Sima Bagheri

Utility of hyperspectral data for bathymetric mapping in a turbid estuary

Abstract Hyperspectral data acquired by Geophysical Environmental Research (GER) Imaging Spectrometer were used for remote bathymetry in the Hudson/ Raritan estuarine waters. Characteristics of the GER image verified by in situ sea truth data indicated that water quality parameters, (i.e., organic/inorganic particulate), were largely uniform during the time of data acquisition. This condition coupled with the uniformity of bottom type provided an opportunity for quantitative bathymetric mapping. Bathymetric data were obtained from a direct ship sampling/bathymetry survey. GER data were used to simulate the spectral response of Landsat-5 TM to define advantages of GER data for bathymetric mapping. It was concluded that under the attending conditions radiometric resolution is at least as important as hyperspectral selectivity for bathymetric applications. However the potential for hyperspectral instruments such as GER to increase radiometric resolution by integrating data within optimal band-widths must be ...

Retrieval of marine water constituents from AVIRIS data in the Hudson/Raritan Estuary

This paper reports on the validation of bio‐optical models in estuarine and nearshore (case 2) waters of New Jersey–New York to retrieve accurate water leaving radiance spectra and chlorophyll concentration from the NASA Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data complemented with in situ measurements. The study area—Hudson/Raritan Estuary—is a complex estuarine system where tidal and wind‐driven currents are modified by freshwater discharges from the Hudson, Raritan, Hackensack, and Passaic rivers. Over the last century the estuarine water quality has degraded, in part due to eutrophication, which has disrupted the pre‐existing natural balance, resulting in phytoplankton blooms of both increased frequency and intensity, increasing oxygen demand and leading to episodes of hypoxia. During 1999–2001 data acquisitions by NASA AVIRIS field measurements were obtained to establish hydrological optical properties of the Hudson/Raritan Estuary: (1) concurrent above‐ and below‐surface spectral irradiance; (2) sampling for laboratory determination of inherent optical properties; and (3) concentrations of optically‐important water quality parameters. We used a bio‐optical model based on Gordon et al. to predict the sub‐surface irradiance reflectance from optically important water constituents. Modelling of reflectance is a prerequisite for processing remote sensing data to desired thematic maps for input into the geographical information system (GIS) for use as a management tool in water quality assessment. A Radiative Transfer Code—MODTRAN‐4—was applied to remove the effects of the atmosphere so as to infer the water leaving radiance from the AVIRS data. The results of this procedure were not satisfactory, therefore an alternative approach was tested to directly correct the AVIRIS image using modelled spectra based on measured optical characteristics. The atmospherically corrected AVIRIS ratio image was used to calculate a thematic map of water quality parameters (i.e. chlorophyll‐a) concentration, which subsequently were integrated into a GIS for management of water quality purposes.

Nearshore Water Quality Estimation Using Atmospherically Corrected AVIRIS Data

The objective of the research is to characterize the surface spectral reflectance of the nearshore waters using atmospheric correction code—Tafkaa for retrieval of the marine water constituent concentrations from hyperspectral data. The study area is the nearshore waters of New York/New Jersey considered as a valued ecological, economic and recreational resource within the New York metropolitan area. Comparison of the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) measured radiance and in situ reflectance measurement shows the effect of the solar source and atmosphere in the total upwelling spectral radiance measured by AVIRIS. Radiative transfer code, Tafkaa was applied to remove the effects of the atmosphere and to generate accurate reflectance (R(0)) from the AVIRIS radiance for retrieving water quality parameters (i.e., total chlorophyll). Chlorophyll estimation as index of phytoplankton abundance was optimized using AVIRIS band ratio at 675 nm and 702 nm resulting in a coefficient of determination of R 2 = 0.98. Use of the radiative transfer code in conjunction with bio optical model is the main tool for using ocean color remote sensing as an operational tool for monitoring of the key nearshore ecological communities of phytoplankton important in global change studies.

Bayesian Estimation of Optical Properties of Nearshore Estuarine Waters: A Gibbs Sampling Approach

A novel approach is developed for the retrieval of inherent optical properties of coastal water, from which water-quality constituent concentrations can be obtained. The technique combines an analytical bio-optical model with statistical modeling for the formulation of posterior probability distributions of phytoplankton absorption, backscattering, and colored dissolved organic matter absorption; a Gibbs Sampler is employed for optimization. In contrast to other methods that typically provide point estimates of the unknown parameters, the proposed method estimates posterior distributions of the parameters, quantifying the uncertainty present in the problem and revealing correlation patterns. The method is tested successfully on synthetic reflectance data and real data measured in situ in the Hudson/Raritan Estuary of New York-New Jersey.

Inherent and apparent optical measurements in the Hudson/Raritan Estuary

Duringan August, 1999 field campaign, measurements were made to establish hydrologicoptical properties of the Hudson/Raritan Estuary (New York-New Jersey): 1)concurrent above-and below-surface spectral irradiance; 2) sampling forlaboratory determination of inherent optical properties; and 3) concentrationsof optically-important water quality parameters. We used a bio optical modelbased on to predict thesubsurface irradiance reflectance from optically important water constituents.This model was then validated with the measured reflectance spectra from thefield spectroradiometers. Modeling of reflectance is a prerequisite forprocessing remote sensing data to desired thematic maps. These are key input tothe geographic information system (GIS) used to manage the water qualitycondition of the estuary.

Hazardous waste site identification using aerial photography: A pilot study in Burlington County, New Jersey, USA

The objective of the project was to identify all hazardous waste sites in Burlington County, New Jersey that could be detected on existing, medium-scale aerial photographs of the county. The complete set of over 1000 black- and-white stereopairs at a scale of 1:12,000 was carefully examined for initial identification of possible sites. All suspicious sites were examined again on color transparencies of the county at the same 1:12,000 scale. Out of the 1094 black- and-white photos, 250 required further checking on color transparencies using a zoom stereoscope. This examination resulted in a final identification of 67 sites, the locations of which were delineated on 1:24,000 USGS maps. The use of air photo interpretation techniques provided an effective procedure for identifying waste sites quickly as well as providing a useful demonstration program for county and state officials.

Utility of Field Spectroradiometer Data in Chlorophyll-a Estimation

We present here results supporting the use of Medium Resolution Imaging Spectrometer (MERIS)-based Near Infrared-Red algorithms for estimating chlorophyll-a (chl-a) concentration in complex coastal waters. The objective of the study was to test the potential of universal applicability of NIR-Red algorithms, calibrated with (a) radiometric measurements and in situ data from inland waters in Nebraska, (b) MERIS data, acquired over Azov Sea in Russia, and (c) data synthetically generated using a radiative transfer model, to estimate chl-a concentration in the Hudson/Raritan Estuary of New York/New Jersey. We used a set of in situ reflectance and water samples collected in the Hudson/Raritan Estuary of New York/New Jersey for this validation. The NIR-Red algorithms produced consistently accurate estimates of chl-a concentration, ranging from 3.9 mg m -3 to 26.3 mg m 3 , with the root mean square error (RMSE) below 2 mg m -3 . The algorithms do not need re-parameterization and it presents a strong case for the use of NIR-Red algorithms for real-time quantitative monitoring of Hudson/Raritan Estuary, and potentially other inland and coastal waters.

Forward Bio-optical Modeling and Calibration

Utilization of remotely sensed data can provide greater economy in many types of hydrologic surveys than using conventional methods. This is possible because certain biological and geochemical constituents of surface/near surface water produce changes in reflectance that can be measured by ocean color remote sensing. To develop analytical algorithms for Case2 waters, an optical (forward) model needs to link the water quality parameters (WQPs) to the inherent optical properties (IOPs), linking these in turn to the subsurface irradiance reflectance R(0−) for retrieval of constituent concentrations using (inverse) modeling. The goal was to establish a monitoring system for retrieval of water constituent concentrations using remote sensing ocean color data. Subsequently, chlorophyll concentration can be used as an indicator for high biomass nuisance blooms, as well as an indicator for super-eutrophic conditions connected to oxygen depletion and dead zone formation.

In-Situ Measurements to Establish the Bio-optical Model

To develop ocean color model for Case 2 waters; it is required to develop an appropriate bio-optical model in order to link the water constituent concentrations to the inherent optical properties (IOPs) and to link the IOPs to the subsurface irradiance reflectance R(0−) recorded by remote sensors. As part of this bio-optical modeling efforts, biweekly field campaigns were carried out in the Hudson/Raritan Estuary of New York-New Jersey during the course of the project (1998–2001) to obtain in-situ measurements of subsurface irradiance reflectance R(0−), together with in situ samples, that were later analyzed in the laboratory for their inherent optical properties and bio-optical modeling. The results of the field campaign with emphasis on August 1999 are presented in this chapter.

Application of Hyperspectral Data

Three decades of airborne imaging spectroscopy have demonstrated the added value of this remote sensing technique to improve the understanding of Earth’s functioning. With the advent of airborne imaging spectroscopy, the specialized image processing system has made the generation of quantitative methods such as semi-analytical and analytical methods possible. Producing thematic maps depicting spatial and temporal distribution patterns of optical water quality parameters are based on the image interpretation and calibration for better monitoring and management of water resources.