Monitoring of turbid coastal and inland waters by airborne imaging spectrometer AISA

Kutser, T.; Hannonen, T.; Kallio, Kari; Koponen, Sampsa; Pulliainen, Jouni; Pyhälahti, Timo; Servomaa, Henri

doi:10.1109/igarss.1998.702290

Cited by 4 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…NIKLAS STRÖMBECK(2001) described various methods to estimate the content of CDOM, phytoplankton and suspend sediments in the water body through making use of AISA+, for monitoring water quality of Sweden lake and water body in littoral [2] . Kutser(1998) et al compared the spectrum of chlorophyll, suspended sediments and TOC obtained in the laboratory and from AISA to carry on monitoring the turbid littoral and the inland water body [3] . Pekka et al (2001) simulated TM data through AISA spectrum and performed regression verification, for assistance to water quality monitoring [4] .…”

Section: Domestic and International Applicationmentioning

confidence: 99%

Inflight experimentation and preliminary marine application of AISA+ in Chinese coastal zone

Wang¹,

Pan²,

Gong³

et al. 2006

Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications

View full text Add to dashboard Cite

Airborne remote sensing has the characteristics of flexible action, wide coverage area and high space resolution, and the hyper-spectral scanner is of very high spectral resolution with more than two hundreds channels in the visible light domain, containing large amount of information, which has tremendous potential in marine application. In 2005, an airborne hyper spectral system AISA+ made by Specim Co. Finland has been tested onboard the Chinese Marine Surveillance Plane. After experimentation and processing with ENVI and some own algorithms, sea surface suspended material is retrieved plus other water quality parameters, showing its application in ocean remote sensing.In this paper, we describe the system futures and experimentation, and then explain the performing of data processing. Some products, such as sea surface suspended material concentration and chlorophyll concentration and other ocean color parameters have been obtained. The preliminary result shows that hyper spectral system AISA+ is of much use for marine surveillance, but more technologies are required to develop for monitoring water quality by AISA+.

show abstract

Section: Domestic and International Applicationmentioning

confidence: 99%

Inflight experimentation and preliminary marine application of AISA+ in Chinese coastal zone

Wang¹,

Pan²,

Gong³

et al. 2006

Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications

View full text Add to dashboard Cite

show abstract

“…The empirical approach aims at establishing a statistical relationship between spectral variables (e.g. reflectance, reflectance ratio or derivative) and the CYB pigments [1][2][3][4][5][6][7][8][9][10][11][12]. However, the performance of varying empirical approaches is dataset dependent because of the variation of imaging and water conditions [e.g., [13][14].…”

Section: Introductionmentioning

confidence: 99%

Cyanobacteria in Inland Waters: Remote Sensing

Li¹

2020

Fresh Water and Watersheds

View full text Add to dashboard Cite

“…These locally based measurements of biological and/or physical (biophysical) variables (such as forest structure, foliar chemistry, algae concentration or coral bleaching) will typically be used as inputs to environmental process models (Jupp 1998). Remotely sensed images can capture landscape heterogeneity and are an important tool for providing spatially distributed biophysical variables to drive these models (Saint 1996;Asner, Wessman et al 1997;Kutser, Hannonen et al 1998). This project will attempt to develop approaches for scaling-up remotely sensed data to estimate biophysical variables, by incorporating an understanding of the nature of electromagnetic radiation and various sensors, the application of geostatistical theory to digital images and the development of robust biophysical modelling tools.…”

Section: Key Pointsmentioning

confidence: 99%

A methodology for scaling biophysical models

Scarth

View full text Add to dashboard Cite

The science of remote sensing is based on analyses of the spectral and spatial information contained in electromagnetic radiation reflected or emitted from the earth's surface. The development of predictive analytical and semianalytical models defining radiative-transfer processes associated with earth surface processes and structures are based on the relationship between the biophysical variables of interest and the signal received by an airborne or satellite sensor. This forward modelling approach provides a mathematical basis to enable researchers to understand and predict the relationships between an object's properties and the resulting digital image. Of greater interest to environmental managers is the inverse problem, where the object properties are estimated from the remotely sensed image data. The availability of this type of information facilitates monitoring and management of terrestrial and aquatic environments. Due to the complex and often non-linear nature of the interactions modelled in the forward approach, the inversion of such a model is often ill-posed, resulting in a solution that is not unique or not a continuous function of the data. This uncertainty limits the efficacy of remotely sensed data for repeatable and robust environmental monitoring, which is unfortunate given the scope and relatively low cost of this product.Although significant research into spatial scaling and data integration has been completed, there has been limited work into scale integration of spectral and spatial data for multiple scale linkage and estimation of biophysical variables. This dissertation, through an analysis of the spatial and spectral dimensions of digital images, endeavours to mitigate the difficulties involved in model inversion by establishing a generic framework to generate well-posed extensions to previously ill-posed biophysical inverse problems, resulting in a solution that is unique and depends continuously on the data.

show abstract

Monitoring of turbid coastal and inland waters by airborne imaging spectrometer AISA

Cited by 4 publications

References 4 publications

Inflight experimentation and preliminary marine application of AISA+ in Chinese coastal zone

Inflight experimentation and preliminary marine application of AISA+ in Chinese coastal zone

Cyanobacteria in Inland Waters: Remote Sensing

A methodology for scaling biophysical models

Contact Info

Product

Resources

About