Quantification of suspended solids in Dal lake,Srinagar using remote sensing technology

Indian Remote Sensing satellite (IRS)-1B, Linear Imaging Self Scanner (LISS)-II spectral digital data was analysed to determine the feasibility of quantifying the concentration of suspended solids in the surface water of inland water body, Dal lake, in Srinagar, India. The water samples collected in concurrent with IRS-1B overpass, were analysed to determine the concentration of suspended solids. The results indicate that a positive functional relationship exist between the concentration of suspended solids and the visible wave length bands 1 and 3 and near infrared band 4. It has been observed that as the concentration of suspended solids increase, the spectral response also increases. It is concluded that IRS LISS-H data can be effectively used to quantify suspended sediment concentration in the Dal lake surface water.     

MAP MAKING FOR PROFIT AND PLEASURE

Some of the economic and operational aspects of mapping are discussed, including the conditions that may offer air survey a competitive advantage over other methods. The financing of national mapping programmes around the world is increasingly market oriented, driven by the need to provide the end users with information that they can turn into sustainable economic growth and social progress. Despite these economic pressures, map makers seem to find their work more enjoyable and rewarding than most professionals.     

THE PHOTOGRAMMETRIC SOCIETY ANALOGUE INSTRUMENT PROJECT: A SECOND EXTRACT

The paper entitled The Photogrammetric Society Analogue Instrument Project was published in The Photogrammetric Record, 14(82): 565-582 (October 1993). It contained, as Appendix A, the entry from the Archive that dealt with the Zeiss Stereoplanigraph. This paper provides a second extract from the Archive concerned with the entries relating to the Barr & Stroud ZA1 plotter, the Williamson Multiplex equipment and the Thompson pinhole plotter.     

Response of GPS occultation signals to atmospheric gravity waves and retrieval of gravity wave parameters

We show that the amplitude of the Global Positioning System (GPS) signals in the radio occultation (RO) experiments is an indicator of the activity of the gravity waves (GW) in the atmosphere. The amplitude of the GPS RO signals is more sensitive to the atmospheric wave structures than is the phase. Early investigations used only the phase of the GPS occultation signals for statistical investigation of the GW activity in the height interval 10–40 km on a global scale. In this study, we use the polarization equations and Hilbert transform to find the 1-D GW radio image in the atmosphere by analyzing the amplitude of the RO signal. The radio image, also called the GW portrait, consists of the phase and amplitude of the GW as functions of height. We demonstrate the potential of this method using the amplitude data from GPS/Meteorology (GPS/MET) and satellite mission Challenge Mini-satellite Payload (CHAMP) RO events. The GW activity is nonuniformly distributed with the main contribution associated with the tropopause and the secondary maximums related to the GW breaking regions. Using our method we find the vertical profiles of the horizontal wind perturbations and its vertical gradient associated with the GW influence. The estimated values of the horizontal wind perturbations are in fairly good agreement with radiosonde data. The horizontal wind perturbations v(h) are ±1 to ±5 m s with vertical gradients dv/dh ±0.5 to ±15 m s km at height 10–40 km. The height dependence of the GW vertical wavelength was inferred through the differentiation of the GW phase. Analysis of this dependence using the dispersion relationship for the GW gives the estimation of the projection of the horizontal background wind velocity on the direction of the GW propagation. For the event considered, the magnitude of this projection changes between 1.5 and 10 m s at heights of 10–40 km. We conclude that the amplitude of the GPS occultation signals contain important information about the wave processes in the atmosphere on a global scale.     

Improved relativistic transformations in GPS

For GPS satellite clocks, a nominal (hardware) frequency offset and a conventional periodic relativistic correction derived as a dot product of the satellite position and velocity vectors, are used to compensate the relativistic effects. The conventional hardware clock rate offset of 38,575.008 ns/day corresponds to a nominal orbit semi-major axis of about 26,561,400 m. For some of the GPS satellites, the departures from the nominal semi-major axis can cause an apparent clock rate up to 10 ns/day. GPS orbit perturbations, together with the earth gravity field oblateness, which is largely responsible for the orbit perturbations, cause the standard GPS relativistic transformations to depart from the rigorous relativity transformation by up to 0.2 ns/day. In addition, the conventional periodic relativistic correction exhibits periodic errors with amplitudes of about 0.1 and 0.2 ns, with periods of about 6 h and 14 days, respectively. Using an analytical integration of the gravity oblateness term (J₂), a simple analytical approximation was derived for the apparent clock rate and the 6-h periodic errors of the standard GPS gravity correction. For daily linear representations of GPS satellite clocks, the improved relativistic formula was found to agree with the precise numerical integration of the GPS relativistic effects within about 0.015 ns. For most of the Block IIR satellites, the 6-h periodical errors of the GPS conventional relativistic correction are already detectable in the recent IGS final clock combinations.     

Uniting space, ground, and underwater measurements for improved estimates of rain rate

Global precipitation is monitored from a variety of platforms including spaceborne, ground-, and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.     

Urban change detection related to earthquakes using an adaptive nonlinear mapping of high-resolution images

We propose a nonlinear mapping method for detecting geographical changes. In our system, two images photographed at different points of time are checked based on an iterative nonlinear mapping. The system automatically extracts feature changes of aerial imageries by computing distribution of the image matching score. We evaluate the change detection ability by using the receiver operating characteristic under misregistration cases, including rotational misalignments.     

Bayesian algorithm for the estimation of the dielectric constant from active and passive remotely sensed data

An inversion technique based on the merging of microwave remotely sensed data is applied to ground-based radiometer and scatterometer data acquired for the same area. The purpose of this technique is to retrieve the dielectric constant of bare soils. The algorithm is based on a Bayesian approach and combines prior information on the dielectric constant and surface roughness with observed data, in order to obtain a marginal posterior probability density function. The function describes how the probability is distributed within the range of the dielectric constant values, given the measured values of emissivity and backscattering coefficient. The algorithm allows for the incorporation of all the available sources of information, such as multipolarization and multifrequency data. Several criteria, which have been used to compare the predicted and the observed values, show that for dielectric constant values higher than 10 the best performance is achieved when data with one polarization and one or two frequencies are exploited. For dielectric constant values of less than 10, the configuration with two polarizations produces the best estimates.     

Boreal forest coherence-based measures of interferometric pair suitability for operational stem volume retrieval

The performance of interferometric synthetic aperture radar (INSAR)-based boreal forest stem volume retrieval is strongly affected by weather conditions around the time of the SAR image acquisitions. Since weather conditions cannot be controlled, the suitability of a particular interferometric pair for stem volume retrieval can only be assessed afterward. In this letter, four objective measures based on observed forest coherence were compared in assessing the suitability of interferometric pairs for stem volume retrieval. These suitability measures can be used to identify the best and worst pairs, i.e., the ones with the most and least favorable weather conditions. Stem volume retrievals were performed using single European Remote Sensing (ERS-1/2) Tandem interferometric pairs by inverting a backscattering-coherence model for boreal forests. A total of 14 ERS Tandem image pairs acquired in varying weather conditions were studied, and the stem volume retrieval performance was assessed against ground-based stem volume estimates on 134 boreal forest stands. Stem volume retrieval performance as measured by R/sup 2/-values between INSAR-estimated stem volumes and ground truth was found to be directly proportional to boreal forest coherence. The interferometric coherence-contrast (ICC), i.e., the difference in coherence between sparsest and densest boreal forest stands was found to be the best of the four studied suitability measures. The ICC could be used as a suitability parameter in the selection of the best interferometric pairs for operational boreal forest stem volume retrieval.     

Neuralizing target superresolution algorithms

Tatem et al. (2001) have designed a Hopfield network-based algorithm for superresolving discrete targets that are larger than the sample spacing of an image. The algorithm iteratively minimizes a criterion function that contains a sigmoidal activation term. We have altered their algorithm to bring it in line with Hopfield's original network by reducing the pseudotemperature of the sigmoid. We found that smaller values of the pseudotemperature lead to faster convergence to a solution and resulting solutions that are more accurate.