Improving phytoplankton classification from hyperspectral measurements taking the SNR into account

The many bands and the high spectral resolution of hyperspectral sensors such as PRISMA, DESIS or EnMAP appear very promising for phytoplankton classification, but their increased sensor noise compared to multispectral sensors imposes limitations on threshold concentrations and the number of phytoplankton groups that can be distinguished. An analytic equation for a spectral weighting function (w) of the sensor bands is presented which optimizes the retrieval of phytoplankton groups from hyperspectral data. The function w depends on the reflectance differences (dR) induced by variable phytoplankton type and concentration, and on the signal-to-noise ratio (SNR) of the measurement. Extensive simulations covering wide concentration ranges of water constituents and major phytoplankton groups have been made to derive typical spectra of dR. Examples of w are presented based on these simulated dR spectra and on measured SNR spectra from hyperspectral satellite sensors. The improvement for phytoplankton classification is demonstrated for simulated measurements and for some hyperspectral images from PRISMA and DESIS

A spectral weighting function for improving phytoplankton classification

A spectral weighting function is presented which optimizes phytoplankton classification from hyperspectral data taking the signal-to-noise ratio of the current image into account. The improvements are illustrated using a DESIS image from Lake Constance

Gewaesseranalyse mit passiver Fernerkundung: Ein Modell zur Interpretation optischer Spektralmessungen

In vorliegender Arbeit wurde analysiert, welche Rückschlüsse sich auf die Inhaltsstoffe eines Gewässers ziehen lassen, wenn mit einem Sensor, der sich außerhalb des Wassers befindet, die im Wasser reflektierte Sonnenstrahlung gemessen wird. Die Messungen wurden in den Jahren 1990/91 am Bodensee durchgeführt, wobei vom Limnologischen Institut der Universität Konstanz begleitende in-situ-Daten zur Verfügung gestellt wurden. Damit die Algorithmen zur Konzentrationsbestimmung über die Reflexion nicht auf den Bodensee beschränkt bleiben, wurden die Zusammenhänge nicht rein statistisch, sondern anhand eines physikalischen Modells untersucht. Deshalb ist sowohl der systematischen Darstellung physikalischer Sachverhalte als auch der Beschreibung der optischen Eigenschaften der Wasserinhaltsstoffe breiter Raum eingeräumt

The Calibration Home Base for Imaging Spectrometers

The Calibration Home Base (CHB) is an optical laboratory designed for the calibration of imaging spectrometers for the VNIR/SWIR wavelength range. Radiometric, spectral and geometric calibration as well as the characterization of sensor signal dependency on polarization are realized in a precise and highly automated fashion. This allows to carry out a wide range of time consuming measurements in an ecient way. The implementation of ISO 9001 standards in all procedures ensures a traceable quality of results. Spectral measurements in the wavelength range 380–1000 nm are performed to a wavelength uncertainty of +- 0.1 nm, while an uncertainty of +-0.2 nm is reached in the wavelength range 1000 – 2500 nm. Geometric measurements are performed at increments of 1.7 µrad across track and 7.6 µrad along track. Radiometric measurements reach an absolute uncertainty of +-3% (k=1). Sensor artifacts, such as caused by stray light will be characterizable and correctable in the near future. For now, the CHB is suitable for the characterization of pushbroom sensors, spectrometers and cameras. However, it is planned to extend the CHBs capabilities in the near future such that snapshot hyperspectral imagers can be characterized as well. The calibration services of the CHB are open to third party customers from research institutes as well as industry

Spectral and radiometric measurement requirements for inland, coastal and reef waters

This paper studies the measurement requirements of spectral resolution and radiometric sensitivity to enable the quantitative determination of water constituents and benthic parameters for the majority of optically deep and optically shallow waters on Earth. The spectral and radiometric variability is investigated by simulating remote sensing reflectance (Rrs) spectra of optically deep water for twelve inland water scenarios representing typical and extreme concentration ranges of phytoplankton, colored dissolved organic matter and non-algal particles. For optically shallow waters, Rrs changes induced by variable water depth are simulated for fourteen bottom substrate types, from lakes to coastal waters and coral reefs. The required radiometric sensitivity is derived for the conditions that the spectral shape of Rrs should be resolvable with a quantization of 100 levels and that measurable reflection differences at at least one wavelength must occur at concentration changes in water constituents of 10% and depth differences of 20 cm. These simulations are also used to derive the optimal spectral resolution and the most sensitive wavelengths. Finally, the Rrs spectra and their changes are converted to radiances and radiance differences in order to derive sensor (noise-equivalent radiance) and measurement requirements (signal-to-noise ratio) at the water surface and at the top of the atmosphere for a range of solar zenith angles

Sensitivity study for aquatic ecosystem monitoring with the DESIS hyperspectral sensor

The aquatic ecosystems of coastal and inland waters are more variable than the open ocean as water constituents and bottom substrates differ considerably in type, concentration and optical properties. Sensors with high spatial, spectral and radiometric resolution are therefore required to provide enough detail for mapping these highly complex environments. A new Earth observation instrument, designed for monitoring spectrally complex areas, is the DLR Earth Sensing Imaging Spectrometer (DESIS). This hyperspectral sensor, which covers a spectral range from 450 nm to 950 nm and has a spatial resolution of 30 meters, will be launched to the ISS in summer 2018. The goal of the present study is to specifically evaluate the performance of DESIS over aquatic ecosystems based on its sensor specifications. For this purpose, a sensitivity study was conducted in order to explore the spectral and radiometric properties of DESIS in the context of optically deep and shallow water mapping. The optical water properties and benthic cover types were chosen to represent typical inland and coastal waters. Forward simulations of hyperspectral measurements were made using the Water Color Simulator software WASI to study the expected DESIS radiances and their signal-to-noise ratios (SNR) for different atmospheric conditions. The impact of sensor noise on the retrieval of water constituents, benthos types and water depth was analyzed by applying inverse modelling to these reflectance spectra. The study assesses the mapping potential and limitations of a DESIS type sensor for these complex environments, which are usually much darker than land surfaces

LimnoVIS - A Robotic Surface Vehicle for Spectral Measurements in Inland Waters

Spectral measurements in aquatic remote sensing are usually carried out from ships, boats or stationary platforms. While the latter only covers a single location, mobile platforms can introduce significant errors due to unexpected movement (drift and rotation), reflection and shadowing effects from the ship’s hull, superstructures and the personnel conducting the measurements. To overcome these caveats, we developed the low-profile robotic platform LimnoVIS that can be operated autonomously or remotely controlled and is capable of keeping its position and orientation accurately through its omnidirectional maneuverability. The onboard measurement system comprises a VIS/NIR spectrometer (350-880 nm, 1 nm resolution) which is connected to four different optics via a fiber optical switch. This allows for rapid subsequent measurement of upwelling radiance above and under water, sky radiance and downwelling irradiance using reflectance standards or a cosine corrector, all by the same spectrometer. LimnoVIS carries also a profiler, which can be lowered by up to 30 m. It is equipped with a spectrometer and a tiltable diffusor for measuring benthic reflectance, LED and halogen lamps, a laser range finder, a camera, and sensors for temperature and pressure. Multiple onboard cameras with recording and live viewing capabilities are used for navigation, visual supervision and documentation of the measurements and for compiling shallow-water orthomosaics. Furthermore, LimnoVIS is equipped with a sonar for deriving bathymetry in the range of 0.5 to 30 m

ProGIRH-DLR: Remote sensing of water quality in the Mantaro River basin through spaceborne and ground-based acquisition of multi- and hyperspectral data

Peru is amongst the most affected countries by climate change in the world, with severe consequences on the availability of water across the country. The GIZ funded project "Multisectoral management of water resources in the Mantaro River basin" (ProGIRH) aims to improve the integrated and climate-sensitive water resource management in the Mantaro River basin. Within this framework, an IMF Team supports the Peruvian national water authority (ANA) in establishing remote sensing methodologies as a complement to traditional sampling-based water analysis. With a permanent focus on capacity building of the regional partners, the Team combines multi- and hyperspectral satellite imagery with in-situ spectral data, in order to define the possibilities and technical requirements necessary to establish a self-dependent and locally managed long-term observation of water quality and availability

Physics-based Bathymetry and Water Quality Retrieval Using PlanetScope Imagery: Impacts of 2020 COVID-19 Lockdown and 2019 Extreme Flood in the Venice Lagoon

The recent PlanetScope constellation (130+ satellites currently in orbit) has shifted the high spatial resolution imaging into a new era by capturing the Earth’s landmass including inland waters on a daily basis. However, studies on the aquatic-oriented applications of PlanetScope imagery are very sparse, and extensive research is still required to unlock the potentials of this new source of data. As a first fully physics-based investigation, we aim to assess the feasibility of retrieving bathymetric and water quality information from the PlanetScope imagery. The analyses are performed based on Water Color Simulator (WASI) processor in the context of a multitemporal analysis. The WASI-based radiative transfer inversion is adapted to process the PlanetScope imagery dealing with the low spectral resolution and atmospheric artifacts. The bathymetry and total suspended matter (TSM) are mapped in the relatively complex environment of Venice lagoon during two benchmark events: The coronavirus disease 2019 (COVID-19) lockdown and an extreme flood occurred in November 2019. The retrievals of TSM imply a remarkable reduction of the turbidity during the lockdown, due to the COVID-19 pandemic and capture the high values of TSM during the flood condition. The results suggest that sizable atmospheric and sun-glint artifacts should be mitigated through the physics-based inversion using the surface reflectance products of PlanetScope imagery. The physics-based inversion demonstrated high potentials in retrieving both bathymetry and TSM using the PlanetScope imagery

Inter-Comparison of Methods for Lake Chlorophyll-a Retrieval: Sentinel-2 Time-Series Analysis

Different methods are available for retrieving chlorophyll-a (Chl-a) in inland waters from optical imagery, but there is still a need for an inter-comparison among the products. Such analysis can provide insights into the method selection, integration of products, and algorithm development. This work aims at inter-comparison and consistency analyses among the Chl-a products derived from publicly available methods consisting of Case-2 Regional/Coast Colour (C2RCC), Water Color Simulator (WASI), and OC3 (3-band Ocean Color algorithm). C2RCC and WASI are physics-based processors enabling the retrieval of not only Chl-a but also total suspended matter (TSM) and colored dissolved organic matter (CDOM), whereas OC3 is a broadly used semi-empirical approach for Chl-a estimation. To pursue the inter-comparison analysis, we demonstrate the application of Sentinel-2 imagery in the context of multitemporal retrieval of constituents in some Italian lakes. The analysis is performed for different bio-optical conditions including subalpine lakes in Northern Italy (Garda, Idro, and Ledro) and a turbid lake in Central Italy (Lake Trasimeno). The Chl-a retrievals are assessed versus in situ matchups that indicate the better performance of WASI. Moreover, relative consistency analyses are performed among the products (Chl-a, TSM, and CDOM) derived from different methods. In the subalpine lakes, the results indicate a high consistency between C2RCC and WASI when a_CDOM (440) < 0.5 m^-1, whereas the retrieval of constituents, particularly Chl-a, is problematic based on C2RCC for high-CDOM cases. In the turbid Lake Trasimeno, the extreme neural network of C2RCC provided more consistent products with WASI than the normal network. OC3 overestimates the Chl-a concentration. The flexibility of WASI in the parametrization of inversion allows for the adaptation of the method for different optical conditions. The implementation of WASI requires more experience, and processing is time demanding for large lakes. This study elaborates on the pros and cons of each method, providing guidelines and criteria on their use