ENV103 Chap.11 Remote Sensing and Raster Analysis
Remote Sensing and Raster Analysis
Remote sensing measures electromagnetic radiation from a surface without touching it. This chapter covers the ground, sky and space platforms, how surfaces reflect different wavelengths, active and passive sensors, the four resolutions, image enhancement and the sea-level case, then moves into Lab 4's raster work: hillshade, slope and writing a raster calculator expression for site selection.
Worked arithmetic covers revisit rates and a slope reclassification, the two places where remote sensing and raster analysis most often turn into numbers.
What this chapter covers
- 01
Ground, sky and space platforms
- 02
Electromagnetic radiation and reflectance
- 03
Active and passive sensors
- 04
Spatial, spectral, temporal and radiometric resolution
- 05
Histogram stretching and enhancement
- 06
Satellite altimetry and sea-level rise
- 07
Hillshade, slope and the raster calculator
Worked example · free
Compare image counts from three revisit rates
- +1Sentinel-1: 24 ÷ 12 = 2 images.
- +1MODIS: 24 days × 1 per day = 24 images.
- +1GOES: 24 × 24 hours × 4 per hour = 2,304 images.
- +1Each step up in revisit rate multiplies the coverage of a fast event, but frequent imaging usually comes with coarser spatial detail, so the choice depends on the question.
Key terms
- Remote sensing
- Remote sensing is measuring electromagnetic radiation from a surface or object without touching it.
- Active sensor
- An active sensor emits its own signal and measures the return, as radar and LiDAR do.
- Passive sensor
- A passive sensor records radiation that is already available, such as reflected sunlight.
- Temporal resolution
- Temporal resolution is how often a sensor images the same place.
- Histogram stretch
- A histogram stretch spreads a narrow range of pixel values across the full display range to reveal detail.
- Hillshade
- A hillshade is a shaded-relief raster calculated from an elevation model to show terrain.
- Raster calculator
- The raster calculator applies an expression to cell values to create a new raster, such as a 1 or 0 suitability layer.
- Satellite altimetry
- Satellite altimetry measures sea-surface height by timing radar echoes from an orbiting satellite.
Remote Sensing and Raster Analysis FAQ
Which four resolutions describe remote-sensing data?
Spatial resolution is the ground size of a pixel, spectral resolution the number and width of wavelength bands, temporal resolution how often a place is imaged, and radiometric resolution how finely brightness is recorded. They interact, so improving one often means accepting less of another.
What does the raster calculator return for a condition?
It evaluates the condition for every cell and returns 1 where it is true and 0 where it is false, so a comparison such as elevation above a threshold becomes a yes or no layer. Two conditions joined with AND keep only cells meeting both. Lab 4 asks you to write your own expression for its condition.
Why put the hillshade above the elevation layer?
The hillshade adds the impression of relief, and at 30% transparency it lets the elevation colours show through. If it sat below an opaque elevation layer it would be hidden, so layer order matters in the finished Lab 4 elevation map.
Where can I find free satellite imagery?
The Week 6 online session points to NASA Earthdata Search, the European Space Agency's explorer, the LINZ Data Service and Google Earth Engine. Its activity uses LINZ to download Sentinel-2 imagery for 2023 to 2024 over your home town, which you can then open in QGIS. The poster brief also lists Sentinel Hub and Earth Engine for NDVI and land-cover data.
Assessment move
Learn remote sensing from the physics outward. Start with the single idea that sensors measure radiation from a distance and that different surfaces reflect different wavelengths, then add the active and passive distinction with one example each from the course. Draw the holy trinity of platforms as three rows, ground, sky and space, and list the sensors the lecture placed on each.
Make a four-row table of the resolutions with a definition and a trade-off for each, and practise converting revisit intervals into image counts, as in the worked example, so temporal resolution has numbers attached. Rehearse the sea-level story as a short paragraph: the problem, why tide gauges are not enough, how altimetry works and what the anomalies show.
For Lab 4, practise the raster workflow in QGIS: load the elevation raster, create slope and hillshade, set the hillshade to 30% transparency above the elevation, write and test your own raster calculator expression, and check how the 1 and 0 values display.
Finally, try the Week 6 online activity of downloading Sentinel-2 imagery for a place you know from the LINZ Data Service; working with your own area makes the resolutions memorable and gives you practice for finding extra data for the poster.