Shrinking lake basins in the proximity of the Indus Suture Zone of northwestern Himalaya: A case study of Tso Kar and Startsapuk Tso,using 1RS-1C data

The study of active tectonics in Himalaya is important as this helps to understand the style of evolutionary process of this gigantic mountain system in more specific terms. The formation of lakes, regarded as the crown stage development of an orogenic belt, is an impressive geomorphic feature that adorns the Himalayan belt end to end. Tso Kar and Startsapuk Tso are the two ancient lakes that lie south of the Indus Suture Zone in the northwestern Himalaya. An attempt has been made to map the former extent of these lakes, using remote sensing techniques, for providing vital clues in elucidating the paleoenvironmental conditions under which these water bodies were developed. It is observed that the dimension of these lakes has constantly fluctuated in time due to ongoing compression in the collision regime and possible climatic influences that have been recorded on a large scale globally. An added advantage of this study has been to evaluate the high spatial resolution data of the Indian Remote Sensing Satellite (IRS-1C) for geomorphological, lithological and structural inferences in the arid, inaccessible and complex terrain like the northwestern Trans Himalaya.     

Mapping groundwater salinity using IRS-1B LISS II data and GIS techniques

A procedure is presented for ground water exploration in terms of depth and quality in an alluvial terrain with shallow groundwater occurrence. The study area forms a part of the marginal Gangetic terrain with a clay-sand sequence. Variation in groundwater quality has been mapped in earlier research on the basis of field sampling and chemical analysis of groundwater. In the present study, a scheme of image processing and GIS techniques using false colour composites, vegetation indices, density slicing, image registration, overlaying, and supervised classification has been applied on IRS-1B LISS II data. Various zones established within the terrain based on our research are in conformity with ground water salinity and depth contours.     

Investigation of erosion on Hope Island using IRS-1D LISS-III data

Hope Island is a long spit formed in Kakinada Bay, India. It acts as a barrier to direct sea currents thus protecting Kakinada town, port and mangroves along the coast. Erosion was noticed at one section of the Island on visual interpretation of IRS-ID LISS-III imagery. In the absence of sea depth data it was difficult to analyse the extent of erosion along the height of the Island above the seabed. Remote sensing based bathymetric estimates were made and used to investigate the erosion problem at selected locations. The work considered the use of remote sensing for determining three-dimensional coastal erosion along slopes of Hope Island.     

Delineation of salt-affected soils and waterlogged areas in the Indo-Gangetic plains using IRS-1C LISS-III data

Waterlogging and subsequent salinization and/alkalinization is the major land degradation problem in irrigated commands in the arid and semi-arid regions. The Linear Imaging Self-scanning Sensor (LISS-III) digital data acquired by the Indian Remote Sensing Satellite (IRS-1C) over part of the Indo-gangetic plains are digitally analysed for delineating salt-affected and waterlogged areas on a IBM RS-6000 system. A comparison with the IRS-1B LISS-II data, with comparable spectral bands and acquired very close to LISS-III data, reveals a relatively poor overall classification accuracy achieved from this data as compared to LISS-II data. This may be attributed to higher intra-class spectral variations resulting from high spatial resolution LISS-III data. The classifiers capable of exploiting the spectral variations in spatial domain, like segmentation, textural analysis, etc., need to be used for exploiting the full potential of IRS-1C LISS-III data for mapping salt-affected soils and other degraded lands.     

The delineation of reclamative groups of ravines in the Indo-Gangetic alluvial plains using IRS-1D LISS-III data

Ravines, the intricate network of gullies and almost the penultimate stage of soil erosion by water, need to be reclaimed and their fertility restored, and normal fertile land needs to be protected from eroding away. Information on the nature, extent spatial distribution and temporal behaviour of ravines is a prerequisite in this endeavour. Spaceborne multispectral measurements by virtue of synoptic coverage at regular intervals hold immense potential for deriving the desired information in a timely and cost-effective manner. We report here the results of a study that was carried out to delineate the reclamative groups of ravines in the Bhind district of Madhya Pradesh, central India, using Linear Imaging Self-scanning Sensor (LISS-III) data from the Indian Remote Sensing Satellite (IRS-1D) mission. The approach essentially involves on-the-screen monoscopic visual interpretation of false colour images generated from pre- and post-monsoon LISS-III digital data after geo-referencing to Survey of India topographic maps at 1:50?000 scale, on a Silicon Graphics workstation using ERDAS/IMAGINE version 8.3, in conjunction with the ground truth and information on the terrain's relief derived from topographical maps. Information on land use/land cover derived from temporal LISS-III data enabled three reclamative categories of ravine to be delineated, namely shallow, medium and deep. The area under deep, medium and shallow ravines has been estimated to be 112?ha, 12?700?ha and 28?600?ha, respectively. The land use/land cover of these units further helped in identifying the areas requiring immediate attention.     

Comparison of adaptive filter,IHS and Fourier transform based techniques for IRS-1C PAN/LISS-III data merging

This paper proposes two techniques for merging of IRS-1C LISS-III and panchromatic images based on Fourier transform and adaptive filtering. Performances of the proposed data merging techniques have been assessed quantitatively along with that of intensity-hue-saturation (IHS) domain data merging using Sobel edge intensity and normalized difference vegetation index (NDVI). Frequency domain merging is found to give minimum spatial distortion, while IHS merging yields the minimum spectral loss.     

Geometric correction accuracy of IRS-1D PAN imagery using topographic map versus GPS control points

Geometric correction accuracy of IRS-1D panchromatic imagery was investigated using GPS- and 1?:?25?000 scale topographic map-derived control points. The differentially corrected GPS-derived coordinates provided markedly more accurate results than did uncorrected handheld GPS- and map-derived GCPs. The rms error value of differentially corrected GPS-derived control points based on second-degree polynomial was in the order of ±3?m. Geometric corrections made with second-degree polynomials, using both the map- and uncorrected handheld GPS-derived control points, yielded rms error values in the order of ±5?m. The results revealed that the uncorrected handheld GPS-derived control points can be a valuable alternative to planimetric control for geometric correction of IRS-1C/D panchromatic imagery with one-pixel size accuracy.     

An assessment of angular variations of red and NIR reflectances in multi-date IRS-1D Wide Field Sensor data

A study has been carried out to assess angular variations in red and near infrared (NIR) reflectance of different features of the Earth's surface in a common overlap area of accumulated four-date Indian Remote Sensing Satellite (IRS-1D) Wide Field Sensor (WiFS) data from the first fortnight of October 2003. An improved dark object subtraction (DOS) method has been used to perform image based atmospheric corrections. Red and NIR reflectance variations of four structurally different classes—dense vegetation (shrub), sparse crop (pearl millet/maize), wasteland and forest with Sun-target-sensor geometry were analysed. A linearly constrained least squares technique was used to estimate red and NIR model coefficients of the linear Ross Thick-Li Sparse (RTLS) semi- empirical Bidirectional Reflectance Distribution Function (BRDF) model and compared with Moderate Resolution Imaging Spectrometer (MODIS) BRDF product coefficients. The relative reflectance difference between two dates as well as anisotropic factors for red and NIR for all classes and dates were also computed. Red and NIR reflectance of the four land cover classes at different locations with different observation geometry were estimated using both WiFS derived and MODIS BRDF product RTLS model coefficients and compared with WiFS observed reflectance. It was found that the mean relative difference in red and NIR reflectances between consecutive dates varied between 4–11% and 6–8%, respectively, while the computed mean anisotropy factors varied between 3–10% in the red and 8–11% in the NIR. A small anisotropy in the Normalized Difference Vegetation Index (NDVI) as a function of the scattering angle was observed for the four land cover classes. This may imply that angular effects in WiFS are relatively small and do not exceed 10–11 % for the land cover classes considered here.     

Forest fire in the Central Himalaya: An extent,direction and spread using IRS LISS-I data

Central Himalaya, comprising eight hill districts of the Garhwal and Kumaun region of Uttar Pradesh, has witnessed one of the most devastating forest fires of recent decades during the months of May-June 1995. In order to provide a reliable estimate of the severity of damage caused due to forest fire and for monitoring of such event in future a methodology has been developed using IRS LISS-I data of the pre and peak fire period (26-27 May 1995). Four districts of Uttara Khand (Almora, Chamoli, Tehri and Pauri) which were severely affected by fire have been selected for this study. The results show that as on 27 May, 1995 a total of 2115 km2 which is 21.5 per cent of the total geographical area of these four districts had been subjected to various degrees of fire damage. The spread of the fire damage ranges from 600m to 2650 m altitude. Chir Pine areas indicated maximum loss followed by Mixed, Oak Mixed and Oak forests. Results of overlap area study show a north-west direction of fire spread with spread rate of nearly 3.82 km2/per hour in chir pine forest. This study stresses the need for high temporal resolution data and real time monitoring system, so as to provide precise information regarding direction and rate of fire spread in order to take prompt fire control measures, especially taking into consideration data available from IRS-1C/1D, IRS-P3/WIFS and planned 1 km resolution INSAT-2E with 3 bands (Red, NIR and MIR) with possibility of every 30 minutes data (6000 km by 6000km) and even one minute data capture (3000 km NS 6000 km NW). This would enhance the chances for 'ON LINE ADVICE' for large scale fire control.     

Forest cover assessment in north-east India--the potential of temporal wide swath satellite sensor data (IRS-1C WiFS)

There is a lack of scientific data on extent, type and the condition of tropical forests. In India, the forest cover assessment is being carried out by the Forest Survey of India (FSI) biennially satellite images. The assessment has not been able to present realistic details, especially for north-east India due to the nature of deforestation/degradation processes (primarily shifting cultivation). The present study suggests a methodology to monitor forest cover using IRS-1C Wide Field Sensor (WiFS) data. It avoids illumination differences and has a better temporal resolution. NOAA Advanced Very High Resolution Radiometer (AVHRR) data have also found considerable acceptance for land cover studies at the regional level. Many studies have found NOAA data deficient in presenting the regional status monitoring due to its coarse resolution. IRS-1C WiFS data with 188 m 2 188 m spatial resolution overcomes this deficiency. The study focuses on the approach of using temporal IRS-1C WiFS data for monitoring the phenological fluxes of forested landscape of north-east India. The Normalized Difference Vegetation Index (NDVI) is evaluated for monitoring seasonal changes in vegetation. Attempts are made to classify forest using the phenological characters as discriminant. A hybrid approach (unsupervised and supervised) of classification provided better results. The overall accuracy of different classes was found to be 82.15%. The Khat ( K hat ) significance coefficient was found to be 0.80. The present assessment of forest cover in the north-east region is 42.24% of the total geographical area. The estimate made by FSI is 64.31% of the geographical area. The estimate that is made based on visual interpretation has always been contested to be on the higher side. Comparison of the map and statistics reveals that inclusion of abandoned and current shifting cultivation areas in forest cover have led to the overestimation. The results indicate that IRS-1C WiFS data can be used to map and monitor vegetation cover at the regional scale. The stratification thus achieved can provide valuable input for land surface characterization for geosphere-biosphere studies.     

C/S分布式并行处理技术在高速局域网平台上实现非线性环境化学胞映射体系的大规模计算

通过100Mb/S集线器连接4台双CPU和2台单CPU计算机构成分布式并行计算的局域网平台，采用VC＋＋6．0高效、稳定、方便和成功地实现了分布式多线程并行计算，将非线性环境化学问题的胞映射大规模计算数值解体系进行了有效划分，并合理地分配到局域网上的每一台计算机上的每一个CPU中，然后通过局域网返回各自的处理结果，最后在客户机上完成各单项任务的总装，达到了可持续利用现有计算机资源和大幅度提高计算效率的目的。用这种低成本方式简单、清晰和快捷地掌握并行处理技术十分适应非计算机专业科研人员用来解决超大负荷计算量的复杂问题。     

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.     

The potential of kernel classification techniques for land use mapping in urban areas using 5m-spatial resolution IRS-1C imagery

Two techniques, integrating texture and spatial context properties for the classification of fine spatial resolution imagery from the city of Athens (Hellas) have been tested in terms of accuracy and class specificity. Both techniques were kernel based, using an artificial neural network and the kernel reclassification algorithm. The study demonstrated the high potential of the kernel classifiers to discriminate residential categories on 5 m-spatial resolution imagery. The overall accuracy percentages achieved were 73.44% and 74.22% respectively, considering a seven-class classification scheme. The adopted scheme was subset of the nomenclature referred to as 'Classification for Land Use Statistics Eurostat's Remote Sensing programme' (CLUSTERS) used by the Statistical Office of the European Communities (EUROSTAT) to map urban and rural environment.     

Towards automated mapping and monitoring of potentially dangerous glacial lakes in Bhutan Himalaya using Sentinel-1 Synthetic Aperture Radar data

The majority of glacial lakes around the world are located in remote and hardly accessible regions. The use of remote sensing data is therefore of high importance to identify and assess their potential hazards. However, the persistence of cloud cover, particularly in high mountain areas such as the Himalayas, limits the temporal resolution of optical satellite data with which we can monitor potentially dangerous glacial lakes (PDGLs). The ability of Synthetic Aperture Radar (SAR) satellites to collect data, irrespective of weather and at day or night, facilitates monitoring of PDGLs by without compromising temporal resolution. In this study, we present a semi-automated approach, based on a radar signal intensity threshold between water and non-water feature classes followed by post-processing including elevations, slopes, vegetation and size thresholds, to delineate glacial lakes in Sentinel-1 SAR images in Bhutan Himalaya. We show the capability of our method to be used for delineating and monitoring glacial lakes in Bhutan Himalaya by comparing our results to 10 m resolution Sentinel-2 multispectral data, field survey data, meteorological data, and a time series of monthly images from January to December 2016 of two lakes. Sentinel-1 SAR data can, moreover, be used for detecting lake surface area changes and open water area variations, at temporal resolution of six days, providing substantial advantages over optical satellite data to continuously monitor PDGLs.     

Mapping the density of woody vegetative cover using Landsat MSS digital data

Abstract

Woody vegetation is an important environmental component in most landscapes. The occurrence of some forms of woody cover is indicative of resource degradation whereas degradation is indicated by lack of cover in other situations. A capacity to measure cover, and hence change, to an acceptable levelof accuracy is thus an important indicator of resource degradation under most conditions. A means of estimating the percentage cover within individual resolution elements of scanner data has been developed and evaluated, with the results achieved being reported in this article. These results are sufficient for the technique to be included as an operational component in a rangelands monitor in New South Wales.     

Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor

Mapping tools are needed to document the location and extent of Phragmites australis, a tall grass that invades coastal marshes throughout North America, displacing native plant species and degrading wetland habitat. Mapping Phragmites is particularly challenging in the freshwater Great Lakes coastal wetlands due to dynamic lake levels and vegetation diversity. We tested the applicability of Hyperion hyperspectral satellite imagery for mapping Phragmites in wetlands of the west coast of Green Bay in Wisconsin, U.S.A. A reference spectrum created using Hyperion data from several pure Phragmites stands within the image was used with a Spectral Correlation Mapper (SCM) algorithm to create a raster map with values ranging from 0 to 1, where 0 represented the greatest similarity between the reference spectrum and the image spectrum and 1 the least similarity. The final two-class thematic classification predicted monodominant Phragmites covering 3.4% of the study area. Most of this was concentrated in long linear features parallel to the Green Bay shoreline, particularly in areas that had been under water only six years earlier when lake levels were 66 cm higher. An error matrix using spring 2005 field validation points (n = 129) showed good overall accuracy—81.4%. The small size and linear arrangement of Phragmites stands was less than optimal relative to the sensor resolution, and Hyperion's 30 m resolution captured few if any pure pixels. Contemporary Phragmites maps prepared with Hyperion imagery would provide wetland managers with a tool that they currently lack, which could aid attempts to stem the spread of this invasive species.     

Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data

The overarching goal of this study was to map irrigated areas in the Ganges and Indus river basins using near-continuous time-series (8-day), 500-m resolution, 7-band MODIS land data for 2001-2002. A multitemporal analysis was conducted, based on a mega file of 294 wavebands, made from 42 MODIS images each of 7 bands. Complementary field data were gathered from 196 locations. The study began with the development of two cloud removal algorithms (CRAs) for MODIS 7-band reflectivity data, named: (a) blue-band minimum reflectivity threshold and (b) visible-band minimum reflectivity threshold.A series of innovative methods and approaches were introduced to analyze time-series MODIS data and consisted of: (a) brightness-greenness-wetness (BGW) RED-NIR 2-dimensional feature space (2-d FS) plots for each of the 42 dates, (b) end-member (spectral angle) analysis using RED-NIR single date (RN-SD) plots, (c) combining several RN-SDs in a single plot to develop RED-NIR multidate (RN-MDs) plots in order to help track changes in magnitude and direction of spectral classes in 2-d FS, (d) introduction of a unique concept of space-time spiral curves (ST-SCs) to continuously track class dynamics over time and space and to determine class separability at various time periods within and across seasons, and (e) to establish unique class signatures based on NDVI (CS-NDVI) and/or multiband reflectivity (CS-MBR), for each class, and demonstrate their intra- and inter-seasonal and intra- and inter-year characteristics. The results from these techniques and methods enabled us to gather precise information on onset-peak-senescence-duration of each irrigated and rainfed classes.The resulting 29 land use/land cover (LULC) map consisted of 6 unique irrigated area classes in the total study area of 133,021,156 ha within the Ganges and Indus basins. Of this, the net irrigated area was estimated as 33.08 million hectares—26.6% by canals and 73.4z5 by groundwater. Of the 33.08 Mha, 98.4% of the area was irrigated during khariff (Southwest monsoonal rainy season during June-October), 92.5% irrigated during Rabi (Northeast monsoonal rainy season during November-February), and only 3.5% continuously through the year.Quantitative Fuzzy Classification Accuracy Assessment (QFCAA) showed that the accuracies of the 29 classes varied from 56% to 100%—with 17 classes above 80% accurate and 23 classes above 70% accurate.The MODIS band 5 centered at 1240 nm provided the best separability in mapping irrigated area classes, followed by bands 2 (centered at 859 nm), 7 (2130 nm) and 6 (1640 nm).     

The identification of rice fields using multi-temporal ERS-1 C band SAR data

In this paper, an approach for the use of spaceborne SAR data for rice field identification, as well as for land use classification, is demonstrated, by using multitemporal data acquired over the Ohgata-mura area, Akita, Japan with ERS-1 C-band SAR, in 1992. Two techniques for reducing the influence of speckle on the accuracy of rice field identification were tested. A comparison of the SAR results with land use survey data collected in 1993, and with Landsat TM data, shows the potential of the present approach.     

Mapping the degree of serpentinization within ultramafic rock bodies using imaging spectrometer data

In 0·4-2·5 μm reflectance spectra of serpentinized peridotites and synthetic olivine-serpentine-magnetite mineral mixtures, serpentinization is responsible for a decrease in contrast of olivine-pyroxene iron absorption features and an appearance and increase in OH^? absorption features near 1·4 μm and 2·3 μm. It is demonstrated that the degree of serpentinization is correlated positively with the depth of the 2·3 μm absorption feature, although small amounts of magnetite may obscure the spectral contrast and decrease the overall brightness of weakly serpentinized samples. This linear relationship is applied to map the degree of serpentinization from GER 63-channel imaging spectrometer data using the following methodology: (1) vegetation masking, (2) calculating the absorption band-depth of the 2·3 μm absorption feature, (3) translating this value into percentage serpentine-group minerals using an empirical linear model, and (4) estimating the degree of serpentinization at the remaining locations using conditional simulation techniques. Comparison or the results of the simulation with 49 field samples showed differences between + 33 per cent and ? 23 per cent serpentine-group minerals estimated.     

A Constructive Criticism of the C/C++ Proposal for Complex Arithmetic

The IEEE 754 and 854 standards regulate the behaviour of real floating-point arithmetic, as implemented in most current hard- and software systems. Although a myriad of libraries for complex floating-point arithmetic is available and in use, there is no general consensus on their implementation. The International C Standard describes in its Annex G guidelines for the implementation of complex arithmetic, in order to achieve a similar behaviour of complex floating-point arithmetic across C-language compliant implementations. In Section 2 we summarize its recommendations and outline the problems inherent to this approach. In Section 3 we describe how the lack of reliability, when computing certain complex-valued expressions, can be overcome. Throughout the discussion the rounding mode is assumed to be round-to-nearest, as in Annex G.