## 2 BDS/GNSS for Earth Observations
### GNSS Positioning  
Primarily, GNSS positioning includes single point positioning (SPP), precise-point positioning (PPP), differential positioning (DGNSS), and real-time kinematic (RTK) positioning techniques. Single point positioning is based on a single GNSS receiver, using pseudorange observations and satellite broadcast ephemerides, without the requirement for an external reference station. It is suitable for mass-market positioning applications, with positioning accuracy typically ranging from several meters to tens of meters [4]. Differential GNSS (DGNSS) relies on a reference station to correct positioning errors at the user's location, improving the accuracy by reducing the errors caused by the atmospheric signal propagation. Real-time kinematic (RTK) positioning attains high accuracy by utilizing the differences in carrier phases between a mobile receiver and a reference station located on the ground. It requires real-time data transmission to maintain centimeter-level accuracy [5]. Conversely, precise point positioning (PPP) relies on an exact satellite orbit and clock corrections, without needing ground GNSS network stations. Nonetheless, it needs accurate data in order to correct satellite-orbit and clock errors. PPP is ideal for rapid deployment, with accuracy reaching the centimeter level [6]. The implementation of PPP in global or regional scale is significantly supported by the presence of continuous networks of reference stations, known as CORS (Continuously Operating Reference Station), which provide free data for scientific purposes. A recent study conducted by [PERSON] et al. demonstrated the abilities of various next-generation, low-cost, multi-constellation, and multi-frequency GNSS sensors, utilizing only the permanent GNSS-CORS multi-constellation stations located in Umbria, Italy [7]. [PERSON] et al. conducted several experiments comparing PPP-RTK, network RTK (NRTK), and long baseline-based RTK (LBRTK). The results showed that both the LBRTK and NRTK techniques delivered comparable performance for baselines up to 40 km, exhibiting discrepancies of under 3 cm horizontally and 4 cm vertically [8]. [PERSON] et al. proposed a novel time-relative positioning algorithm, acknowledging that, as widely recognized, and the PPP technique offered high-precision positioning data but needed an initialization period of 10-30 min. In their approach, current epoch parameters such as the position vector and the ambiguities of the float ionosphere-free (IF) model were estimated. Results from numerical tests conducted during both static and dynamic conditions revealed that the proposed positioning algorithm achieved an accuracy of just a few centimeters within one hour. It is evident that by combining GPS, BeiDou, and Galileo, the positioning accuracy was significantly improved, due to the increased number of satellites and a more favorable geometric distribution concerning DOP (Dilution of Precision) [9]. In contrast, [PERSON] and [PERSON] introduced a novel approach for network processing, which achieved single-frequency PPP-RTK. Tests conducted with daily GNSS data gathered from a CORS network, along with a single-frequency rover receiver (u-blox), demonstrated that the success rate for ambiguity resolution in the CORS network reached 98.89% [10]. Recently, an intriguing review has been published on selected topics related to GNSS CORS, including structure monitoring, accuracy, network monitoring, and reference frames. Given the extensive range of articles discussed in this work, readers are encouraged to pursue further research on the subject [11]. An intriguing study was presented by [PERSON] et al. [12], which demonstrated the efficacy of the multi-GNSS PPP method in a static configuration. This research utilized the free, open-source software RTKLib (version 2.4.2 p13), including satellite orbits and accurate clock data from CLS (Collecte Localisation Satellitique) and CNES (Centre National d'Etudes Spatiales).