Accuracy assessment of GPS precise point positioning (PPP) technique using different web-based online services in a forest environment
Bibliographic record
Abstract
Since Global Positioning System (GPS) has been routinely conducted in many engineering projects, it is also effectively applied to the assessment and preventing of forest and natural resources. Depending on the GPS survey method preferred in the applications performed around the forest environments, different level point positioning accuracy can be achieved. Traditionally, for many precise positioning applications, relative static positioning has been used. The data obtained have been analyzed with high-cost scientific and commercial software, which are required a good knowledge of processing procedures. However, in recent years, web based online services that use Precise Point Positioning (PPP) technique, developed as a special type of relative positioning, that enables to process and analyze the static data easily, have become a significant alternative for users. These developments on GPS based surveyings that significantly make contributions to the studies applied around the forest environment, in terms of time, cost, accuracy and labour are preferred in many engineering facilities. In this study, it is aimed to research performance of GPS PPP technique and web based online services in positioning applications especially performed around the forest environments. For this purpose, two test stations have been established in different locations around the forest area, located in Campus of Davutpasa, Yildiz Technical University, Istanbul, and stations have been observed repeatedly in static GPS surveying mode for 3 days and per day with 3-hours observation duration. The observations have been computed by commercial software as using final GPS ephemerides products so called TopconTools v8.2 and also by web based online services namely OPUS, AUSPOS, CSRS-PPP, GAPS and APPS. From the results, when 3D positioning differences have been examined, it is seen that the positional accuracy is range from 0.024 m to 0.251 m for TP01 and from 0.078 m to 1.033 m for TP02 with respect to both relative solution and PPP solution, which is used by web based online services. When the results have been examined for only CSRS-PPP, APPS and GAPS services, which are used PPP solution, it is seen that the positional accuracy for 3D positioning differences is range from 0.024 m to 0.251 m for TP01 and from 0.078 m to 0.859 m for TP02. The results show that since the static GPS data is collected for duration of 3-hours and more, PPP technique and the web based online services using this technique for precise positioning applications around the forest environment give effective solutions to the users and at the same time decrease the survey cost with respect to equipment and software.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".