Cloud classification in NOAA AVHRR imageries using spectral and textural features

Clouds contribute significantly to the formation of many of the natural hazards. Hence cloud mapping and its classification becomes a major component of the various physical models which are used for forecasting natural hazards. The problem of cloud data classification from NOAA AVHRR (advance very high resolution radiometer) satellite imagery using image transformation techniques is considered in this paper. The singular value decomposition (SVD) scheme is used to extract the salient spectral and textural features attributed to satellite snow and cloud data in visible and IR channels. The goals of this paper are to discriminate between clear sky and clouds in an 8 × 8 pixel array of 1.1 km AVHRR data. If clouds are present then classify them as low, medium or high range. This scheme can effectively segregate clouds and non-cloud features in the visible and IR bands of the imagery. It can also classify clouds as low, medium or high range with a success rate of 70–90%. Computer-based snow and cloud discrimination and automatic cloud classification system will help the forecaster in various climatological applications, viz., energy balance estimation, precipitation forecasting, landslide forecasting, weather forecasting and avalanche forecasting etc.     

A multi-model decision support system (MM-DSS) for avalanche hazard prediction over North-West Himalaya

Natural Hazards - Avalanche forecasting is carried out using physical as well as statistical models. All these models have certain limitations associated with their mathematical formulation that...     

Evaluation of time scale of meteorological,hydrological and agricultural drought indices

Natural Hazards - The present study was carried out to characterize drought in the Marathwada region of Maharashtra, which experiences recurring droughts, through meteorological, hydrological and...     

Chandra and XMM–Newton observations of the low-luminosity X-ray pulsators SAX J1324.4−6200 and SAX J1452.8−5949

We present results from our Chandra and XMM–Newton observations of two low-luminosity X-ray pulsators  SAX J1324.4−6200  and  SAX J1452.8−5949  which have spin periods of 172 and 437 s, respectively. The XMM–Newton spectra for both sources can be fitted well with a simple power-law model of photon index,  Γ∼ 1.0  . A blackbody model can equally well fit the spectra with a temperature,   kT ∼  2 keV, for both sources. During our XMM–Newton observations,  SAX J1324.4−6200  is detected with coherent X-ray pulsations at a period of 172.86 ± 0.02 s while no pulsations with a pulse fraction greater than 18 per cent (at 95 per cent confidence level) in 0.2–12 keV energy band are detected in  SAX J1452.8−5949  . The spin period of  SAX J1324.4−6200  is found to be increasing on a time-scale of     which would suggest that the accretor is a neutron star and not a white dwarf. Using subarcsec spatial resolution of the Chandra telescope, possible counterparts are seen for both sources in the near-infrared images obtained with the son of infrared spectrometer and array camera (SOFI) instrument on the New Technology Telescope. The X-ray and near-infrared properties of  SAX J1324.4−6200  suggest it to be a persistent high-mass accreting X-ray pulsar at a distance  ≤8 kpc  . We identify the near-infrared counterpart of  SAX J1452.8−5949  to be a late-type main-sequence star at a distance ≤10 kpc, thus ruling out  SAX J1452.8−5949  to be a high-mass X-ray binary. However, with the present X-ray and near-infrared observations, we cannot make any further conclusive conclusion about the nature of  SAX J1452.8−5949  .     

Major ion chemistry of Renuka Lake and weathering processes, Sirmaur District, Himachal Pradesh, India

Renuka Lake in the Lesser Himalaya, Himachal Pradesh is in a valley surrounded by mountains comprised of highly crumpled, shattered, crushed, folded and dislocated rocks consisting of carbonaceous shales-slates often pyrite-ferrous, limestone, quartzites, boulder beds, etc. A detailed and systematic study of the major ion chemistry of the lake, clay mineral composition of the bed and core sediments and the Pb²¹⁰ isotope estimation in the latter was conducted. The chemistry is dominated by carbonate weathering and (Ca + Mg) and (HCO₃ + SO₄) accounts for about 90% of the cations and anions. The SO₄ content is almost the same as the HCO₃. The low contribution of (Na + K) to the total cations and the (Ca + Mg) and HCO₃ data tends to indicate that silicate weathering has not been the potential source of major ions to the lake waters. This difference may be related to the increasing susceptibility to weathering of carbonate over silicate rocks exposed in the catchment and also seepage of water at the bottom. The high sulphate content in waters is derived from dissolution of pyrite-ferrous reduced black shales, which constitute a significant lithology in the catchment. The chemical index of alteration (CIA) value in core sediments is on an average 76, which is comparable with average shale (70-75) and the rate of sedimentation 3.3 mm/year based on measurement of Pb²¹⁰, indicating a fairly high weathering rate in the catchment. Illite is the dominant clay mineral (52-90%) in the bed and core sediments, chlorite constitutes 7-48% and the kaolinite-chlorite mixed silicate layer is l-2%. This is consistent with the shale-slate, sandstone lithology in the valley.     

Total information content as an index of soil moisture

Accurate estimation of soil moisture through remote sensing technique has been a challenge till date. In optical and thermal remote sensing, there is no index developed to detect the changes in soil moisture levels. In microwave region, soil roughness and other target parameters equally affect the technique for soil moisture estimation. Therefore, a computational technique in C language based on Shannon’s Information Theory (Shannon, 1948) has been developed to calculate total information content from multispectral radiometer data. The total information content is a compressed single value, which quantifies the information content of soil spectral reflectance in the electromagnetic spectrum range (400–1100 nm) under study. This technique was tested over a wide range of soil moisture levels. The study revealed that as compared to other techniques total information content index is very sensitive to change in moisture content of soil. This technique could not only quantify the soil moisture content in optical and near infra red region, but also led to a simplified one dimensional separability and clustering analysis.     

Satellite based study of land transformation in Ludhiana District, Punjab

This study reveals the temporal changes in the land use/land cover of district Ludhiana from the years 1970 to 2001 and reports on the change that has occurred in land use/land cover as a result of change in cropping pattern. The changes were analysed through the data obtained from statistical abstract 1969–70, False Colour Composite (FCC) of IRS-IC LISS-III satellite data of March 2001 and ground truth. There has been a decrease in agricultural land by 2100 ha. but still it occupies 83.76% of the total geographical area (TGA). The wasteland shows a declining trend whereas forest cover has increased from 1.07 to 2.71% of TGA. Area under non-agricultural uses has increased from 10.13 to 12.50% of TGA. There has also been a great change in the cropping pattern of the district. Crops such as groundnut, gram and cotton have nearly disappeared and wheat and rice dominate the region. This change has substantially resulted in the decrease of area under wastelands.     

Lithofacies and palaeosol analysis of the Middle and Upper Siwalik Groups (Plio–Pleistocene), Haripur-Kolar section, Himachal Pradesh, India

The Middle–Upper Siwalik Groups (Plio–Pleistocene) are exposed at Haripur-Kolar, Himachal Pradesh, India. The succession is 2800-m thick and has been subdivided into Unit M1 of the Middle Siwalik and four units U1–U4 of the Upper Siwalik Group, on the basis of facies associations, and type and degree of development of palaeosols. The available magnetostratigraphic ages for bases of Units U1, U3 and U4 are 5.5, 2.6 and 1.77 Ma, respectively. The top of the section has been dated as 19 ka.

Lithofacies association and palaeocurrent analysis indicates that the Middle and Upper Siwalik Groups were formed mainly by a basin transverse fluvial system. Two types of river systems, which differ in their size, can be documented in Unit-M1, Unit U1 and Unit-U2: one trunk river system similar to the modern Kosi and the other smaller river system, which formed tributaries to the former. The large rivers were mainly braided in nature. The Unit U3 and lower part of Unit U4 were deposited in the piedmont depositional system mainly by small braided streams and the upper part of the Unit U4 was deposited during a period of arid climate by sediment gravity-flows.

Integration of fluvial lithofacies and pedofacies helps to identify two fluvial depositional systems from the modern Indo-Gangetic Plains. The Lowland System involved deposition on alluvial megafans and interfan areas, which resulted in sand-rich and mud-rich sequences with weekly developed soils. The Upland System allowed large tracts to act as high ground for thousands of years, thereby giving rise to sandstone poor intervals with moderately to strongly developed soils. Occurrence of moderately to strongly developed soils was controlled by uplifting and tilting of large tectonic blocks, without any relation to distance from the main channels. Rate of subsidence apparently controlled the occurrence of Lowland and Upland systems. Deposition of the Unit M1, Unit U1 and Unit U2 took place under Upland and Lowland systems, very similar to those identified from the modern Indo-Gangetic Plains. The warm and humid climate between 5.3 and 2.6 Ma led to the formation of red Alfisols with calcrete nodules at places. Slightly cooler and drier climate starting at about 2.6 Ma and approximately coinciding with the onset of global-scale glaciation, produced poorly developed yellow soil with common development of nodular calcretic horizon and calcitc material disseminated in the groundmass. At ca. 0.9 Ma, a probable significant change to still drier and cooler climate produced typical sediment gravity-flows in the piedmont system, that continued until at least up to 19 ka.     

Ground validation of an algorithm for estimating surface suspended sediment concentrations from multi-spectral reflectance data

Pollution of water resources by sediments eroded from degraded watersheds is a critical concern around the world. Current methods for locating these eroding areas and off-site damage to water resources through visual observations and field sampling with subsequent laboratory analysis are time consuming and expensive. There is thus, a justified interest in developing algorithms for quick estimation of suspended sediment concentrations in large water-bodies from remotely sensed data. This paper presents the results of a ground validation study on characterization and quantification of surface suspended sediment concentrations (SSC) in sediment laden water bodies through an n-waveband specific numerical index, total information content. A comparison of SSC-predictive potential of the proposed new index, derived from four broad (100–300 nm) Landsat MSS, five broad (40–300 nm) Landsat TM and eight narrow (20–40 nm) IRS-P4 OCM spectral bands, with that of the conventional (NIR-Red and NIR+Red) indices, computed from the same spectral band data, is also presented. The study reveaied that at SSCs 250 mg/1, the proposed index (derived from either broad / narrow landsat MSS/TM or IRS-P4 OCM spectral data) could lead to SSC predictions (with mean errors within 20%) comparable with those obtained with the conventional indices (derived from the same spectral band data). It could further be observed that, in general, lower sediment concentrations (i.e. SSCs 150 mg/1) were associated with higher prediction inaccuracies. A comparison of the mean errors of predictions associated with the proposed and the conventional (NIR-Red and NIR+Red) indices computed from broad and narrow band data for SSCs 150 mg/I, revealed that an increase in number of wavebands (from 4 MSS to 5 TM or 8 OCM bands) and a decrease in the bandwidth of these wavebands (from broad MSS/ TM bands to narrow OCM bands) led to a significant increase in the prediction accuracy of the proposed new index. These prediction accuracies were observed to be the highest with the proposed index calculated from narrow OCM-P4 spectral data. However this could not be observed with the conventional indices at any of the SSC ranges and with the proposed index at SSCs 250 mg/l. This shows that the lower SSC-predictive potential of proposed index was a significant function of both the number and the bandwidth of spectral bands used for its computation. In fact in one of the cases, lower SSC (150 mg/l) -predictive accuracy of the proposed index was found to be significantly higher than that of the conventional (NIR+R) index. The proposed algorithm could thus compress the information contained in the entire reflectance spectrum of the sediment laden water bodies to their sediment type and concentration specific characteristic values. This characteristic of the proposed index was not shared by any of the conventional indices, based on only two waveband data. In fact the proposed index appears to be the only mean of completely compressing and quantifying the information contained in all the information channels of a narrow band spectrometer (consisting of 200 wavebands) to be shortly launched by ISRO for satellite based inventory of natural resources.     

Comparative evaluation of water quality zonation within Dwarka River Basin,India

This study evaluates the thematic representation of drinking water quality of 211 habitations along the Dwarka River Basin (DRB), West Bengal, India. The dominant water type is Ca–Mg–HCO₃. Statistical analysis of the spatial dataset indicates a clustering pattern (with a nearest-neighbour ratio of 0.368 and Z score of 29.774). Two different techniques, spatial interpolation of water quality index (WQI) and composite water quality index (WQI_C) of physico-chemical constituents, were implemented to compare their performance. The WQI_C indicates approximately 11.68% of the total study area is at non-permissible levels, whereas the normal WQI technique predicts about 1.64% of the area is in non-permissible zones. Spatial water quality zonation by means of the overlay technique was superior to the conventional WQI technique in precisely distinguishing the characteristics of the permissible area with respect to even a single WHO recommended water quality parameter.