The Landsat Explorer is a specialized remote sensing tool designed to visualize and analyze Earth's surface using multi-temporal satellite imagery. Built with the ArcGIS Maps SDK for JavaScript, it leverages server-side processing to render massive datasets instantly in the browser.
Users can toggle between different years (e.g., 2023 vs. 1990) to observe land cover changes, urban expansion, and environmental shifts. The application dynamically adapts its analysis tools based on the currently visible layer.
The sidebar automatically detects which imagery layer is visible (e.g., "Landsat 1990") and updates the available tools and metadata accordingly.
Click anywhere on the map to retrieve precise metadata for that specific pixel, including Acquisition Date, Sensor Type, Cloud Cover, and Sun Elevation.
The Landsat program is the longest-running enterprise for acquisition of satellite imagery of Earth. It is a joint NASA/USGS program that has been continuously capturing data since July 23, 1972.
Landsat satellites orbit the Earth at an altitude of approximately 705 km (438 miles), capturing scenes that are 185 km (115 miles) wide. Each pixel in a Landsat image represents an area of 30x30 meters (about the size of a baseball diamond).
Over the last five decades, Landsat sensors have evolved to capture more segments of the light spectrum. Understanding these bands is key to interpreting the imagery.
| Band # | Name | Primary Use |
|---|---|---|
| 1 | Coastal / Aerosol | Shallow water penetration, dust, and smoke detection. |
| 2 | Blue | Water depth, chlorophyll absorption. |
| 3 | Green | Peak vegetation reflection (greenness). |
| 4 | Red | Vegetation health (chlorophyll absorption). |
| 5 | Near Infrared (NIR) | Biomass content, shorelines, plant health. |
| 6 | SWIR 1 | Moisture content in soil and vegetation. |
| 7 | SWIR 2 | Geological rock formation, mineral deposits. |
| 8 | Panchromatic | 15m resolution sharpening band. |
| 9 | Cirrus | High altitude cloud detection. |
| 10 | TIRS 1 | Surface temperature (Thermal). |
| 11 | TIRS 2 | Surface temperature verification. |
Introduced the Thematic Mapper (TM) sensor, adding the Blue band for water and SWIR bands for geology.
| Band # | Name | Primary Use |
|---|---|---|
| 1 | Blue | Water body penetration. |
| 2 | Green | Vegetation vigor. |
| 3 | Red | Chlorophyll absorption. |
| 4 | Near Infrared | Biomass and shorelines. |
| 5 | SWIR 1 | Soil moisture, vegetation moisture. |
| 6 | Thermal | Surface temperature (lower resolution). |
| 7 | SWIR 2 | Geology and minerals. |
The original sensors. Note the band numbering was different (4, 5, 6, 7 instead of 1, 2, 3, 4).
| Band # | Color | Primary Use |
|---|---|---|
| 4 | Green | Sediment and vegetation. |
| 5 | Red | Cultural features (cities/roads). |
| 6 | NIR 1 | Boundary between land and water. |
| 7 | NIR 2 | Atmospheric penetration. |
This application uses Raster Functions to apply mathematical transformations to the raw data on the server side. Below is a guide to the key templates available in this dashboard.
Use: Crop monitoring and vegetation health.
Highlights agriculture in bright green. Crops appear vibrant green, bare earth appears magenta, and non-crop vegetation appears dull green. The SWIR-1 band is sensitive to moisture content in plants and soil.
Bands: Short-wave Infrared 1, Near Infrared, Blue (SWIR-1, NIR, Blue)
Use: Plant health, biomass assessment, and shoreline mapping.
Vegetation reflects near-infrared light very strongly. In this view, healthy vegetation appears bright red. Urban areas appear cyan/blue. This is the industry standard for traditional remote sensing analysis.
Bands: Near Infrared, Red, Green (NIR, Red, Green)
Use: General mapping, urban planning, and visual inspection.
Displays the imagery as the human eye would see it. DRA (Dynamic Range Adjustment) versions are recommended to enhance contrast in hazy or dark scenes.
Bands: Red, Green, Blue
Use: Fire scar mapping, mineral exploration, and penetrating smoke/haze.
SWIR bands penetrate atmospheric haze and smoke better than visible light. Hot surfaces (active fires) often appear bright red/orange. Wet soil appears dark, while dry soil is bright.
Bands: SWIR-2, SWIR-1, Red
Use: Identification of rock formations, faults, and lithology.
Particular mineral compositions reflect SWIR light differently. This combination allows geologists to distinguish between rock types that might look identical in natural color.
Bands: SWIR-2, SWIR-1, Blue
Use: Coastal water analysis, sediment mapping, and underwater features.
Uses the Coastal Aerosol band (Band 1), which is designed to penetrate shallow water. It highlights suspended sediment and can map shallow underwater topography (bathymetry).
Bands: Red, Green, Coastal
Use: Urban sprawl mapping and city boundary definition.
Man-made materials (concrete, asphalt) appear in distinct shades of magenta/red, contrasting sharply with the green of vegetation. This makes it easy to see where the city ends and nature begins.
Bands: SWIR-2, SWIR-1, Near Infrared
Use: Quantifying vegetation density and health.
A calculated scientific index.
Raw: Returns values from -1.0 to 1.0 (Black/White).
Colorized: Applies a color scale. Dark green indicates dense,
healthy vegetation. Yellow indicates sparse vegetation. Red/Brown indicates barren
land or water.
Formula: (NIR - Red) / (NIR + Red)
Use: Drought monitoring and fuel moisture levels for fire risk.
Highlights moisture content in vegetation and soil. Wet areas appear blue; dry areas appear orange. High values indicate high canopy water content (no drought stress).
Formula: (NIR - SWIR-1) / (NIR + SWIR-1)
Use: Urban Heat Island (UHI) studies and energy audits.
Uses the Thermal Infrared bands (TIRS) to estimate the temperature of the ground surface (not air temperature). Presented in degrees Celsius.
Bands: Band 10 (Thermal)