter	Dark gradient section with typewritten text reveal
Timeline	Full-page horizontal scroll takeover — four days of events with O₂ depletion meter
How Fast	Implosion physics + interactive reaction-time fish game
Science	Carbon fibre and pressure science explanation with diagram placeholders
Ending	Closing note (placeholder for final text)

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Methods and Tools

Design & Prototyping

• Figma — wireframing, layout prototyping, and visual direction

Development

• HTML5, CSS3, JavaScript (Vanilla) — fully hand-coded, no frameworks
• VS Code — primary code editor
• FFmpeg — video conversion and optimisation for web scroll-scrubbing (H.264, -movflags faststart, 30fps cap)

Mapping

• Mapbox GL JS v3.3 — interactive globe, satellite basemap, animated route line, search perimeter, custom fog and atmosphere settings
• Mapbox Studio — custom map styles

AI Assistance

• Claude (Anthropic) — code generation, structural logic, scroll interaction systems, embedded game
• ChatGPT (OpenAI) — research synthesis, content drafting

Version Control & Hosting

• Git — version control
• GitHub / GitHub Pages — repository hosting and free static site deployment

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Data Sources

All data used in this project is derived from publicly available sources. No proprietary datasets were used.

Source	What was used
BBC News	Timeline of events, search operation reporting, crew information
The New York Times	Expedition background, OceanGate company history, search coverage
Wikipedia	Coordinates of the Titanic wreck site, OceanGate submersible specifications, crew biographical details
OceanGate company records	Dive history (87 prior dives), submersible specifications, mission descriptions (via archived public materials)
Mapbox	Satellite basemap tiles, globe projection
US Coast Guard (public statements)	Search zone size (~26,000 km²), timeline of official notifications, debris field discovery

Key coordinates used

Location	Latitude	Longitude
St. John's Harbour (departure)	47.5615° N	52.7126° W
Titanic wreck site	41.7344° N	49.9424° W
Titan last known position	~41.7° N	~49.9° W

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This project was produced as part of a Cartography Course. It responds to the brief of narrative cartography — using spatial data and geographic methods to tell a story that is not primarily about place, but in which place is inseparable from meaning.

The North Atlantic is not incidental to this story. The distance from shore, the depth of water, the size of the search area — these are not background details. They are the story.

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Acknowledgements

In memory of Stockton Rush, Paul-Henri Nargeolet, Hamish Harding, Shahzada Dawood, and Suleman Dawood.

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Built with HTML, CSS, JavaScript, and Mapbox GL JS · Hosted on GitHub Pages

[kush-a26]

Project Progress
Narrative Concept & Structure
This project is a long-form narrative cartography piece titled The Startup Mirage — an investigation into the geographic inequality of India's startup funding ecosystem, built around the central question: did Startup India's promise of a nationwide entrepreneurship revolution actually reach everyone?
The narrative follows five chapters:

The Promise — Modi's 2016 Startup India launch and 3,12,866 registered startups
The Collapse — animated counter dropping from 3,12,866 to 708 (the number that received any investor backing)
The Corridor — Karnataka, Maharashtra and Tamil Nadu dominating VC funding
The Human Stories — three real unfunded startups from Nagaland, Bihar and Rajasthan
The Government's Reach — public funding compared against private capital

Datasets Used

YNOS Venture Engine (ynos.in) — primary dataset. State-level startup counts retrieved via API using filters: "All VC Funded", "All Angel Funded", "All Govt. Funded". Accessed March 2025. Subscription-based access.
Datameet India Maps (github.com/datameet/maps) — India state boundary GeoJSON used for choropleth mapping
DPIIT / Startup India — total registered startup count (3,12,866) cross-referenced with official government records
Mapbox GL JS v3.3.0 — map rendering and scrollytelling transitions
YNOS public startup profiles — Bauaok Private Limited (Nagaland), SciGlyph Exploration (Bihar), Contree (Rajasthan)

Tools & Technology
Built as a single-file HTML scrollytelling experience using Mapbox GL JS for map rendering, vanilla JavaScript for scroll-driven chapter transitions and the animated funding counter, and Georgia/Helvetica Neue typography following long-read editorial conventions.

Final Narrative Cartography Project

🔗 Live Project: https://kush-a26.github.io/startup-mirage/

Format: Published webpage — long-form scrollytelling experience
Map as central element: The map drives every chapter transition. As the reader scrolls, the map zooms into specific states, changes colour layers between registered vs VC-funded vs government-funded startups, and isolates individual states (Nagaland, Bihar, Rajasthan) to tell human stories at a geographic scale.
Key findings visualised:

3,12,866 registered startups → only 708 received any investor backing (0.23%)
Karnataka's VC conversion rate (7.28%) vs Bihar's (0.18%) — a 40× gap
8 states and union territories have zero VC-funded startups
Government funding is more geographically distributed but does not produce scaling capital

Dataset credits: YNOS Venture Engine · Datameet India Maps · DPIIT Startup India · Mapbox GL JS

[ShreyaDan]

The Aravallis, Redefined

A geospatial analysis of how definitions reshape India’s oldest mountain range

For some reason the link is not opening. Copy ther link and open in a new window. : (
Project link: https://cartopraphynarrative.framer.website/

Narrative
The Aravalli range is one of the world’s oldest mountain systems, stretching across western and northern India. Unlike dramatic mountain chains, it appears as a low and fragmented landscape, often blending into plains, cities and industrial areas. Beneath this terrain lies significant mineral wealth. For decades, the Aravallis have supported mining of marble, granite, limestone and metals that feed construction and industry. Even though the range is geologically continuous, it is not mapped the same way everywhere. Geological, forest and revenue maps each define the landscape differently.

In recent years, court-led efforts have introduced measurable criteria like elevation and land records to identify the Aravallis. When these are applied, the mapped extent begins to shift. These changes do not just redraw boundaries. They affect where mining is restricted and where it can continue.

This project looks at how the same landscape can appear differently depending on how it is defined, and how those definitions shape both protection and extraction.

The Aim

• To understand the exact location of the range
• To examine how definitions shape landscapes on official maps
• To compare geological continuity with administrative classification
• To visualise the impact of elevation thresholds and land records
• To map the relationship between Aravalli boundaries and mining activity

How the map works here
The map functions as a comparative and interactive tool rather than a static representation. It allows users to toggle between different layers, including:

• Geological extent of the Aravallis
• Forest cover and protected areas
• Revenue land classifications
• Elevation-based thresholds
• Mining locations and lease areas

figjam: https://www.figma.com/board/gMgmlnazCGhJ4WJqDF1jpa/Interactive-Cartography?node-id=0-1&t=PyjtNsjR1dZn6KyS-1
mapbox url : mapbox://styles/shreyadan06/cmkfeyfd8000j01sg3ctk9s9n

References:
https://www.downtoearth.org.in/environment/nearly-50-per-cent-of-aravallis-to-become-vulnerable-to-mining-if-new-definition-is-applied-dte-analysis
https://studyhub.net.in/geology/aravalli-craton-aravalli-supergroup/
https://indianexpress.com/article/legal-news/supreme-court-accepted-govts-100-m-aravalli-rule-its-own-panel-had-opposed-it-10435665/
https://imgs.mongabay.com/wp-content/uploads/sites/30/2019/10/18024637/Aravallis-Report-WII-May-2017-1-min_compressed.pdf
https://sankala.org/the-aravallis-a-fading-green-legacy-amidst-urbanization/
https://moef.gov.in/uploads/pdf-uploads/pdf_682f0a92983b08Wall.pdf
https://www.researchgate.net/figure/Change-analysis-of-Aravalli-Landscape-Gurgaon-Faridabad-and-Mewat-during-1996-2018_fig5_342428445
https://www.researchgate.net/figure/Field-visit-photographs-of-the-different-classes-of-Aravalli-of-the-year-2019_fig5_357579017
https://www.researchgate.net/figure/Priority-Conservation-Areas-for-Aravallis-Haryana-India_fig4_327387799

https://fsi.nic.in/forest-report
https://www.naturalearthdata.com/

[sambit571]

Migration towards life

Every winter, thousands of migratory birds travel from breeding grounds in Siberia and northern Russia along the Central Asian Flyway to Chilika Lake. As wetlands freeze and food declines, they move south to this brackish lagoon, which offers abundant fish, crustaceans, and safe roosting habitats between November and February.

Narrative
Winter in the North

Migration for survival.
Central Asia, Siberia, Mongolia, Tibetan Plateau
Monthly temperature drop (Oct–Dec)
Snow cover extent
Wetland freeze
Map expression
Time-slider map: temperature falling below survival thresholds
Wetlands turning unavailable (frozen/covered)

Direction to south

India is warm as compared to north
Data layers
Global flyways Central Asian Flyway
Mountain barriers like Himalayas
Map expression
Flow lines narrowing into India like a funnel
Himalayas shown as a deflection wall, not a crossing

Why Chilika Lake

Selection criteria
Surface area: ~1,165 km² (seasonally varying)
Salinity gradient (fresh → brackish → saline)
Fish biomass & benthic organisms
Shallow water depth
Historical wetland persistence
Data layers
Wetland size comparison (India’s major wetlands)
Salinity zones
Productivity indices (chlorophyll proxy)
Ramsar sites overlay
Map expression
Chilika glowing as a high-fitness node
Other wetlands shown as partial/seasonal failures

Data layers
Stopover wetlands (Central Asia, Iran, Pakistan)
Distance between refueling points
Mortality risk zones
Wind assistance corridors
Map expression
Line thickness reducing (attrition)
Pulsing nodes at stopovers
Broken/dotted lines where wetlands have vanished

Seasonal at Chilika

Data layers
Monthly bird counts (Nov–Feb peak)
Species diversity vs month
Feeding zone density inside the lake
Map expression
Density heatmap over Chilika
Species icons appearing over time

Future

Migration is a system, not an event.
Data layers
Climate projections (wetland salinity, water levels)
Loss of stopover wetlands
Trend lines of bird counts
Map expression
Scenario maps: stable, degraded, and collapse
Broken flyway futures

Project link - https://www.figma.com/design/Lixc4qgKt3BlSSJgrOXRRx/narrative-carto?node-id=282-2&t=RWbScaKyWbc21hmV-1

Reference

697.pdf
172454-415871-1-PBMigrationofbirdspublished.pdf
1702028722PJZ_MH20230724085011-R2_Rasooletal.pdf
atlasmovementofswsiberianwb.pdf
ChilikabookChapter.pdf
chilka.pdf
Guidebook_MBP_map_July_2021.pdf
ijeditor1,+article+3+(1).pdf
IWSS Migratory Bird Profiles.pdf
s12594-023-2324-y.pdf
WetlandsinRussia_Vol_4_English.pdf

[Oin-ok]

### Narrative Concept & Structure

Project Title:
India’s Waste Geography: Where Does Your Garbage Go?

Core Idea:
This project explores the hidden journey of urban waste in India, tracing how garbage moves from spaces of consumption to peripheral dumping grounds. It frames waste not as disappearance, but as spatial displacement, revealing unequal geographies of burden.

Narrative Arc (Scroll-based):

Introduction — Disappearance Illusion
Waste leaves homes, but not the system.

National Overview — Where Waste Accumulates
Key landfill cities across India

Zoom-In — City-Level Systems
Focus on major urban nodes (Delhi, Mumbai, Chennai, etc.)

Landfill Scale — How Big Is This Problem?
Area-based comparison using proportional symbols

Peripheral Impact — Who Lives Nearby?
Edges of cities as sacrifice zones

Conclusion — Rethinking Responsibility
What if waste never left your neighborhood?

Evolving Map (Process Notes)
Stage 1 — Base Mapping

• Imported landfill dataset (CSV) into QGIS and Mapbox
• Plotted landfill locations using latitude–longitude
• Verified positions using satellite imagery

Stage 2 — Symbolisation

• Implemented proportional circle scaling using landfill area (hectares)
• Ensured visual hierarchy: larger dumps appear dominant

Stage 3 — State-Level Understanding

• Identified states with landfill presence
• Highlighted concentration in major urban-industrial regions

Stage 4 — Mapbox Integration

• Uploaded dataset as tileset
• Styled using data-driven expressions for circle radius
• Added interactive globe map to zoom in to each marked landfields

Stage 5 — Narrative Structuring

• Transitioned from static mapping → scroll-based storytelling
• Designed zoom transitions (India → City → Landfill)

Datasets Used

1. Landfill Locations Dataset (Primary)

Source: Compiled from:

• Central Pollution Control Board (CPCB)
• Municipal corporations (Delhi, Mumbai, Chennai, etc.)
• Google earth https://earth.google.com/web/search/Ghazipur+landfill,+Ghazipur+Dairy+Farm,+Ghazipur,+New+Delhi,+Delhi/@28.62499359,77.3285885,233.24415644a,2268.2477628d,35y,359.99997977h,0t,0r/data=Cj4iJgokCQ6n4JdZoTxAEX8Y4-2UnjxAGet7bAOZVVNAIQSY0g9WVFNAKhAIARIKMjAyMi0wMi0xNRgBQgIIAToDCgEwQgIIAEoICKOx8dcDEAA

Attributes:

• City
• Landfill name
• Latitude / Longitude
• Area (hectares)

2. Base Map & Geography

Source: Mapbox (OpenStreetMap-based tiles)

Used for:

• National and city-level basemap
• Road and spatial context

3. Satellite Verification

Sources:

• United States Geological Survey (Landsat)
• Google Earth

Used to:

Validate landfill locations
Understand spatial extent and surroundings

Process & Ideation:

https://www.figma.com/design/Pqt8iY9RVVzoRrCyiuwt8R/Cartography_Linkedin?node-id=169-178&t=2CpMw0CVALasuWaw-1

WIP Narrative Cartography:
https://gazipur-landfield.framer.website/

Note: I am still exploring how to present the narrative flow in one go. Understood and learned a lot about Mapbox and QGIS. I look forward to exploring more and adding to the final update.

[navya-geo]

The Ship That Stopped The World

A Narrative Cartography of the Suez Canal Blockage

Article Link: View the Story

Project Overview

This project presents the 2021 blockage of the Suez Canal as a narrative cartographic experience.
Rather than documenting the incident, the project explores how a highly optimized global trade system reveals its fragility when disrupted.

The narrative unfolds through scroll-based interaction, where spatial scale, movement, and density are used to communicate:

Global dependence on narrow infrastructures
The mismatch between system scale and physical constraints
The cascading effects of localized failure.

Instead of just reading about the event, the user is guided through the geographic and economic scale of the disaster, watching the data and map update dynamically as they scroll through the narrative.

Narrative Structure

The story goes as a spatial narrative that moves from impact → context → cause → consequence, using map transitions to guide understanding.

1. Disruption (Cold Open)
   The narrative begins with a tight view of the Suez Canal, where the Ever Given is shown lodged across the canal.
   The viewer is immediately presented with the problem, without explanation.

2. Global Context
   The map zooms out to reveal global shipping routes, showing how the canal functions as a critical shortcut in world trade.
   The incident is reframed as part of a larger system.

3. Structural Vulnerability
   The narrative returns to the canal, focusing on its narrow dimensions and the volume of trade passing through it.
   This establishes the canal as a bottleneck within a global network.

4. Scale Mismatch
   The size of the ship is introduced through comparison, highlighting the tension between the scale of modern vessels and the capacity of the canal.

5. The Incident
   The grounding of the ship is explained through a brief reconstruction, connecting environmental conditions and spatial constraints.

6. Accumulation
   Ships begin to appear at both ends of the canal, increasing day by day.
   The passage of time is visualized through growing spatial density.

7. Systemic Impact
   The map zooms out again to show rerouted global trade and extended routes around Africa, illustrating how a local disruption affects global movement.

8. Reflection
   The narrative concludes by highlighting other global chokepoints, suggesting that similar vulnerabilities exist elsewhere.

summary

HOOK → Scale of the incident (before explanation)
CONTEXT → Why this waterway controls everything
JOURNEY → Eight days of calm before the rupture
INCIDENT → The moment + the cargo it trapped
CONSEQUENCES → Four days of mounting damage + rescue + economic fallout
AFTERMATH → Resolution of this specific incident
BIGGER PICTURE→ This was one of six. And they're all at risk.
CLOSING → Systemic fragility. No plan B.

Tools & Technologies

Structure & Styling: HTML5, CSS3 (VSCode)
Logic & Interactivity: Vanilla JavaScript
Mapping Engine: Mapbox GL JS (using flyTo camera animations, 3D models, and dynamic styling)
Data Formats: GeoJSON (for shipping lanes, the canal boundaries, fleet locations, and global chokepoints), GLB- Evergiven 3d model
Data Sources:
Global Shipping Lanes -https://www.kaggle.com/datasets/sndorburian/shipping-lanes-geojson?resource=download/ https://www.arcgis.com/home/item.html?id=8e0fc0ad8abe4955885e1f6041b9de32
The Suez Canal route as a linestring - Draw my own on in mapbox tracing the canal from Port Said to Port Suez and created a geojson file
Ship route coordinates (Malaysia → Suez) - Hard-coded lat/long from geographic reference
Waiting fleet positions - Satellite Imageries
Chokepoint coordinates (6 straits)- Hard-coded lat/long from geographic reference

Other sources referred:
BBC / Reuters / AP — General incident reporting, sandstorm conditions, 74 km/h wind speed, timeline of events
Wikipedia, US Energy Information Administration (EIA), Bloomberg
IMF / World Bank — General trade dependency figures
Natural Earth / OpenStreetMap — Geographic coordinates for chokepoints, canal dimensions
https://globalmaritimetraffic.org/gmtds-data.html
https://www.arcgis.com/home/item.html?id=b76d6f8bd668410e897a6570fdf392c5
https://en.wikipedia.org/wiki/2021_Suez_Canal_obstruction
https://www.nytimes.com/2021/07/17/world/middleeast/suez-canal-stuck-ship-ever-given.html

[Shravaniii1508]

Footsteps To Vitthal

Narrative and structure:

1. Started with explaining walking pilgrimage places in India (tours done annually on a fixed timeline)
2. Interactive map regarding the same
3. Information about the pandharpur wari and its existence
4. Cartographic journey explanation of the route and activities
5. Conclusion

Tools used
Mapbox, codepen, mapy, github, vev, figma, google earth, adobe premiere pro

Published link to the article
https://a-shravanis.vev.site/wari

If the link expires, here is the screen record
https://drive.google.com/drive/folders/1ky2u368ezK5OoQ5i43cnNHuuCgPs-5-k?usp=sharing

What is left to do

1. Design improvements 

2. Information refinement in cartographic journey section
3. Add conclusion and sources in the article

Screenshots of interactive informative map of indian walking pilgrimage tours

Screenshots for showing cartographic journey to pandharpur - mapy and codepen

Sources

• Wikipedia – Pandharpur Wari history

[https://en.wikipedia.org/wiki/Pandharpur_Wari](url)

• Sahapedia – Vitthal and Pandharpur tradition
  [https://www.sahapedia.org/pandharpur-wari-pilgrimage-saints-sandals-and-salvation](url)

• Britannica – Vithoba deity
  https://www.britannica.com/topic/Vithoba

• Maharashtra Tourism – Pandharpur
  https://www.maharashtratourism.gov.in/-/pandharpur

• Uttar Pradesh Tourism, Braj Bhoomi Parikrama overview
  https://uptourism.gov.in/pdf/E-Brochure/Brajbhoomi.pdf

• Cultural documentation on Braj Parikrama traditions
  https://www.sahapedia.org/braj-mandal-parikrama

• Sabarimala official route and pilgrimage details
  https://www.sabarimala.com/trek-routes.html

• Kerala Tourism overview of the pilgrimage season
  https://www.keralatourism.org/sabarimala/pilgrimage-season

• Gujarat Tourism and regional coverage
  https://www.gujarattourism.com/saurashtra/junagadh/girnar.html

• Media reports on Girnar Lili Parikrama participation
  https://indianexpress.com/article/india/girnar-lili-parikrama-6426458/

• Government of Maharashtra Wari documentation
  https://mahadma.maharashtra.gov.in/en/pandharichi-wari/

• http://timesofindia.indiatimes.com/articleshow/122328079.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst

• https://timesofindia.indiatimes.com/city/kolhapur/over-27l-warkaris-visit-pandharpur-for-ashadi-ekadashi/articleshow/122328079.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst

• https://www.hindustantimes.com/cities/pune-news/recordbreaking-ashadhi-wari-ai-powered-drones-count-over-27-lakh-devotees-101752000053098.html

[pratyushr58]

The Blocked River

Disruption of Hilsa Migration in the Ganga River System

Project Overview

This project examines how disruptions in the Ganga river system have altered the natural migration of the Hilsa fish. Using maps, it traces how barriers and changing river conditions have shortened this movement, reshaping access and distribution within India.

Narrative Structure

The story follows a sequential, map-driven structure:

• Context – Establishing the natural migration system (sea → river → upstream)
• Before – Historical extent of Hilsa migration into inland India
• Turning Point – Physical interruption at the Farakka Barrage
• Impact – Uneven outcomes along the river (upstream decline, downstream concentration)
• Environmental Change – Salinity intrusion affecting breeding conditions
• Comparison – Hooghly vs Meghna systems showing differing river conditions
• Redistribution – Shift in Hilsa availability across regions
• Substitution – Transition from river-based movement to transport-based supply
• Conclusion – Hilsa as an indicator of fragmented river systems

Process, Storyboard and References : https://www.figma.com/design/wk30YYKbN3ej8HZMADsDs6/Narrative-Cartography?node-id=1-4&t=YqLBXc89xV5FH45T-1

Project Link: https://pratyushr58.github.io/NarrativeCartography/

Current Status

Narrative and storyboard finalized
Map sequence defined
Initial visual structure implemented as a long-form webpage

Next Steps

Refine individual maps for stronger visual clarity
Strengthen key transitions across different frames
Finalize annotations and narrative text for each section