As a part of an ongoing laser induced fluorescence (LIF) project, out laboratories have developed a fluorescence imaging system (FIS) to acquire fluorescence images at wavelengths centered at 450 nm, 550 nm, 680 nm, and 740 nm. The system consists of ultraviolet (UV) fluorescent lamps as an exciting source, automated filter wheel, and charge coupled device (CCD) camera. The automated filter wheel and CD camera are controlled by a microcomputer via a computer interface,a nd digital images are captured. The FIS is capable of capturing steady state fluorescence and chlorophyll fluorescence induction images. Experimental studies were conducted to demonstrate the utility of the FIS. One such study included experiments to observe the effects of ethylenediurea (EDU) in soybean leaves with FIS. Five different concentrations of EDU were sued to establish a doe-response relationship. Although visual effects of EDU treatment were not apparent, the intensities of the fluorescence images of the plant leaves varied depending on the EDU concentration, the location on the leaf surface and the emission wavelength. EDU appeared mainly to affect the photosynthetic apparatus causing non-uniform increases in red and far-red fluorescence. Ratio images of red-green and blue/far-red were found to be sensitive indicators in detecting EDU effects. A ratio of fluorescence induction to steady state fluorescence had a curvilinear relationship with EDU-dosage. Such kinetic measurements can be used to assess photosynthetic activity in response to a range of chemical and environmental stresses. This study demonstrates that FIS is an excellent tool to detect stress symptoms before the onset of visible injury. It will enhance our understanding of the interactions among photosynthetic activity, vegetative stresses and fluorescence responses. Characterization of steady state fluorescence patterns in leaves is of significant value in our LIF research studies, and images taken with FIS greatly complement non-imaging fluorescence measurements by finding the spatial distribution of fluorescence in leaves.

Green vegetation when excited by specific wavelengths of light dissipates a portion of the absorbed energy as light emissions in the form of fluorescence in several broad areas of the spectrum. Currently, leaf level fluoresence emissions have been broken down into five primary regions, namely; ultraviolet (UV), blue, green, red, and near-infrared (NIR). The optimal excitation wavelengths for each of these bands was verified for healthy soybean leaves through the use of the EEM. Intact vegetation when excited at 280 nm emits substantial fluorescence in two bands; the first centered near 335 nm, and the second centered near 440 nm. UV band fluorescence from vegetation treated with varying levels of nitrogen decreases relative to the blur fluorescence as a function of total protein concentration. These studies indicate that in vivo UV band fluorescence can be utilized as a non-destructive tool to remotely sense variations in protein concentration due to nitrogen fertilization level. It has been well established that this fluorescence emission originates from proteins contain aromatic amino acids. The majority of plant proteins contain these amino acids and as a result have the potential to fluorescence in the region of the spectrum discussed here. Pure ribulose 1,5-bisphosphate carboxylase in aqueous solution exhibited intense UV fluorescence characteristics with excitation and emission distributions similar to those of intact vegetation. Due to its high concentration we believe this protein contributes to the UV band fluorescence emanating from the intact leaf. The red and NIR fluorescence emissions can be excited within the broad wavelength region from 250 to 675 nm with excitation maxima at 430 nm, 470 nm, 600 nm, and 660 nm. The ratio of red to NIR fluorescence excitation spectra produces a ratio spectrum which exhibits striking similarities to the action spectrum of photosynthesis. The relative differences between these two emission bands depend on the wavelength of excitation. Moreover, by comparing the ratio spectrum of a healthy versus nitrogen deficient leaf, one finds areas of crossover where trends can be completely reversed by changing excitation wavelength. As a result, the success of studies involving the measurement of chlorophyll a fluorescence depend greatly on the appropriate selection of excitation wavelength. Fluorescence sensing systems based on the above emission bands are being proposed or developed for ground based mobile vans, helicopters, and small aircraft. The goals of these efforts were to better define the origins of fluorescence and to improve our understanding of these light emissions in relationship to the physiological status of the plant.

This paper presents a methodology for selecting texture measures to maximize the discrimination of agricultural land use classes in SAR images. The images were acquired during the first flight of the Shuttle Imaging Radar-C experiment, in April 1994. L and C band SAR data at HH, HV and VV polarizations, both in ground range and slant range and in two different passes were analyzed. The kappa statistic was used to identify meaningful texture measures to discriminate seven classes. The results show that the classifications of land use based only on tonal averages produced a kappa coefficient only slightly higher than 0.50. A kappa threshold of 0.90 was reached with the simultaneous inclusion of 15 texture measures for the six images.

From May 11 to July 31, 1992 the Cloud Experiment OberPfaffenhofen And Transports took place as a field experimental contribution to the global energy and water cycle experiment. The DLR Institute of Radio Frequency Technology participated with its experimental SAR system E- SAR. Multitemporal X-, C- and L-band data from 8 dates and three ERS-1 images between May 20 and July 30, 1992 are analyzed in regard to the influence of changing plant backscatter constituents and to investigate the impact of increasing ground cover in the different wavelength on soil moisture mapping. Backscatter curves of four crops are shown, which indicate the possibility for crop monitoring and preferred times for crop classification. Detection of soil moisture changes is only possible with L-band and only under grain crops. Maximum likelihood and isocluster classifications were applied on several single- and multifrequency, mono- and multitemporal channel combinations. The overall classification accuracies were higher than with supervised methods. Maximum likelihood classification allowed identification of ten crop types with accuracies of up to 84 percent, when a temporal multifrequency data set was used.

To model the impact of the landcover on the climatic and hydrological cycles, an exact knowledge of two facts is necessary: the landuse and the amount of biomass. The study area for this work is the catchment of the Ammer river, which covers about 1200 km² in the Bavarian Alpine Foreland. Optical remote sensing data are proved to provide good information sources to derive landuse classifications for large areas. But due to the fact that commonly used classification algorithms are solely based on the spectral information, this often leads to misclassifications, because different classes can show similar spectral signatures. To derive a sufficient landuse classification for the testsite purely from remote sensing data, shows up to be difficult. Due to the increasing cloudiness at the border of the alps, the use of multitemporal data is limited. Moreover, the diverse structure of the testsite limits the use of Bayes- theory based classification approach, non-spectral geographical ancillary data, such as climatic and soil data are integrated. Rules for influencing parameters were derived and taken into account in the classification procedure. The developed approach is based on the possibility theory and fuzzy subsets. The results are verified with a digital ground truth map and show a substantially increase of the classification accuracies. To calculate the evaporation, besides the landuse pattern the development of the vegetation cover is of importance. To monitor the vegetation dynamics, multitemporal optical data are not available. Therefore, ERS-SAR radar data are used for this task. Since grassland is the dominating agricultural landuse, investigations were made on the utilization of radar data for the determination of the temporal development of grassland biomass. It is shown that there is a correlation between the signal intensity and the vegetation height of meadows. Due to the fact that the height highly correlates with the biomass, the grassland biomass can be estimated in the testsite.

The information content of optical remote sensing data of broad band multispectral sensors is well known. Many investigations were conducted which analyze the correlations between TM-bands or indices derived from these bands with plant parameters like LAI, biomass and water content. Hyperspectral data of imaging spectrometers assess the reflectance properties of plant canopies in much more detail. To which extent this additional spectral information improves the determination of plant parameters is still a task of intensive research. This task is analyzed on the basis of different imaging spectrometer data, field spectrometer measurements, and agricultural ground truth acquired over a farming area in the Upper Rhine valley. In addition to multispectral approaches further spectral analyses, which parameterize the red edge position and water absorption features at 1.0 micrometers , are performed and the results are compared to NDVI. It is shown (1) that in comparison to the NDVI the red edge position is more sensitive to biomass changes, (2) that hyperspectral data are needed for the determination of the red edge position (3) that modeling of the water absorption allows the extraction of information on plant water content, (4) that the relations between NDVI and the water absorption feature are species dependent, and (5) that absorption features of cellulose in the SWIR can be connected with different maturing stages of vegetation.

The Resurs-01 satellite data now being made commercially available are bridging the gap between NOAA AVHRR and Landsat TM with a resolution in visible and near-infrared bands of 170 meters and a re-imaging capability of about four days at the equator. The combination of the mid-range ground resolution and the high repeat cycle gives data sets ideal for vegetation mapping and monitoring in scales ranging from 1:250,000 to 1:2,000,000. The normalized difference vegetation index (NDVI) has become the primary tool for accurate description of continental land cover and can be calculated both, from the channels of the Landsat Thematic Mapper and from the Resurs-01 MSU-SK instrument. The primary objective of this study was to compare the spectral information content of the Landsat Thematic Mapper and Resurs-01 MSU-SK NDVI data for an agricultural landscape of Central Italy.

We address the problem of predicting the propagation of forest fires, by estimating the local direction of the wind. Since the wind direction depends on many local factors, we propose to use aerial photographs and to analyze the shape of the smoke. First, a classification is performed with a learning strategy in order to identify pixels located in the smoke area. Then, we give algorithmic details of the computation of the medial graph, used to describe the shape of the smoke. Finally, the wind direction is given by the direction of edges along the nodes of the longest path of the medial graph. Interesting results illustrate the method.

Our understanding of the derivation of soil moisture content from observing the interaction between electromagnetic waves and bare soil on the one hand, and vegetated terrain on the other has developed at different rates. The retrieval of soil moisture from radar measurements for bare surfaces is possible by means of inversion algorithms based on theoretical surface scattering models. The interaction between electromagnetic waves and vegetated terrain involves both surface and volume scattering. The development of theoretical models for vegetated terrain is therefore extremely difficult. One such attempt was initiated by Lang and resulted in the development of a backscattering model following the wave approach. We use this model to investigate the effect of different crop parameters on the radar signal. This results in the definition of the conditions under which retrieval of soil moisture is still possible. These conditions are expressed both in terms of vegetation parameters and antenna configuration.

A recently developed two-source energy balance model using directional radiometric surface temperature observations has been modified to use radiometric surface temperature observations at two substantially different view angles for computing surface fluxes without the need of an air temperature measurement. Near simultaneous dual-angle thermal infrared observations have been available form the along track scanning radiometer (ATSR) aborad the first European Remote Sensing Satellite (ERS-1) and therefore could be used operationally with this model. The required inputs to the new version of the model (2ANGLE_PT) are similar to the original model (1ANGLE_PT). They include directional radiometric surface temperature and its view angle, fractional vegetation cover or leaf area index, vegetation height and approximate leaf width, an estimate of the fraction of green or active vegetation, net radiation, and surface layer wind speed. Both versions of the model partition net radiation absorbed by the active vegetation into latent heat (LE) and sensible heat (H) flux according to the Priestley-Taylor (PT) approximation. The model- derived fluxes using multiple angle radiometric surface temperature observations collected from ground-based observations during the First ISLSCP Field Experiment (FIFE) conducted in the tall grass prairie in eastern Kansas during the summers of 1987 and 1989 are compared to measured surface fluxes. Differences between predicted and measured H using the 2ANGLE_PT model were significant while the original 1ANGLE_PT model yielded differences of 45-50 percent, on average. The 2ANGLE_PT model predictions of LE yielded differences of 25 percent with measured values while the 1ANGLE_PT model had differences of 15-20 percent on average. Using a simple technique to estimate daytime total LE from the 'instantaneous' values with the two versions of the model resulted in differences between 20 to 25 percent. Given the uncertainty that the surface flux measurements in FIFE were 20-40 percent, the performance of the models were marginal for H, but reasonable for LE. Since the 2ANGLE_PT model dies not require an air temperature observation, which cannot be measured for each satellite pixel and provided at the time of the satellite observation, this model has operational capabilities for computing regional LE with satellite observations having two substantially difference view angles, such as from the ATSR.

For the purpose of spatial modeling of actual evapotranspiration (aET) at different scales from the field- to the landscape-scale the PROMET model-family has been developed. It is based on a gridded approach which allows the easy integration of parameters derived from remote sensing data. The model consists of a kernel for the process description and a spatial parameter modeler, which provides and organizes the spatial input data at different scales from the field- to the mesoscale. It is shown, that the results of the kernel-model at filed scale compares well with measured aET for different land-uses. After verification on the field scale the model is run on a 100 X 150 km mesoscale test-site at a resolution of 1 km. Fractional land-cover was determined using time-series of NOAA-AVHRR data and an unmixing procedure for forest, grassland, agriculture, urban areas and water. It is shown, that this unmixed land-use information corresponds well with a LANDSAT land-use classification conducted in the test region. A digital elevation model and a soil map, interpolated meteorological data from the German Weather Service and data on the development of LAI and plant height was added to the data set. The model was run over one growing season on an hourly basis. To verify the spatial pattern of the modelled aET the model results of one date were compared with surface temperature distributions measured from NOAA/AVHRR at the same time. Both are in good agreement.

In this work we present the application of the recently introduced modal matching technique to meteorological radar data. Showing how it is possible to retrieve, by means of a suitable data processing, more information about rainfall patterns and their evolution. The advantages for shape analysis and recognition of this algorithm, based on the evaluation of the eigenvalues of the dynamic equilibrium equation, are shown. Moreover, shape analysis allows to integrate data from different sources at different scales. Therefore, accurate global analysis and forecasts of rainfall movements can be achieved. The characteristics and implementation problems of this technique are also addressed, as well as some examples of complex artificial shape data. Finally, a case study of a rain even occurred in Northern Italy is shown.

This paper reports the experimentation of a joint use of ground-based radar and satellite radiometer to calibrate and validate passive microwave data for rainfall monitoring. In particular, the utilization of radar vertical profile maps in order to figure out the passive microwave signatures is outlined. The experimentation has been conducted utilizing active microwave data acquired from the Chilbolton radar and passive microwave data acquired from the DMSP SSM/I instruments. The two microwave data type have been processed in order to be overlayable in time and space, and several parameters have been estimated from the SSM/I data. Radar vertical profile maps have been classified to outline the cloud structure and the obtained information have been utilized to make statistical analysis of passive microwave parameters related to rainfall over land. In particular, an attempt to divide the cloud structure into three meaningful layers has been worked out; this is important as the different channels of SSM/I can penetrate in a diverse way cloud structure. The result are in accordance to theory and outline the importance of utilizing radar vertical profiles in order to figure out the passive microwave measurements.

This research study focuses on using a spaceborne imaging radar, ERS-1, for monitoring wetland ecosystems of southern Florida. the tropical climate of southern Florida is characterized by distinct wet and dry seasons which cause significant changes in water tables of wetland ecosystems. The period of time during which freshwater wetlands are flooded has been severely altered by human activities over the past two decades. Canals and drainage ditches lower water tables, roads create natural barriers to surface water flow, and changes in land cover alter surface water flow. The purpose of this study is to evaluate the utility of the ERS-1 C-band VV-polarization SAR data for monitoring the spatial and temporal patterns of flooding in wetlands of southern Florida. Surface water levels were measured at several wetland sites from May to November of 1995. Relationships between ERS-1 SAR backscatter and surface water levels in sparse canopy forested ecosystems and herbaceous ecosystems are demonstrated. The impedance of surface water flow by anthropogenic structures is also apparent in the ERS-1 imagery and may be monitored. Monitoring capabilities allow managers to assess the impacts of anthropogenic features on overland flow, erosion, wetland ecology, and coastal and estuarine processes. Long-term monitoring provides information on where to establish culverts and where it is necessary to divert water back into ecosystems to restore natural water flow patterns.

LANDSAT TM data were used to determine the spatial patterns of water quality parameters, in particular pigment concentration, secchi disk depth, calcite, suspended sediments, and surface temperature. A prerequisite to quantitatively determining water quality parameters from LANDSAT data is to correct sensor noise. Methods to correct LANDSAT specific noise such as sensor reflectance. Ground truth measurements of pigment concentration and secchi disk depth were available for 17 scenes. A strong correlation of measured pigment concentration and LANDSAT derived reflectance was found for 13 scenes. A scene independent pigment algorithm was not found however. Using ground truth measurements to calibrate the surface reflectance to pigment concentration allows a determination of the concentration with an accuracy better than 1 (mu) g/1. Secchi disk depth estimates can be obtained with an accuracy of better than 0.5 m. Surface temperatures were calculated from TM data without ground truth measurements. After appropriate image processing, LANDSAT derived surface temperatures yield an accuracy of 0.53 degrees K.

In this work active and passive remote sensing techniques have been merged to collect information upon the distribution of natural, anthropic and industrial pollutants in the Venetian Lagoon. Some IR and UV images, sensed by a bispectral Daedalus AA3500 scanner, on board of an Italian Guardia di Finanza aircraft flying at 3000 m, have been integrated with lidar measurements, appropriately processed and georeferenced by means of GPS receivers, in order to display large scale distributions. The lidar fluorosensor, installed on a boat, has covered many different sites of the lagoon, while measuring amounts of chlorophyll, dissolved organic matter and oil slick. Lidar data have been used to calibrate the bispectral images acquired by the airborne scanner at low height by means of appropriate regression models. The models have shown a good correlation between the two different types of collected data. Finally, small scale detailed thematic maps of the distributions of the above- mentioned bio-chemical parameters have been produced for some risk sites of the lagoon, with the characterization and localization of pollutant sources.

A model of the subsurface irradiance distribution that is based on the two-flow equations and allows for variations of the concentrations of various water quality constituents with depth has been described by Bostater, Ma, and McNally. This model allows output of the irradiance spectra at various depths. By combining the two-flow model with the hydrodynamic model of Blumberg and Mellor, the effect of the absorption of irradiance as a function of wavelength and depth on water temperature, density, turbulent kinetic energy, pressure, and the resulting circulation in an idealized ocean basin is studied. The two-flow model is set up to allow variation of the water quality parameters to occur in three layers, any number of layers, or to be constant with depth and thus affect the absorption of the sun's energy. Three simulations were run using (a) clear water coefficients, (b) a vertical distribution of chlorophyll, and (c) a vertical distribution of suspended sediments. For comparison, coefficients and attenuation for various water types included in the Princeton Ocean Model were used for comparison.

An analytical solution to the two-flow equations developed by Bostater, et al. is modified, and a sensitivity analysis is performed on the remote sensing model which contains both diffuse and specular light components. The resulting model simulates the solution to two different cases of the two- flow equations. The Case I model uses the two-flow irradiance equations where sub-surface collimated or specular irradiance is evaluated implicitly. All of the irradiance is assumed to become completely diffuse when it enters the water column. The Case II model uses equations that explicitly include collimated irradiance in the water column. Both models are simulated in three different ways in this paper based on the vertical distribution of the constituents in the water column. The concentrations of the water quality parameters can be assumed (a) constant with depth, (b) divided into three distinct layers with different concentrations in each layer, or (c) divided into n layers of differing concentrations. The solutions to the two-flow equations with and without the specular, collimated irradiance and assuming a uniform water column, are given by Bostater et. a. This paper focuses on the derivation of the layered Case I and II models, a sensitivity analysis performed on the Case II model coefficients, and comparisons of the output from the differing model assumptions are presented.

The airborne systems are used for complex investigations of coastline very successfully, for example it can be used to measure the depth of the sea, to discover the reefs and so on. Such information may be used in navigation too. The specific conditions of navigation in the North and Pole seas defines the necessity of exact knowledge about the ice cracks in order to find the possible direction of the ship movement. The active optical system, working in the near IR region, has many advantages before the passive one, especially if it is necessary to work during the polar night and at bad weather conditions. In this article we discuss the demands to the laser active airborne systems, that given the accurate picture of the ice with high resolution in the daytime and nighttime conditions. Such system based on the laser, mechanical scanner and avalanche photodiode is very compact, reliable and informative. The picture of the ice surface can be shown on the TV monitor, can be written to the memory and can be delivered to the processing center by the radiochannel. The experimental results are shown together with results of this system probing in the conditions of the North Pole Ocean.

Remote sensing is becoming an increasingly important tool for the effective direction of oil spill countermeasures. Cleanup personnel have recognized that remote sensing can increase spill cleanup efficiency. The general public expects that the government and/or the spiller know the location and the extent of the contamination. The Emergencies Science Division (ESD) of Environment Canada, is responsible for remote sensing during oil spill emergencies along Canada's three coastlines, extensive inland waterways, as well as over the entire land mass. In addition to providing operational remote sensing, ESD conducts research into the development of airborne oil spill remote sensors, including the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) and the Laser Ultrasonic Remote SEnsing of Oil Thickness (LURSOT) sensor. It has long been recognized that there is not one sensor or 'magic bullet' which is capable of detecting oil and related petroleum products in all environments and spill scenarios. There are sensors which possess a wide filed-of-view and can therefore be used to map the overall extent of the spill. These sensors, however lack the specificity required to positively identify oil and related products. This is even more of a problem along complicated beach and shoreline environments where several substrates are present. The specific laser- based sensors under development by Environment Canada are designed to respond to special roles in oil spill response. In particular, the SLEAF is being developed to unambiguously detect and map oil and related petroleum products in complicated marine and shoreline environments where other non-specific sensors experience difficulty. The role of the SLEAF would be to confirm or reject suspected oil contamination sites that have been targeted by the non- specific sensors. This confirmation will release response crews from the time consuming task of physically inspecting each site, and direct crews to sites that require remediation. The LURSOT sensor will provide an absolute measurement of oil thickness form an airborne platform. There are presently no sensors available, either airborne or in the laboratory which can provide an absolute measurement of oil thickness. This information is necessary for the effective direction of spill countermeasures such as dispersant application and in-situ burning. This paper will describe the development of laser-based airborne oil spill remote sensing instrumentation at Environment Canada and identify the anticipated benefits of the use of this technology to the oil spill response community.

This paper deals with laboratory and filed experiments carried out in the last few years by the authors for the detection of underwater temperature by Raman scattering. Laboratory experiments have been aimed at the implementation of a procedure to be transferred to the remote sensing application, so that only relative parameters have been considered. Field experiments have been carried out during oceanographic campaigns in the Tyrrhenian Sea with a high spectral resolution lidar. The results outline the usefulness of high spectral resolution lidars for the detection of underwater temperature, opening the possibility of applying more refined elaboration procedures for the extraction of underwater temperature.

A key part of the global thermohaline circulation and hence the world's heat balance, deep ocean convection is the process by which the deep waters of the North Atlantic are renewed. This paper details the results of a study to identify remotely sensible surface signatures for deep ocean convection. Remote sensing efforts have focused on the microwave part of the electromagnetic spectrum due to the all-weather capability. In particular, the high resolution imaging capability of synthetic aperture radar is explored for the existence of convective signatures. Key findings are the existence of a definite identifiable radar surface signature in convective regions and a set of conditions under which one would expect to observe these signatures.

TOPEX/Poseidon and ERS-1 altimeter data have successfully been used to demonstrate the capability of these altimeters to study the mesoscale field in the MEditerranean Sea and to investigate the seasonal variability of the Sea Level and eddy statistics in this basin. The analysis reveals a strong, but sub-basin dependent, seasonal signal. A comparison between mesoscale features detected by the two altimeters and contemporaneous features observed using Sea Surface Temperature maps definitively proves the direct relation between sea level anomalies and the MEditerranean eddy field. The comparison between the two altimeter performance is very good and underline importance to combine the information of TOPEX/Poseidon and ERS-1 to study the Mediterranean mesoscale eddy field.

The 'Odden' is a large sea ice feature that forms in the East Greenland Sea which generally forms at the beginning of the winter season and can cover 300,000 km². Throughout the winter, the outer edge of the Odden may advance and retreat by several hundred kilometers on time scales of a few days to weeks. Satellite passive microwave observations from 1978 through 1995 provide a continuous record of the spatial and temporal variations of this extremely dynamic phenomenon. The 17 year record shows both strong inter- and intra-annual variations in Odden extent and temporal behavior. An analysis of the satellite passive microwave derived ice area and extent time series along with meteorological data from the Arctic Drifting Buoy Network determined the meteorological forcing required for Odden growth, maintenance and decay. The key meteorological parameters which cause the rapid ice formation and decay associated with the Odden are, in order of importance, air temperature, wind speed, and wind direction. Atmospheric pressure was found not to play a significant role in the Odden events. Air temperature and wind direction are the dominant variables with temperatures below -9.5 degrees C and winds from the west required to trigger significant Odden ice formation events.

The lidar fluorosensor equipment has ben used in an extensive marine campaign over the northern Adriatic sea. The apparatus, consisting of an UV lidar fluorosensor together with a laser fluorometer, has been installed on board of a small ship. The lidar fluorosensor was directly pointed to the marine surface, while the laser fluorometer was monitoring the water inside a cell continuously filed by a pump from one meter sea depth. The laser induced fluorescence (LIF) signals at selected wavelengths have been recorded by the two apparata to monitor the distribution of the different species. DOM and chlorophyll signals were detected upon excitation at (lambda) equals 355 nm, while organic pollutants and oils were excited at (lambda) #EQ 266 nm. In both cases, the corresponding water Raman signal was used for normalization. Absolute concentrations of different species were obtained, when possible, after calibrating LIF data against analytical chemical results on a number of water samples. The distribution of several substances, such as industrial pollutants, anthropogenic releases and chlorophyll from phytoplankton were obtained along the ship route. A differential GPS instrument installed on board of the ship has been used to precisely georeference the data, in order to produce thematic maps of the investigated areas containing the distribution of the different monitored species.

A flow through absorption tube is described and applied. The tube is similar in concept to a 50 cm pathlength cylindrical cuvette described previously by Bostater and Gimond. The new absorption tube allows for continuous, underway measurements of water absorption signatures. Water is allowed to flow through the tube, and in this way the spectral change or track of absorption can be measured as a function of time or space when operated from a stationary or moving platform. Data gathered from various environments ranging from very turbid to clear water is analyzed and described. Concentrations of chlorophyll-a, suspended matter, and dissolved organic matter are quantitatively determined by calculating a double inflection ratio spectra for all combinations of bands from 362-1115 nm using 252 channels as described by Bostater. The absorption tube described here demonstrates the utility of continuous, underway measurements of absorption for estimating concentrations of water quality parameters.

The Venice lagoon collects different realities, such as the historical Venice town, the main industries of Marghera, and a large traffic harbor. The water exchange is mainly provided by tidal movements. In such an environment, a continuous monitoring is necessary to avoid water eutrophication and pollution phenomena like sudden algal blooms and anoxia. In the framework of a national project some measurement campaigns were carried out during recent years to point out the usefulness of fluorescence lidar also in this particular marine environment. A high spectral resolution fluorescence lidar operated from different platforms along the Venice lagoon with simultaneous traditional monitoring and sampling. The experiments demonstrated the advantages of lidar remote sensing in the monitoring of the lagoon water quality. The results are comparable to conventional field measurements with the advantage that, in measurements scheduled over an extended time, the need of maintenance is not costly and tedious as for in situ measurements.

The SALE experiment was carried out in September 1994 in waters of the Southern Tyrrhenian Sea and in Sicilian coastal waters. The aim of the experiments was the test of lidar potential in the simultaneous measurement of atmospheric and marine parameters in this particular environment. A DIAL and fluorescence lidar were successfully employed for the monitoring of volcanic emissions and marine parameters, respectively. the paper describes and discusses the main results of this experiment.