/pdf/remote-sensing-of-the-environment-4yfxjaaswe.pdf

Remote sensing of the environment

https://dspace.stir.ac.uk/bitstream/1893/21536/1/RSE-IW-special-issue_Intro-FINAL-09-09-2014.pdf

Remote sensing of inland waters: challenges, progress and future directions

The empirical approach of remote sensing has a proven capability to provide timely and accurate information on inland and near-coastal transitional waters. This article gives a thorough review of empirical algorithms for quantitatively estimating a variety of parameters from space-borne, airborne and in situ remote sensors in inland and transitional waters, including chlorophyll-a, total suspended solids, Secchi disk depth (z SD), turbidity, absorption by coloured dissolved organic matter (a CDOM) and other parameters, for example, phycocyanin. Current remote-sensing instruments are also reviewed. The theoretical basis of the empirical algorithms is given using fundamental bio-optical theory of the inherent optical properties (IOPs). Bands, band ratios and band arithmetic algorithms that could be used to produce common biogeophysical products for inland/transitional waters are identified. The article discusses the potential role that empirical algorithms could play alongside more advanced model-based algo...

A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters

https://www.calmit.unl.edu/people/agitelson2/pdf/2012/2012-RSE-Water-review.pdf

Review of constituent retrieval in optically deep and complex waters from satellite imagery

Aquatic vegetation is an important component of wetland and coastal ecosystems, playing a key role in the ecological functions of these environments. Surveys of macrophyte communities are commonly hindered by logistic problems, and remote sensing represents a powerful alternative, allowing comprehensive assessment and monitoring. Also, many vegetation characteristics can be estimated from reflectance measurements, such as species composition, vegetation structure, biomass, and plant physiological parameters. However, proper use of these methods requires an understanding of the physical processes behind the interaction between electromagnetic radiation and vegetation, and remote sensing of aquatic plants have some particular difficulties that have to be properly addressed in order to obtain successful results. The present paper reviews the theoretical background and possible applications of remote sensing techniques to the study of aquatic vegetation.

Remote sensing of aquatic vegetation: theory and applications

https://www.geo.uzh.ch/microsite/rsl-documents/research/publications/peer-reviewed-articles/2010_Guanter_Ruiz_Atmospheric_Correction_Manusk-2853774336/2010_Guanter_Ruiz_Atmospheric_Correction_Manusk.pdf

Atmospheric correction of ENVISAT/MERIS data over inland waters: Validation for European lakes

https://www.zora.uzh.ch/id/eprint/29858/2/Odermatt_Giardino_Chlorophyll_MERIS_Manusk_2010_AM_V.pdf

Chlorophyll retrieval with MERIS Case-2-Regional in perialpine lakes

Research, monitoring and management of large marine protected areas require detailed and up-to-date habitat maps. Ningaloo Marine Park (including the Muiron Islands) in north-western Australia (stretching across three degrees of latitude) was mapped to 20 m depth using HyMap airborne hyperspectral imagery (125 bands) at 3.5 m resolution across the 762 km2 of reef environment between the shoreline and reef slope. The imagery was corrected for atmospheric, air-water interface and water column influences to retrieve bottom reflectance and bathymetry using the physics-based Modular Inversion and Processing System. Using field-validated, image-derived spectra from a representative range of cover types, the classification combined a semi-automated, pixel-based approach with fuzzy logic and derivative techniques. Five thematic classification levels for benthic cover (with probability maps) were generated with varying degrees of detail, ranging from a basic one with three classes (biotic, abiotic and mixed) to the most detailed with 46 classes. The latter consisted of all abiotic and biotic seabed components and hard coral growth forms in dominant or mixed states. The overall accuracy of mapping for the most detailed maps was 70% for the highest classification level. Macro-algal communities formed most of the benthic cover, while hard and soft corals represented only about 7% of the mapped area (58.6 km2). Dense tabulate coral was the largest coral mosaic type (37% of all corals) and the rest of the corals were a mix of tabulate, digitate, massive and soft corals. Our results show that for this shallow, fringing reef environment situated in the arid tropics, hyperspectral remote sensing techniques can offer an efficient and cost-effective approach to mapping and monitoring reef habitats over large, remote and inaccessible areas.

/pdf/ningaloo-reef-shallow-marine-habitats-mapped-using-a-2dpu5x7hl8.pdf

Ningaloo reef: shallow marine habitats mapped using a hyperspectral sensor.

A physically based algorithm is used for automatic processing of MERIS level 1B full resolution data. The algorithm is originally used with input variables for optimization with different sensors (i.e. channel recalibration and weighting), aquatic regions (i.e. specific inherent optical properties) or atmospheric conditions (i.e. aerosol models). For operational use, however, a lake-specific parameterization is required, representing an approximation of the spatio-temporal variation in atmospheric and hydrooptic conditions, and accounting for sensor properties. The algorithm performs atmospheric correction with a LUT for at-sensor radiance, and a downhill simplex inversion of chl-a, sm and y from subsurface irradiance reflectance. These outputs are enhanced by a selective filter, which makes use of the retrieval residuals. Regular chl-a sampling measurements by the Lake's protection authority coinciding with MERIS acquisitions were used for parameterization, training and validation.

/pdf/water-quality-monitoring-for-lake-constance-with-a-2kge5o2xzs.pdf

Water Quality Monitoring for Lake Constance with a Physically Based Algorithm for MERIS Data

An operational satellite-based approach was implemented to monitor turbidity and organic absorption in the Mekong river system. Using physics-based algorithms linked together in a fully automated processing chain, more than 300 Landsat Enhanced Thematic Mapper (ETM) scenes and 1000 MODIS scenes, representing five years of data, were used to produce standardized, quantitative time series of turbidity and organic absorption across Vietnam, Thailand, Cambodia, Laos, and China. To set up this system, the specific inherent optical properties (SIOPs) of the Mekong river system were determined through three separate field campaigns, laboratory analysis, and subsequent optical closure calculations. Following this, a range of satellite data types was tested using the derived Mekong-specific inherent optical properties, including Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m data, Landsat ETM, Medium Resolution Imaging Spectrometer (MERIS), Satellite Pour l’Observation de la Terre (SPOT) 5, RapidEye, ...

Thomas Heege

Papers

Atmospheric correction of ENVISAT/MERIS data over inland waters: Validation for European lakes

Chlorophyll retrieval with MERIS Case-2-Regional in perialpine lakes

Ningaloo reef: shallow marine habitats mapped using a hyperspectral sensor.

Water Quality Monitoring for Lake Constance with a Physically Based Algorithm for MERIS Data

Operational multi-sensor monitoring of turbidity for the entire Mekong Delta