Hakan S. Kutoglu

Snow Depth Variations Estimated from GPS-Reflectometry: A Case Study in Alaska from L2P SNR Data

Snow is a water resource and plays a significant role in the water cycle. However, traditional ground techniques for snow monitoring have many limitations, e.g., high-cost and low resolution. Recently, the new Global Positioning System-Reflectometry (GPS-R) technique has been developed and applied for snow sensing. However, most previous studies mainly used GPS L1C/A and L2C Signal-to-Noise Ratio (SNR) data to retrieve snow depth. In this paper, snow depth variations are retrieved from new weak GPS L2P SNR data at three stations in Alaska and evaluated by comparing with in situ measurements. The correlation coefficients for the three stations are 0.79, 0.88 and 0.98, respectively. The GPS-estimated snow depths from the L2P SNR data are further compared with L1C/A results at three stations, showing a high correlation of 0.94, 0.93 and 0.95, respectively. These results indicate that geodetic GPS observations with SNR L2P data can well estimate snow depths. The samplings of 15 s or 30 s have no obvious effect on snow depth estimation using GPS SNR L2P measurements, while the range of 5°–35°elevation angles has effects on results with a decreasing correlation of 0.96 and RMSE of 0.04 m when compared to the range of 5°–30° with correlation of 0.98 and RMSE of 0.03 m. GPS SNR data below 30° elevation angle are better to estimate snow depth.

Georeferencing Accuracy Assessment of High-Resolution Satellite Images Using Figure Condition Method

In the case of sensor-independent georeferencing, accuracy of the used model is commonly assessed by misfits separately obtained from ground control points and independent check points. However, applying only this approach has some disadvantages. This paper proposes using the figure condition method to support the common approach. Applying the figure condition process, a more rigorous analysis of accuracy for the used models can be conducted, and one can decide whether the used model is proper or not. In this contribution, a case study is carried out using affine and extended affine models for high-resolution IKONOS Geo, OrbView-3 Basic, and QuickBird OrthoReady Standard images. The results obtained are subjected to the analysis of figure condition.

A comparison of two well known models for 7-parameter transformation

The transformation between two geocentric coordinate systems is carried out by the seven-parameter similarity transformation comprising three translations, three rotations and one scale difference. A number of approaches are available to realise this. Nevertheless, the Bursa-Wolf and Molodensky-Badekas models are generally favored for their simplicity. Except for their translations and their rms values both models yield similar results. Choosing a model producing more realistic translations is, of course, of paramount interest to surveyors. In this study, investigation of the causes of differences between translations of both models and which of these models produces more precise results is taken into consideration. The outcome of this investigation showed that the mathematical model of the Bursa-Wolf as opposed to the Molodensky-Badekas causes high correlations between transformation parameters, so Molodensky-Badekas model determines the translations better than the former.

Positive and negative ionospheric responses to the March 2015 geomagnetic storm from BDS observations

The most intense geomagnetic storm in solar cycle 24 occurred on March 17, 2015, and the detailed ionospheric storm morphologies are difficultly obtained from traditional observations. In this paper, the Geostationary Earth Orbit (GEO) observations of BeiDou Navigation Satellite System (BDS) are for the first time used to investigate the ionospheric responses to the geomagnetic storm. Using BDS GEO and GIMs TEC series, negative and positive responses to the March 2015 storm are found at local and global scales. During the main phase, positive ionospheric storm is the main response to the geomagnetic storm, while in the recovery phase, negative phases are pronounced at all latitudes. Maximum amplitudes of negative and positive phases appear in the afternoon and post-dusk sectors during both main and recovery phases. Furthermore, dual-peak positive phases in main phase and repeated negative phase during the recovery are found from BDS GEO observations. The geomagnetic latitudes corresponding to the maximum disturbances during the main and recovery phases show large differences, but they are quasi-symmetrical between southern and northern hemispheres. No clear zonal propagation of traveling ionospheric disturbances is detected in the GNSS TEC disturbances at high and low latitudes. The thermospheric composition variations could be the dominant source of the observed ionospheric storm effect from GUVI

Monitoring of mining induced land subsidence using L- and C-band SAR interferometry

\hbox {[O]/[N}_{2}]

Automatic processing of interferometric SAR and accuracy of surface deformation measurement

[O]/[N2] ratio data as well as storm-time electric fields. Our study demonstrates that the BDS (especially the GEO) observations are an important data source to observe ionospheric responses to the geomagnetic storm.

Unsustainable urban development for Zonguldak metropolitan area (NW Turkey)

A datum transformation between two geodetic datums primarily requires to compute transformation (datum) parameters through the common points whose the coordinates are available in both datums. The coordinates are burdened with errors caused by different reasons. During the estimation, some parts of these errors are absorbed into the parameters. Therefore, different combinations of common points lead to different sets of the datum parameters. Amounts of the differences between the different parameter sets are dependent on the amounts of the errors which are absorbed in the estimation. In this study, it is investigated how the distribution of common points effects on the estimations in datum transformation. The results of the investigations using two local applications in Turkey show that the point distribution highly determining factor on how much the errors effect on the estimations.

Direct determination of local coordinates from GPS without transformation

In this study, we applied InSAR technique to Zonguldak Hardcoal Basin in Republic of Turkey using JERS-1/SAR, RADARSAT and PALSAR data in order to monitor mining induced surface displacement.