Satellite Before/After Comparison (NASA GIBS)

x402

Satellite Before/After Comparison (NASA GIBS) is a paid API for AI agents from agentsvc.io, paid per call via x402, $0.013/call, status unknown (last checked 2026-10-12).

Generates a side-by-side JPEG comparing NASA satellite imagery of the same location on two dates, with pixel-level change metrics and a plain-language assessment of whether changes are real or weather-related.

Price / call$0.013

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Output

Returns a composite JPEG image (2× requested width + 8 px) showing the two dates side by side with date labels overlaid, plus JSON metrics including the share of changed pixels, overall brightness change, cloud/haze/snow coverage estimates for each date, and a plain-language interpretation stating whether the detected change is likely real environmental change or attributable to atmospheric conditions like clouds or snow.

Example use cases

Wildfire damage assessment

“Pull up a side-by-side NASA satellite comparison of Paradise, California — I want to see what it looked like before November 8 2018 versus right after, using a 50 km radius and MODIS Terra, and tell me if the changes are real or just weather noise.”

Flood extent monitoring

“Can you compare satellite imagery of Kherson, Ukraine before and after the Nova Kakhovka dam collapse in June 2023? Use VIIRS SNPP, a 100 km radius, and show me how much of the land area visibly changed.”

Seasonal deforestation tracking

“Show me a before-and-after satellite view of the Pará state in Brazil comparing January 2022 to January 2023 — I want to see if there's been measurable deforestation and whether the change is genuine or obscured by clouds.”

Technical details

Endpoint

POSThttps://agentsvc.io/api/v1/proxy/satellite-compare?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a quick, visually interpretable before-and-after comparison of a geographic area using freely available NASA satellite data, especially for event-driven change detection (wildfires, floods, hurricanes, deforestation). It is ideal when you want both a shareable image and quantitative change metrics without needing commercial high-resolution imagery. Prefer it over single-image satellite endpoints when temporal comparison is the core need, and over full GIS pipelines when a lightweight, paid-per-call, no-infrastructure approach is sufficient.

Side effects

Requested dates may have no available imagery (NASA GIBS archive gaps, especially for VIIRS before 2012)
High cloud or snow coverage on one or both dates can make pixel-change metrics unreliable or mask real change
Place name not found in GeoNames for small or ambiguous localities — use lat/lon instead
Radius too large (>500 km) or too small (<5 km) will be rejected by schema validation
Invalid date format or date_after earlier than date_before will cause an error
MODIS resolution (~250 m/pixel) may not detect fine-scale changes in small areas

Input

Schema · Request body

Field	Type	Description
lat	number
lon	number
bbox	array
layer	string
place	string	Place name instead of coordinates, e.g. "Valencia, Spain" (GeoNames, cities and towns)
width	integer	Width of each of the two images; the composite is 2 x width + 8 px
radius_km	number
date_after	string	YYYY-MM-DD, default yesterday
date_before	string	YYYY-MM-DD, default 365 days before date_after
include_separate	boolean	Also return both images separately as base64

Output

Schema · Response

{
  "type": "json",
  "example": {
    "data": {
      "bbox": {
        "max_lat": -18.2995,
        "max_lon": -66.6243,
        "min_lat": -19.2005,
        "min_lon": -67.5757
      },
      "note": "Daily true-color mosaics at about 250 m per pixel. Change metrics are compute...",
      "layer": "modis_terra",
      "width": 520,
      "change": {
        "after": {
          "no_data_pct": 0,
          "mean_brightness": 49.8,
          "cloud_or_snow_pct": 6.4,
          "cloud_haze_or_snow_pct": 18.3
        },
        "before": {
          "no_data_pct": 13,
          "mean_brightness": 42.6,
          "cloud_or_snow_pct": 0.5,
          "cloud_haze_or_snow_pct": 8.6
        },
        "reading": "Visible change in part of the area (for example water level, burn scars, floo...",
        "reliable": true,
        "changed_pixels_pct": 20.1,
        "mean_brightness_change_pct": 7.3
      },
      "height": 264,
      "layout": "side_by_side: left = date_before, right = date_after, date labels on top",
      "layer_id": "MODIS_Terra_CorrectedReflectance_TrueColor",
      "mime_type": "image/jpeg",
      "date_after": "2016-05-10",
      "size_bytes": 22150,
      "attribution": "NASA EOSDIS GIBS / Worldview",
      "date_before": "2014-05-10",
      "image_base64": "/9j/2wBDAAYEBAUEBAYFBQUG…"
    },
    "success": true
  }
}

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