The Landsat program is the longest-running enterprise for acquisition of satellite imagery of Earth — a joint NASA/USGS program continuously capturing data since July 23, 1972. Landsat satellites orbit at ~705 km altitude capturing scenes 185 km wide, with each pixel representing a 30×30 m ground area.
Over five decades Landsat sensors evolved to capture more of the electromagnetic spectrum. Understanding these bands is key to interpreting imagery.
| Band | Name | Primary Use |
|---|---|---|
| 1 | Coastal / Aerosol | Shallow water, dust, smoke detection |
| 2 | Blue | Water depth, chlorophyll absorption |
| 3 | Green | Peak vegetation reflection |
| 4 | Red | Vegetation health (chlorophyll absorption) |
| 5 | Near Infrared (NIR) | Biomass, shorelines, plant health |
| 6 | SWIR 1 | Moisture content in soil and vegetation |
| 7 | SWIR 2 | Geological formations, mineral deposits |
| 8 | Panchromatic | 15 m 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) — defined the 30 m standard.
| 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 and vegetation moisture |
| 6 | Thermal | Surface temperature |
| 7 | SWIR 2 | Geology and minerals |
Original Multispectral Scanner (MSS) at 60 m resolution. Bands numbered 4–7.
| Band | Color | Primary Use |
|---|---|---|
| 4 | Green | Sediment and vegetation |
| 5 | Red | Cultural features (cities, roads) |
| 6 | NIR 1 | Land/water boundary |
| 7 | NIR 2 | Atmospheric penetration |
Templates apply Raster Functions — server-side mathematical transformations to the raw data. Select a template from the sidebar to apply it.
Use: Crop monitoring and vegetation health.
Highlights agriculture in bright green. Crops appear vibrant green, bare earth appears magenta. The SWIR-1 band is sensitive to moisture content in plants and soil.
Bands: SWIR-1, NIR, Blue
Use: Plant health, biomass assessment, shoreline mapping.
Vegetation reflects near-infrared light strongly — healthy vegetation appears bright red. Urban areas appear cyan/blue. Industry standard for traditional remote sensing.
Bands: NIR, Red, Green
Use: General mapping, urban planning, visual inspection.
Displays imagery as the human eye would see it. DRA (Dynamic Range Adjustment) versions enhance contrast in hazy or dark scenes.
Bands: Red, Green, Blue
Use: Fire scar mapping, mineral exploration, smoke/haze penetration.
SWIR bands penetrate atmospheric haze better than visible light. Hot surfaces (active fires) appear red/orange. Wet soil is dark, dry soil is bright.
Bands: SWIR-2, SWIR-1, Red
Use: Identification of rock formations, faults, and lithology.
Mineral compositions reflect SWIR light differently, allowing geologists to distinguish rock types that look identical in natural color.
Bands: SWIR-2, SWIR-1, Blue
Use: Coastal water analysis, sediment mapping, underwater features.
Uses the Coastal Aerosol band (Band 1) designed to penetrate shallow water, highlighting suspended sediment and shallow underwater topography.
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.
Bands: SWIR-2, SWIR-1, NIR
Use: Quantifying vegetation density and health.
A calculated scientific index.
Raw: Values from −1.0 to 1.0 (black and white).
Colorized: Dark green = dense healthy vegetation · Yellow = sparse · Red/Brown = barren or water.
Formula: (NIR − Red) / (NIR + Red)
Use: Drought monitoring, fuel moisture levels, fire risk.
Highlights moisture content in vegetation and soil. Wet areas appear blue; dry areas appear orange. High values = high canopy water content.
Formula: (NIR − SWIR-1) / (NIR + SWIR-1)
Use: Urban Heat Island studies, energy audits.
Uses the TIRS thermal bands to estimate ground surface temperature (not air temperature), presented in degrees Celsius.
Bands: Band 10 (Thermal Infrared)
| Processing Template | Live Pixel Analysis |
|---|---|
| Runs on Esri's servers before the image is delivered to your browser | Runs in your browser, pixel-by-pixel, as tiles arrive |
| Preset composites: Agriculture, Color Infrared, SWIR, Geology, etc. | Scientific indices you control: NDVI, NDMI, NBR, NDWI, NDBI, BSI, NDSI, Thermal |
| Output is a rendered RGB image — bands are already baked in | Works directly on raw sensor band values (all 11 bands for Landsat 8/9) |
| Fast — no extra computation in the browser | Real-time — re-computes instantly as you move the threshold slider |
| Active when: Analysis Mode is set to — Off — | Active when: Any mode other than — Off — is selected |
| Compatible with all imagery layers | Pauses the Processing Template — both cannot run simultaneously |
🗂️ The 4 Imagery Layers — Don't Miss This
This application contains four separate Landsat imagery layers, each captured at a different date. They are all loaded into the map simultaneously but only one is active at any time. The active layer is what both the Processing Template and Live Pixel Analysis actually operate on.
🎚️ The Threshold Slider
Every mode exposes a threshold slider whose meaning changes depending on the mode:
| Slider Type | How It Works |
|---|---|
| Mask modes (NDVI Mask, NBR, NDWI, NDBI, BSI, NDSI) | Sets the cut-off value. Pixels above or below the threshold change color to indicate detection. Raise the value to tighten the detection; lower it to be more inclusive. |
| Colormap modes (NDVI Color, NDMI) | Sets the reference breakpoint in the gradient. Pixels are colored across a continuous spectrum — the slider shifts where "neutral" falls on the scale. |
| Thermal | Shifts the midpoint of the heat colormap. Slide left (−) to reveal subtle cool differences; slide right (+) to emphasize hotter surfaces. |
The slider updates the map in real time as you drag — no need to release.
Use: Isolate living vegetation above a density threshold.
Computes the Normalized Difference Vegetation Index per pixel. Pixels at or above the threshold are rendered in a yellow-to-deep-green gradient (sparse → dense vegetation). Pixels below the threshold — water, bare soil, urban — are rendered transparent, letting the basemap show through. This is the fastest way to instantly see where vegetation exists and how dense it is.
Formula: (NIR − Red) / (NIR + Red) · Bands 5 & 4
Slider: NDVI Threshold — default 0.20. Raise to show only denser canopy; lower to include sparse cover.
Reading the map: Bright green = dense healthy forest · Yellow-green = sparse or stressed vegetation · Transparent = non-vegetated
Use: Visualize the full NDVI spectrum from water to dense forest in one view.
Every pixel is assigned a color based on its NDVI value — nothing is hidden. Water and very bare surfaces (strong negative NDVI) appear black. As NDVI rises through bare soil, sparse scrub, and healthy canopy, the colormap shifts through grey → yellow → light green → vivid green. Unlike the Vegetation Mask, this mode shows you the full gradient across the scene.
Formula: (NIR − Red) / (NIR + Red) · Bands 5 & 4
Slider: Breakpoint — shifts where "neutral" (0.0) falls in the gradient, allowing you to stretch contrast into a specific vegetation density range.
Use: Drought monitoring, canopy water content, pre-fire fuel moisture.
The Normalized Difference Moisture Index (also called NDWI-vegetation) measures water content held in plant leaves and soil using NIR and SWIR-1. High positive values (blue) indicate well-hydrated vegetation. Low or negative values (orange) indicate drought stress, dry fuel, or bare ground — areas at elevated fire risk.
Formula: (NIR − SWIR-1) / (NIR + SWIR-1) · Bands 5 & 6
Slider: NDMI Threshold — default 0.00. Pixels above are colored blue (moist); pixels below are colored orange (stressed).
Use: Wildfire burn scar mapping, post-fire recovery monitoring.
NBR is the definitive index for wildfire analysis. Healthy vegetation reflects strongly in NIR and absorbs SWIR-2. Burned areas flip this relationship — they absorb NIR and reflect SWIR-2. Pixels below the threshold appear red-to-orange (burned / severely impacted); pixels above appear yellow-to-green (healthy or recovering vegetation). Apply this mode to imagery captured before and after a fire to quantify the burn extent.
Formula: (NIR − SWIR-2) / (NIR + SWIR-2) · Bands 5 & 7
Slider: NBR Threshold — default 0.10. Lower values flag more area as burned; raise to detect only the most severely burned cores.
Use: Open water body detection, flood mapping, coastline delineation.
The Normalized Difference Water Index (McFeeters 1996) uses Green and NIR to highlight open surface water. Water reflects green light and absorbs NIR; vegetation does the opposite. Pixels at or above the threshold render in light-to-deep blue (shallow → deep water). Land pixels below the threshold render in tan/brown. Extremely useful for flood extent mapping — compare layers from before and after a flood event.
Formula: (Green − NIR) / (Green + NIR) · Bands 3 & 5
Slider: NDWI Threshold — default 0.00. Lower the threshold to detect turbid or shallow water that a strict cutoff would miss.
Use: Urban extent mapping, impervious surface detection, sprawl analysis.
The Normalized Difference Built-up Index exploits the fact that urban materials (concrete, asphalt, metal roofing) reflect SWIR-1 more than NIR — the inverse of vegetation. Pixels at or above the threshold render magenta/pink (built-up area). Vegetated pixels render green. This mode is excellent for quantifying urban growth by comparing different layer years.
Formula: (SWIR-1 − NIR) / (SWIR-1 + NIR) · Bands 6 & 5
Slider: NDBI Threshold — default 0.00. Raise to select only the most reflective (densest) urban surfaces; lower to include suburban and low-density development.
Use: Agricultural soil monitoring, erosion mapping, land degradation assessment.
The Bare Soil Index combines SWIR-1, Red, NIR, and Blue to separate exposed soil from vegetated surfaces. It is more specific than NDVI for discriminating between bare agricultural fields, construction sites, and desertification. Pixels above the threshold render orange-brown (exposed/dry soil); pixels below render green (vegetated).
Formula: ((SWIR-1 + Red) − (NIR + Blue)) / ((SWIR-1 + Red) + (NIR + Blue)) · Bands 6, 4, 5, 2
Slider: BSI Threshold — default 0.00. Particularly useful in spring before crop emergence to map field boundaries.
Use: Snowpack extent, glacier mapping, seasonal snow cover tracking.
Snow and ice reflect Green light intensely but absorb SWIR-1 — giving them a strong positive NDSI. Pixels at or above the threshold render cyan-to-white (patchy → deep snowpack). Terrain and vegetation render grey-brown. The standard detection threshold of 0.40 is used by MODIS and USGS for operational snow products and is the default here.
Formula: (Green − SWIR-1) / (Green + SWIR-1) · Bands 3 & 6
Slider: NDSI Threshold — default 0.40 (scientific standard). Lower to detect patchy or melting snow; raise if clouds are being misclassified as snow.
Use: Urban Heat Island analysis, thermal pollution, land surface temperature mapping.
Uses Landsat 9's TIRS Band 10 (10.6–11.2 µm). Because raw thermal DN values vary between scenes, the app performs a per-tile normalization — it finds the minimum and maximum thermal values in each tile and stretches them across a blue → cyan → green → yellow → red colormap. This ensures consistent rendering even when switching between layers from different seasons. Cool surfaces (water, forest) appear blue; warm surfaces (bare soil, asphalt, industrial areas) appear yellow-red.
Band: TIRS 1 — Band 10 (Thermal Infrared, 100 m resampled to 30 m)
Slider: Heat Contrast — shifts the colormap midpoint. Slide left (−) to pull out cool-surface detail; slide right (+) to emphasize hot-surface differences. Default 0.00 = balanced stretch.
⚠️ Not available for Landsat 1–3 (MSS) or Landsat 4–7 (TM) layers — thermal band numbering differs. The app will auto-detect and display a warning if the active layer lacks thermal data.