Combination of GPS and VLBI on the observation level during CONT11—common parameters,ties and inter-technique biases

Multi-technique space geodetic analysis software has been developed which allows to combine data on the observation level. In addition to local tie information, site-wise common parameters, i.e., troposphere and clocks, can be estimated with this software. Thus, it will be discussed how common parameters have to be estimated and where biases/offsets need to be taken into account. To test such a novel concept, Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) data from the CONT11 campaign are being utilized. Since the VLBI baselines of this campaign extend over several thousands of kilometers, GPS data are processed in precise-point positioning mode and satellite orbits and clocks are kept fixed to the IGS final products. From the obtained results, it can be shown that the combination of space geodetic data on the observation level leads to a consistent improvement of station position repeatability as well as nuisance parameters like troposphere estimates. Furthermore, estimation of common parameters (troposphere or clocks) at co-located sites helps to improve the solution further and derive an utmost physically consistent model of the concerned parameters.     

A complete VLBI delay model for deforming radio telescopes: the Effelsberg case

Deformations of radio telescopes used in geodetic and astrometric very long baseline interferometry (VLBI) observations belong to the class of systematic error sources which require correction in data analysis. In this paper we present a model for all path length variations in the geometrical optics of radio telescopes which are due to gravitational deformation. The Effelsberg 100 m radio telescope of the Max Planck Institute for Radio Astronomy, Bonn, Germany, has been surveyed by various terrestrial methods. Thus, all necessary information that is needed to model the path length variations is available. Additionally, a ray tracing program has been developed which uses as input the parameters of the measured deformations to produce an independent check of the theoretical model. In this program as well as in the theoretical model, the illumination function plays an important role because it serves as the weighting function for the individual path lengths depending on the distance from the optical axis. For the Effelsberg telescope, the biggest contribution to the total path length variations is the bending of the main beam located along the elevation axis which partly carries the weight of the paraboloid at its vertex. The difference in total path length is almost \(-\) 100 mm when comparing observations at 90 \(^\circ \) and at 0 \(^\circ \) elevation angle. The impact of the path length corrections is validated in a global VLBI analysis. The application of the correction model leads to a change in the vertical position of \(+120\)  mm. This is more than the maximum path length, but the effect can be explained by the shape of the correction function.     

A demonstration of 1–2 parts in 107 accuracy using GPS

By interferometric analysis ofGPS phase observations made at Owens Valley, Mojave, and Mammoth Lakes, California, we determined the coordinate components of the71–245–313 km triangle of baselines connecting these sites. A separate determination was made on each of four days, April 1–4, 1985. The satellite ephemerides used in these determinations had been derived from observations on other baselines. Therms scatters of the four daily determinations of baseline vector components about their respective means ranged from a minimum of6 mm for the north component of the71-km baseline to a maximum of34 mm for the vertical component of the245-km baseline. To test accuracy, we compared the mean of ourGPS determinations of the245-km baseline between Owens Valley and Mojave with independent determinations by others using very-long-baseline interferometry(VLBI) and satellite laser ranging(SLR). TheGPS-VLBI difference was within 2 parts in10 ⁷ for every vector component. TheGPS-SLR difference was within6 parts in10 ⁸ in the horizontal coordinates, but83 mm in height.     

A New Approach to 3D Dense LiDAR Data Classification in Urban Environment

Classification of Mobile Mapping LiDAR (Light Detection and Ranging) data is a challenge in the research community since the day when laser scanner system were integrated and mounted on vehicles for collection of 3D data in urban environment. The approach proposed here for classifying LiDAR data is analogous to the process followed for classifying data from satellite images. Pixel based and segmentation based methods have been employed in past for classifying images obtained from satellites. These methods were based on spectral properties of objects present in the images. But for Mobile mapping LiDAR data this approach has been applied and tested for the first time. The properties of this data are completely different from that of satellite images. So even if the basic approach remains the same, many changes have to be made in the entire classification process. The paper here aims to propose the basic procedure of using pixel-wise classification on dense 3D LiDAR data.     

Building Extraction from LIDAR Point Cloud Data Using Marked Point Process

This paper presents a new algorithm for building extraction from LIDAR (Light Detection and Ranging) point cloud data on the basis of a marked point process based building model. In this building model, the positions and geometries of buildings are modeled by a point process and its marks, respectively. The geometric marks for buildings include their length, width, direction, height. By Bayesian paradigm, a posterior distribution for the marked point process conditional on the LIDAR point cloud data is obtained. The Reversible Jump Markov Chain Monte Carlo (RJMCMC) based scheme is designed to simulate the posterior distribution. Finally, Maximum A Posteriori (MAP) strategy is used to obtain the optimal building detection. The proposed algorithm is tested by a set of LIDAR point cloud data. The results show its efficiency in complex residential environments.     

Morphological evolution of the Krishna delta

The study of the modern delta of the Krishna river has yielded data to identify ancient deltas and their characteristics. Continental landforms like levees and abandoned channels, marine landforms like beach ridges, swamps and spits are recorded from the study of aerial photos. The evolution of the delta is discussed, comparative ages for the landforms arrived at. The history of the delta is reconstructed based on the relationship between the former shore lines and the sub-delta lobes. Delta prospects for oil and gas are indicated at the intersecting zones of the abandoned channels and strandlines.     

Further remarks on the altimetry-gravimetry problems

The two Altimetry-Gravimetry linearized boundary value problems, both characterized by gravity anomaly boundary data on the continents, while on the oceans either the gravity potential or its radial derivative is assumed to be known, are investigated in their modified version, in the spherical boundary approximation. A constant unknown bias is added to the data set on the oceans, while a vanishing zerodegree harmonic component is assumed as additional constraint. Existence, uniqueness and regularity results are obtained, it is proved that, in order to obtain regularization of the solution, not only regular data must be imposed, on the continents and on the oceans, but suitable constraints on the coast line are needed.     

PSO-Based Optimal Selection of Zernike Moments for Target Discrimination in High-Resolution SAR Imagery

Target discrimination is the key step of automatic target detection in synthetic aperture radar (SAR) images. In this paper, a new algorithm, effective and robust feature sets for target discrimination in high resolution SAR images has been proposed. Two main steps in target discrimination of SAR images have been developed, the feature extraction based on Zernike moments (ZMs) having linear transformation invariance properties and the PSO based feature selection to select the optimal feature subset of Zernike moments for decreasing computational complexity of feature extraction step. The input regions of interest (ROIs) have been segmented and passed to a number of preprocessing stages such as histogram equalization, position and size normalization. Two groups of Zernike moments (shape and margin (intensity) characteristic) have been extracted from the preprocessed images and they have been applied to the feature selection step. Each group includes 34 moments with different orders and iterations. The selected moments have been applied to a SVM classifier. The proposed scheme has been tested on the MSTAR database. The Receiver Operational Characteristics (ROC) curve and the performance of proposed method using some measured data have been analyzed. Experimental results demonstrate the efficiency of the proposed approach in target discrimination of SAR imagery.     

Contrast enhancement of landsat data on multispectral data analysis system

Contrast enhancement, one of the image processing techiques, is developed on the Multispectral Data Analysis System (MDAS) for enhancing the LANDSAT data. The purpose of image processing for enhancement is to improve the obscure objects data in the image to stand out more readily for good sensing to the human eye. It is observed on MDAS that some of the LANDSAT scenes when examined on the color display, give inadequate information for the required objective of interpretation. This is due to poor tonal contrast in the scene because of prevailing climatological conditions at the time of satellite pass over that area. Also, the LANDSAT data usually occupy a small subset of the total brightness range 0–127. To provide optimal contrast and variation for color compositing, contrast enhancement may by performed on the data before going to trie information processing (categolization) on the landsat scene. This paper describes the algorithms of parametric linear and non linear contrast enhancement techniques. A typical example to differentiate the degree of salinity in the soils was tested with the suggested algorithms and the results are tabulated in the form of photographs. The test area is selected from Haryana (frame no. 158-040 dated 2nd May, 1977) for testing the algorithms. The enhancement software developed on the MDAS stretches all the four Landsat bands and generates an output tape with the format similar to LANDSAT computer compatible tape (CCT). The stretched results of 5 and 7 bands are displayed in this paper. A false color composite which appears as on the color displya could also be generated from 4, 5 and 7 bands. The enhanced output was found to be useful for easily categorizing the data into various categories on MDAS.     

Morphostructure of the krishna and the godavari delta region

Morphostructure is a form of the earth’s relief, developed due to tectonic movements. Structures which have undergone movement in the Quaternary time are commonly recognised in areas of low relief and recent deposition. A number of morphpstructures are delineated through geomorphologlcal studies in the Krishna and the Godavari delta region of the coastal Andhra Pradesh which are likely to entrap oil and gas. The morphostructural trends are in confirmation with the known regional trends.     

Mapping of wastelands through remote sensing techniques and their reclamation—A case study

Wasteland map (1∶100,000) of Rewasa catchment (Sikar district) has been prepared using aerial photographs and Landsat TM imagery. Thematic Mapper data were helpful in identifying the types of wastelands and details could be derived from the aerial photographs. The types of wastelands identified are sands, gullied land, salt affected areas, and barren rocky area. Depending upon the nature of wasteland, suitable rehabilitation measures like plantations, afforestation have been proposed.     

A note on observation decorrelation,variances of residuals,and redundancy numbers

A technique for processing correlated observations suitable for large, sparse, least-squares adjustments is reviewed. Correlated coordinate differences derived from the Global Positioning System are used as illustrative examples. However, the methods examined are suitable for all types of correlated observations. The computation of variances of residuals, redundancy numbers, and marginally detectable errors is considered for sparse systems.     

Marine regression along parts of the Indian Coast during the Quaternary — A study using satellite images

Features of marine regression along the Indian Coast during the Quaternary have been studied using the Landsat Imagery for the possible causes and mechanisms of their formation. The occurrence of these features, specially cheniers, is very prominent along the Krishna — Godavari coast. Variations in the inland distances of the cheniers at different locations along the coast indicate differential regressions of the coast at different places. Progradation of the coast and local uplift are identified as the main factors for the same. The topography of the shelf before the regression has played an important role in the development of the regression surfaces of varying widths and the spatial arrangement of the regression features. Morphostructural factors have hindered the formation of deltas along the western coast and also the formation of regression features. Some of the gently sloping coasts without the regression features are the active zones of sediment erosion. The study points to the possibility that some of the coasts/deltas are tectonically active zones. The Krishna Godavari delta is undergoing uplift and the coasts/deltas of the Sundarbans, Mahanadi, Kerala and Saurasthtra are undergoing down-warping. This fact needs to be confirmed using data form deep drillings, geophysical tests and other sources. The confirmation of these phenomena will have a significant effect on the depth of sediment deposition, their maturity and finally on the formation, occurrence and migration of hydrocarbons.     

Geoinformatic Modeling of Groundwater Resource Mapping of Shear Zone Regions- A Case Study on Attur Valley,Tamil Nadu,India

The general tendency of mapping groundwater resource using remote sensing and Geographic Information System (GIS) techniques involve assigning higher weightage to geomorphology. But this cannot be used as a thumb rule everywhere, especially an area where many ductile and brittle zones are prevalent. The influence of texture and structure of sheared rocks might play a control over retaining and permitting groundwater to flow. Attur valley is characterized by the presence of many shear zones and faults and hence the rocks are highly fissile within the shear zones. The present study tries to establish a new ranking and weightage scheme and hence a new spatial model for groundwater resource mapping in shear zone area like Attur Valley. This spatial model can be verified with field data such as water level data, pump test and resistivity data.     

A new coarse-time GPS positioning algorithm using combined Doppler and code-phase measurements

A new coarse-time Global Positioning System (GPS) positioning algorithm based on the use of Doppler and code-phase measurements is proposed and described. The proposed method was demonstrated to be essential for reducing the time to first fix and the power consumption in a GPS receiver. Only 1 ms of data is required to obtain a positioning fix with accuracy comparable to that of the traditional GPS navigation algorithm. The algorithm is divided into two parts. In the first part, the Doppler measurement of the GPS signal is used to determine the coarse user position. With proper constraints, the required time accuracy for the Doppler measurements can be relaxed to be as long as 12 h. In the second part of the algorithm, the accurate user position is calculated by means of the 1 ms code-phase data. The traditional tracking process is no longer necessary in the proposed algorithm. Using the acquired 1-ms code-phase measurement, the positioning accuracy was determined to be approximately a few tens of meters in our experimental results. However, if the data length is extended to 10 ms, the positioning accuracy can be improved to within 10–20 m, which is similar to that of the traditional GPS positioning method. Various experiments were conducted to verify the usefulness of the proposed algorithm.     

Vegetation cover classification in Sariska National Park and surroundings

Appraisal of spatial distribution of vegetation types is an important aspect for wildlife habitat suitability and ecological studies. Remote sensing provides quick, accurate and cost and time effective methods for vegetation cover mapping. In the present study Landsat MSS data was digitally classified into various land use/forest type classes. Forested land was about 52 per cent of the study area. Four forest types, namelyAnogeissus pendula, Boswellia serra ta, mixedAnogeissus-Butea and mixed Acacia-Zizyphus occupied 28.47 percent, 6.60 percent, 18.60 percent and 9.70 percent of the forested land, respectively. The area under National Park was 51.28 percent of total study area. About 61 percent of the Park area was under tree-covered vegetation. Overall accuracies for classified and smoothened-classified images were 89.37 percent and 91.96 percent, respectively. The vegetation of the area is controlled by topography and edaphic factors.     

Computer processing of LANDSAT-1 data and imagery generation

LANDSAT-1 (ERTS-1) data of the complete scene, 1218-04320, covering an area 185 Km x 185 Km in the Godavari Valley, India was computer processed in the Computer Division of the Oil and Natural Gas Commissíon to produce an imagery of readily recognizable land forms. Comparison with the original maps supplied by NASA showed an amazing agreement in quality. Computer oriented data enhancement techniques were developed and the data was reprocessed with the help of these techniques. The resulting imagery reveal an improvement over the originals. The computer software package developed to-date comprises nine different programmes to process the LANDSAT data on the IBM 360, 370 series.     

Palaeogeomorphic reconstruction of quaternary delta in alluvial plains of West bengal and Orissa

In the vast alluvial plains of West Bengal and Orissa several deltaic plains exist, occurring in an off-lap sequence. These deltas were formed in the background of eustatic fluctuations during the Quaternary Period. They were built partly during rising sea level and pertly during stationary sea level stages. Landform analysis through aerial photographs as well as Landsat imagery interpretation, attested by field study, helped to establish the palaeogeomorphology of these Quaternary deltas. Possible mode of sedimentation during different phases of sea level fluctuations has been worked out     

Global positioning system carrier phase: Description and use

After removing the modulation from the Global Positioning System (GPS) signal (L ₁ orL ₂) a pure carrier signal remains. Suppose this carrier is continuously and precisely tracked by aGPS receiver. Furthermore, suppose the phase of the carrier is periodically measured and recorded (nearly simultaneously at two or more locations) with respect to receiver oscillators having the same nominal frequency as theGPS carrier. This paper first considers alternative modeling and processing approaches to these observational data for static operations. Then an approach to dynamic relative positioning using triple differences is presented. This approach should lend itself to performing centimeter accuracy relative surveys in seconds rather than hours. An approach to fixing cycle slips, automatically, is included.     

Soil and soil conservation survey for watershed management in parts of North cachar hills and karbi — Anglong districts of ASSAM

Soil and Soil Conservation surveys for watershed management were conducted using aerial photos of 1:60,000 scale in parts of North Cachar and Karbi-Anglong districts of Assam. The area was divided into different river catchments and sub-watersheds. The erosion, slope, landuse and soils in relation to physiogrphy were studied in each sub-watershed. The different physiographic units identified in the area were high, medium, low and very low hills; pediplains; alluvial plain and the valleys. These units were further subdivided based on slope, landuse and erosion etc. The soils were classified according to Soil Taxonomy. For priority determination, weightage was alloted to each of the sub-watersheds considering their physiography, slope, landuse, erosion,soil texture, depth and delivery ratio and sediment yield was calculated for each subwatershed. It has been found that out of 122875 ha, an area of 1745 ha had very high priority, 30590 ha high, 37290 ha medium, 51957 ha low and 1294 ha very low priority for soil conservation purposes.