u/Ok-Jello7724

Have you ever wanted to do something but ended up not doing it just because you were worried about what people would say?

I feel like a lot of us grew up hearing "3eib, nas hatgool shنو?" whenever we wanted to do something that didn't fit society's expectations.

And honestly, that shit gets to you over time.

You start overthinking everything, holding yourself back, and making choices based on how people might see you instead of what you actually want. Before you know it, you're living your life trying to keep everyone else happy, even if it means being unhappy yourself.

The funny thing is, people will talk either way. You could do everything the way they expect you to, and they'd still find something to say.

So why do we let their opinions have so much control over our lives?

Have you ever given up on something you really wanted because of your family or fear of being judged? Or do you think caring about what people say is sometimes necessary?

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Hi everyone,

I am working on my Geomatics Engineering capstone project focusing on post-conflict urban assessment and infrastructure recovery within a core 1.42 km² study area in Khartoum CBD, Sudan.

My initial spatial baseline is defined approximately by:

- Study Area: Khartoum CBD, bounded by Al-Jamhuriya St, Al-Mek Nimr / Al-Jaish Ave, the railway area near Souq Al-Arabi, and Al-Qasr Ave.

- Target CRS: EPSG:32636 (WGS 84 / UTM Zone 36N)

- Main features: Buildings, roads, land use, and other relevant urban infrastructure.

Rather than manually digitizing the baseline data, I would like to develop a reproducible and semi-automated QGIS workflow for data acquisition and preparation.

I would particularly appreciate advice on:

1. Data acquisition: What are the most reliable plugins or direct services (WFS/WCS/QuickOSM, etc.) for obtaining building footprints, road networks, land-use/land-cover, and other urban infrastructure data for this specific area?

2. Data organization: What is the recommended way to structure these datasets into a clean GIS database/geopackage while maintaining consistent CRS, attributes, topology, and metadata?

3. Remote sensing integration: What workflow would you recommend for preparing this baseline for multi-temporal satellite imagery, change detection, and building/infrastructure damage assessment?

4. Reproducibility: Are there recommended QGIS processing models, Python scripts, or plugins that could automate part of this workflow and make it easier to update when new imagery or datasets become available?

I am especially interested in approaches that are practical for a relatively small urban study area and can be implemented using QGIS and open/free data sources where possible.

Any recommendations for datasets, plugins, workflows, or common pitfalls would be greatly appreciated.

Thanks in advance!

\​

Hi everyone!

I’m a final-year Geomatics/Surveying Engineering student currently trying to decide on a graduation project. I’m mainly interested in GIS and Remote Sensing, and I’d like to work on something that is both technically meaningful and useful beyond just being an academic project.

Some areas I’m considering are:

\\- Environmental & climate monitoring — rainfall variability using datasets such as ERA5, dust storms, or land/surface deformation.

\\- Hydrology & hazard assessment — flood mapping using satellite imagery, NDWI, DEMs, or spatial databases.

\\- Urban & infrastructure mapping — LULC change detection, updating existing maps, or using ML/DL for feature extraction.

I’m also interested in combining Google Earth Engine, Python, GIS, and machine learning where appropriate.

For those working or studying in GIS, Remote Sensing, or Geomatics:

If you were starting your final-year project today, what kind of project would you choose?

Are there any datasets, workflows, or current industry/research trends that you think would be particularly valuable to learn?

I’m especially interested in ideas that can demonstrate practical skills and potentially make a good portfolio project—not just something that produces a map at the end.

Any suggestions, project ideas, or criticism of the areas I’m considering would be greatly appreciated!

Thanks!

​

Hi everyone,

I’m a final-year Geomatics/Surveying Engineering student planning a capstone project on post-war urban reconstruction and resilient infrastructure in Khartoum, Sudan.

I’m considering two approaches:

Option A — 3D City Modeling + BIM/GIS

\- Extract buildings from satellite/aerial imagery using ML/DL (e.g., U-Net)

\- Create a LoD1/LoD2 3D city model

\- Integrate GIS with Civil 3D/BIM

\- Develop a framework for reconstructing underground utilities and drainage

Option B — SAR + Hydrology + BIM/GIS

\- Use Sentinel-1 SAR for flood/surface-change detection

\- Combine DEMs and rainfall data for hydrological/runoff modeling

\- Identify flood-prone areas and surface-water accumulation

\- Use the results to plan conceptual drainage corridors in Civil 3D

My questions:

1. Which option has stronger academic and professional value?

2. Is Option B too ambitious for an undergraduate project, or should I focus deeply on one pipeline?

3. What free/open datasets would you recommend (Sentinel, GEE, ERA5, DEMs, OSM, etc.) given the difficulty of field validation?

4. What would be a good way to include ML/DL without turning the project into an AI project?

I’d especially appreciate advice from professionals/researchers in GIS, remote sensing, surveying, hydrology, BIM, or post-disaster reconstruction.

My goal is to produce something technically realistic that could contribute to future reconstruction efforts in Sudan.

Thank you!

​

Hi everyone,

I’m a final-year Geomatics/Surveying Engineering student planning a capstone project on post-war urban reconstruction and resilient infrastructure in Khartoum, Sudan.

I’m considering two approaches:

Option A — 3D City Modeling + BIM/GIS

\- Extract buildings from satellite/aerial imagery using ML/DL (e.g., U-Net)

\- Create a LoD1/LoD2 3D city model

\- Integrate GIS with Civil 3D/BIM

\- Develop a framework for reconstructing underground utilities and drainage

Option B — SAR + Hydrology + BIM/GIS

\- Use Sentinel-1 SAR for flood/surface-change detection

\- Combine DEMs and rainfall data for hydrological/runoff modeling

\- Identify flood-prone areas and surface-water accumulation

\- Use the results to plan conceptual drainage corridors in Civil 3D

My questions:

1. Which option has stronger academic and professional value?

2. Is Option B too ambitious for an undergraduate project, or should I focus deeply on one pipeline?

3. What free/open datasets would you recommend (Sentinel, GEE, ERA5, DEMs, OSM, etc.) given the difficulty of field validation?

4. What would be a good way to include ML/DL without turning the project into an AI project?

I’d especially appreciate advice from professionals/researchers in GIS, remote sensing, surveying, hydrology, BIM, or post-disaster reconstruction.

My goal is to produce something technically realistic that could contribute to future reconstruction efforts in Sudan.

Thank you!

​

Hi everyone!

I’m a final-year Geomatics/Surveying Engineering student currently trying to decide on a graduation project. I’m mainly interested in GIS and Remote Sensing, and I’d like to work on something that is both technically meaningful and useful beyond just being an academic project.

Some areas I’m considering are:

\- Environmental & climate monitoring — rainfall variability using datasets such as ERA5, dust storms, or land/surface deformation.

\- Hydrology & hazard assessment — flood mapping using satellite imagery, NDWI, DEMs, or spatial databases.

\- Urban & infrastructure mapping — LULC change detection, updating existing maps, or using ML/DL for feature extraction.

I’m also interested in combining Google Earth Engine, Python, GIS, and machine learning where appropriate.

For those working or studying in GIS, Remote Sensing, or Geomatics:

If you were starting your final-year project today, what kind of project would you choose?

Are there any datasets, workflows, or current industry/research trends that you think would be particularly valuable to learn?

I’m especially interested in ideas that can demonstrate practical skills and potentially make a good portfolio project—not just something that produces a map at the end.

Any suggestions, project ideas, or criticism of the areas I’m considering would be greatly appreciated!

Thanks!

​

Hi everyone!

I’m a final-year Geomatics/Surveying Engineering student currently trying to decide on a graduation project. I’m mainly interested in GIS and Remote Sensing, and I’d like to work on something that is both technically meaningful and useful beyond just being an academic project.

Some areas I’m considering are:

\- Environmental & climate monitoring — rainfall variability using datasets such as ERA5, dust storms, or land/surface deformation.

\- Hydrology & hazard assessment — flood mapping using satellite imagery, NDWI, DEMs, or spatial databases.

\- Urban & infrastructure mapping — LULC change detection, updating existing maps, or using ML/DL for feature extraction.

I’m also interested in combining Google Earth Engine, Python, GIS, and machine learning where appropriate.

For those working or studying in GIS, Remote Sensing, or Geomatics:

If you were starting your final-year project today, what kind of project would you choose?

Are there any datasets, workflows, or current industry/research trends that you think would be particularly valuable to learn?

I’m especially interested in ideas that can demonstrate practical skills and potentially make a good portfolio project—not just something that produces a map at the end.

Any suggestions, project ideas, or criticism of the areas I’m considering would be greatly appreciated!

Thanks!

​

For me, Kendrick Lamar is probably the best lyricist ever, and I don't think it's just because he can rap well.

The thing with Kendrick is that you can listen to a song 10 times and still catch something you missed before. His lyrics have so many layers — wordplay, storytelling, different perspectives, symbolism, social commentary, personal shit… and somehow he puts all of that together without making it feel forced.

What really gets me is how he can tell a whole story through a song. He'll switch perspectives, change his voice, change his flow, and suddenly you're looking at the whole situation from a completely different angle.

good kid, m.A.A.d city, To Pimp a Butterfly, and DAMN. are probably the biggest examples of this. You can literally find people still analyzing those albums years later and coming up with interpretations you never even thought about.

And honestly, I think his delivery is a huge part of his lyricism too. It's not just what's written on the page. The way he pauses, changes his voice, switches flows, or emphasizes certain words can completely change the meaning.

There are obviously a lot of incredible lyricists — Nas, André 3000, Black Thought, MF DOOM, Eminem, Jay-Z, etc.

But if I had to pick one, I'm taking Kendrick.

Who do you guys think is the best lyricist ever, and what makes them better than Kendrick?

I'm a Surveying Engineering student trying to decide which specialization to focus on. I'm interested in both GIS and Land Surveying, but I'm not sure which offers better long-term career opportunities, salary, growth, and flexibility. For those who have worked in either field, which would you recommend and why?