UPN “Veteran” Yogyakarta’s Land Asset Area Planning in Semanu Gunung Kidul, Yogyakarta

Land is an asset in today’s era of development. A patch of land’s management must be planned so that its utilization can be done proportionally and professionally. The Special Region of Yogyakarta, namely Gunung Kidul Regency, has yet to have a reliable base map with high accuracy for each patch of land within its area, which results in the hampering of land use due to the lack of spatial information available. The lack of clear status and spatial information is felt by UPN “Veteran” Yogyakarta that has several patches of land in Gunung Kidul Regency, namely Kuwon Kidul, Pacarejo, Semanu, Gunung Kidul Regency. This research will create a base map scaled to 1:500 accompanied with information about height differences of said area and a recommended planning area considering three different aspects: geology, environment, and agriculture. The creation of a topographic map is useful for construction planning that will be conducted in the area. During this research, the topographic measurement and data processing were done in 11 days on field. The topographic measurement and data processing were conducted through five stages: initial survey, GNSS measurement, detail measurement, and data processing using software to produce a topographic map. The map result and measurement on field using Total Station showed that UPN “Veteran” Yogyakarta does not have a level surface and has good data density.

Three- and Four-Dimensional Topographic Measurement and Validation

This paper reports on the activities carried out in the context of “Dragon project 32278: Three- and Four-Dimensional Topographic Measurement and Validation”. The research work was split into three subprojects and encompassed several activities to deliver accurate characterization of targets on land surfaces and deepen the current knowledge on the exploitation of Synthetic Aperture Radar (SAR) data. The goal of Subproject 1 was to validate topographic mapping accuracy of various ESA, TPM, and Chinese satellite system on test sites in the EU and China; define and improve validation methodologies for topographic mapping; and develop and setup test sites for the validation of different surface motion estimation techniques. Subproject 2 focused on the specific case of spatially and temporally decorrelating targets by using multi-baseline interferometric (InSAR) and tomographic (TomoSAR) SAR processing. Research on InSAR led to the development of robust retrieval techniques to estimate target displacement over time. Research on TomoSAR was focused on testing or defining new processing methods for high-resolution 3D imaging of the interior of forests and glaciers and the characterization of their temporal behavior. Subproject 3 was focused on near-real-time motion estimation, considering efficient algorithms for the digestion of new acquisitions and for changes in problem parameterization.

Complementary Keratoconus Indices Based on Topographical Interpretation of Biomechanical Waveform Parameters: A Supplement to Established Keratoconus Indices

Purpose. To build new models with the Ocular Response Analyzer (ORA) waveform parameters to create new indices analogous to established topographic keratoconus indices. Method. Biomechanical, tomographic, and topographic measurements of 505 eyes from the Homburger Keratoconus Centre were included. Thirty-seven waveform parameters (WF) were derived from the biomechanical measurement with the ORA. Area under curve (ROC, receiver operating characteristic) was used to quantify the screening performance. A logistic regression analysis was used to create two new keratoconus prediction models based on these waveform parameters to resample the clinically established keratoconus indices from Pentacam and TMS-5. Results. ROC curves show the best results for the waveform parameters p1area, p2area, h1, h2, dive1, mslew1, aspect1, aplhf, and dslope1. The new keratoconus prediction model to resample the Pentacam topographic keratoconus index (TKC) was WFTKC = −4.068 + 0.002 × p2area − 0.005 × dive1 − 0.01 × h1 − 2.501 × aplhf, which achieves a sensitivity of 90.3% and specificity of 89.4%; to resample the TMS-5 keratoconus classification index (KCI) it was WFKCI = −3.606 + 0.002 × p2area, which achieves a sensitivity of 75.4% and a specificity of 81.8%. Conclusion. In addition to the biomechanically provided Keratoconus Index two new indices which were based on the topographic gold standards (either Pentacam or TMS-5) were created. Of course, these do not replace the original topographic measurement.