საიტზეა ჩასასმელი
QGIS - Field calculator : $area vs. area($geometry)
Calculating the area of features is a common task in GIS. Two popular methods for this in the field calculator are $area and area($geometry). Although they may appear similar, the method you choose depends on the specific context and the level of accuracy you need.
About $area:
This function calculates the area of the current feature and adjusts based on the project settings. If an ellipsoid is defined in the project, the area will be calculated ellipsoidally. If no ellipsoid is set, the calculation defaults to a flat, planimetric approach. The units used for the area are determined by the project’s settings.
About area($geometry):
This function calculates the area of a polygon geometry. The calculation is always planimetric and is based on the Spatial Reference System (SRS) of the geometry. The units of the result correspond to those of the SRS. Unlike $area, this method doesn’t consider the project’s ellipsoid settings or custom area unit configurations.
To break down Ellipsoidal and Planimetric 💻
Ellipsoidal 🌍
Ellipsoidal = Country / Regional : Ideal for large-scale mapping where curvature needs to be considered for accurate area measurements.
Planimetric 🗺️
Town/City: Best for local mapping where Earth's curvature doesn’t significantly affect accuracy. Calculates area on a flat plane.
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14 Best Free Sources to Download Geospatial Data
🗺️ Maps & Boundaries :
1️⃣ Natural Earth – Small-scale maps (political & natural), lightweight for global projects.
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📊 General GIS Data:
1️⃣3️⃣ ArcGIS Hub – 350,000+ open datasets from global institutions.
1️⃣4️⃣ DIVA-GIS – Boundaries, land cover, population & agricultural datasets.
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There are a few online options to learn GIS for free. Take advantage of resources that provide you access to free courses from some of the world’s best universities and institutions.
Learn GIS on your own or supplement your existing geospatial education with these free resources.
A type of distance learning, MOOC offers free education via the Internet to ten of thousands of students simultaneously.
Penn State offered the first known GIS related MOOC entitled “Maps and the Geospatial Revolution” in July of 2013 based off a four-part video series by the same name: “Geospatial Revolution“.
In the ten years since that first GIS MOOC, the amount of free GIS courses available has grown.
Esri now offers a series of GIS MOOCs each year covering spatial analysis, cartography, imagery analysis, and mapping apps.
UC Davis offers a five-series course on GIS that can be audited for free.
The number of free GIS courses you can take as a MOOC has grown enormously since the first class offered by PSU. You can search for other geospatial courses by browsing the listings at MOOC platforms like Coursera and EdX.
There are some options for self-guided GIS learning.
Many U.S. public libraries have a subscription to LinkedIn Learning for Libraries, a subscription-based site that provides online tutorials. Check with your local library to see if they have a subscription, providing you with free access to this site’s GIS tutorials.
The Open Textbook Library provides free access several GIS textbooks. Some of these books like Earth, Space, and Environmental Science Explorations with ArcGIS Pro are self-guide GIS workbooks that users can follow to learn geospatial analysis and tools.
OpenCourseWare (OCW) are free courses published by universities and made publicly available on the Internet. Unlike a MOOC where all students are learning the same materials on the same schedule, OpenCourseWare materials are asynchronous and the students navigate through the materials on their own. High ranking universities such as MIT, Yale, UC Berkeley, and the University of Michigan offer OpenCourseWare. The downside is that some of these courses are dated (especially for technical classes) but the underlying principles and concepts are still valuable.
Some examples of OpenCourseWare GIS courses:
Tufts University – Introduction to Geographic Information Systems (GIS) for Urban and Environmental Analysis
MIT – Introduction to Spatial Analysis (more GIS courses from MIT)
Penn State – Open Courses from the Geography Department with several for GIS
Esri offers a substantial amount of both free and fee-based courses teaching a range of courses mostly specific to learning Esri’s suite of GIS software.
There are currently over 330 free courses available from Esri (click the “free training” box to view).
Examples of some of Esri’s free GIS courses are: Getting Started with GIS, Classifying Objects Using Deep Learning in ArcGIS Pro, and Python for Everyone.
Free registration is required with Esri to take any of its courses.
Udemy offers a free “QGIS for beginners” course. The courses cover learning spatial analysis, managing data, cartography, and remote sensing.
The QGIS site offers a training manual for learning QGIS broken down by modules, each with a lesson.
More: Free Ways to Learn QGIS
QGIS and ArcGIS aren’t the only GIS software tools out there.
This highly rated tutorial teaches “Geospatial Analysis With Python” using opens source GeoPandas.
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Refine your skills and keep up with updates:
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↳ Attend Python meetups and conferences
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Do you use
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𝐇𝐢𝐠𝐡-𝐋𝐞𝐯𝐞𝐥 𝐒𝐡𝐚𝐫𝐞𝐝 𝐀𝐏𝐈
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𝐎𝐭𝐡𝐞𝐫 𝐈𝐧𝐟𝐨𝐕𝐢𝐬
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𝐆𝐫𝐚𝐩𝐡𝐬 𝐚𝐧𝐝 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐬
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𝐎𝐭𝐡𝐞𝐫 𝐝𝐨𝐦𝐚𝐢𝐧-𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐜
- scikit-image - https://ow.ly/Izqo50PUXVp
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𝐋𝐚𝐫𝐠𝐞-𝐝𝐚𝐭𝐚 𝐫𝐞𝐧𝐝𝐞𝐫𝐢𝐧𝐠
- datashader - https://ow.ly/gOtm50PUXVN
- vaex - https://ow.ly/XKOt50PUXVv
- mpl-scatter-density - https://ow.ly/9R8F50PUXWm
𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐢𝐧𝐠
- gradio - https://ow.ly/cb0h50PUXW0
- streamlit - https://ow.ly/HG6350PUXVo
- dash - https://ow.ly/YGkG50PUXVq
- panel - https://ow.ly/WiXj50PUXWo
𝐂𝐨𝐥𝐨𝐫𝐦𝐚𝐩𝐩𝐢𝐧𝐠
- palettable - https://ow.ly/SN1A50PUXVu
- colorcet - https://ow.ly/JpwX50PUXVG
- cmocean - https://ow.ly/HNkS50PUXWp
For the other 100 libs check their site: https://lnkd.in/dJ7QzwPX
20 GIS DATA SOURCES & THEIR WEBSITES
1. USGS Earth Explorer
Data Type: Satellite imagery, aerial photos, elevation data
Website: https://lnkd.in/dhfrySmj
2. Natural Earth
Data Type: Free vector & raster data for cultural, physical, & raster datasets
Website: https://lnkd.in/d49hkqTS
3. OpenStreetMap (OSM)
Data Type: Free editable map of the world, includes road networks, buildings, etc.
Website: https://lnkd.in/dKZqF7gT
4. Copernicus Open Access Hub
Data Type: Sentinel satellite imagery (Sentinel-1, Sentinel-2, etc.)
Website: https://lnkd.in/dhKKDmVT
5. NASA Earthdata
Data Type: Earth science data from NASA’s satellites
Website: https://earthdata.nasa.gov
6. European Space Agency (ESA) Earth Observation Data
Data Type: Satellite data from ESA's missions
Website: https://eoportal.org
7. Geospatial Data Abstraction Library (GDAL)
Data Type: Raster & vector geospatial data formats
Website: https://gdal.org/
8. LandsatLook Viewer
Data Type: Landsat satellite imagery
Website: https://lnkd.in/dRvM_nvs
9. World Resources Institute (WRI)
Data Type: Environmental & socio-economic data
Website: https://www.wri.org
10. Global Administrative Areas (GADM)
Data Type: Administrative boundaries of countries
Website: https://gadm.org
11. FAO GeoNetwork
Data Type: Global datasets on agriculture, fisheries & ecosystems
Website: https://lnkd.in/dTv87zG6
12. Global Forest Watch
Data Type: Forest cover, loss & conservation data
Website: https://lnkd.in/ddXF8xgu
13. DIVA-GIS
Data Type: Environmental & biodiversity data
Website: https://diva-gis.org/
14. Earth Observing System (EOS) Data Analytics
Data Type: Satellite data analysis platform for vegetation, climate & land cover
Website: https://eos.com
15. National Geospatial-Intelligence Agency (NGA) GEOnet Names Server (GNS)
Data Type: Geographical feature names
Website: https://lnkd.in/dwdvwkxT
16. Google Earth Engine
Data Type: Massive amount of satellite imagery & geospatial datasets.
Website: https://lnkd.in/dVun-hzp
17. WorldClim
Data Type: Global climate data, including temperature & precipitation
Website: https://www.worldclim.org
18. OpenTopography
Data Type: High-resolution topographic data, particularly LiDAR data
Website: https://lnkd.in/d8Q9P33t
19. Geofabrik
Data Type: Shapefiles, maps, map tiles & web mapping solutions
Website: https://www.geofabrik.de/
20. MODIS (Moderate Resolution Imaging Spectroradiometer)
Data Type: Environmental data from NASA's Terra & Aqua satellites
Website: https://lnkd.in/dFFET9Xe
1️⃣. 𝙐𝙣𝙞𝙫𝙚𝙧𝙨𝙞𝙩𝙮 𝙤𝙛 𝘼𝙡𝙖𝙨𝙠𝙖 - Remote Sensing of Wildfires
2️⃣. 𝙐𝙣𝙞𝙫𝙚𝙧𝙨𝙞𝙩𝙮 𝙤𝙛 𝙏𝙚𝙣𝙣𝙚𝙨𝙨𝙚𝙚 - Spatial Data Management
3️⃣. 𝙀𝙏𝙃 𝙕𝙪𝙧𝙞𝙘𝙝 - Web Cartography
4️⃣. 𝙐𝙣𝙞𝙫𝙚𝙧𝙨𝙞𝙩𝙮 𝙤𝙛 𝙏𝙤𝙧𝙤𝙣𝙩𝙤 - Spatial Analysis and Satellite Imagery
5️⃣. 𝙐𝘾 𝘿𝙖𝙫𝙞𝙨 - Imagery, Automation, and Applications
The most popular Google Earth Engine Tutorials Published in 2024:
- Flood Detection: https://lnkd.in/dDPQ95pe
- Drought Mapping: https://lnkd.in/ddsKiA7x
- Soil Moisture Estimation: https://lnkd.in/dSqKGAsm
- Drought Monitoring: https://lnkd.in/dif6sxKw
- Global Canopy Height: https://lnkd.in/dwBscWha
- Crop Type Detection: https://lnkd.in/dHfsZAA7
- Crop Water Stress: https://lnkd.in/d8bjXGRd
- Precipitation Downscaling: https://lnkd.in/d74tJTbX
- Biomass Prediction: https://lnkd.in/dmaQA9AN
- Oil Spill Detection: https://lnkd.in/ddyM-sEn
- Lake Area Estimation: https://lnkd.in/dWnd3f3x
- Ground Water Monitoring: https://lnkd.in/dhC-jDdX
- Water Turbidity: https://lnkd.in/dGfnaTsH
- Urban Flood: https://lnkd.in/dd9SVnYG
- Urban Heat Island: https://lnkd.in/dGt_SxZW
- Wildfire Detection: https://lnkd.in/gi9vBHAF
- Landcover Product: https://lnkd.in/dMCQR-vt
- Coastline Change Detection: https://lnkd.in/dKGyxDFZ
- Deforestation Monitoring: https://lnkd.in/d-yNQjBJ
- Methan Monitoring: https://lnkd.in/dG5xtx2R
These Python libraries and frameworks are game-changers in geospatial analysis:
🔗 ArcGIS - Leverage the full ArcGIS experience in Python: https://lnkd.in/dgC6sKJH
🗺️ Cartopy - Python meets CARTO's analytical platform: https://lnkd.in/dc8ijXRg
✨ Contextily - Elegant map visualizations made easy: https://lnkd.in/dTdQsmKX
🖼️ Descartes - Ideal for plotting geospatial imagery: https://lnkd.in/d4andF4Y
📂 Fiona - Streamline transformations between GIS data structures: https://lnkd.in/d8sJ3Q5a
🌐 Folium - Create stunning map visualizations: https://lnkd.in/dfSsE-MB
🛠️ Gdal - The Geospatial Data Abstraction Library: https://lnkd.in/dYBJBaAY
📌 Geohash - Geohashing made simple: https://lnkd.in/dB-m8a4s
📜 Geojson - For handling JSON geospatial data: https://lnkd.in/daGs2WYq
🐼 Geopandas - The foundation for geospatial Python 101: https://lnkd.in/dBTFKKV3
📍 Geopy - Advanced geocoding made effortless: https://lnkd.in/dfAzR8Xa
🧭 h3 - Uber's spatial indexing library: https://h3geo.org/docs/
📊 kepler.gl - Stunning large-scale map visualizations: https://kepler.gl
🚀 Mosaic - Scaling geospatial workflows on Databricks: https://lnkd.in/duPCdkTd
🌏 Overpy - Access OpenStreetMap with ease: https://lnkd.in/dj5hN7Pp
🛤️ OSMnx - Handling OSM networks effectively: https://lnkd.in/dm3pHgUS
🖥️ PyQGIS - Unlock the power of QGIS in Python: https://lnkd.in/dShWyWVr
📐 PySAL - Python Spatial Analysis Library: https://pysal.org
🎨 Pydeck - Interactive large-scale data visualization: https://lnkd.in/dGBFu-iw
📏 Pyproj - Simplify CRS projections: https://lnkd.in/dNG9fdkm
🌍 Pyrosm - Visualizing OSM data effectively: https://lnkd.in/d4vrrAC7
🔄 RTree - Classic spatial indexing made robust: https://lnkd.in/dURMiYpU
🛰️ Rasterio - Perfect for satellite image analysis: https://lnkd.in/dEMC6ve6
🚶♂️ Scikit-mobility - Analyze GPS mobility data efficiently: https://lnkd.in/dpHhaX2J
🧱 Shapely - A go-to library for handling geometries: https://lnkd.in/d568datK
1. ArcGIS API for Python - https://ow.ly/QZwv50PRFzi
2. arcpy - https://ow.ly/p9ig50PRFzB
3. Cartopy - https://ow.ly/oJfm50PRFzQ
4. contextily - https://ow.ly/QNYv50PRFzO
5. Datashader - https://ow.ly/rP9150PRFzR
6. Earth Engine API - https://ow.ly/rcIg50PRFzl
7. EarthPy - https://ow.ly/V3LC50PRFzh
8. EarthViews - https://ow.ly/J3SI50PRFzG
9. ENVI Py - https://ow.ly/eSQS50PRFzP
10. Fiona - https://ow.ly/txrr50PRFz5
11. Folium - https://ow.ly/nfVL50PRFzU
12. GDAL - https://ow.ly/iIwv50PRFzJ
13. GeoAlchemy - https://ow.ly/5F9T50PRFF4
14. geocoder - https://ow.ly/JNo950PRFF1
15. GeoDjango - https://ow.ly/uJYO50PRFFi
16. GeoMesa - https://ow.ly/65QO50PRFET
17. GeoPandas - https://ow.ly/I7Kk50PRFEO
18. GeoPandas-Bokeh - https://ow.ly/OjC650PRFF7
19. geoplot - https://ow.ly/IqLe50PRFEW
20. geos - https://ow.ly/CQ5g50PRFEM
21. GeoPy - https://ow.ly/n9KI50PRFFh
22. geospatial-learn - https://ow.ly/8l2A50PRFEJ
23. GeoViews - https://ow.ly/J3SI50PRFzG
24. gpsd-py3 - https://ow.ly/X23u50PRFFI
25. gpxpy - https://ow.ly/nvGz50PRFFz
26. h3-py - https://ow.ly/XsuM50PRFFG
27. ipyleaflet - https://ow.ly/Xswc50PRFFm
28. laspy - https://ow.ly/wjcR50PRFFA
29. Mosaic - https://ow.ly/AIko50PRFFv
30. OSMnx - https://ow.ly/nKGs50PRFFp
31. Overpy - https://ow.ly/skGr50PRFFE
32. PDAL - https://ow.ly/ckGn50PRFFy
33. PyCRS - https://ow.ly/XsXJ50PRFFq
34. Pydeck - https://ow.ly/E29A50PRFFM
35. PyGeodesy - https://ow.ly/fmaw50PRFFx
36. Pyproj - https://ow.ly/fXaY50PRFFt
37. PyRAT - https://ow.ly/iSTT50PRFFs
38. PySAR - https://ow.ly/f1hQ50PRFFC
39. PyVista - https://ow.ly/E15a50PRFFB
40. Pysal - https://ow.ly/6vcm50PRFFF
41. RasterFrames - https://ow.ly/G6UW50PRFFL
42. Rasterio - https://ow.ly/MONn50PRFFo
43. Rasterstats - https://ow.ly/O5Tg50PRFFN
44. RSGISLib - https://ow.ly/fnJH50PRFFu
45. scikit-mobility - https://ow.ly/Rvfm50PRFFJ
46. Sedona - https://ow.ly/igSb50PRFFH
47. simplekml - https://ow.ly/OyKv50PRFFK
48. TorchGeo (PyTorch) - https://ow.ly/SEma50PRFFw
49. WhiteboxTools - https://ow.ly/ncm450PRFFn
50. Xarray - https://ow.ly/7sBO50PRFFr
𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/dgWQnx7b
📊 𝐃𝐀𝐓𝐀 𝐒𝐎𝐔𝐑𝐂𝐄𝐒
1. Budapest Open Data Atlas - https://zurl.co/c5ohB
2. Catchment Characterisation and Modelling - https://zurl.co/KQaLm
3. EU H2020 Funding - https://zurl.co/2IAdO
4. European Environment Agency - https://zurl.co/fXXql
5. Geofabrik - https://zurl.co/pNvwb
6. Global Self-consistent Hierarchical High-resolution Shoreline - https://zurl.co/N89PW
7. GTS Public Transport - https://zurl.co/nteEB
8. IUCN Red List of Threatened Species - https://zurl.co/VIp2a
9. Koordinates - https://zurl.co/3EYnf
10. Major Watersheds of the World Delineation - https://zurl.co/xXXNY
11. MarineRegions - https://zurl.co/WEvwb
12. NASA’s Meteorite Landing Data - https://zurl.co/qUqDh
13. Randolph Glacier Inventory - https://zurl.co/koiKh
14. Road Network of Ancient Rome - https://zurl.co/AH27B
15. UFO Sightings - https://zurl.co/DdoaT
16. Earth's Magnetic Model - https://zurl.co/UJ0ak
17. Global Administrative Areas - https://zurl.co/b1bKR
18. Global River Widths from Landsat - https://zurl.co/eHzMO
19. Harvard Dataverse - https://zurl.co/dfrhT
20. Humanitarian Data Exchange - https://zurl.co/F7wNd
21. MapCruzin - https://zurl.co/1J867
22. NASA SEDAC - https://zurl.co/hZ4A5
23. Natural Earth - https://zurl.co/BXXfL
24. OSM - https://zurl.co/Rfdh8
25. Overture Maps - https://zurl.co/Q5WcE
26. PREDICTS Database - https://zurl.co/vfY0k
27. USGS Geographic Names Information System (GNIS) - https://zurl.co/lMvSm
28. The Paleobiology Database - https://zurl.co/8tpOM
29. Pleiades Ancient Places - https://zurl.co/sGlCx
30. Africa GeoPortal - https://zurl.co/HMWXd
31. Austrian Government Open Data Portal - https://zurl.co/5owia
32. Data Basin - https://zurl.co/jST04
33. Esri Open Data Hub - https://zurl.co/6clIa
34. FAO GeoNetwork - https://zurl.co/gJI95
35. Global Biodiversity - https://zurl.co/JtyNb
36. GeoNetwork - https://zurl.co/9QP7M
37. ISCGM Global Map - https://zurl.co/mvwvr
38. National Centers for Environmental Inf. - https://zurl.co/GoaQC
39. Ocean Biodiversity Information System - https://zurl.co/Lzdt3
40. UN FAO Global Land Cover Network - https://zurl.co/0XXML
Here I collected 25 of my Python tutorials on various geospatial data science topics:
1. 𝐑𝐚𝐬𝐭𝐞𝐫𝐢𝐳𝐢𝐧𝐠 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 — 𝐀 𝐋𝐞𝐠𝐨 𝐌𝐚𝐩 - https://zurl.co/cyLYg
2. 𝐒𝐩𝐚𝐭𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐫𝐩𝐨𝐥𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 - https://zurl.co/g0DSM
3. 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐢𝐧𝐠 𝟑𝐃 𝐒𝐩𝐚𝐭𝐢𝐚𝐥 𝐃𝐚𝐭𝐚 𝐖𝐢𝐭𝐡 𝐏𝐲𝐝𝐞𝐜𝐤 - https://zurl.co/SfH5u
4. 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐢𝐧𝐠 𝐑𝐨𝐚𝐝 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 - https://zurl.co/JkCve
5. 𝐈𝐬𝐨𝐜𝐡𝐫𝐨𝐧𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 - 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐢𝐧𝐠 𝐖𝐚𝐥𝐤𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐀𝐫𝐞𝐚𝐬 - https://zurl.co/fKd3a
6. 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐢𝐩𝐬 𝐟𝐨𝐫 𝐆𝐞𝐨𝐏𝐚𝐧𝐝𝐚𝐬 - 𝐃𝐨 𝐆𝐞𝐨𝐬𝐩𝐚𝐭𝐢𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 𝐋𝐢𝐤𝐞 𝐚 𝐏𝐫𝐨 - https://zurl.co/Kwywj
7. 𝐔𝐄𝐅𝐀 𝐄𝐮𝐫𝐨 𝟐𝟎𝟐𝟒 𝐌𝐚𝐩 - https://zurl.co/i7d9d
8. 𝐏𝐮𝐛𝐥𝐢𝐜 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭 𝐀𝐜𝐜𝐞𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 - https://zurl.co/zkbc2
9. 𝐖𝐡𝐞𝐫𝐞 𝐃𝐨 𝐄𝐔 𝐇𝐨𝐫𝐢𝐳𝐨𝐧 𝐇𝟐𝟎𝟐𝟎 𝐅𝐮𝐧𝐝𝐢𝐧𝐠𝐬 𝐆𝐨? - https://zurl.co/8vuG1
10. 𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐒𝐚𝐭𝐞𝐥𝐥𝐢𝐭𝐞 𝐈𝐦𝐚𝐠𝐞 𝐓𝐢𝐦𝐞𝐥𝐚𝐩𝐬𝐞𝐬 - https://zurl.co/CTc8G
11. 𝐋𝐢𝐯𝐚𝐛𝐥𝐞 𝐂𝐢𝐭𝐢𝐞𝐬’ 𝐔𝐫𝐛𝐚𝐧 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 - https://zurl.co/NPJyV
12. 𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐲𝐢𝐧𝐠 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭𝐚𝐭𝐢𝐨𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐔𝐬𝐢𝐧𝐠 𝐆𝐓𝐅𝐒 𝐃𝐚𝐭𝐚 - https://zurl.co/tOTzh
13. 𝐓𝐡𝐞 𝐆𝐞𝐨𝐬𝐩𝐚𝐭𝐢𝐚𝐥 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐒𝐭𝐚𝐜𝐤 𝐢𝐧 𝟐𝟎𝟐𝟑 - https://zurl.co/Vu1DE
14. 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰𝐢𝐧𝐠 𝐭𝐡𝐞 𝐆𝐥𝐨𝐛𝐚𝐥 𝐂𝐡𝐨𝐜𝐨𝐥𝐚𝐭𝐞 𝐓𝐫𝐚𝐝𝐞 - https://zurl.co/65LHQ
15. 𝐔𝐬𝐢𝐧𝐠 𝐂𝐨𝐥𝐨𝐫 𝐭𝐨 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭 𝐚 𝐂𝐨𝐦𝐩𝐥𝐞𝐱 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐨𝐟 𝐓𝐡𝐫𝐞𝐚𝐭𝐞𝐧𝐞𝐝 𝐒𝐩𝐞𝐜𝐢𝐞𝐬 - https://zurl.co/qXvBo
16. 𝐃𝐞𝐞𝐩 𝐃𝐢𝐯𝐞 𝐢𝐧𝐭𝐨 𝐄𝐒𝐀’𝐬 𝐒𝐞𝐧𝐭𝐢𝐧𝐞𝐥 𝐀𝐏𝐈 - https://zurl.co/UNqmt
17. 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐚 𝐆𝐥𝐨𝐛𝐚𝐥 𝐖𝐢𝐥𝐝𝐥𝐢𝐟𝐞 𝐆𝐈𝐒 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 - https://zurl.co/5Nfiw
18. 𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐲𝐢𝐧𝐠 𝐓𝐨𝐩𝐢𝐜𝐚𝐥 𝐇𝐨𝐭 𝐒𝐩𝐨𝐭𝐬 𝐢𝐧 𝐔𝐫𝐛𝐚𝐧 𝐀𝐫𝐞𝐚𝐬 - https://zurl.co/bkG6i
19. 𝐃𝐨 𝐀𝐥𝐥 𝐭𝐡𝐞 𝐑𝐨𝐚𝐝𝐬 𝐋𝐞𝐚𝐝 𝐭𝐨 𝐑𝐨𝐦𝐞? - https://zurl.co/knxZQ
20. 𝐔𝐫𝐛𝐚𝐧 𝐀𝐜𝐜𝐞𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲 — 𝐇𝐨𝐰 𝐭𝐨 𝐑𝐞𝐚𝐜𝐡 𝐃𝐞𝐟𝐢𝐛𝐫𝐢𝐥𝐥𝐚𝐭𝐨𝐫𝐬 𝐨𝐧 𝐓𝐢𝐦𝐞 - https://zurl.co/yD0KX
21. 𝐓𝐡𝐞 𝐖𝐨𝐫𝐥𝐝 𝐌𝐚𝐩 𝐰𝐢𝐭𝐡 𝐌𝐚𝐧𝐲 𝐅𝐚𝐜𝐞𝐬 — 𝐌𝐚𝐩 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐢𝐨𝐧𝐬 - https://zurl.co/HELQY
22. 𝐀𝐬𝐬𝐞𝐬𝐬𝐢𝐧𝐠 𝐔𝐫𝐛𝐚𝐧 𝐆𝐫𝐞𝐞𝐧 𝐄𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐔𝐬𝐢𝐧𝐠 𝐕𝐢𝐞𝐧𝐧𝐚’𝐬 𝐎𝐩𝐞𝐧 𝐃𝐚𝐭𝐚 𝐏𝐨𝐫𝐭𝐚𝐥 - https://zurl.co/w9pOz
23. 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐋𝐚𝐫𝐠𝐞-𝐒𝐜𝐚𝐥𝐞 𝐑𝐚𝐬𝐭𝐞𝐫 𝐏𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐃𝐚𝐭𝐚 - https://zurl.co/2jub5
24. 𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐢𝐧𝐠 𝐔𝐫𝐛𝐚𝐧 𝐍𝐞𝐢𝐠𝐡𝐛𝐨𝐫𝐡𝐨𝐨𝐝𝐬 - https://zurl.co/jjNAU
25. 𝐑𝐞𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐚 𝟑𝐃 𝐌𝐚𝐩 𝐨𝐟 𝐀𝐧𝐭𝐚𝐫𝐜𝐭𝐢𝐜𝐚 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 - https://zurl.co/hCTpZ