Remote Sensing

On board the satellite platform is a sensor called a thematic mapper. The earth's rotation below the satellite allows this sensor to scan a new area of the planet's surface with each consecutive pass. The width of the area scanned, called the swath, is determined by the resolution of particular satellite.(4)

The thematic mapper detects the solar energy reflected off the earth's features as well as the earth's own thermal energy on a number of well-defined light bands of the electromagnetic spectrum. For the bands sensing reflected light, the sensor can distinguish spatial features at a resolution of 30 m per pixel for the older Landsat-5 satellite platforms and 10m per pixel for the newer SENTINEL-2 platforms. This means that features 30 m in size are identifiable for Landsat-5, while SENTINEL-2 can pick up objects 10m in size. Regarding the temporal resolution, Landsat has a revisit period of 16 days, unlike Sentinel, which is only 5 days. The thematic mapper's thermal channel, however, identifies features at the much lower resolution of up to 120 m. The energy detected by the sensor is recorded electronically, not on photographic film. The images produced by remote sensing are not photographs.

Because various features on the earth's surface interact with and reflect solar energy differently in the various bands, the thematic mapper can be used to identify clearly a broad range of elements of land cover and marine flora and fauna. For example, water absorbs near-infrared light, so the ocean looks very dark in the near-infrared band. Vegetation, including forests on land and kelp forests in the ocean, reflects near-infrared light and therefore looks much brighter than water and provides a nice contrast for mapping kelp. The thematic mapper's fourth band detects reflected energy in this range, so it is particularly useful for identifying and mapping vegetation in a given area. Data from the thematic mapper are transmitted to stations on the ground.

Here are just a few of the multitude of uses of remote sensing

• Meteorology - profiling of atmospheric temperature, pressure, water vapor, and wind velocity.

• Oceanography-measuring Sea surface temperature, mapping ocean currents, and wave energy.

• Glaciology - measuring ice cap volumes, ice stream velocity, and sea ice distribution.

• Geology - identification of rock type, mapping faults and structure.

• Geodesy - measuring the figure of the earth and its gravity field.

• Topography and cartography - improving digital elevation models for the development of better maps.

• Agriculture, forestry, and botany - monitoring the biomass of land vegetation, monitoring the health of crops, forecasting crop yields.

• Hydrology - assessing water resources from snow, rainfall and underground
  aquifers.

• Disaster warning and assessment - monitoring of floods, landslides and fires and monitoring volcanic activity, assessing damage zones from natural disasters.

• Planning applications - mapping ecological zones, monitoring deforestation, monitoring urban land use.

• Oil and mineral exploration - locating natural oil seeps and slicks.

• Military - developing precise maps for planning, monitoring military infrastructure, monitoring ship and troop movements . . . Unfortunately, this is where most of the Worlds Government funding for remote sensing goes.

Using remote sensing in marine environments can be a little more complicated that looking at features on the land surface. The reason for this is because water reflects light differently and this can cause a number of complications in find the ideal image to use as well as in processing it, down the line.

Some of these complications include: (5)

• Tides - the deeper you go under water, the harder it is to see objects and organisms on the seafloor, this means that if an image is take during high tide instead of low tide, you might not be able to accurately assess the seafloor, which makes the identification of species like kelp and corals more difficult.

• Glint - sunlight is reflected off the surface of the water, which can picked up by the satellite and obscure your image. The shape and slope of the waves effect the glint off the water surface.

• Turbidity - if there has been a recent storm, it can cause resuspension of sediments off the seafloor. This can block you from being able to sea the through to the seafloor because the satellite will pick up the sediments in the water instead.

• Atmospheric conditions - like cloud cover cover cover the areas of the sea you might be looking at. They can also cause reflection back to the satellite and block your view.

• Pixel size compared to the size of the kelp - often, due the resolution of the satellite, the pixel size is much larger than the size of each individual kelp plant. This means that you often need a dense stand of kelp to be able to pick it up accurately.

So, in an ideal world we would like an image which was taken during a period with no cloud cover, clear water conditions, a flat sea surface and at low tide. Otherwise, you will need to account for these different aspects when processing your images.

A number of different tools have been developed over the years to help process remote sensing satellite images.

Here are an example of a few different software packages scientist can use.

1. ACOLITE(6) - can be used to process Landsat (5/7/8) and Sentinel-2 (A/B) images. and can be used for coastal and inland water applications. A great feature is that it is able to perform the atmospheric correction by default.

2. SNAP(7) - stands for the Sentinel Application Platform. It is a open toolbox for processing products from a variety of satellite missions such as Copernicus Sentinel-1, Sentinel-2 and Sentinel-3. It uses its multimission ground systems to acquire, process, distribute and archive data from satellites owned by other organisations.

3. QGIS(8) - open access mapping software, which can be used to visualise products from processing your satellite images.