Determination of chlorophyll concentration changes in Lake Garda using an image-based radiative transfer code for Landsat TM images

The distribution of phytoplankton chlorophyll concentration in Lake Garda (Italy) was estimated using Landsat Thematic Mapper (TM) data acquired at two different times, February 1992 and March 1993. To investigate the waterleaving radiance adequately, the contribution of the atmospheric path radiance reaching the sensor should be removed. In this work a completely image-based atmospheric correction method was applied by means of an inversion technique based on a simplified radiative transfer code (RTC). A semi-empirical approach of relating atmospherically corrected TM spectral reflectances to in situ measurements through regression analysis was used. Limnological parameters were measured near to the TM images dates; some of the in situ measurements were used to define algorithms relating chlorophyll concentration measurements to water surface reflectance and the others too were used to validate the results of the predictive model. The models developed, which performed better (r² = 0.818) when concentrations were higher than > 3.0 mg m³, were used to map chlorophyll concentration throughout the lake. Spatial distribution maps of chlorophyll concentration and concentration changes were produced with contour intervals of 1 mg m³.     

Mapping the concentrations of total suspended matter in Lake Taihu,China, using Landsat‐5 TM data

Remote sensing techniques can be used to estimate and map the concentrations of suspended matter in inland water, providing both spatial and temporal information. Although an empirical approach to remote sensing of inland waters has been carried out frequently, satellite imagery has not been incorporated into routine lake monitoring programmes due in part to the lack of a standard prediction equation with multi‐temporal capacity for suspended matter. Empirical and physical models must be developed for each lake and its corresponding turbidity composition if they are to be compared over time, or with other bodies of water.

This study aimed to develop and apply multi‐temporal models to estimate and map the concentrations of total suspended matter (TSM) in Lake Taihu, China. Two Landsat‐5 Thematic Mapper (TM) images and nearly contemporaneous in situ measurements of TSM were used. A modified Dark‐Object Subtraction (DOS) method was used, and appeared to be adequate for atmospheric correction. The relationships were examined between TSM concentrations and atmospherically corrected TM band and band ratios. Results of this study show that the ratio TM4/TM1 has a strong relationship with TSM concentrations for lake waters with relatively low concentrations of phytoplankton algae. However, TM3 provided a strong predictive relationship with TSM concentrations despite varied water quality conditions. Different prediction models were developed and compared using multiple regression analysis. The Akaike Information Criteria (AIC) approach was used to choose the best models. The validation of the multi‐temporal capability of the best models indicated that it is feasible to apply the linear regression model using TM3 to estimate TSM concentrations across time in Lake Taihu, even if no in situ data were available.     

Delineation of seasonal changes of chlorophyll frontal boundaries in Mediterranean Coastal waters with Nimbus-7 Coastal Zone Color Scanner data

The seasonal changes in chlorophyll-like pigment distribution in the Northwestern Mediterranean Sea (Gulf of Lions) were monitored during the year 1979. Data were collected from the Coastal Zone Color Scanner (CZCS), carried on the Nimbus-7 satellite. A series of cloud-free images covering the whole year was selected and processed to evaluate chlorophyll-like pigment concentrations. The upwelling subsurface radiance of the ocean (L_ss) was extracted from the apparent upwelling signal reaching the satellite sensor (L_O) using an algorithm removing atmospheric effects. Chlorophyll-like pigment concentration (C) was then derived from L_ss in different wavelengths. Characteristic boundaries between water masses with different phytoplankton content were obtained. The results demonstrate that phytoplankton distribution is a good indicator of seasonal variations of oceanic fronts. Features such as coastal upwellings, cyclonic eddies, or plume of the Rhône river could be monitored.     

The use of NOAA-AVHRR NDVI data to assess herbage production in the arid rangelands of Central Australia

NOAA-AVHRR data are examined for their potential application in assessing primary productivity in the arid rangelands of Central Australia. Field measurements of herbage biomass are correlated with four indices derived from NOAA-II Normalized Difference Vegetation Index (NDVI) data. Pre-flight and sensor degradation calibrations of bands 1 and 2 and atmospheric correction techniques are also tested. Regional herbage production can be readily estimated using backgroundadjusted maximum NDVI values for a growth season, with NDVI data derived from sensor degradation calibrations of bands 1 and 2 and corrected for atmospheric effects by band 4– band 5 temperature differences (T₄ – T₅,). Correlations between temporal sums of NDVI and herbage biomass data are relatively poor and unsuitable for herbage assessment in Central Australia.     

Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research

Atmospheric correction is an important preprocessing step required in many remote sensing applications. The authors are engaged in the project 'Human Dimensions of Amazonia: Forest Regeneration and Landscape Structure' in NASA/INPE's Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) programme. This project requires use of corrected Landsat TM data since research foci integrate ground-based data and TM to: (1) measure and model biomass; (2) classify multiple stages of secondary succession; (3) model land cover/land use changes; and (4) derive spectral signatures consistent across different study areas. The 30+ scenes of TM data are historic and lack detailed atmospheric data needed by physically-based atmospheric correction models such as 6S (Second Simulation of the Satellite Signal in the Solar Spectrum). Imagebased DOS models are based on image measurements and explored in this article for application to LBA study areas. Two methods using theoretical spectral radiance and image acquisition date respectively were used to convert TM DN values to at-satellite radiance. Three image-based models were employed using each method to convert at-satellite radiance to surface reflectance. Analyses of these six different image-based models were conducted. The Improved Imagebased DOS was the best technique for correcting atmospheric effects in this LBA research with results similar to those obtained from physically-based approaches.     

Evaluation of the potential of the Thematic Mapper for marine application

Abstract

The potential of the Thematic Mapper (TM) on board Landsal-5 for marine applications has been investigated with reference to the well-known performance of the Coastal Zone Color Scanner of Nimbus-7. The study consisted of (a) a sensitivity analysis, considering such fundamental error sources as retrieval algorithm sensitivity, atmospheric correclion, instrument noise and signal digitization and (b) the interpretation of a TM scene by the procedure suggested in (a). The evidence provided by the experimental test validated the positive conclusions of the theoretical work, indicating that the analysis of TM bands 1 to 4 data should be capable of yielding quantitative information of satisfactory quality on fundamental water quality parameters, such as chlorophyll (i.e. phytoplankion) and suspended sediment concentrations.     

Mapping leaf area index over a mixed natural forest area in the flooding season using ground-based measurements and Landsat TM imagery

Leaf area index (LAI) is an important structural parameter in terrestrial ecosystem modelling and management. Therefore, it is necessary to conduct an investigation on using moderate-resolution satellite imagery to estimate and map LAI in mixed natural forests in southeastern USA. In this study, along with ground-measured LAI and Landsat TM imagery, the potential of Landsat 5 TM data for estimating LAI in a mixed natural forest ecosystem in southeastern USA was investigated and a modelling method for mapping LAI in a flooding season was developed. To do so, first, 70 ground-based LAI measurements were collected on 8 April 2008 and again on 1 August 2008 and 30 July 2009; TM data were calibrated to ground surface reflectance. Then univariate correlation and multivariate regression analyses were conducted between the LAI measurement and 13 spectral variables, including seven spectral vegetation indices (VIs) and six single TM bands. Finally, April 08 and August 08 LAI maps were made by using TM image data, a multivariate regression model and relationships between April 08 and August 08 LAI measurements. The experimental results indicate that Landsat TM imagery could be used for mapping LAI in a mixed natural forest ecosystem in southeastern USA. Furthermore, TM4 and TM3 single bands (R ² > 0.45) and the soil adjusted vegetation index, transformed soil adjusted vegetation index and non-linear vegetation index (R ² > 0.64) have produced the highest and second highest correlation with ground-measured LAI. A better modelling result (R ²?=?0.78, accuracy?=?73%, root mean square error (RMSE)?=?0.66) of the 10-predictor multiple regression model was obtained for estimating and mapping April 08 LAI from TM data. With a linear model and a power model, August 08 LAI maps were successfully produced from the April 08 LAI map (accuracy?=?79%, RMSE?=?0.57), although only 58–65% of total variance could be accounted for by the linear and non-linear models.     

An algorithm for the identification of benthic algae in the Venice lagoon from Thematic Mapper data

Abstract

An algorithm for the identification of benthic algae in the Venice lagoon using Thematic Mapper data has been developed from a study combining water optics modelling with remote sensing routines tailored to the local situation. The sensitivity and validity range of the algorithm have been assessed by an error analysis considering both the atmospheric correction uncertainty and the masking cfTect of water turbidity. The procedure has been tested on a TM scene of 7 June 1989 yielding a thematic map which classifies algae according to depth.     

Assessing the potential of VEGETATION sensor data for mapping snow and ice cover: A Normalized Difference Snow and Ice Index

The VEGETATION (VGT) sensor in SPOT 4 has four spectral bands that are equivalent to Landsat Thematic Mapper (TM) bands (blue, red, near-infrared and mid-infrared spectral bands) and provides daily images of the global land surface at a 1-km spatial resolution. We propose a new index for identifying and mapping of snow/ice cover, namely the Normalized Difference Snow/Ice Index (NDSII), which uses reflectance values of red and mid-infrared spectral bands of Landsat TM and VGT. For Landsat TM data, NDSII is calculated as NDSII_TM=(TM3-TM5)/(TM3+TM5); for VGT data, NDSII is calculated as NDSII_VGT=(B2-MIR)/(B2+MIR). As a case study we used a Landsat TM image that covers the eastern part of the Qilian mountain range in the Qinghai-Xizang (Tibetan) plateau of China. NDSIITM gave similar estimates of the area and spatial distribution of snow/ice cover to the Normalized Difference Snow Index (NDSI=(TM2-TM5)/(TM2+TM5)) which has been proposed by Hall et al. The results indicated that the VGT sensor might have the potential for operational monitoring and mapping of snow/ice cover from regional to global scales, when using NDSII_VGT.     

Neotectonic analysis of Mendha river basin,Rajasthan, India

Abstract

The study presented here examined the tectonically active Mendha River basin, Rajasthan, India. Landsat TM data in bands 2, 3 and 4 were used in this study. The neotectonic features were extracted through the digital analysis of the principal component (PC) and directional filtered images. However, the regional view of the study area was examined through the false colour composite (FCC). A map of the neotectonic features was generated by incorporating the limited field observations and this yielded the extensions of the neotectonic features.     

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.     

Porphyry copper alteration mapping at the Meiduk area,Iran

Using the Crosta technique, principal component transformations on six and four Thematic Mapper (TM) bands are tested in the Meiduk area, Kerman Province, Iran for mapping alteration haloes and enhancing new prospecting sites. The Crosta test is performed on both unstretched and stretched bands. Eigenvector loadings for some visible and infrared bands of TM, bands 1, 3, 4, 5 and 7, show that in each case the first principal component is an indication for albedo and the third for vegetation. Features with lower importance such as iron oxides or hydroxyls are concentrated in subsequent principal components. PC4 of unstretched data transformation on bands 1, 4, 5 and 7 enhances the hydroxyl-bearing areas around the porphyry intrusives. Some enhanced areas coincide with present porphyry deposits, and some indicate new prospects suggested for further exploration investigations. PC4 of unstretched data transformation on bands 1, 3, 4 and 5 indicates that iron oxide stained areas coincide with sedimentary terrains and is not suitable for exploration. The results of principal component transformation on stretched TM bands are relatively similar to the unstretched one but the images are brighter and the distinction between lithological units is easier. Different colour composites of hydroxyl and iron oxide images enhance alteration haloes around porphyry intrusives and sedimentary terrains. New prospects and the already known porphyry copper deposits are enhanced in white colour when the F image is considered for red, H image for green and the 'H + F' image as blue in a colour composite image. No new prospect is enhanced in the iron oxide stained terrains. The Crosta technique for hydroxyl mapping is used in this study to map alteration around porphyry intrusives and proved to be suitable for porphyry copper exploration in volcanic magmatic belts of Iran.     

Statistical evaluation of remotely sensed data for water quality monitoring

The primary objective of this study was to determine relationships between water quality parameters (WQPs) and digital data from the Landsat satellite to estimate and map the WQP in the Porsuk Dam reservoir. Suspended sediments (SS), chlorophyll a (chl-a), NO₃-N and transmitted light intensity depth (TLID) were the parameters for water quality determination used in this study. Collection of these data, obtained from the General Directorate of State Hydraulic Works (GDSHW) was synchronized with the Landsat satellite overpass of the September 1987. The relationships between the brightness values (BV) of the TM data and WQP were determined. Using the TM data, we developed multiple regression equations to estimate the WQPs, and the validation of these equations was checked by using ANOVA. The effects of SS, NO₃-N and chl-a on TLID were tested not only for ground data, but also for TM datasets. Regression equations were developed for two different datasets and the homogeneity of those equations was tested. Finally, these regression equations evaluated from digital TM data and ground data were applied to map TLID values.     

Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery

Abstract

An algorithm is developed for automatic atmospheric correction of satellite imagery of the Earth's surface. The algorithm is based solely on the satellite image being corrected and on climatology of the area. It is applicable to low resolution (1 km field of view) and high resolution (10-80m field of view) imagery of land areas for the solar spectrum. The algorithm requires that some pixels in the image will correspond to dense dark vegetation as the surface cover. Once the presence of such pixels is established, the algorithm automatically chooses these pixels, derives the atmospheric optical thickness (a measure of the amount of haze) and corrects the image. The algorithm is sensitive to the assumed reflectance of the dense dark vegetation. As a result, the accuracy of the corrected surface reflectance (p) is expected to be δp-±0.01. It is not very sensitive to the assumed aerosol characteristics, the accuracy of satellite calibration or the knowledge of the exact fraction of the image covered by the dense dark vegetation. The correction algorithm was applied to clear and hazy Landsat Multispectral Scanner images of the same area in the Washington D.C. and the Chesapeake Bay region. The aerosol optical thickness (t_a) derived from the imagery shows a good agreement with simultaneous sunphotometer measurements from the ground within δT_a=±0.20 in band 1 (0.5.0.6) and δt_a=±0.05 in band 2 (0.6-0.7μm). The images in the hazy and clear days were corrected and compared. The comparison shows, for example, that the vegetation index was corrected from 0-39 in the clear day and 0-21 in the hazy day to 0-57± 0.01 in these two days. The algorithm, in its present form, can be applied to satellite imagery that includes at least two channels in the visible part of the spectrum, preferably blue and red. Application to the Advanced Very High Resolution Radiometer type of sensor (with one broad channel in the visible part of the spectrum) would need some modifications.     

Sun-stimulated chlorophyll fluorescence 2: Impact of atmospheric properties

Abstract

The Sun-stimulated chlorophyll fluorescence is a small but significant property of phytoplankton which can be detected using remote-sensing techniques. Besides the influence of oceanic properties, chlorophyll fluorescence is masked by atmospheric extinction. While an increase in chlorophyll concentration of 1 mg/m³ causes an increase in the upwelling radiances of about 0·03Wm^?2sr^?1 μm^?1 just above the water surface and due to the chlorophyll fluorescence, the upward radiances measured at λ_F = 685nm and at the top of the atmosphere ranges from 8 to 20Wm^?2sr^?1 μm^?1 for realistic atmospheric turbidity variations and a solar zenith distance of Θ_s = 50·7°. Additionally, the fluorescence, peaking at λ_F = 685nm with a half-width of about 10 nm, is reduced by the absorption of O₂ and H₂O. However, the fluorescence signal is nearly unaffected, when wavelengths λ≥686nm are exluded and a spectral interval of Δλ_F = 5nm is used for the radiance measurements.     

Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean

Optical measurements including remote sensing provide a potential tool for the identification of dominant phytoplankton groups and for monitoring spatial and temporal changes in biodiversity in the upper ocean. We examine the application of an unsupervised hierarchical cluster analysis to phytoplankton pigment data and spectra of the absorption coefficient and remote-sensing reflectance with the aim of discriminating different phytoplankton assemblages in open ocean environments under non-bloom conditions. This technique is applied to an optical and phytoplankton pigment data set collected at several stations within the eastern Atlantic Ocean, where the surface total chlorophyll-a concentration (TChla) ranged from 0.11 to 0.62 mg m^− 3. Stations were selected on the basis of significant differences in the ratios of the two most dominant accessory pigments relative to TChla, as derived from High Performance Liquid Chromatography (HPLC) analysis. The performance of cluster analysis applied to absorption and remote-sensing spectra is evaluated by comparisons with the cluster partitioning of the corresponding HPLC pigment data, in which the pigment-based clusters serve as a reference for identifying different phytoplankton assemblages. Two indices, cophenetic and Rand, are utilized in these comparisons to quantify the degree of similarity between pigment-based and optical-based clusters. The use of spectral derivative analysis for the optical data was also evaluated, and sensitivity tests were conducted to determine the influence of parameters used in these calculations (spectral range, smoothing filter size, and band separation). The results of our analyses indicate that the second derivative calculated from hyperspectral (1 nm resolution) data of the phytoplankton absorption coefficient, a_ph(λ), and remote-sensing reflectance, R_rs(λ), provide better discrimination of phytoplankton pigment assemblages than traditional multispectral band-ratios or ordinary (non-differentiated) hyperspectral data of absorption and remote-sensing reflectance. The most useful spectral region for this discrimination extends generally from wavelengths of about 425-435 nm to wavelengths within the 495-540 nm range, although in the case of phytoplankton absorption data a broader spectral region can also provide satisfactory results.     

Radiometric comparison of the LANDSAT-5 TM and MSS sensors

Abstract

This paper analyses the radiometric accuracy of LANDSAT-5 Thematic Mapper (TM) data and of LANDSAT-5 Multispectral Scanner (MSS) data, using concurrent TM and MSS images recorded simultaneously over the city of Montreal, Quebec, Canada. The data sets were obtained from the Canada Centre for Remote Sensing (CCRS), and have been preprocessed for geometric correction, and for radiometric 23calibration utilizing the in-flight calibration lamp data. The comparison of the TM and MSS normalized apparent reflectances computed for 12 different typical cover types using the post-launch calibration dynamic ranges shows the relevance of the CCRS processing systems. The significant linear regressions, obtained between channels from the two sensors, and the analysis of the ground reflectance corrected for atmospheric absorption and scattering as well as for pixel adjacency effects, can serve both to assess detector degradation with time and to rescale data to match those from other LANDSAT sensors.     

Bio‐optical properties and estimation of the optically active substances in Lake Tianmuhu in summer

Bio‐optical properties in an optically complex and biologically productive region of Lake Tianmuhu were determined in three cruises from June to August 2006. The concentrations of three optically active substances, tripton C _Tripton (calculated from total suspended matter and chlorophyll‐a (Chla) and phaeophytin‐a (Pa)), phytoplankton pigment C _Chla+Pa , and chromophoric dissolved organic matter (CDOM) a _CDOM(440), were predicted from the estimated irradiance reflectance based on in situ measurements and laboratory analyses. The total relative contributions of phytoplankton, tripton, CDOM and pure water over the range of photosynthetically active radiation (PAR) (400–700 nm) were 36.1%, 24.2%, 15.9% and 23.8%, respectively. The dominant contribution of phytoplankton to the total absorption was due to high phytoplankton pigment concentration. The range and variation in irradiance reflectance and diffuse attenuation coefficient derived from a bio‐optical model, based on inherent optical properties, compared well with the measured variability. A reasonably strong relationship (R² = 0.92) was observed between irradiance reflectance at 780 nm R(780) and C _Tripton. For our data set, the best algorithm for C _Chla+Pa used the three‐band reflectance model [R ^?1(688)?R ^?1(717)]×R(747). The a _CDOM(440) could be estimated using the ratio of irradiance reflectance R(682)/R(555). The retrieval accuracy (R²) of tripton, phytoplankton pigment and CDOM was 0.92, 0.87 and 0.91, respectively, while the rms. error was 0.90 mg l^?1 (18.2%), 3.27 µg l^?1 (14.8%) and 0.073 m^?1 (15.3%), respectively. Estimation of the concentrations of the three optically active substances was reasonably accurate based on inherent optical properties measurement.     

Crown closure estimation of oak savannah in a dry season with Landsat TM imagery: Comparison of various indices through correlation analysis

In this paper, we assess the capability of Landsat Thematic Mapper (TM) for oakwood crown closure estimation in Tulare County, California. Measurements made from orthorectified aerial photographs for the same area were used as a reference. The linear relationship between crown closure and digital values of each band of the TM image was examined. TM Band 3 had the highest correlation ( @ = m 0.828; R 2 = 0.687) with crown closure measurements. The simple ratio (SR) and the normalized difference vegetation index (NDVI) were generated for correlation analysis and only NDVI showed better correlation ( A = 0.836; R 2 = 0.699) than use of single bands. An additional index (NIR N - R N )/(NIR N + R N ), called NDVIN, was experimented, NDVISQ ( N = 2) and NDVICUB ( N = 3) showed some improvements over SR and NDVI ( A = 0.855; R 2 = 0.732 for N = 3). Through multiple regression with all six bands, we found that there was a considerable amount of improvement in variability explanation over any individual band or index tested ( R 2 = 0.803). NIR, red and blue bands were able to adequately model crown closure as using all the six TM bands ( R 2 = 0.802). Principal component analysis (PCA) and Kauth-Thomas (K-T) transform were applied to reduce multi-collinearity among bands. The third principal component and greenness in K-T transform showed similar effects to those of NDVI. Transformation of digital numbers (DNs) to radiances kept the results of single band and multiple band estimation the same, and did not improve the index estimation very much. A simple radiometric correction of the TM image improved results for the NDVI ( A = 0.840; R 2 = 0.705) and NDVISQ estimation ( A = 0.861; R 2 = 0.741), but worsened estimation results of single band and multiple bands.     

A drainage system analysis evaluation of,and comparison between,Landsat-3 RBV,Landsat-5 TM and SPOT PA imageries covering the Central Macedonia district,Greece

Abstract

Landsat-3 RBV, Landsat-5 TM imageries and SPOT PA stereopair diapositives were visually interpreted for the purpose of finding the accuracy of certain morphometric variables of three drainage basin sample areas in Central Macedonia, North Greece, drawn separately from each of the above three types of satellite imageries and comparisons were made between the efficiency of drainage systems drawn from each of the above imageries and the drainage systems extracted from the available topographic maps of 1:50000 scale.

The main findings were the following: (1) SPOT PA stereopair diapositives of 1:200000 scale can be used to map drainage systems to an order of magnitude slightly more than TM imagery of 1:125000 scale, but significantly more than RBV imagery of 1:125000 scale. This slight superiority of SPOT imagery over TM imagery implies that the greater spectral range of TM, compared with the shorter range of SPOT imageries, vastly outweighs the advantage of SPOT'S superior resolution, but not the superiority of stereoscopic view; (2) TM imagery can be used to map drainage systems to an order of magnitude significantly more than RBV imagery; and (3) RBV imagery can be used to map drainage systems to an order of magnitude less than topographic maps of 1:50000 scale but better than topographic maps of 1:100000 scale.