The Real Time Kinematic (RTK) method is widely used in the land surveying. Whereas RTK method has the advantage of practical use, positioning accuracy depends mostly on the baseline length due to the atmospheric errors. In general, RTK measurements are made by using GPS and GLONASS satellite systems. For this reason, the positioning performance of the technique is adversely affected under restricted satellite geometry conditions such as urban canyons. At present, most receivers on the market have the ability to track signals of Galileo and BeiDou satellites. Therefore, in this study, the positioning performance of RTK with different satellite combinations (GPS-only, GPS+GLONASS, GPS+GLONASS+GALILEO+BeiDou) was examined with a comparative approach. A field test was carried out considering approximately 20, 40, 60, and 80 km length of baselines. Three different cut off elevation angles – namely, 10°, 20°, and 30° – were chosen for the field test. The results were investigated in terms of accuracy and precision. Also, the ground truth coordinates of the rovers were obtained by post-processing relative method using GAMIT/GLOBK software. The results showed that multi-GNSS combinations provided better repeatability at the 10° cut off angle option. The accuracy of GPS-only solutions varied between 0.63/2.17 cm and 2.40/4.94 cm for horizontal and vertical components, respectively. However, the multi-GNSS combinations did not have a remarkable superiority in terms of position accuracy even at high satellite cut off angle (30°) compared to the GPS-only RTK.

Precise point positioning with ambiguity resolution (PPP-AR) is a powerful tool for geodetic and time-constrained applications that require high precision. The performance of PPP-AR highly depends on the reliability of the correct integer carrier-phase ambiguity estimation. In this study, the performance of narrow-lane ambiguity resolution of PPP using the Least-squares AMBiguity Decorrelation (LAMBDA) and bootstrapping methods is extensively investigated using real data from 55 IGS stations over one-month in 2020. Static PPP with 24-, 12-, 8-, 4-, 2-, 1- and ½-h sessions using two different cutoff angles (7° and 30°) was conducted with three PPP modes: i.e. ambiguity-float and two kinds of ambiguity-fixed PPP using the LAMBDA and bootstrapping methods for narrow-lane AR, respectively. The results show that the LAMBDA method can produce more reliable results for 2 hour and shorter observation sessions compared with the bootstrapping method using a 7° cutoff angle. For a 30° cutoff angle, the LAMBDA method outperforms the bootstrapping method for observation sessions of 4 h and less. For long observation times, the bootstrapping method produced much more accurate coordinates compared with the LAMBDA method without considering the wrong fixes cases. The results also show that occurrences of fixing the wrong integer ambiguities using the bootstrapping method are higher than that of the LAMBDA method.

In the middle of 2011, Trimble introduced the RTX correction service to support RT-PPP applications. In this study, the performance of Trimble RTX correction service is investigated over a one-month period using five different GNSS constellations – namely, GPS-only, GPS + GLONASS, GPS + Galileo, GPS + GLONASS + Galileo, and GPS + GLONASS + Galileo + BeiDou. The results show that positioning accuracy and convergence time are significantly improved with the use of the multi-GNSS constellation compared with the GPS-only solution. The result of the converged positioning accuracy indicates that the GPS + GLONASS + Galileo + BeiDou combination improves the accuracy by 63%, 54%, and 60% for north, east, and up components, respectively, compared with the GPS-only solution. The mean convergence time is reduced by the GPS + GLONASS+ Galileo + BeiDou combination by 70%, 71%, and 38.6% compared with the GPS-only solution in the north, east, and up components, respectively. 1.2 (north), 1.5 (east), and 2.3 cm (up) root mean square errors (RMSEs) of converged positioning from the GPS + GLONASS + Galileo + BeiDou combination are computed.

The precise point positioning (PPP) method has become more popular due to powerful online global navigation satellite system (GNSS) data processing services, such as the Canadian Spatial Reference System-PPP (CSRS-PPP). At the end of 2020, the CSRS-PPP service launched the ambiguity resolution (AR) feature for global positioning system (GPS) satellites. More reliable results are obtained with AR compared to the results with traditional ambiguity-float PPP. In this study, the performance of the modernized CSRS-PPP was comparatively assessed in terms of static positioning and zenith total delay (ZTD) estimation. Data for 1 month in the year 2019 obtained from 47 international GNSS service (IGS) stations were processed before and after modernization of the CSRS-PPP. The processes were conducted for GPS and GPS + GLONASS (GLObalnaya NAvigatsionnaya Sputnikovaya Sistema) satellite combinations. Besides, the results were analyzed in terms of accuracy and convergence time. According to the solutions, the AR feature of the CSRS-PPP improved the accuracy by about 50% in the east component for GPS + GLONASS configuration. The root-mean-square error (RMSE) of the ZTD difference between modernized CSRS-PPP service and IGS final troposphere product is 5.8 mm for the GPS-only case.

The water resource management is crucial to protect environment and ecological cycle. The detection of temporal and spatial changes in the lake's water extent is important for sustainable land planning. Therefore, the areal changes over the wetlands must be well monitored. Bafa Lake is an essential downstream water in the Büyük Menderes Basin which is the largest river basin of the Aegean Region. Google Earth Engine (GEE) is an easy-to-use online remote sensing data processing platform based on cloud computing. In this study, the long-term spatio-temporal changes of Bafa Lake between 1984-2022 have been analyzed using Landsat-5/8 satellite images on the GEE platform. A total of 1093 Landsat images were processed. The annual water areas were computed through composite images per year. The water area extraction was done using the normalized water difference index (NDWI). The minimum and maximum lake water areas in 38 years were detected as 5474 ha and 6789 ha in 1990 and 2006, respectively. In the accuracy assessment according to random sampling points, the Overall Accuracy (OA) was calculated as 98% and the kappa coefficient as 0.96. The water surface area was increased by 3.9% from 1984 to 2022. Between 2015-2022, the maximum increase or decrease in the lake area compared to the previous year observed as less than 1%. Therefore, there has not been a notable variation in the water area of Bafa Lake in the past few years.

Göreli konum belirleme yöntemine alternatif olarak ortaya çıkan Hassas Nokta Konum Belirleme (PPP) yöntemi son yıllarda yaygın olarak kullanılmaktadır. PPP yöntemi mutlak konum belirleme yönteminin özel bir durumu olup, bu yöntem ile tam sayı belirsizlik çözümündeki ilerleme sayesinde tek bir GNSS alıcısı kullanılarak yüksek doğruluklu konum bilgisi elde edilebilmektedir. Son birkaç yılda ise farklı servislerin (IGS, BKG, ESA, EUREF, GFZ vb.) sunduğu gerçek zamanlı düzeltme bilgisi ve ürünleri sayesinde PPP yöntemi gerçek zamanlı olarak (RT-PPP) kullanılmaya başlamıştır. RT-PPP’ ye olan ilginin oldukça yüksek olması yöntemin gelişimine hız katmıştır. Bu bağlamda birçok yazılım üretilmiştir. Bu çalışmada, bu yazılımlardan BKG/BNC, RTKLIB/RTKNAVI, PPP-WIZARD kullanılarak, RT-PPP yönteminin konum belirleme performansı test edilmiştir. Bu amaçla ISTA IGS/RTS istasyonuna ait gerçek zamanlı koordinat değerleri 1 saniye epok aralığında elde edilmiştir. Elde edilen sonuçlar doğruluk ve hassasiyet bakımından incelenmiştir. Sonuçlara göre, yakınsama süresi göz ardı edildiğinde BKG/BNC ve RTKLIB/RTKNAVI ile yatay bileşende genellikle ± 10 cm, düşey bileşende ise ± 20 cm gibi bir doğruluğun elde edilebildiği görülmüştür. Ancak PPP-WIZARD yazılımı kullanılarak elde edilen koordinatların doğruluğu oldukça düşüktür.