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One question, one place, worked on public imagery.

Every engagement starts with one question about one place. The method is shown on public, open data first, so you can judge it before anything is scoped.

Umbra 0.16 m radar over the Port of Savannah.

Public open-data archive

Examples · From public, open data

Four ways to see a place from orbit

No single sensor answers every question. Knowing which one to reach for, and how to combine them, is most of the work. Here is what each kind is for, then a worked example over one place.

  • Radar

    All-weather radar

    Radar makes its own illumination, so it sees day or night and straight through cloud, smoke, and storm, over land and open sea alike.

    Good for: The dependable workhorse: spotting vessels at sea, activity on the ground, and change anywhere darkness or weather would blind a camera.

  • Radar

    Multi-polarization radar

    Radar that listens in more than one orientation at once, which reveals what a surface is made of, not just where it is.

    Good for: Telling forest from field from flood from built structure. It powers vegetation and biomass mapping (BIOMASS), wide-area land, ice, and ground-motion monitoring (NISAR), and the steady global watch behind maritime and land change (Sentinel-1).

  • Optical

    High-resolution optical

    A camera in space: natural-color imagery at the finest spatial detail, when the skies are clear.

    Good for: The sharpest look for identifying, counting, and mapping, what is this object, how many are there, and exactly where.

  • Optical

    Multispectral

    Optical imagery captured in many color bands, including light the eye cannot see.

    Good for: Reading the health and make-up of the surface: crop stress and irrigation, water and wetlands, burn scars, and land-cover change across whole regions.

Fig. 01

Full-spectrum scene over the Port of Savannah

“What can satellite data tell us about a single port, this week, last month, and last year, without waiting on an analyst?”

Most providers show you one image from one sensor. Here the same square mile of port is seen five different ways, high-detail radar, all-weather radar, and optical, drawn from open archives and registered to one common footprint. Click any panel to see it full size.

What the figure shows
The same cut of the Port of Savannah seen by five sensors, radar and optical, each brought onto one common footprint so the panels can be read against one another.
Industries
Maritime & ports · Defense & intelligence · Infrastructure & energy · Insurance & risk
Provenance
Multi-sensor, Capella · Umbra · Sentinel-1 · Sentinel-2 · NISAR · Port of Savannah, Georgia, USA · Public open-data archive
Caveat
Every image here comes from a public open-data archive. The same workflow can run on tasked or proprietary imagery under NDA.

Guided tour

1 / 7
Aerial basemap of Port of Savannah AOI

Start here: the Port of Savannah

This is one square mile of a working container port, just an aerial map with no satellite data on it yet. The tour adds five different satellites, one at a time, to see what each one reveals. Use Next to walk through them.

A 3 km × 3 km cut centered on Garden City Terminal, the busiest container yard at the Port of Savannah. Stacked container rows, gantry cranes, intermodal rail, and a slip on the Savannah River. The scene is the question: what does each sensor add at this resolution?

Scene: Garden City Terminal, Port of Savannah (3 km × 3 km · 32.116–32.144°N, 81.139–81.171°W), basemap © Esri, Maxar, Earthstar Geographics. All sensor imagery from public open-data archives.

Fig. 02

The same tanker anchorage, read by two different sensors

“If one sensor misses a vessel, or cannot see at all that night, does the answer still hold?”

Three kilometers of water off the east end of the Kharg oil terminal, seen twice. A radar satellite read it at half past two in the morning, in complete darkness. An optical satellite passed twenty-eight hours later in daylight. Two instruments that share no physics, running two separate detectors, found every vessel in this frame independently.

What the figure shows
A single vessel picture over one anchorage built from two independent sensors, with the objects each sensor found, and the ones both sensors agree on, drawn against a common footprint.
Industries
Maritime & ports · Defense & intelligence
Provenance
Multi-sensor, Sentinel-2 optical + Sentinel-1 all-weather radar · Kharg Island tanker anchorage, Persian Gulf · 29.264°N 50.414°E · Public open-data archive
Caveat
Both scenes come from free public archives. The two passes are a day apart, so agreement means a vessel that stayed put, not a simultaneous look.
Radar · 02 May 2026 · 02:39 UTC · darknessOptical · 03 May 2026 · 07:07 UTC · daylight
Radar · 02 May 2026 · 02:39 UTC · darkness
Base
Layers
Both plates are orthorectified to one common footprint, so switching the base leaves every box where it was: the same position lands on the same water in either sensor. Every vessel here carries both a radar and an optical box.
Sentinel-1, 2026-05-02 · Sentinel-2, 2026-05-03 · 29.264°N 50.414°E