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In the atmospheric correction algorithm for Sea-viewing Wide Field-of-view Sensor, the effects of the spectral variation of the aerosol radiance contributions at the two near-infrared (NIR) bands are estimated directly from sensor-measured radiance. The aerosol effects at the NIR are then extrapolated into the visible through a process of aerosol model selection from evaluation of the NIR single-scattering epsilon value, which is defined as the ratio of the single-scattering aerosol reflectance between two NIR bands. The aerosol radiance contribution at the visible wavelengths is then removed. In this paper, a slightly different approach in the aerosol model selection and extrapolation, i.e. using the NIR multiple-scattering epsilon instead of the single-scattering epsilon, is examined. The NIR multiple-scattering epsilon is the ratio of the aerosol multiple-scattering reflectance between two NIR wavelengths. Simulations show that, in general, both methods give comparable results. Statistically, more than 95% of cases in the retrieved ocean colour spectrum are within required accuracy for both methods. For clear atmosphere, however, the results of the atmospheric correction using the single-scattering epsilon method usually performed slightly better than the multiple-scattering epsilon method. On the other hand, for the large aerosol optical thickness the multiple-scattering epsilon method has slightly better retrievals for the Tropospheric aerosols. Some detailed analyses and discussions are provided to explain differences in these two approaches for extrapolating and retrieving the aerosol effects in the visible. [ABSTRACT FROM AUTHOR]

Although satellite remote sensing techniques have been widely implemented for a variety of applications, using either single or time-series images, few studies have explicitly considered atmospheric effects, and how they can most effectively be minimized. Despite the considerable number of available atmospheric correction algorithms, there is little literature concerning their relative merits. Over water bodies, atmospheric effects account for the majority of the at-satellite measured radiance in the visible bands, and therefore targets of this type provide an opportunity for assessing the effectiveness of the different methods available. This paper reports a study of atmospheric effects and their correction, using multi-spectral satellite remote sensing data for an area to the west of London that includes eight large water reservoirs and a major international airport (Heathrow). Through comparisons of reflectance within a time series of 12 Landsat-5 Thematic Mapper (TM) images, the overall impact of atmospheric contributions is shown. The available atmospheric correction literature is then reviewed, and the methods applied to the satellite imagery of the reservoirs. The results are compared with reflectances acquired using a field spectro-radiometer. A critical appraisal of the results, and of problems encountered in applying the various methods, leads to an evaluation of their value in practice. [ABSTRACT FROM AUTHOR]

In this paper, we present a study consisting of the application of radar interferometry for river/sea ice monitoring in inhabited regions and on commercial waterways. The sites studied are located in Canadian regions where ice jams constitute a common winter hazard that can cause extensive socio-economic damage and impose severe restrictions on ship traffic. ERS and Radarsat images were jointly used with traditional in situ observations to detect ice break-up in order to prevent ice jams and related problems. A coherence study served to define the synthetic aperture radar interferometry (InSAR) limits for river/sea ice dynamics monitoring. Other factors that also help to define the limits of InSAR technology for this application include the frequency of image acquisition, the minimum dimension of detected ice floes and the determination of appropriate ice types. Significant phase shifts were found for small ice floes of several hundred metres with ERS-tandem images. The analysis of the interferograms showed that it is possible to detect deformations in the ice shelf and to discriminate quantitatively the horizontal and vertical components of ice movement when the interferograms are combined with traditional observations such as meteorological data, water level, water flow and ice charts. The deformation estimated on a piece of fast river ice can be interpreted as the first sign of the ice break-up. On an estuary river that is a busy seaway, a qualitative interpretation of the interferograms served to highlight the interaction of river and tidal flows affecting the ice cover. We showed, in particular, the potential of radar interferometry and its integration with other techniques to help the authorities to prevent problems related to ice jams. [ABSTRACT FROM AUTHOR]

The paper presents results for spectral and textural analysis of the rock units in Landsat Thematic Mapper (TM) images, dual-band (L and C) and dual-polarization (HH and HV) Shuttle Imaging Radar (SIR)-C images, and C-band HH polarization Standard Beam 4 and Extended High Incidence Beam 3 Radarsat images from a study area between California and Arizona, USA. Fractal dimension, lacunarity and grey-level co-occurrence matrix (GLCM) textural feature images were created from the SIR-C and Radarsat images. Fractal dimensions were calculated using a differential box counting method and lacunarity measures were obtained using a new grey-scale lacunarity estimation method for 36 sample images extracted from the SIR-C and Radarsat images. The fractal dimension and lacunarity curves and class signature separability analysis show that, for rock unit discrimination using image textural features in the study area, the SIR-C L-HH image is more suitable than other SIR-C images and Radarsat images, and that co-polarization (HH) generally provides more textural information than cross-polarization (HV) in the study area. The study also shows that lacunarity measures can reveal the scaling properties of radar image textures for rock units. The combination of spectral information from Landsat TM images and textural information from radar images improves the image classification accuracy of rock units in the study area. [ABSTRACT FROM AUTHOR]

Release of an annual global terrestrial net primary production (NPP) data layer has begun in association with the Moderate Imaging Spectroradiometer (MODIS) sensor, a component of the NASA Earth Observing System. The task of validating this product will be complicated by the mismatch in scale between ground-based NPP measurements and the coarse resolution (1 km) of the NPP product. In this paper we describe three relevant approaches to scaling NPP from the plot level to the approximately 25-km 2 footprint of the sensor, and discuss issues associated with operational comparisons to the MODIS NPP product. All approaches revealed considerable spatial heterogeneity in NPP at scales less than the resolution of the MODIS NPP product. The effort to characterize uncertainty in the validation data layers indicated the importance of treating the combination of classification error, sampling error, and measurement error. Generally, the optimal procedure for scaling NPP to a MODIS footprint will depend on local vegetation type, the scale of spatial heterogeneity, and available resources. In all approaches, high resolution remote sensing can play a critical role in characterizing land cover and relevant biophysical variables. [ABSTRACT FROM AUTHOR]

The geometric processing of remote sensing images becomes a key issue in multi-source data integration, management and analysis for many geomatic applications. This paper first reviews the source of geometric distortions, compares the different mathematical models being currently used for geometric distortion modelling, details the algorithms, methods and processing steps and finally tracks the error propagation from the input to the final output data. [ABSTRACT FROM AUTHOR]

New missions and technically advanced sensors are being developed by researchers to monitor our planet from space at different spatial and spectral resolutions. Characterizing the terrestrial biomes on a global scale is a key issue in understanding climate change and the evolution of the Earth's atmosphere system. New advanced models on radiation in plant stands and more heterogeneous biomes are used to interpret satellite- and airborne sensor data and identify information on the Earth's surface. This paper presents an investigation on estimation of canopy and leaf level quantities by multidirectional remotely sensed data in three spectral bands. The purpose is to evaluate the goodness of a model in a controlled environment, using artificial input data. The results of the experiment indicate that the required information on leaf optical properties can be derived with a good accuracy within the constraints of the experiment. Estimated stand structure characteristics are more prone to error. Scaling issues, including temporal, spectral and spatial resolution, and surface heterogeneity are not addressed in this experiment. [ABSTRACT FROM AUTHOR]

In this paper, an analytical algorithm for the determination of land surface vegetation Leaf Area Index (LAI) with the passive microwave remote sensing data is developed. With the developed algorithm and the Tropical Rainfall Measuring Mission/Microwave Imager (TRMM/TMI) remote sensing data collected during the Global Energy and Water Experiment (GEWEX) Asian Monsoon Experiment in Tibet (GAME/Tibet) Intensive Observation Period (IOP'98), the regional and temporal distributions of the land surface vegetation LAI have been evaluated. To validate the developed algorithm and the retrieval results, the maximum-composite Normalized Difference Vegetation Index (NDVI) data over the same study area and period are used in this study; the cloud contaminated NDVI values have been replaced by the cloud-free values reconstructed by the Harmonic ANnalysis of Time Series (HANTS) technique. The results show that the retrieved LAI is in good agreement with the cloud-free NDVI in regional and temporal distributions and in their statistical characteristics; the vegetation characteristics can be clearly assessed from the regional distribution of the retrieved LAI. As lower frequency microwave radiation can penetrate atmosphere and thin cloud layer, with the application of the passive microwave remote sensing data, the developed algorithm can be used to monitor the land surface vegetation condition more effectively. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing data with bandwidth of nanometre (nm) level have tens or even several hundreds of channels and contain abundant spectral information. Different channels have their own properties and show the spectral characteristics of various objects in image. Rational feature selection from the varieties of channels is very important for effective analysis and information extraction of hyperspectral data. This paper, taking Shunyi region of Beijing as a study area, comprehensively analysed the spectral characteristics of hyperspectral data. On the basis of analysing the information quantity of bands, correlation between different bands, spectral absorption characteristics of objects and object separability in bands, a fundamental method of optimum band selection and feature extraction from hyperspectral remote sensing data was proposed. [ABSTRACT FROM AUTHOR]

The VEGETATION instrument is the starting point of a European Earth monitoring system that was developed jointly by France, the European Commission, Belgium, Italy and Sweden. Since April 1998, VEGETATION has provided a high quality global monitoring of the day-to-day land cover dynamics at 1 km resolution. The whole dataset is now available free of charge to the broad range of potential users and applications. The quality of delivered products in terms of radiometry, geometry and additional processing for directional and atmospheric effects stands VEGETATION as an excellent tool for the monitoring of surface hydrology, crops, forest and land cover. Surface reflectances that are delivered by the operational VEGETATION system are corrected for molecular and aerosol scattering, for water vapour, ozone and other gas absorption. So far, the only well known Maximum Value Composite (MVC) technique was used in the construction of 10-day synthesis. An additional enhanced composite product is now available, which evaluates the atmospheric optical depth and normalizes angular Sun-target-sensor variations. After presenting the VEGETATION instrument and products, this paper introduces the new compositing schemes ( Duchemin and Maisongrande 2002, Duchemin et al. 2002 ) and presents samples of the new products. [ABSTRACT FROM AUTHOR]

A typical remote sensing data clustering is the maximum likelihood supervised procedure. It consists of the estimation of a suitable mixture of distributions, based on training samples only, and in the subsequent pixel-by-pixel classification, performed by maximizing the likelihood ratio. In this way all the information on the parameters of the distributions, contained in the unsurveyed samples, is lost. In the paper it is proposed to apply a suitable Bayesian method, known as a data augmentation algorithm, to fully exploit the information contained in the data. The method is presented in detail and applied to an elementary simulated example proving its capability of achieving almost the theoretical limit for the classification error. Comparisons with current classification methods as well as an application to a real dataset are reported. [ABSTRACT FROM AUTHOR]

Objective measurement of habitat change using remote sensing requires processing of the images to enhance the bottom reflectance signal. This process typically uses correction techniques to remove the influence of the water column on bottom reflectance, and to enable the accurate correction of the imagery for varying bathymetry. Such correction measures depend on reliable estimates of water column light attenuation. An investigation into the spatial variation in attenuation in a typical tropical region was undertaken. Measurements of gross spatial variations in downwelling attenuation around San Andres and Old Providence islands in the western Caribbean were made using a PAR sensor. Measurements of specific attenuation were also made for blue, green and red light using filters fitted to the sensor. High spectral resolution attenuation measurements were also made using a spectroradiometer. Results showed a four-fold variation in light attenuation in shallow littoral regions alone. Spectral attenuation measurements suggested that this variation was largely the result of scattering by particulate matter rather than varying concentrations of dissolved yellow substances. These findings suggest that the results of studies where single measurements of 'average' attenuation have been used to depth-correct remotely sensed imagery should be interpreted with a high degree of caution. The paper goes on to show that simple models can be empirically obtained where attenuation can be spatially predicted with confidence, based on the variables of water depth, distance to and size of mangrove beds, and distance to and size of towns. The models obtained showed high statistical significance, with 89% and 78% of the spatial variation in attenuation explained for San Andres and Old Providence, respectively. It is postulated that the use of such approaches for the estimation of attenuation will lead to more accurate depth correction and hence improved interpretation of remotely... [ABSTRACT FROM AUTHOR]

This paper describes the use and appraises the performance of acoustic ground discrimination systems (AGDS) for marine benthic biotope mapping for those who are more familiar with satellite or airborne remote sensing. The operation of AGDS is described and the nature of the data produced compared with more conventional remotely sensed data. Analysis of the AGDS data involves the interpolation of track point data to create areal coverages that can then be interpreted using classification and image processing techniques. AGDS data have been shown to be variable both within and between surveys and systems which affects the performance of interpretation. Additionally, the marine environment imposes limitations on the way that ground sampling can be undertaken and the spatial extent of information that can be obtained. In summary, the main issues that contribute to variability and uncertainty of biotope maps based on AGDS-based methodology are: (1) errors in position fixing of both AGDS and the ground samples; (2) inconsistent performance of the AGDS system; (3) single frequency of AGDS and its effect on discrimination; (4) tracking intensity of AGDS survey; (5) heterogeneity of the seabed at the scale of resolution of the system; (6) lack of vista for designating training sites and the reliance on buffers around ground samples; (7) unsuitable biotope categories. Variability due to AGDS hardware is often beyond the control of surveyors, but quality control procedures can at least alert operators to poor quality data. Performance of AGDS surveys also depends on intensity of both tracking and ground sampling in relation to heterogeneity of the sea floor. This relationship can be investigated through exploratory spatial data analysis, particularly the variogram. The performance of biotope maps can be measured using error and similarity matrices. The accuracy of the biotope maps resulting from AGDS surveys is modest when compared with the performance of satellite or... [ABSTRACT FROM AUTHOR]

This paper uses the Special Issue of the International Journal of Remote Sensing on Remote Sensing of the Coastal Marine Environment to highlight recent advances in knowledge of remote sensing of the coastal zone and to define a series of priorities where future research into the application should be addressed. Advances were identified in the benefit of high spatial and spectral resolution data and complementary remote sensing techniques (e.g. optical and acoustic, optical and Synthetic Aperture Radar (SAR)). Further benefits are identified in rapid and more frequent data acquisition, faster and more automated processing and a greater sampling intensity over conventional field-based techniques. Issues associated with adoption of remotely sensed data for management are discussed. Research priorities include the need for improved understanding and description of biotope classes and the functional interpretation of biotope maps and continued developments in understanding the radiative transfer properties of coastal environments. New knowledge is required on spatial and temporal variations of water column optical properties and its constituents. Methods for the best approaches to processing hyperspectral data require further investigation, as does the need for further testing of hyperspectral sensors for bottom type discrimination using data obtained at space-borne altitudes. Areas of value which continue to remain poorly investigated include the improvements to be gained from synergistic use of multi-wavelength remote sensing approaches, change detection techniques and multi-temporal comparisons and knowledge-based approaches to improve classification. The importance of specifically dedicated coastal zone sensors is discussed, as is alternative means of deployment (e.g. International Space Station (ISS) and Un-inhabited Aerial Vehicles (UAVs)). The potential role of airborne digital photography for marine mapping is highlighted. The lack of accurate near-shore... [ABSTRACT FROM AUTHOR]

In this paper we study the existence of effective wavenumber for any sensor by means of simple mathematics. We implement a numeric algorithm, based on the developed mathematical background, into a computer program named 'srf2radi', which is freely available via anonymous File Transfer Protocol (FTP) at ftp://ftp.uv.es/pub/src/. The number of effective wavenumbers for each temperature and their accuracy are also computed and studied for NOAA-16 Advanced Very High Resolution Radiometer Version 3 (AVHRR/3) channel 4. These effective wavenumbers can be used to obtain radiance-temperature relationships with physical meaning for any sensor in user-defined temperature intervals. [ABSTRACT FROM AUTHOR]

The gain response of the detectors in the cold focal plane of Landsat-4 and Landsat-5 Thematic Mapper (TM) is known to fluctuate temporally. This is believed to be caused by an interference effect due to a film build-up on the cold focal plane dewar window. This paper analyses the effect using a thin-film interference model. This model relates detector gain to film thickness through indices of refraction of the materials involved. The dewar window material is zinc selenide (ZnSe) with a known index of refraction, thus the index of refraction of the film in TM band 5 and band 7 can be determined by fitting the model to the gain data from each detector. The film is found to be quite absorptive in band 7, but only slightly absorptive in band 5. Film thickness has been determined to be as much as 1400 nm from the data sample used. This model is also used to remove gain variation for gain characterization over instrument lifetime. An accurate model of this effect can improve the calibration of Landsat-4 and Landsat-5 by 3-4% in band 5 and band 7. It is also applicable to Landsat-7 Enhanced Thematic Mapper Plus (ETM+) if this thin-film build-up is present. [ABSTRACT FROM AUTHOR]

One of the products to be derived from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) will identify locations where land cover changes attributable to human activities are occurring. The product aims to serve as an alarm where rapid land cover conversion can subsequently be analysed with higher resolution sensors such as Landsat 7. This paper describes the production procedure and change detection algorithms for the 250 m MODIS land cover change product. Multiple change detection algorithms, including three spectral methods and two texture methods, are utilized to generate the product from the two 250 m MODIS bands. The change detection methods are implemented with look-up tables (LUTs) which are initially generated using data from the Advanced Very High Resolution Radiometer (AVHRR) and Landsat Thematic Mapper (TM) until MODIS data become available. The results from the five methods are combined to improve confidence in the product. We test the performance of each method against several sets of simulated MODIS data derived from Landsat TM image pairs. The test data represent tropical deforestation, agricultural expansion and urbanization. The commission errors of the five methods and the combination are approximately 10%, with reasonable omission errors less than 25%. [ABSTRACT FROM AUTHOR]

In this paper we demonstrate SAR system capability for detecting and characterizing marine surface slicks. During an aircraft measurement campaign over the Gulf of Genoa (Italy), a multi-frequency SAR system, operating in P-, L- and C-bands, explored a sea area heavily covered by slicks. At the same time in situ measurements were performed with an interferential microwave probe, installed on board a small boat, capable of measuring high resolution sea spectra up to frequencies of capillary waves. By plotting SAR pixel intensity versus sea wave Bragg frequency we obtained wide portions of the sea spectrum region affected by the surface film damping. Spectra derived from SAR imagery and from gauge data present comparable slopes and furthermore the ratio between clean to slicked water spectrum obtained with the two techniques were surprisingly similar. This demonstrates the multi-frequency SAR systems ability to detect and characterize sea surface films assuming the Bragg mechanism in the radar backscatter. The outlined analysis suggests a simple methodology to monitor coastal water quality by using airborne SAR. [ABSTRACT FROM AUTHOR]