The computation of the geoid model in the state of São Paulo using two methodologies and GOCE models

The purpose of this manuscript is to compute and to evaluate the geoid model in the State of São Paulo from two methodologies (Stokes' integral through the Fast Fourier Transform - FFT and Least Squares Collocation - LSC). Another objective of this study is to verify the potentiality of GOCE-based. A special attention is given to GOCE mission. The theory related to Stokes' integral and Least Squares Collocation is also discussed in this work. The spectral decomposition was employed in the geoid models computation and the long wavelength component was represented by EGM2008 up to degree and order 150 and 360 and GOCE-based models up to 150. The models were compared in terms of geoid height residual and absolute and relative comparisons from GPS/leveling and the results show consistency between them. In addition, a comparison in the mountain regions was carried out to verify the methodologies behavior in this area; the results showed that LSC is less consistent than FFT

DETERMINISTICALLY-MODIFIED INTEGRAL ESTIMATORS OF GRAVITATIONAL TENSOR

The Earth's global gravity field modelling is an important subject in Physical Geodesy. For this purpose different satellite gravimetry missions have been designed and launched. Satellite gravity gradiometry (SGG) is a technique to measure the second-order derivatives of the gravity field. The gravity field and steady state ocean circulation explorer (GOCE) is the first satellite mission which uses this technique and is dedicated to recover Earth's gravity models (EGMs) up to medium wavelengths. The existing terrestrial gravimetric data and EGM scan be used for validation of the GOCE data prior to their use. In this research, the tensor of gravitation in the local north-oriented frame is generated using deterministically-modified integral estimators involving terrestrial data and EGMs. The paper presents that the SGG data is assessable with an accuracy of 1-2 mE in Fennoscandia using a modified integral estimatorby the Molodensky method. A degree of modification of 100 and an integration cap size of for integrating terrestrial data are proper parameters for the estimator

The SAMI Galaxy Survey: cubism and covariance, putting round pegs into square holes

We present a methodology for the regularization and combination of sparse sampled and irregularly gridded observations from fibre-optic multiobject integral field spectroscopy. The approach minimizes interpolation and retains image resolution on combining subpixel dithered data. We discuss the methodology in the context of the Sydney-AAO multiobject integral field spectrograph (SAMI) Galaxy Survey underway at the Anglo-Australian Telescope. The SAMI instrument uses 13 fibre bundles to perform high-multiplex integral field spectroscopy across a 1° diameter field of view. The SAMI Galaxy Survey is targeting ~3000 galaxies drawn from the full range of galaxy environments. We demonstrate the subcritical sampling of the seeing and incomplete fill factor for the integral field bundles results in only a 10 per cent degradation in the final image resolution recovered. We also implement a new methodology for tracking covariance between elements of the resulting data cubes which retains 90 per cent of the covariance information while incurring only a modest increase in the survey data volume

C‐band SAR backscatter characteristics of Arctic sea and land ice during winter

Synthetic Aperture Radar (SAR) data has become an important tool for studies of polar regions, due to high spatial resolution even during the polar night and under cloudy skies. We have studied the temporal variation of sea and land ice backscatter of twenty-four SAR images from the European Remote Sensing satellite (ERS-1) covering an area in Lady Ann Strait and Jones Sound, Nunavut, from January to March 1992. The presence of fast ice in Jones Sound and glaciers and ice caps on the surrounding islands provides an ideal setting for temporal backscatter studies of ice surfaces. Sample regions for eight different ice types were selected and the temporal backscatter variation was studied. The observed backscatter values for each ice type characterize the radar signatures of the ice surfaces. This time series of twenty-four SAR images over a 3-month period provides new insights into the degree of temporal variability of each surface. Ice caps exhibit the highest backscatter value of -3.9 dB with high temporal variability. Valley glacier ice backscatter values decrease with decreasing altitude, and are temporally the most stable, with standard deviations of 0.08–0.10 dB over the 90-day period. First-year ice and lead ice show a negative trend in backscatter values in time and a positive correlation of up to 0.59 with air temperature over the 90-day period. For first-year ice and lead ice, episodes of large temperature fluctuations (±12°C) are associated with rapid changes in backscatter values (±2 dB). We attribute the backscatter increase to a temperature-induced increase in brine volume at the base of the snow pack. Multi-year ice, conglomerate ice and shore ice are relatively stable over the 3-month period, with a backscatter variation of only a few dBs. An observed lag time of up to three days between backscatter increase/decrease and air temperature can be attributed to the insulation effect of the snow cover over sea ice. The net range of the backscatter values observed on the most temporally stable surface, valley glacier ice, of about 0.30 dB indicates that the ERS-1 SAR instrument exceeds the 1 dB calibration accuracy specified for the Alaska SAR Facility processor for the three winter months