Where to Find Geospatial and Mapping OSINT Tools in Legendary OSINT

All geospatial and mapping OSINT resources in the Legendary OSINT repository are centralized in docs/geospatial-mapping.md, which serves as a curated index of satellite imagery platforms, location estimation services, and GIS analysis tools.

Legendary OSINT is a curated collection of open-source intelligence (OSINT) resources maintained by K2SOsint. Unlike repositories that host executable scripts, this project uses a flat Markdown structure under the docs/ directory to catalog external tools. The primary keyword, geospatial and mapping OSINT, is comprehensively covered in a dedicated file that links directly to dozens of web-based and desktop applications.

Locating the Geospatial Tool Index

According to the Legendary OSINT source code, the definitive reference for location-based investigations resides in docs/geospatial-mapping.md. This file is referenced by the central README.md, which functions as the table of contents for the entire repository.

The design is intentionally "read-only": the repository does not host code that interfaces directly with these services. Instead, docs/geospatial-mapping.md provides hyperlinks to external platforms, allowing analysts to discover and launch tools without downloading heavy dependencies. This lightweight approach reduces maintenance overhead while enabling community contributors to update URLs or add new services via simple Markdown edits.

Categories of Geospatial and Mapping OSINT Tools

The geospatial-mapping.md file organizes resources into six functional categories. Each entry includes a short description and a direct hyperlink to the live service.

Satellite Imagery Platforms

This section lists high-resolution and multispectral imagery sources. Representative tools include Google Earth Pro for historical imagery analysis, Sentinel Hub for programmatic Sentinel-2 access, NASA Worldview for near real-time Earth observation, USGS EarthExplorer for Landsat archives, and Maxar Discovery for commercial satellite data.

Street-Level and Web Mapping

For ground-truth verification and navigation analysis, the repository indexes major mapping services. Key entries include Google Maps, Bing Maps, the OpenStreetMap ecosystem, Mapillary for crowd-sourced street imagery, and HERE WeGo for alternative routing data.

Location Estimation Services

These tools assist in geolocating photographs or estimating coordinates from visual cues. Notable platforms include GeoSpy.ai for AI-powered image geolocation, Picarta for reverse image searching with GPS extraction, TIB Labs for forensic photo analysis, Findthatspot for terrain matching, and PeakFinder for mountain identification.

Satellite Tracking and Orbital Data

For monitoring spacecraft or predicting overflights, the documentation lists orbital mechanics databases. Essential resources include Space-Track.org for official satellite ephemeris, N2YO for real-time tracking maps, Heavens Above for amateur satellite spotting, SatNOGS for open satellite ground station data, and Celestrak for space debris tracking.

Sun and Shadow Analysis

Shadow calculation tools help verify the time and date of photograph capture. Featured utilities include ShadeMap and ShadowMap for interactive shadow simulations, SunCalc and SunEarthTools for solar position calculations, and the BellingCat ShadowFinder for forensic timestamp verification.

Desktop GIS and Analysis Suites

For advanced spatial processing, the file references full-featured geographic information systems. Primary applications include QGIS for open-source desktop analysis, ArcGIS Online for Esri's cloud platform, and Gephi for network visualization of geospatial relationships.

Automating Workflows with Listed Tools

While Legendary OSINT provides only the index, analysts can integrate these services into Python pipelines. Below are practical implementations for two of the listed platforms.

Downloading Sentinel-2 Imagery via Sentinel Hub

The following script uses the Sentinel Hub API to download satellite imagery programmatically, as referenced in the repository's satellite imagery section:

import requests

# Replace with your Sentinel Hub instance ID and OAuth token

INSTANCE_ID = "your-instance-id"
ACCESS_TOKEN = "your-access-token"

# Example query: a 10 km square around Paris, 2023-06-01

url = f"https://services.sentinel-hub.com/ogc/wms/{INSTANCE_ID}"
params = {
    "SERVICE": "WMS",
    "REQUEST": "GetMap",
    "VERSION": "1.3.0",
    "LAYERS": "TRUE_COLOR",
    "CRS": "EPSG:3857",
    "BBOX": "2.28,48.81,2.44,48.90",   # lon-lat in EPSG:4326

    "WIDTH": "512",
    "HEIGHT": "512",
    "FORMAT": "image/png",
    "TIME": "2023-06-01/2023-06-01",
}
headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
resp = requests.get(url, params=params, headers=headers)

with open("paris_sentinel.png", "wb") as f:
    f.write(resp.content)
print("Image saved as paris_sentinel.png")

This implementation follows the Sentinel Hub entry documented in docs/geospatial-mapping.md.

Scripting QGIS with PyQGIS

For automating desktop GIS workflows, this snippet demonstrates loading shapefiles into QGIS using the Python API:

from qgis.core import QgsApplication, QgsVectorLayer, QgsProject

# Initialize QGIS (adjust the prefix path to your installation)

qgs = QgsApplication([], False)
qgs.setPrefixPath("/usr", True)
qgs.initQgis()

# Path to the shapefile you wish to analyse

shp_path = "/path/to/your_data.shp"
layer = QgsVectorLayer(shp_path, "My Layer", "ogr")
if not layer.isValid():
    raise RuntimeError("Failed to load layer")

# Add to the current project

QgsProject.instance().addMapLayer(layer)
print("Layer added to QGIS")

# When done, clean up

qgs.exitQgis()

This code corresponds to the QGIS tool listed under the Geospatial Analysis section of the repository.

Summary

• Primary location: All geospatial and mapping OSINT tools are indexed in docs/geospatial-mapping.md within the Legendary OSINT repository.
• Architecture: The repository uses a flat Markdown structure with no executable code, functioning as a curated hyperlink directory.
• Coverage: The file spans six categories including satellite imagery, street mapping, location estimation, orbital tracking, shadow analysis, and GIS software.
• Integration: Tools listed in the documentation can be automated via Python APIs, as demonstrated with Sentinel Hub and PyQGIS examples.

Frequently Asked Questions

Where is the main geospatial tools list located in Legendary OSINT?

The master list resides at docs/geospatial-mapping.md in the repository root. This file is linked from the main README.md and contains categorized hyperlinks to all referenced satellite, mapping, and analysis platforms.

Does Legendary OSINT host executable code for these mapping tools?

No. According to the repository's design philosophy, the project maintains a "read-only" index of external tools. It provides Markdown documentation linking to web services and download pages rather than hosting API clients or analysis scripts directly.

What types of satellite imagery tools are included?

The geospatial-mapping.md file catalogs platforms for high-resolution commercial imagery (Maxar Discovery, Google Earth Pro), free government data (USGS EarthExplorer, NASA Worldview), and programmatic APIs (Sentinel Hub). These range from historical archives to near real-time observation streams.

How can I contribute new geospatial tools to the repository?

Contributors can submit pull requests that modify docs/geospatial-mapping.md to add new tool entries. Because the repository uses pure Markdown without complex build processes, updates require only adding a bullet point with the tool name, description, and URL to the appropriate category section.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}