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Earth Observation

 

 

Earth Observation in the frame of EO-MINERS - Overview of remote sensing methods, sensors and applications

Remote sensing application

Agriculture - Satellite and airborne images are used as mapping tools to classify crops, examine their health and viability, and monitor farming practices. Agricultural applications of remote sensing include the following (CCRS: Tutorial: Fundamentals of Remote Sensing):

Salinity mapping
Salinity mapping in agriculturas fields in Uzbekistan (source: TAU)

 

Forestry - Forestry applications of remote sensing include the following:

Reconnaissance mapping: Objectives to be met by national forest/environment agencies include forest cover updating, depletion monitoring, and measuring biophysical properties of

Commercial forestry: Of importance to commercial forestry companies and to resource management agencies are inventory and mapping applications: collecting harvest information, updating of inventory information for timber supply, broad forest

Environmental monitoring: Conservation authorities are concerned with monitoring the quantity, health and diversity of the Earth's forests.

LiDAR-derived image
LiDAR-derived above ground carbon content for a UK deciduous woodland (source: UK Forestry Comission)

Geology - Remote sensing is used as a tool to extract information about the land surface structure, composition or subsurface, but is often combined with other data sources providing complementary measurements. Multispectral data can provide information on lithology or rock composition based on spectral reflectance. Radar provides an expression of surface topography and roughness, and thus is extremely valuable, especially when integrated with another data source to provide detailed relief.
Geological applications of remote sensing include the following:

ASTER multispectral image
ASTER multispectral sensor false colour composite image emphasising geological features inYemen (http://www.satimagingcorp.com/)

 

Hydrology - Remote sensing offers a synoptic view of the spatial distribution and dynamics of hydrological phenomena, often unattainable by traditional ground surveys. Radar has brought a new dimension to hydrological studies with its active sensing capabilities, allowing the time window of image acquisition to include inclement weather conditions or seasonal or diurnal darkness.

Examples of hydrological applications include (CCRS: Tutorial: Fundamentals of Remote Sensing):

  • wetlands mapping and monitoring,
  • soil moisture estimation,
  • snow pack monitoring / delineation of extent,
  • measuring snow thickness,
  • determining snow-water equivalent,
  • river and lake ice monitoring,
  • flood mapping and monitoring,
  • glacier dynamics monitoring (surges, ablation)
  • river /delta change detection
  • drainage basin mapping and watershed modeling
  • irrigation canal leakage detection
  • irrigation scheduling

 

Sea ice - Remote sensing data can be used to identify and map different ice types, locate leads (large navigable cracks in the ice), and monitor ice movement. With current technology, this information can be passed to the client in a very short timeframe from acquisition. Users of this type of information include the Coast Guard, port authorities, commercial shipping and fishing industries, ship builders, resource managers (oil and gas / mining), infrastructure construction companies and environmental consultants, marine insurance agents, scientists, and commercial tour operators.

Satelite sea ice
Antarctic sea ice concentration, ranging from 0 percent (purple) to 100 percent (white) on 07 August 2004. Antarctica is shown in grey, and the unfrozen ocean is shown in dark blue. Sea ice concentration was calculated from data measured by the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) sensor aboard NASA's Aqua satellite.
Image courtesy of Matt Smith, Information Technology & Systems Center, University of Alabama at Huntsville. (Source: The National Snow and Ice Data Center, USA).

Examples of sea ice information and applications include (CCRS: Tutorial: Fundamentals of Remote Sensing):

  • ice concentration
  • ice type / age /motion
  • iceberg detection and tracking
  • surface topography
  • tactical identification of leads: navigation: safe shipping routes/rescue
  • historical ice and iceberg conditions and dynamics for planning purposes
  • ice condition (state of decay)
  • wildlife habitat
  • pollution monitoring
  • meteorological / global change research

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Land cover and Land use - Resource managers involved in parks, oil, timber, and mining companies, are concerned with both land use and land cover, as are local resource inventory or natural resource agencies. Changes in land cover will be examined by environmental monitoring researchers, conservation authorities, and departments of municipal affairs, with interests varying from tax assessment to reconnaissance vegetation mapping. Governments are also concerned with the general protection of national resources, and become involved in publicly sensitive activities involving land use conflicts.

Land use applications of remote sensing include the following (CCRS: Tutorial: Fundamentals of Remote Sensing):

  • natural resource management
  • wildlife habitat protection
  • baseline mapping for GIS input
  • urban condition and expansion / encroachment
  • routing and logistics planning for seismic / exploration / resource extraction activities
  • target detection - identification of landing strips, roads, clearings, bridges, land/water interface
  • legal boundaries for tax and property evaluation
  • damage delineation (tornadoes, flooding, volcanic, seismic, fire)

 

ATLAS image
Land cover classification of Sope Creek watershed based on the Advanced Terrestrial Land Applications Sensor (ATLAS) airborne remote sensing instrument (source: http://wwwghcc.msfc.nasa.gov/land/ncrst/atlasclass.html)

 

Oceans & Coastal Monitoring - Coastlines are environmentally sensitive interfaces between the ocean and land and respond to changes brought about by economic development and changing land-use patterns. Often coastlines are also biologically diverse inter-tidal zones, and can also be highly urbanized. With over 60% of the world's population living close to the ocean, the coastal zone is a region subject to increasing stress from human activity. Government agencies concerned with the impact of human activities in this region need new data sources with which to monitor such diverse changes as coastal erosion, loss of natural habitat, urbanization, effluents and offshore pollution. Many of the dynamics of the open ocean and changes in the coastal region can be mapped and monitored using remote sensing techniques.

satellite image
This satellite image depicts a daily snapshot of fall surface water temperature patterns on the Northeast U.S. continental shelf. Cooler temperatures are represented by darker colors shading to blue. Warmer temperatures, such as those associated with the Gulf Stream are represented by the warmer colors shading to red.
(source: http://www.nefsc.noaa.gov/ecosys/ecology/Overview/)

 

Ocean applications of remote sensing include the following (CCRS: Tutorial: Fundamentals of Remote Sensing):

Atmosphere monitoring - Measurements and observations of the atmosphere (and especially the troposphere) are the most important pre-requisite to our understanding of weather and climate. Numerical models of the atmosphere have revolutionized the preparation of weather forecasts, although rather than reducing the need for observations such models have increased awareness of the importance of data through assimilation schemes. Indeed, the accuracy of forecasts relies crucially upon how well the initial state of the atmosphere can be described and this requires detailed measurements throughout the entire depth of the atmosphere.
Over the last half century, the increasing availability of low cost computers and sensors has enabled a move away from a reliance on the collection of weather data at traditional sites and enclosures. However, perhaps the greatest contribution to improving accuracy in weather prediction and monitoring is the advent of new observing systems based on satellite and airborne platforms. These technologies have completely revolutionized the networking of conventional meteorological instrumentation and have facilitated a colossal advance in both the spatial and temporal scale of weather measurement (Chapman et. al 2011)
Satellite systems provide a unique opportunity to monitor Earth-atmosphere system processes and parameters continuously. In view of the great benefit provided by spaceborne Earth-atmosphere remote sensing, there were strong efforts to construct Earth observing satellite systems in the past. Satellite based observations of the Earth and the atmosphere started with the first meteorological satellite, the Television InfraRed Observation Satellite (TIROS-1), launched in 1960. During the following decades several satellite systems with different sensors provided data for a wide range of atmospheric parameters that enhanced our understanding of Earth-atmosphere processes and dynamics. Nowadays, operational satellite systems provide invaluable measurements of atmospheric parameters at regular intervals on a global scale (Thies and Bendix, 2011).

Meteorological parameters measured by remote sensing

Infrared geostationary satellite image
Cloud Classification image based on an Infrared geostationary satellite (source: http://www.satmos.meteo.fr/html_en/Archive_CT_MSG.html).

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