Using remote sensing to estimate sea ice thickness in the Bohai Sea,China based on ice type

It is challenging to use traditional remote sensing techniques to accurately determine the extent and thickness of ice in the Bohai Sea, on account of the presence of sea impurities (i.e. mud, salt bubbles and sand) and shape irregularities. Accordingly, we performed a series of reflectance spectra experiments to empirically link remote measurements of surface reflectance with in situ sea ice thickness measurements in the Bohai Sea. Two years of Thematic Mapper (TM) band 2 and Moderate Resolution Imaging Spectroradiometer (MODIS) band 4 data were used to distinguish between the following sea ice types, using spectral reflectance thresholds of 6.4, 9.6, 10.3 and 12.1%: (a) clean nilas ice (a thin elastic crust of ice up to 10 cm thick that, under pressure, may deform by finger rafting; (b) nilas ice and pancake ice (roughly circular accumulations of frazil ice, usually less than about 3 m in diameter, with raised rims caused by collisions); (c) grey and grey–white ice; and (d) cumulative ice (<30 cm). By establishing a relationship between sea ice type and ice thickness, a novel, practical and low-cost remote sensing technique is introduced to estimate the extent and distribution of sea ice thickness over a large spatial scale. The results obtained by remote sensing are validated with in situ ice shape measurements. The MODIS and TM data are used to distinguish between three ice thickness grades (6–9, 10–20 and 20–30 cm).     

Assessment of grassland degradation near Lake Qinghai,West China,using Landsat TM and in situ reflectance spectra data

The severity of grassland degradation near Lake Qinghai, West China was assessed from a Landsat Thematic Mapper (TM) image in conjunction with in situ samples of per cent grass cover and proportion (by weight) of unpalatable grasses (PUG) collected over 1?m² sampling plots. Spectral reflectance at each sampling plot was measured with a spectrometer and its location determined with a Global Positioning System (GPS) receiver. After radiometric calibration, the TM image was geometrically rectified. Ten vegetation indices were derived from TM bands 3 and 4, and from the spectral reflectance data at wavelengths corresponding most closely to those of TM3 and TM4. Regression analyses showed that NDVI and SAVI are the most reliable indicators of grass cover and PUG, respectively. Significant relationships between TM bands-derived indices and in situ sampled grass parameters were established only after the former had been calibrated with in situ reflectance spectra data. Through the established regression models the TM image was converted into maps of grass cover parameters. These maps were merged to form a degradation map at an accuracy of 91.7%. It was concluded that TM imagery, in conjunction with in situ grass samples and reflectance spectra data, enabled the efficient and accurate assessment of grassland degradation inside the study area.     

Multi-spectral facies in prevalent carbonate strata of an area of Migiurtinia (northern Somalia): analysis and interpretation

Rock expression in a multi-spectral image is referred to as multi-spectral image facies. Thematic Mapper (TM) multi-spectral facies of sedimentary rock bodies outcropping in an overall arid area of northern Somalia were interpreted by: (1) comparison with laboratory reflectance spectra of weathered surfaces of rock samples from the study area; (2) considering the correlation between spectra of weathered and unweathered surfaces; and (3) petrographic analysis. Aerial photo analysis provided stratigraphic and morphological information.

The rocks studied comprise mainly carbonate and evaporitic strata. TM facies appeared to be related to rock composition, presence and nature of weathering processes, scale of the lithological variability, stratal pattern in the erosional profile and outcrop morphology. Specific weathering products are, in their turn, apparently related to properties of the host rocks, such as composition and texture. Six prominent 741 (red, green, blue) facies were identified: a red facies, diagnostic of lichen coating, masking carbonate absorptions in TM7; a yellow-green laterally persistent couplet, unchecked in the field; a banded brown and yellow facies, expression of carbonate shelf strata; a purplish-red facies indicating a silcritic duricrust; a yellow facies related to fine crystalline dolostones; a cyan facies due to strong absorption in band 7, diagnostic of hydrous sulphate minerals. The comparison with a classification of the rocks based on reflectance characteristics of unweathered samples facilitated the interpretation of the remote responses and the correlation with lithostratigraphic units previously recognized in the area by different authors.     

Influence of desert varnish on the reflectance of gossans in the context of Landsat TM data,southern Red Sea Hills,Sudan

Laboratory spectra have been used for studying the characteristics of desert varnish in the context of Landsat TM data in order to establish its influence on the reflectance of gossans and their discrimination. Supported by limited chemical analysis, reflectance values from selected rock samples have been processed using statistical methods, and spectral plots produced and visually interpreted. Spectral analysis shows that paucity and Mn/Fe proportion in desert varnish, lightness or darkness of the rock, its mineral composition, and the wavelength under consideration control the effect of desert varnish on Landsat TM data. In general, overall reflectance of rocks is reduced by up to 70% in the VIS parts and about 20% in the SWIR parts of the electromagnetic spectrum due to desert varnish. For acidic rocks this effect seems to be intense, whereas mafic rocks are less influenced. The latter generally display spectral crossovers partly due to Mn/Fe content. In the VIS region absorption bands turn to featureless spectra due to desert varnish, whereas in the SWIR spectra are generally subdued but preserved. This has apparently little consequence on the discrimination of gossans from other rock types on composites constituted by bands from the VIS, IR and SWIR parts.     

沉积岩石信息的热红外多光谱遥感探测及有效性评价

在对热红外多光谱（ＴＩＭＳ）遥感的探测机理及其图像专题信息提取方法的综合分析基础上，以不同沉积岩石的化学成分，矿物组成，结构，反射和发射光谱特征的实验室分析温度测试结果为依据，对不同沉积岩石的热红外多光谱遥感成像机制进行了探讨，并对比分析了不同沉积岩石ＴＩＭＳ图像和ＴＭ图像的识别效果。     

Regional scale prospecting for non-sulphide zinc deposits using ASTER data and different spectral processing methods

ABSTRACT

The Ravar-Kuhbanan-Bahabad belt (RKBB) in Central Iran contains several carbonate-hosted non-sulphide Zn (zinc)-Pb (lead) deposits. The Gujer Zn mine area located in the middle of the RKBB was selected as the case study. Due to its large extent, dolomitic envelope in carbonate host rocks can be considered as a more appropriate exploratory target than small Zn-rich gossans or blind karst filling ore. Based on previous studies, the occurrence of red sandstone as a candidate of supplying metal for mineralization and evaporate as sulphate source for mineralized liquids in the vicinity of carbonate rocks can be important exploratory key in the RKBB. Non-sulphide Zn deposits were formed through oxidation of primary Mississippi Valley-type (MVT) deposits in the study area. Remote sensing studies were undertaken using visible to near-infrared (VNIR) and shortwave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the objective of lithological mapping. Five traverse lines containing a total of 81 samples were designed and followed with subsequent chemical analysis, thin section studies, and spectroscopy to verify the results. Two types of carbonates, namely, magnesian dolomite as host rock and surrounding calcitic limestone, were realized through using magnesium oxide (MgO) to calcium oxide (CaO) ratio. Based on spectroscopy studies, calcite and dolomite showed distinct absorption features at 2.35 µm and 2.32 µm, respectively, in ASTER band 8 while a shoulder at 2.25 µm was seen in ASTER band 7 for dolomite. Three image processing methods including spectral angle mapper (SAM), linear spectral unmixing (LSU), and mixture-tuned matched-filtering (MTMF) were applied to separate dolomite and limestone. The accuracy of image classification was numerically estimated using a confusion matrix. Limestone with the accuracy of 95.83% was more precisely enhanced using MTMF method compared to SAM and LSU methods. Highest accuracy of 75% for dolomite was obtained through using LSU method. Red sandstone and evaporate units were classified using MTMF and SAM/LSU methods, respectively. Rock units with the highest accuracy were selected and simply overlain on an image of ASTER in a GIS platform to create the potential map of the study area. Results showed that ASTER data can be successfully used to prepare a potential map for regional scale prospecting for carbonate-hosted non-sulphide Zn-Pb deposits in geological setting and climate condition similar to the RKBB.     

An optimal model for estimating suspended sediment concentration from Landsat TM images in the Caofeidian coastal waters

Suspended sediment concentration (SSC) is one of the most critical parameters in water quality and environmental evaluations. Remote sensing has the potential for monitoring the dynamics and spatial distribution of SSC efficiently. The primary objective of this study is to develop retrieval models that are reliable and sensitive to SSC levels in the Caofeidian area, a new seaport in northeast China, based on Landsat-5 Thematic Mapper (TM) images and a set of in situ data sets, including spectral reflectance data and water quality data. The study finds that the band reflectance ratio and binary combination factor (i.e. the ratio of the reflectance to the particle size) are more effective than single band reflectance, and a non-linear model is more potent than a linear model for predicting SSC in the Caofeidian waters. A quadratic polynomial regression model of the R_TM3/R_TM2 ratio is proposed as the optimal retrieval model after evaluating various models with respect to different sensitive factors. The accuracy of the model is acceptable with a relative error and a root mean square error of 25.35% and 7.22 mg l^–1, respectively; the correlation coefficient between the observed and estimated SSCs is 0.986. This study also indicates that the band reflectance ratio and binary combination factor are effective in weakening and even partially eliminating the effects of the changes in the sediment type (i.e. particle size and refractive index). And the band reflectance ratio is more efficient. Using the proposed model and TM data, SSC levels for the entire region were estimated. Such results can serve as a baseline for future environmental monitoring efforts.     

Defining the Landsat TM/ETM+ and CHRIS/PROBA spectral regions in which turbidity can be retrieved in inland waterbodies using field spectroscopy

This article describes the results obtained by an existing campaign in which in situ spectroradiometric measurements using a GER1500 field spectroradiometer, Secchi disk depth, and turbidity measurements (using a portable turbidity meter) were acquired at Asprokremmos Reservoir in Paphos District, Cyprus. Field spectroradiometric and water quality data span 18 sampling campaigns during the period May 2010–October 2010. By applying several regression analyses between ‘In-Band’ mean reflectance values against turbidity values for all spectral bands corresponding to Landsat TM/ETM+ (Bands 1 to 4) and CHRIS/PROBA (Bands A1 to A62), the highest correlation was found for Landsat TM/ETM+ Band 3 (R² = 0.85) and for CHRIS/PROBA Bands A30 to A32 (R² = 0.90).     

Assessment of two methods to monitor wetness to control dust emissions,Owens Dry Lake,California

Legally mandated control of blowing dust from 250 km² Owens Dry Lake, eastern California, USA is accomplished by wetting within shallow flooding basins. Monitoring of surface wetness is required to assess dust-control compliance. The cost, scale, heterogeneity and limited access prevent the use of moderate-resolution satellite data (e.g. Landsat Thematic Mapper (TM), 28.5 m, chosen a priori as the monitoring base) for calibrating directly to surface wetness. Instead, calibration and testing employed controlled spectrometry converted to equivalent broadbands of TM as surrogates.

Spectra, photography and surface assessments were obtained from twenty-nine 0.07 m² undisturbed surfaces varying from flooded to dry and emissive. Two competing broadband methods to assess surface wetting were tested with Landsat TM-equivalent data: TM band 5-equivalent reflectance (TMB5) as a surface wetness analogue; and tasseled cap wetness (TCW), calculated using all six TM-equivalent reflectance bands. Five performance criteria were evaluated: (1) progressive ranking, wet to dry; (2) wet and dry at ends of each index’s distribution; (3) no overlap, wet to dry; (4) large separation, moist/protected to dry/dust-emissive; and (5) clear yes/no dichotomy, whether moist/protected or not. For all criteria, TMB5 outperformed TCW. TMB5 reflectance of 0.19 provided an empirically consistent, verifiable threshold: below this, surfaces are sufficiently wet and protected from windborne dust emission.     

The derivation of water volume reflectances from airborne MSS data using in situ water volume reflectances,and a combined optimization technique and radiative transfer model

Abstract

Water volume reflectance images of three water cooling reservoirs were derived from airborne Daedalus DS-1260 multispectral scanner (MSS) data using a radiative transfer model to eliminate atmospheric effects and to derive downwell-ing irradiances. Sixty in situ water volume reflectances and the associated sensor and sun geometries were input into the radiative transfer model. Using the radiative transfer model to generate water volume reflectance values at each field site, an optimization procedure minimized the difference between modelled and in situ water volume reflectances resulting in optimized sensor brightness value to radiance conversion gain and bias factors, and optimized surface visual range and mean terrain background reflectance. Subsequently water volume reflectance images were derived at six wavelengths encompassing the blue to near-infrared using the optimized atmospheric parameters and conversion factors as inputs into the radiative transfer model. Modelled reflectance images were evaluated for accuracy by statistical comparison to the in situ reflectances, and for improved contrast by subjective comparison to the original images. Daedalus DS-1260 MSS bands 3, 4, 5, 7 and 8 modelled reflectances explained 19, 78, 86, 89 and 82 per cent, respectively of the in situ reflectance variances, while band 2 correlation was not significant (p<0.05). All generated reflectance image histograms showed dramatic improvement in contrast when compared with the histograms depicting variance within the original images.     

Measurements and analysis of in situ multi-angle reflectance of turbid inland water: a case study in Meiliang Bay,Taihu Lake,China

The bidirectional reflectance properties of the anisotropic light field above the water surface are important for a range of applications. The bidirectional reflectance distribution function of oceanic waters has been well characterized but there is a lack of information for turbid inland waters. In addition, there is a lack of bidirectional reflectance data measured in turbid inland waters partially due to the difficulty in collecting in situ water-surface multi-angle remote-sensing reflectance data. To facilitate bidirectional reflectance studies of turbid inland waters using in situ multi-angular reflectance data, we have designed and developed a simple hand-held 3D positioning pole to position the spectrometer optical fibre probe and a specific method to collect the multi-angular reflectance data above the water surface with this pole. Using this device, we collected multi-angular reflectance data in Meiliang Bay, Taihu Lake, China, and analysed the uncertainties in this method. We analysed the bidirectional distribution characteristics of the data, and compared the findings to those in the literature. Both uncertainty analysis and bidirectional distribution characteristics analysis showed that our method is effective in collecting multi-angular reflectance above the water surface and can be applied to validate bidirectional correction models in the future.     

Estimation of chlorophyll‐a concentration and trophic states for inland lakes in Northeast China from Landsat TM data and field spectral measurements

Landsat TM data and field spectral measurements were used to evaluate chlorophyll‐a (Chl‐a) concentration levels and trophic states for three inland lakes in Northeast China. Chl‐a levels were estimated applying regression analysis in the study. The results obtained from the field reflectance spectra indicate that the ratio between the reflectance peak at 700 nm and the reflectance minimum at 670 nm provides a relatively stable correlation with Chl‐a concentration. Their determination of coefficients R ² is 0.69 for three lakes in the area. From Landsat TM data, the results show that the most successful Chl‐a was estimated from TM3/TM2 with R ² = 0.63 for the two lakes on 26 July 2004, from TM4/TM3 with R ² = 0.89 for the two lakes on 14 October 2004, and from the average of TM2, TM3 and TM4 with R ² = 0.72 for the three lakes tested on 13 July 2005. These results are applicable to estimate Chl‐a from satellite‐based observations in the area. We also evaluate the trophic states of the three lakes in the region by employing Shu's modified trophic state index (TSI_M) for the Chinese lakes' eutrophication assessment. Our study presents the TSI_M from different TM data with R ² more than 0.73. The study shows that satellite observations are effectively applied to estimate Chl‐a levels and trophic states for inland lakes in the area.     

Mapping lithology of the Sarfartoq carbonatite complex, southern West Greenland, using HyMap imaging spectrometer data

The Sarfartoq carbonatite complex occurs in the southern West Greenland in a transition zone between Archaean gneiss complex to the south and a Proterozoic mobile belt to the north. The Sarfartoq carbonatite complex consists of a core zone composed of dolomite carbonatite and minor søvite (calcite carbonatite) surrounded by a fenite zone and a marginal zone of gneisses frequently altered due to hydrothermal activity. High spatial and spectral resolution imaging spectrometer data recorded by the HyMap imaging system were used to map lithology of the Sarfartoq carbonatite complex. A careful analysis of the spectral reflectance properties of the carbonatite lithology preceded the HyMap data analysis stage. The spectral reflectance measurements showed that the various lithologic units including dolomite carbonatite, søvite, fenite and the marginal alteration zone have distinct spectral reflectance characteristics. The analysis of the HyMap data was based on an unsupervised clustering algorithm, the Self Organizing Maps (SOM), for the mapping of the main lithology and a hierarchical tree for the mapping of sparsely occurring søvite rocks. Spectral mixture analysis was applied to map fractional abundances and compare with the SOM results. The resulting lithological map shows the spatial distribution of dolomite carbonatite, søvite, fenite with abundant carbonatite dykes (representing the outer core of the carbonatite complex), fenite and hematized gneiss (marginal alteration zone). The results compare well with the field data collected for the assessment of the mapping accuracy and due to the spatially contiguous nature of the hyperspectral data could be used to better map the outcropping carbonatite lithology. The spectral reflectance measurements and the mapping results provide information of petrological importance for the carbonatite core zone.     

Quantitative monitoring of inland water using remote sensing of the upper reaches of the Huangpu River,China

In this paper, a quantitative framework using common and readily available remote sensing data, including ground hyperspectral data, multispectral remote sensing images and a regular in situ water quality monitoring programme, is proposed to monitor inland water quality. The entire framework has three steps: (1) collecting and processing basic data, including remote sensing data and water quality data; (2) examining the relationships between water quality parameters and water reflectance from both remote sensing images and in situ measurement data. According to their relationships with ground hyperspectral reflectance, the water quality parameters are classified into three categories, and the corresponding monitoring models using remote sensing data are presented for these three categories; and (3) analysing the spatial distribution by using water quality concentration maps generated with the monitoring models. The upper reaches of the Huangpu River were chosen as our study area to test this framework. The results show that the concentration maps inverted by the proposed models are in accordance with the actual situation. Therefore, we can conclude that the proposed framework for quantifying water quality based on multisource remote sensing data and regular in situ measurement data is an effective and economic tool for the rapid detection of changes in inland water quality and subsequent management.     

Radiometric resolution for monitoring vegetation How many bits are needed?

Abstract

The number of radiometric quantizing levels required for satellite monitoring of vegetation resources was evaluated by using in situ collected spectral reflectance data, an atmospheric radiative transfer simulation model and a satellite sensor simulation model. Reflectance data were converted to radiance data; passed through a model atmosphere to an altitude of 706 km; and subsequently quantized at 16,32,64,128,256 and 512 digital count levels for Thematic Mapper bands TM3 (0·63-0·69 μm) and TM4 (0·76-0·90 μm), The simulated digital count data were regressed against in situ biological data to quantify the relationship(s) between quantizing levels.

Results of the analysis demonstrated that solar zenith angle had an effect on QEΔρ, that 256 quantizing levels gave a 1-3 per cent improvement per channel over 64 quantizing levels, and that 256 quantizing levels gave a 1 per cent improvement per channel over 128 quantizing levels. No improvements were found for 256 versus 512 quantizing levels.     

Discrimination of sedimentary lithologies using Hyperion and Landsat Thematic Mapper data: a case study at Melville Island,Canadian High Arctic

The use of remote-sensing techniques in the discrimination of rock and soil classes in northern regions can support a diverse range of activities, such as environmental characterization, mineral exploration and the study of Quaternary paleoenvironments. Although images with low spectral resolution can commonly be used in the mapping of classes possessing distinct spectral properties, hyperspectral images offer greater potential for discrimination of materials characterized by more subtle reflectance properties. In an effort to better constrain the utility of broadband and hyperspectral datasets in high-latitude research, this study investigated the effectiveness of Landsat Thematic Mapper (TM) and EO-1 Hyperion data for discrimination of lithological classes at eastern Melville Island, Nunavut, Canada. TM data were classified using a standard neural-network algorithm, and both TM and Hyperion data were linearly unmixed using ground-truth spectra. TM classification results successfully discriminate between classes over much of the study area, although with incomplete separation between clastic and carbonate materials. TM unmixing results are poor, with useful class separation restricted to vegetation and red-weathered sandstone classes. Hyperion results effectively depict the fractional cover of end members, although the abundance images of several classes contain background abundance values that overestimate surface exposure in some areas. For the study area and surface classes involved, noisy hyperspectral data were found to be of greater utility than higher-fidelity broadband multispectral data in the generation of fractional abundance images for an inclusive set of surface-cover classes.     

Comparison between in situ and MODIS-derived spectral reflectances of snow and sea ice in the Amundsen Sea,Antarctica

The spectral albedo and directional reflectance of snow and sea ice were measured on sea ice of various types, including nilas, grey ice, pancake ice, multi-year pack ice, and land-fast ice in the Ross, Amundsen and Bellingshausen seas during a summer cruise in February through March 2000. Measurements were made using a spectroradiometer that has 512 channels in the visible and near-infrared (VNIR) region in which 16 of the 36 bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) are covered. Directional reflectance is also retrieved from the MODIS radiometrically calibrated data (Level 1B) concurrently acquired from the first National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellite, Terra. The locations of the ground ice stations are identified accurately on the MODIS images, and the spectral albedo and directional reflectance values at the 16 VNIR MODIS bands are extracted for those pixel locations. MODIS-derived reflectance is then corrected for the intervening atmosphere whose parameters are retrieved from the MODIS atmospheric profiles product (MOD07_L2) for the same granule. The corresponding spectral albedo and directional reflectance with the same viewing geometry as MODIS are derived from our ground-based spectroradiometer measurements. Because the footprint of the ground spectroradiometer is much smaller than the pixel sizes of MODIS images, the averaged spectral reflectance and albedo in the vicinity of each ice station are simulated for the corresponding MODIS pixel from the ground spectral measurements by weighting over different surface types (various ice types and open water). An accurate determination of ice concentration is important in deriving ground reflectance of a simulated pixel from in situ measurements. The best agreement between the in situ and MODIS measurements was found when the ground had 10/10 ice concentration (discrepancy range 0.2–11.69%, average 4.8%) or was oneice-type dominant (discrepancy range 0.8–16.9%, average 6.2%). The more homogeneous the ground surface and the less variable the ground topography, the more comparable between the in situ and satellite-derived reflectance is expected.     

新疆柯坪地区沉积岩光谱特征分析

从新疆柯坪地区的沉积岩样品分析入手，阐述岩石样品的光谱测量方法，分析其光谱特征，探讨沉积岩的矿物成分，岩石表面结构、颜色、风化及环境等因素对其光谱特征的影响。     

Reflectance spectra of minerals and their discrimination using Thematic Mapper,IRS and SPOT multi-spectral data

Abstract

Minerals and rocks show varying spectral reflectances under different spectral ranges of the electromagnetic spectrum and such spectral responses vary because of colour, texture, crystal structure, specific gravity and other physical and optical properties. Hence in order to optimise the spectral ranges which may be used in the recognition of the minerals and the rocks, spectral reflectance measurements were carried out for 29 minerals under the visible and near-infrared ranges of the electromagnetic spectrum covered by the TM bands 1, 2, 3 and 4, IRS bands 1, 2, 3 and 4 and SPOT bands 1, 2 and 3. The analysis of the data identifies the optimum spectral bands for distinguishing the different minerals and the mineral aggregates/rocks     

Detecting marine intrusion into rivers using EO-1 ALI satellite imagery: Modaomen Waterway,Pearl River Estuary,China

Because of increasing marine intrusion into the Pearl River Estuary (PRE) in China, salinity has become one of the important and necessary hydrological and water quality monitoring parameters. In this research, we examined the relationships between the reflectance from Earth Observing-1 (EO-1) Advanced Land Imager (ALI) satellite imagery and total suspended solids (TSS) based on the synchronous in situ spectra analysis of the river water, in an attempt to detect salinity using remote sensing technique. The study site was the Modaomen Waterway in the PRE, Guangdong Province, China. We found a strong negative linear relationship between in situ reflectance at 549 nm and TSS concentrations (R ²?=?0.91, p < 0.001) when the salinity of the river was less than 1.46‰. It indicates that the TSS near Pinggang and Nanzhen in Modaomen Waterway of PRE tends to be dominated by organic mater carried by the particles and this is one major reason for the inverse relation between reflectance and TSS. Meanwhile, a strong correlation was observed between salinity and TSS (R ²?=?0.70, p < 0.001). The salinity-TSS model accounted for 70% of variation in salinity and allowed the estimation of salinity with a root mean square error (RMSE) of less than 0.036‰ when the TSS concentrations were between 7.4 and 28 mg l^?1. Therefore, we were able to develop a new method of detecting surface salinity of the river estuary from the calibrated EO-1 ALI reflectance data. The EO-1 ALI derived surface salinity and TSS concentrations were validated using in situ data that were collected on 18 December 2005, synchronous with EO-1 ALI satellite imagery acquisition. The results showed that the semi-empirical relationships are capable of deducing the TSS concentrations and then salinity from EO-1 ALI imagery in the PRE under low salinity. The methodology of detecting salinity from ALI imagery provides potential to monitor coastal saltwater intrusion and provides the water supply and conservancy authorities with useful spatial information to spatially understand and manage the marine intrusion.