Harald Krawczyk

Investigation of interpretation possibilities of spectral high-dimensional measurements by means of principal component analysis: a concept for physical interpretation of those measurements

Subject of the paper is the investigation of the information content of high dimensional multispectral remote-sensing measurements in the VIS-NIR region for ocean-atmosphere problems. The final goal of such measurements is the separation of atmospheric influence and the retrieval of detailed information of water constituents. Primary questions appearing during interpretation process are: how many independent parameters can be found from the measurements? what is the physical sense of these parameters? what is the accuracy of the parameters? One has to take into account that the properties of the measuring device, like channel position, bandwidth, number of channels and measurement accuracy have a great influence on the interpretation. One possible method to get answers to the above questions is the Principle Component Analysis (PCA). A problem in PCA is the physical interpretation of the mathematically obtained results - Eigenvalue, Eigenvector and Principle Components. Because the results of PCA interpretation depend on the statistical properties of the measurement data, they must be mapped back to the absolute measurement quantities (radiances). To get a physical interpretation of the PCA results a detailed investigation with a simulated data set using a simplified (but nonlinear) model was realized (atmosphere after Gordon, Sturm, water reflectances after Sathyendranath, Morel, Prieur). It will be presented a concept, how in-situ measurements can be involved into interpretation model with PCA.

Regional products for the Baltic Sea using MERIS data

For many questions of the coastal zone management the knowledge on the biological and ecological state of coastal waters is of high importance. Due to the complexity of this water type, characterized by different classes of water constituents, a sophisticated methodology needs to be applied for quantitative remote sensing. Within the MAPP‐Project (MERIS Applications and Regional Products Project) a specific remote sensing interpretation algorithm was developed for the regional assessment of water constituents in the Baltic Sea. This is a part of the ESA Cat‐1 proposal ID 1413 GEMEL‐3 (“Generation of MERIS Level‐3 products for European multidisciplinary regional applications”). The operational implementation in a MERIS‐value‐adding system allows a near real‐time estimation of chlorophyll sediment and gelbstoff concentrations on a regular basis. The algorithm, based on a principal component inversion (PCI) technique and the model will be introduced. The applicability of the model will be demonstrated on a couple of comparisons of MERIS reflectances and in‐situ measurements. The potential of the model shall be demonstrated on available MERIS data.

Capabilities for the retrieval of coastal water constituents (case II) using multispectral satellite data

The difficulty of the remote sensing of coastal water is the presence of more than one constituent with high variability ranges, different correlation and spectral behavior. They are superimposing in their influence on the resulting total spectrum. Simple ratio algorithms applied to remote sensing data fail on the quantitative determination of the single constituents. However, coastal regions are of great interest for remote sensing since most of the consequences of urbanization are manifested here. For the improvement of remote sensing of coastal zones it is not only necessary to build a new generation of sensors that offer spectrally higher resolved data, but one has to develop a new methodology that allows the separation and determination of the water constituents based on the entire spectral signature of the different components of the water body. The imaging spectrometer MOS flying on the Indian remote sensing satellite IRS-P3 provides since March 1996 remote sensing data in 13 spectral channels for the scientific community. We implemented a new methodological approach to derive different case II water constituents as well as atmospheric turbidity for the application of MOS-data in costal regions. A new point of the method is the uniform consideration of atmospheric and water constituent influences on the remote sensing signal. The paper will present a short overview on the algorithms essentials and examples for the large variability of coastal waters around Europe basing on the results of the retrieved water constituents using the MOS algorithm. It will demonstrate the promising potential of this new algorithm for discrimination of single constituents under case II conditions. Derived maps of chlorophyll like pigments, sediments and aerosol optical thickness are shown and will be discussed.

The hyperspectral sensor DESIS on MUSES: Processing and applications

The hyperspectral instrument DLR Earth Sensing Imaging Spectrometer (DESIS) will be developed and integrated in the Multi-User-System for Earth Sensing (MUSES) platform installed on the International Space Station (ISS). The DESIS instrument will be launched to the ISS mid of 2017 and installed in one of the four slots of the MUSES platform. The MUSES / DESIS system will be commanded and operated by the publically traded company Teledyne Brown Engineering (TBE), which initiated the program. TBE provides the MUSES platform and the German Aerospace Center (DLR) develops DESIS and establishes a Ground Segment for processing, archiving, delivering and calibrating the data used for scientific and humanitarian applications. Harmonized products will be generated by the Ground Segment established at Teledyne. This article describes the processing ground segment and the foreseen data validation activities. Finally comments regarding the data policy and foreseen scientific uses are given.

ENMAP data product standards

EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) is a German, Earth observing, imaging spectroscopy, spaceborne mission planned for launch in 2017. In order to ensure data product standards during the complete mission lifetime operational workflows are established. These cover all activities for pre- and in-flight spectral, radiometric, and geometric characterization and calibration as well as for the independent product validation of the quality controlled images. Spectral and radiometric calibration of the hyperspectral imager covering the wavelength range from 420 nm to 2450 nm is especially based on satellite onboard sources and a full aperture diffuser. Geometric calibration and validation is based on acquisitions of selected reference sites, but also compared to further ground-truth, air-, and spaceborne missions. Standardized products including geometric and/or atmospheric corrections are generated by a fully-automatic hyperspectral image processing chain.

Application of a multispectral interpretation algorithm to remote sensing data over the Baltic Sea

In the Institute for Space Sensor Technology a new generation of remote sensing imaging spectrometers was developed, measuring the reflected from the ocean atmosphere system radiance in the visible to near-infrared spectral range. This Modular Optical Scanner was successfully launched on 21 March 1996 with an Indian satellite to a polar sunsynchronous orbit, and on 23 April 1996 with the Russian Priroda Module on the MIR station. For the purpose of interpretation of these measurements over oceans and coastal zones has been developed a special algorithm based on Principal Component Analysis, using a special inversion technique for a given ocean-atmosphere physical mode. An important question in the description of such models are the inherent optical properties of the water. In the paper will be given a description of the derivation of the interpretation algorithm for different water constituents, with an inherent atmospheric correction. It will be shown how specific optical properties are influencing the interpretation results. This work was performed in cooperation with the Baltic Sea Research Institute Warnemuende.

EnMAP radiometric inflight calibration, post-launch product validation, and instrument characterization activities

This study reports the calibration and validation activities for the Environmental Mapping and Analysis Program (EnMAP; www.enmap.org). EnMAP is a German imaging spectroscopy satellite mission with the declared goal to investigate the Earths surface with a so far surpassing quality. The key scientific questions to which EnMAP will contribute are related to climate change impacts, land cover changes and processes, natural resources, biodiversity and ecosystems, water availability and quality, geohazards and risk management. The satellite operates in a sun synchronous orbit in 650 km height with a local time of the descending node set to 11:00 and an across tilt opportunity to improve the local revisit time. Two pushbroom spectrometers with 242 channels in total cover the spectral range from 420 nm to 2450 nm with a mean resolution of 6.5 nm in the visible and 10 nm in the shortwave-infrared. The ground nadir pixel size is 30 m and 1000 spatial pixels generate a swath with of 30 km. For the CalVal activities, the routine calibration is conducted within the ground segment of DLR, while the independent validation activities are lead by GFZ. Data is operationally processed on-ground to standardized calibrated products and delivered to the international user community [1]. Standardized data products will comprise radiance and reflectance products that make use of calibration information gained pre- and inflight. To ensure high quality standards, additional independent product validation activities are planned.

Four years of ocean colour remote sensing with MOS-IRS

The imaging spectrometer MOS on IRS-P3 was launched in March 1996 as the first example of a new generation of ocean colour sensors. It consists of three different spectrometers in the visible/near-infrared spectral region with 18 channels. The IRS-P3 mission is focused on the remote sensing of case 2 water, particularly the derivation of different water constituents in coastal waters. Due to the more complex spectral behaviour of case 2 water, a new methodological approach was developed which works directly with satellite measured top-of-atmosphere radiance and accounts for the correlation of the different water constituents as well as for the spectral shape. This paper gives an overview of the mission, the scientific goals and the development and improvement of the retrieval algorithms. The potential of the algorithm is demonstrated and examples of selected European coasts are shown. Derived maps of water constituents are presented.

Remote Sensing of Coastal Water Quality in the Baltic Sea Using MERIS

Remote sensing of water quality parameters using spaceborne imaging spectrometers has become a widely spread technology during the last years. Especially MERIS on ESA’s ENVISAT with its 250 m spatial resolution provides new opportunities for applications in coastal and inland waters. To make use of the information content of spectrally highly resolved data new retrieval algorithms had to be developed based on bio-optical and radiative transfer modeling and inversion by the use of principal component analysis. The paper will review the approaches and algorithms developed at DLR for research and operational applications to assess and monitor water quality in case-2 waters (coastal and inland waters). Special focus will be on yellow substance dominated waters and exceptional algal blooms in the Baltic Sea. In addition to the methodological aspect the processing system and infrastructure to provide daily water quality services in the frames of GMES will be introduced.

Interpretation of satellite remote sensing data in the Baltic sea with special respect to Harmful Algae Bloom events

Satellite ocean colour remote sensing is an effective tool for monitoring the environmental state of coastal zones and open oceans. Cyanobacterial blooms in the Baltic Sea and other Harmful Algal Blooms represent extreme events in aquatic ecosystems for which specially adapted ocean colour interpretation algorithms are needed. Here, an algorithm, developed for the Baltic Sea waters, derives information from MERIS satellite data on chlorophyll-like pigments, suspended particulates and dissolved organic matters. The presentation comprises demonstrations and intercomparisons of a local Baltic Sea algorithm and a global MERIS interpretation algorithm for the summer bloom events 2003.