Evaluation of the Lakshadweep Sea as a site for vicarious calibration of the Ocean Colour Monitor

The uncertainty in the top-of-the-atmosphere (TOA) radiance is a result of uncertainties in aerosol components, water-leaving radiance (due to seawater constitutions) and whitecap radiance. This paper investigates the variability of these individual terms over the Arabian Sea and particularly in Lakshadweep region, to establish a site for vicarious calibration of the Ocean Colour Monitor (OCM). We found that fractional coverage of whitecap radiance is less than 0.5% for winds lower than 8 m s^?1 and its radiance contribution can be assigned to a constant value. For higher winds, the contribution from whitecap radiance to TOA radiance has to be considered along with the atmospheric stability factor. The Lakshadweep Sea, for most of the time, is characterized by a low concentration of chlorophyll-a, an oligotrophic water body and maritime aerosol.     

Satellite remote sensing of total ozone column (TOC) over Pakistan and neighbouring regions

Total ozone column (TOC) obtained from the Ozone Monitoring Instrument (OMI) on board the Aura satellite was utilized to examine the spatio-temporal distribution of atmospheric ozone over Pakistan and adjoining regions of Afghanistan, India, and Iran for October 2004 to March 2014. This region has not yet been evaluated in greater detail. A yearly spatial averaged value of 278 ± 2 DU was found over the region. A decadal increase of 1.3% in TOC value over study region was observed for the first time. Large spatial and temporal variability of TOC was found over the study region. Elevated ozone columns were observed over the regions with high NO₂ and CO concentrations. Analysis indicated that Srinagar city has the highest averaged value of 290 ± 3 DU whereas Jodhpur city showed the highest increasing trend of 1.9% per decade. A monthly averaged maximum value of 289 ± 8 DU and a minimum of 264 ± 5 DU were found during April and November, respectively, over the region. January showed a decreasing trend of ?0.8% and February exhibited the highest increasing trend of 5.1% per decade. Forward trajectory analysis showed the possibility of ozone transport from eastern parts of the study region towards the Indian Ocean (Bay of Bengal) through the subtropical jet stream creating low values at higher meridians in October. TOC data deduced from OMI and the Atmospheric Infrared Sounder were compared to check the level of correlation and the results showed significant correlation (r = 0.75) and an acceptable average relative difference of 4.2%.     

Assessment of total columnar ozone climatological trends over the Indian sub-continent

In the present study, long term satellite and Dobson spectrophotometer Total Column Ozone (TCO) data have been used to study the interannual variability and also to assess climatological trends in TCO over different geographical locations of Indian sub-continent. TCO data were analyzed for the period 1957 to 2015 over New Delhi (28.63° N, 77.18° E), Varanasi (25.30° N, 83.02° E), Pune (18.53° N, 73.84° E) and Kodaikanal (10.0° N, 77.47° E). An extensive validation was performed for Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) retrieved TCO data independently with Dobson Spectrophotometer TCO measurements over New Delhi, Varanasi, Pune and Kodaikanal. The results of this exercise showed good correlation coefficient (r) of 0.87 (0.88), 0.84 (0.82), 0.91 (0.80) and 0.84 (Data not available) respectively. Climatological mean TCO over New Delhi, Varanasi, Pune and Kodaikanal are 275.02 ± 6.44 DU, 269.03 ± 7.34 DU, 260.78 ± 5.07 DU and 258.71 ± 6.36 DU respectively for the period 1957 to 2015. An increasing trend over New Delhi (0.20 DU year^–1), Pune (0.18 DU year^–1), Kodaikanal (0.14 DU year^–1) and decreasing trend over Varanasi (0.01 DU year^–1) were observed. High significance of TCO trend was found at New Delhi (p-value < 0.0001), Pune (p-value = 0.002) and Kodaikanal (p-value = 0.003) with negligible trend over Varanasi with p-value of 0.84. The TCO variations at different geographical locations associated with upper atmospheric meteorological parameters such as lower Stratospheric Temperature (ST) at 65 hPa and Tropopause Height (TH) were also addressed. Annual lower stratospheric temperature shows positive relationship with TCO and Stratospheric ozone over the study sites. Further, decadal variability in TCO with respect to solar activity at New Delhi was also analyzed.     

Using multiple radiometric correction images to estimate leaf area index

Ecological applications of remote-sensing techniques are generally limited to images after atmospheric correction, though other radiometric correction data are potentially valuable. In this article, six spectral vegetation indices (VIs) were derived from a SPOT 5 image at four radiometric correction levels: digital number (DN), at-sensor radiance (SR), top of atmosphere reflectance (TOA) and post-atmospheric correction reflectance (PAC). These VIs include the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), slope ratio of radiation curve (K), general radiance level (L), visible-infrared radiation balance (B) and band radiance variation (V). They were then related to the leaf area index (LAI), acquired from in situ measurement in Hetian town, Fujian Province, China. The VI–LAI correlation coefficients varied greatly across vegetation types, VIs as well as image radiometric correction levels, and were not surely increased by image radiometric corrections. Among all 330 VI–LAI models established, the R ² of multi-variable models were generally higher than those of the single-variable ones. The independent variables of the best VI–LAI models contained all VIs from all radiometric correction levels, showing the potentials of multi-radiometric correction images in LAI estimating. The results indicated that the use of VIs from multiple radiometric correction images can better exploit the capabilities of remote-sensing information, thus improving the accuracy of LAI estimating.     

Water‐vapour retrieval from Meteosat 8/SEVIRI observations

This paper aims to propose operational algorithms to retrieve the total atmospheric water vapour content (W) using the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on‐board Meteosat 8. MODTRAN3.5 was used to obtain simulated data in the thermal infrared channels IR10.8 and IR12.0, in order to determine the numerical values of the coefficients of the algorithms. The algorithm proposed for land pixels takes into account the SEVIRI observation geometry and the radiometric temperatures obtained in the split‐window channels at two different times during a day and requires a minimum difference of 10 K in terms of temperature between the two situations. Comprehensive error analyses gave rms errors lower than 0.5 g cm^?2 when observations were taken between the nadir and 50°. The algorithm is validated with in situ values, i.e. radiosondes and W measurements with a CIMEL CE318 sun photometer, both obtained from a field campaign, with rms validation errors of 0.2 and 0.7 g cm^?2, respectively. Additionally, six stations all over the SEVIRI field of view were selected to validate the algorithm from radiosondes data, providing an rms error of 0.4 g cm^?2. Concerning sea pixels, the linear atmosphere–surface temperature relation is adapted to SEVIRI and takes into account the sea‐surface temperature, the atmospheric effective temperature, and the radiometric temperature in the IR10.8 channel. The total error obtained from this methodology has a value between 0.8 and 1.1 g cm^?2, and the validation is carried out using radiosonde data from four stations near the sea, providing rms errors lower than 0.6 g cm^?2.     

A study of spatial and temporal dynamics of total ozone over Southwest China with multi-source remote-sensing data

This article describes a study of the spatial and temporal dynamics of total ozone over Southwest China using satellite-retrieved total ozone products from 1996 to 2008 and a ground-based Dobson spectrophotometer. The findings indicated that the value of total ozone (265.7 Dobson unit (DU)) over Southwest China is lower than the value (273.7 DU) over the adjacent region at the same latitude by about 8 DU, and is about 13.8 DU lower than the global average at the same latitude (279.5 DU), and that there is a distinctly low-value area due to the higher elevation. The relationship of total ozone and the elevation presents a negative correlation, the terrain being the main factor to affect this condition. In the long term, the variation of total ozone exhibits a slightly increasing trend from 1996 over this region. Total ozone presents an obvious seasonal change, with the largest value appearing in springtime and the smallest appearing in wintertime. The difference between the regional seasonal mean value of total ozone in springtime and wintertime is about 28 DU, although the difference between the maximum and minimum monthly total ozone throughout a year is up to 50 DU. There is a positive correlation between the variation of total ozone and relative humidity. Relative humidity may be an important factor impacting on the pattern of seasonal change of total ozone.     

Evaluation of MODIS ocean colour products at a northeast United States coast site near the Martha's Vineyard Coastal Observatory

Moderate Resolution Imaging Spectroradiometer (MODIS) marine and atmospheric products were evaluated using match‐ups of MODIS and in situ measurements collected by an above‐water radiometric system, the SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM), deployed near the Martha's Vineyard Coastal Observatory from 2004 to 2005. The products evaluated include the normalized water‐leaving radiance L _wn in the visible and near‐infrared bands, and the aerosol optical thickness at 870 nm τ_a(870), and the Ångström exponent α(531). With a restricted match‐up criterion, the result shows that the MODIS‐retrieved L _wn at 488, 531 and 551 nm agree very well with SeaPRISM measurements, giving mean per cent differences δ(%) of 3–7%, absolute mean per cent differences |δ|(%) of ～16%, and coefficient of determination R ² of 0.84–0.88. However, the MODIS‐retrieved L _wn at 412 nm are underestimated significantly with δ(%), |δ|(%) and R ² of ?35%, 57% and 0.32, respectively, corresponding to a consistent overestimation and underestimation for the MODIS‐retrieved τ_a(870) and α(531), respectively. Temporal patterns of match‐ups revealing two distinct cases of the discrepancy of MODIS retrievals from in situ SeaPRISM measurements are discussed.     

Near‐surface air temperature estimation from ASTER data based on neural network algorithm

An algorithm based on the radiance transfer model (MODTRAN4) and a dynamic learning neural network for estimation of near‐surface air temperature from ASTER data are developed in this paper. MODTRAN4 is used to simulate radiance transfer from the ground with different combinations of land surface temperature, near surface air temperature, emissivity and water vapour content. The dynamic learning neural network is used to estimate near surface air temperature. The analysis indicates that near surface air temperature cannot be directly and accurately estimated from thermal remote sensing data. If the land surface temperature and emissivity were made as prior knowledge, the mean and the standard deviation of estimation error are both about 1.0 K. The mean and the standard deviation of estimation error are about 2.0 K and 2.3 K, considering the estimation error of land surface temperature and emissivity. Finally, the comparison of estimation results with ground measurement data at meteorological stations indicates that the RM‐NN can be used to estimate near surface air temperature from ASTER data.     

Comparison of Landsat 8 OLI and Landsat 7 ETM+ for estimating grassland LAI using model inversion and spectral indices: case study of Mpumalanga,South Africa

The leaf area index (LAI) is the key biophysical indicator used to assess the condition of rangeland. In this study, we investigated the implications of narrow spectral response, high radiometric resolution (12 bits), and higher signal-to-noise ratio of the Landsat 8 Operational Land Imager (OLI) sensor for the estimation of LAI. The Landsat 8 LAI estimates were compared to that of its predecessors, namely Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (8 bits). Furthermore, we compared the radiative transfer model (RTM) and spectral indices approaches for estimating LAI on rangeland systems in South Africa. The RTM was inverted using artificial neural network (ANN) and lookup table (LUT) algorithms. The accuracy of the models was higher for Landsat 8 OLI, where ANN (root mean squared error, RMSE = 0. 13; R² = 0. 89), LUT (RMSE = 0. 25; R² = 0. 50), compared to Landsat 7 ETM+, where ANN (RMSE = 0. 35; R² = 0. 60), LUT (RMSE = 0. 38; R² = 0. 50). Compared to an empirical approach, the RTM provided higher accuracy. In conclusion, Landsat 8 OLI provides an improvement for the estimation of LAI over Landsat 7 ETM+. This is useful for rangeland monitoring.     

Simulation of high-resolution mid-infrared (3–5 μm) images using an atmosphere radiative transfer analytic model

Future mid-infrared satellite missions exploring the Earth will feature advanced high spatial resolution and directional imaging instruments. Consistent end-to-end simulation of them is an important task, and is sometimes the only way to adapt and optimize a sensor and its observation conditions, to choose and test algorithms for data processing, to estimate errors and to evaluate the capabilities of the whole sensor system. However, contrary to other wavelength ranges, the mid-infrared is highly dependent on atmospheric scattering and emission. Therefore, simulation of atmospheric radiative transfer for remote sensing images will remain a challenging task, because few studies on this topic include a full treatment of atmospheric effects. With a given resolution and directional capabilities of the instrument, and combining with land surface temperature and emissivity data obtained from airborne imagery, TOA (top of atmosphere) radiance images have been simulated pixel by pixel, coupling the atmospheric radiative transfer analytic model extended from MODTRAN4 and the atmospheric adjacency effect model derived from point spread function (for atmospheric directional and adjacency effect). In this way, all major scattering and emission contributions of atmosphere were considered. Based on different atmospheric conditions and geometrical relations between the scene, the Sun and the sensor, simulated TOA radiance images were produced according to simulated workflows, 10-m spatial resolution and a spectral range of 3.5–3.9 μm. Analysis of results indicates that the analytic model and adjacency effect model are more suitable for mid-infrared imaging simulation than other existing models. This paper describes the principle of the two models, the applied methodology, the set-up of the actual image simulations, and then discusses the final results obtained.     

On a theorem of Megan and Zabczyk

It will be proved that for any linear infinite-dimensional control system [xdot](t) = Ax(t) + Bu(t) and for any p ? [1, ∞], the implication that ‘complete stabilizabitity ? the T-controllability operator for L ^p -controls is surjective’ holds true provided A generates a strongly continuous group of bounded linear operators. This extends a theorem by Megan and Zabczyk in several directions. In particular, not necessarily separable Banach spaces are allowed, and also the class of controls which are sufficient to ensure exact controllability is restricted.     

Applicability of the PROSPECT model for Norway spruce needles

The potential applicability of the leaf radiative transfer model PROSPECT (version 3.01) was tested for Norway spruce (Picea abies (L.) Karst.) needles collected from stress resistant and resilient trees. Direct comparison of the measured and simulated leaf optical properties between 450–1000 nm revealed the requirement to recalibrate the PROSPECT chlorophyll and dry matter specific absorption coefficients k _ab(λ) and k _m(λ). The subsequent validation of the modified PROSPECT (version 3.01.S) showed close agreement with the spectral measurements of all three needle age‐classes tested; the root mean square error (RMSE) of all reflectance (ρ) values within the interval of 450–1000 nm was equal to 1.74%, for transmittance (τ) it was 1.53% and for absorbance (α) it was 2.91%. The total chlorophyll concentration, dry matter content, and leaf water content were simultaneously retrieved by a constrained inversion of the original PROSPECT 3.01 and the adjusted PROSPECT 3.01.S. The chlorophyll concentration estimated by inversion of both model versions was similar, but the inversion accuracy of the dry matter and water content was significantly improved. Decreases in RMSE from 0.0079 g cm^?2 to 0.0019 g cm^?2 for dry matter and from 0.0019 cm to 0.0006 cm for leaf water content proved the improved performance of the recalibrated PROSPECT version 3.01.S.     

Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin

This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO₂) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO₂ from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO₂ column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO₂ column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO₂ column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO₂ columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO₂. A detailed analysis of volcanic SO₂ transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO₂ at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO₂ enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO₂. For the first time, we present significant influence of volcanic SO₂ from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO₂ levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively.     

Cover Digital Mosaic of The Netherlands from LANDSAT-MSS data in natural colour

Upwelling radiance and downwelling irradiance measurements were made at 0-65 nm intervals in the 400-700 nm spectral range from an aircraft flown at an altitude of 150m around 07.30, 10.06 and 11.07hours GMT. Each time the location was different and at each location the measurements were repeated three times. The NIMBUS-7 satellite overpass was at 10.04 hours GMT.

The aerosol optical path length was evaluated from the in situ measured downwelling irradiance. The time dependence of the calibration slopes and intercepts of the Coastal Zone Colour Scanner (CZCS) was incorporated according to recent work by Gordon el at. The atmospheric contributions were removed from the measured radiances and from the CZCS data. The resulting water-leaving radiances were normalized so as to minimize those variations in the water-leaving radiance which arise from varying solar irradiance at the sea surface.

A comparison between the normalized water-leaving radiance retrieved from airborne measurements (10.06 hours GMT) and from the CZCS data (10.04 hours GMT) indicates that (i) the calibration slopes of 443 and 520 nm spectral channels should be slightly larger than those calculated according to Gordon et al., whereas (ii) there is a converse indication for the 550 nm spectral channel.

The calibration slopes of the CZCS channels 1-3 detectors were calculated by forcing the CZCS value of the normalized water-leaving radiance to be equal to the one resulting from the airborne measurements. The slopes are remarkably close to the values calculated by using the method of Gordon et al.     

Evaluation of atmospheric correction and high-resolution processing on SeaDAS-derived chlorophyll-a: an example from mid-latitude mesotrophic waters

Over the last 15 years, great effort has gone into the development of chlorophyll-a (chl-a) retrieval algorithms for case 2 waters, where variations in the water leaving radiance signal are not well correlated with concentrations of chl-a. In this study, we investigate the effectiveness of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived chl-a retrieval algorithms in the less productive coastal waters around Tasmania, Australia. Algorithms were evaluated using matches between satellite imagery and in-situ water samples (number of samples, n = 16–65) derived from a 604 sample data set collected over a 9-year period. Three aerosol correction models and three chl-a retrieval algorithms were evaluated using both standard and high-resolution processing procedures using the National Aeronatics and Space Adminstration’s SeaDAS software package. chl-a retrievals were evaluated in Bass Strait, where in-situ chl-a was less than 1 mg m^?3 and retrievals were less affected by coloured dissolved organic matter. chlor_a, the default SeaDAS chl-a product, with the Management unit of the North Sea Mathematical models aerosol correction algorithm performed best (root mean square error (RMSE) = 0.09 mg m^?3; mean absolute percentage error (MAPE) = 34%; coefficient of determination, R² = 0.75). The fluorescence line height algorithm using Rayleigh corrected top of atmosphere reflectances (RMSE = 0.11 mg m^?3, MAPE = 41%, R² = 0.61) may provide an alternative in waters where full atmospheric correction is problematic and the two-band red/near-infrared algorithm failed to provide a meaningful estimate of chl-a. High-resolution processing of MODIS imagery improved spatial resolution but reduced chl-a retrieval accuracy, reducing the agreement between measured and predicted levels by between 12% and 25% depending on the retrieval algorithm. The SeaDAS default chlor_a product proved superior to the alternatives in mid-latitude mesotrophic coastal waters with low chl-a concentrations. In addition, there appears little benefit in using MODIS high-resolution processing mode for chl-a retrievals.     

Improvement of the Umkehr ozone profile by the neural network method: analysis of the Belsk (51.80°N, 20.80°E) Umkehr data

Vertical profiles of atmospheric ozone by the neural network (NN) method are compared with those obtained by the standard Umkehr inversion algorithm – UMK92. Both methods used the same input, the so-called N values, derived from Umkehr measurements at Belsk (51.80°N, 20.80°E), Poland, by the Dobson spectrophotometer No 84. The vertical profiles of ozone from satellite observations, Microwave Limb Sounder (MLS) overpasses for the period 2004–2009, and from ozonesoundings performed at the nearby aerological station, Legionowo (52.4° N, 21.0° E), for the period 2000–2009 provide a reference data set for the NN model building. The NN methodology appears to be a promising tool for extracting information about the vertical ozone profile from ground-based Umkehr measurements, despite some limitations of the NN method itself, such as the results being limited to the analysed station, sensitivity to errors in the reference data sets, and lack of possibility to determine the actual retrieval errors. Accuracy of the NN ozone profiles is better for all Umkehr layers than that by the standard Umkehr inversion algorithm when NN and UMK92 profiles are compared with the reference profiles. It is especially pronounced for comparisons with the ozonesonde profiles for layers 4 and 1, where the absolute error changes from 10.6 Dobson units (DU) (UMK92) to 4.4 DU (NN) and from 6.6 DU (UMK92) to 3.5 DU (NN), respectively (1 Dobson unit is equal to 2.69 × 10²⁰ molecules/m²). The mean (over all Umkehr layers) correlation coefficient between NN-MLS, and NN-ozonesonde profiles is 0.75 and 0.85, respectively. The corresponding correlation coefficients for the comparison with UMK92 profiles are lower, i.e. 0.61 and 0.64, respectively.     

Evaluation of CMODIS-measured radiance by a hyperspectral model

A Chinese Moderate Resolution Imaging Spectrometer (CMODIS), an ocean colour sensor onboard the ‘Shenzhou-3’ spaceship, was launched on 25 March 2002. Because CMODIS was not equipped with any onboard calibration systems, there were major concerns about the accuracy of the CMODIS radiance measurements as well as the reliability of the data processing and oceanographic applications. To clarify these concerns, a hyperspectral satellite remote sensing radiance evaluation model (HRSREM) was developed, based on a radiative transfer model with consideration of multiple-scattering effects and atmospheric absorption. The model was used to compute the total radiance at the top of the atmosphere (TOA) to evaluate the CMODIS-derived radiance. The accuracy of the model was validated by Gordon's algorithms [Wang, M. and Gordon, H.R., 1994 Wang, M. and Gordon, H.R. 1994. A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS. Remote Sensing of Environment, 50: 231–239. [Crossref], [Web of Science ®] , [Google Scholar], A simple, moderately accurate, atmospheric correction algorithm for SeaWiFS. Remote Sensing of Environment, 50, pp. 231–239] and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data. The results show that the average relative error in the atmospheric scattering radiance computed by the HRSREM is less than 1.5% and the average error in the HRSREM TOA radiance is about 3.0%. Therefore, the HRSREM can be used to evaluate the accuracy of CMODIS-measured radiance. The results show that CMODIS has relatively small errors at the visible bands but large errors at the near-infrared (NIR) bands with an average error of more than 100%. The laboratory calibration coefficients are not reliable and the CMODIS data were recalibrated by the HRSREM to recover the archive of CMODIS data.     

Absolute vicarious calibration of OCM2 and AWiFS sensors using a reflectance-based method over land sites in the Rann of Kutch,Gujarat

A study was carried out to estimate vicarious calibration coefficients for the OCM2 (Ocean Color Monitor) sensor onboard Oceansat-2 and also the AWiFS (Advanced Wide Field Sensor) sensor onboard Resourcesat-1 using reflectance measurements over three land sites – Dhrangadhra, Desalpar, and Bhachau – in the Rann of Kutch, Gujarat, India, on four dates (17 October 2010, 25 and 29 April 2011, and 1 May 2011). Hyperspectral field reflectance measurements of the study sites (of extent ?2 km?×?2 km) in the wavelength range 325–2500 nm, along with measurements of atmospheric parameters (aerosol optical depth (AOD), water vapour, ozone) and sensor spectral response functions, were input to the 6S atmosphere correction code to compute top-of-atmosphere (TOA) at-satellite radiance in the eight visible and near infrared (NIR) bands of OCM2 and the four visible, NIR, and shortwave infrared (SWIR) bands of the AWiFS sensor. The uncertainty in vicarious calibration coefficients due to measured spatial variability of field reflectance, aerosol optical thickness (AOT), water vapour, and ozone, was also computed for the OCM2 sensor for three dates (25 and 29 April 2011, 1 May 2011). The effect of surface anisotropy on TOA radiance was studied using a 15 day Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) product covering the study sites.

The results show that there is an indication of change in calibration coefficients in OCM2, for band 2 (25 April Desalpar data), bands 2 and 5 (29 April Desalpar data), and bands 2–5 and 7 in Bhachau (1 May data), all at the 1σ level. For these bands, in the inverse mode, the 6S corrected surface reflectance was closer to field surface reflectance when estimated at-sensor radiances were used as input to the code. For AWiFS, there was no evidence of change in calibration coefficients of all four bands at the 1σ level. It was found that site spatial variability was a critical factor in estimating change in sensor calibration coefficients and influencing uncertainty in TOA radiance for all three sites.     

Derivation of a threshold function for the Advanced Very High Resolution Radiometer 3.75 µm channel and its application in automatic cloud discrimination over snow/ice surfaces

The distinct contrast between the reflectance of solar radiation in Advanced Very High Resolution Radiometer (AVHRR) channel 3 (3.75?µm) by clouds and by bright surfaces provides an effective means of cloud discrimination over snow/ice surfaces. A threshold function for the top-of-atmosphere (TOA) albedo in channel 3 (r ₃) is derived and used to develop an improved method for cloud discrimination over snow/ice surfaces that makes explicit use of TOA r ₃. Corrections for radiance anisotropy and temperature effects are required to derive accurate values of r ₃ from satellite measurements and to utilize the threshold function. It has been used to retrieve cloud cover fractions from National Oceanic and Atmospheric Administration (NOAA)-14 AVHRR data over the Arctic Ocean and over the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site in Barrow, Alaska. The retrieved cloud fractions are in good agreement with SHEBA (Surface HEat Budget of the Arctic Ocean) surface visual observations and with NSA cloud radar and lidar observations, respectively. This method can be utilized to improve cloud discrimination over snow/ice surfaces for any satellite sensor with a channel near 3.7?µm.     

A fast distributed approximation algorithm for minimum spanning trees

We present a distributed algorithm that constructs an O(log n)-approximate minimum spanning tree (MST) in any arbitrary network. This algorithm runs in time Õ(D(G) + L(G, w)) where L(G, w) is a parameter called the local shortest path diameter and D(G) is the (unweighted) diameter of the graph. Our algorithm is existentially optimal (up to polylogarithmic factors), i.e., there exist graphs which need Ω(D(G) + L(G, w)) time to compute an H-approximation to the MST for any $H\,\in\,[1, \Theta({\rm log} n)]We present a distributed algorithm that constructs an O(log n)-approximate minimum spanning tree (MST) in any arbitrary network. This algorithm runs in time ?(D(G) + L(G, w)) where L(G, w) is a parameter called the local shortest path diameter and D(G) is the (unweighted) diameter of the graph. Our algorithm is existentially optimal (up to polylogarithmic factors), i.e., there exist graphs which need Ω(D(G) + L(G, w)) time to compute an H-approximation to the MST for any . Our result also shows that there can be a significant time gap between exact and approximate MST computation: there exists graphs in which the running time of our approximation algorithm is exponentially faster than the time-optimal distributed algorithm that computes the MST. Finally, we show that our algorithm can be used to find an approximate MST in wireless networks and in random weighted networks in almost optimal ?(D(G)) time.