In This Space
Image credit: ACRI-ST and Hatfield Consultants
Water Quantity & Quality
To understand environmental baseline conditions in remote areas with many water bodies, summary information on water bodies and their baseline trophic status can be retrieved and monitored using EO. This would typically be achieved through in-situ sampling programs, but the sheer number of lakes in some regions can make this is impossible to achieve.
Productivity of the water bodies can be indirectly assessed by measuring parameters such chlorophyll-a (Chl-a), total phosphorus (TP), total nitrogen (TN) and Secchi disk depth (SDD).
Chl-a concentration is a good descriptor for biological productivity and can be related linearly to biomass as a function of species composition, light adaptation, age of an algae community, and nutrient supply to the cells. Chl-a shows distinct absorption in the blue and red bands of multi-spectral optical satellite imagery, which is the basis for generation of Chl-a products. Maximum reflectance can be observed in the green band. Also the near-infrared band is correlated to the amount of Chl-a.
The SDD parameter expresses transparency of the water and is correlated to the spectral response of multi-spectral optical satellite imagery (e.g., Landsat). It can be assessed by using, for example, a blue/green satellite band ratio.
Improved multi- and hyperspectral sensors (e.g., EnMap) will increase discrimination of Chl-a and SDD parameters.
The water body nutrients product delivers value coded areas (raster) estimating chlorophyll-a and Secchi disk depth as surrogates for biological productivity. A report provides summary statistics on productivity for each water body identified.
Known restrictions / limitations
Retrieval of Chl-a and SDD data must be based on multi-spectral optical data that are adequately corrected before statistical analysis can be carried out. In quantitative studies, the interactions of incident energy with the atmosphere are large enough to significantly affect the incoming radiance. This is particularly important for surfaces like water, where the reflected light fraction is very low: around 1-10% of the sensor-measured radiance. As a consequence, the sensor-recorded radiance of the lake surface can be very low compared to the path radiance.
Lifecycle stage and demand
Pre-License and Exploration: When a company is considering exploration in a new remote area, baseline information on water bodies is useful.
Development: When development is being planned, a company will requires detailed information about the water bodies in the region, including assessing overall productivity and sensitivity. Lakes and rivers may be impacted by oil and gas operations and may become the receiving environment for produced water.
Production: Ongoing monitoring of a range of water quality parameters will be required to assess potential environmental impacts of oil and gas production on water bodies. This would typically be based on in-situ monitoring, but EO data can extend such monitoring.
Decommissioning: Ongoing calculations of water body nutrients as a part of environmental monitoring required post-production.
Geographic coverage and demand
Coverage and demand is global, but focused on remote regions with numerous lakes (e.g., Alaska, Canada).
Input data sources
Optical: VHR2, HR1, HR2, MR1, MR2
Multispectral mode is necessary to extract nutrients information; panchromatic bands are not used.
Supporting data: Limnological in-situ measurements
Spatial resolution and coverage
Spatial resolution: 1–300 m.
Varies depending on input imagery used and client needs. Available data may cover all scales: regional (15 – 30 m); basin (2.5 – 15 m); and licence/project (0.25 – 2.5 m).
Minimum Mapping Unit (MMU)
Variable, depending on source data resolution. An MMU as small as 0.25 ha is possible using VHR2.
Accuracy / constraints
Thematic accuracy: Depends on the parameter and sensor used for its calculation.
Spatial accuracy: The goal would be 1 pixel, but depends on reference data.
Accuracy assessment approach & quality control measures
Retrieval of Chl-a and SDD needs to be calibrated with in-situ limnological measurements.
Frequency / timeliness
Observation frequency: Depending on the sensor, starting from daily acquisitions (MODIS) to weekly or monthly based on sensors such as RapidEye and Landsat (dependent on cloud cover). It is unlikely that regular monitoring will be needed for inland water bodies, unless as part of construction monitoring or in response to a spill.
Timeliness of delivery: Processing can be completed in near real time (< 24 hours).
On-demand availability from commercial suppliers.
New acquisitions can be requested globally (VHR2, HR1).
HR2 and MR2 products available for public search.
Delivery / output format
Hatfield Consultants / SRC
OTM / GeoVille
# of Pages:
Internal – Project consortium and science partners
External – ESA
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