Pri izvedbi so sodelovali različni deležniki: - konzorcij geodetskih podjetij (zunanji izvajalec), izbran na javnem razpisu (LGB d.o.o., Digi data d.o.o., Geodetski zavod Celje d.o.o., Ljubljanski ...urbanistični zavod d.d., Monolit d.o.o), je skrbel za določitev referenčnih - veznih točk na podlagi terenske izmere in interpretacije podatkov državnega ortofota (DOF) ter podatkov LIDAR in za zajem dodatnih geometrijskih pogojev iz arhivskih elaboratov zemljiškega katastra; - Geodetski inštitut Slovenije je sodeloval v projektu kot vmesni člen med zunanjim izvajalcem in Geodetsko upravo Republike Slovenije (v nadaljevanju: geodetska uprava) ter skrbel za nemoteno izmenjavo podatkov, kontrolo in arhiviranje rezultatov zunanjega izvajalca ter razne prikaze in statistično obdelavo; - ekipa referentov izboljšave (skupaj 30 referentov), sestavljena iz sodelavcev vseh območnih geodetskih uprav in Urada za nepremičnine, ki je s posebej razvitimi oziroma kupljenimi programskimi rešitvami izvajala proces lokacijske izboljšave z metodo homogenizacije podatkov; - ekipa referentov geodetskih pisarn, ki so se vključevali v projekt, ko se je izvajal na območju njihovih pisarn, tako da so skrbeli za pripravo vhodnih podatkov iz obstoječih lokalnih baz zemljiškega katastra in evidentiranje rezultatov. Ob občasni pomoči ostalih sodelavcev v geodetski pisarni pa so skrbeli še za odpravo napak in neskladij med podatki, ki so bila ugotovljena v procesu lokacijske izboljšave. V informacijskem sistemu zemljiškega katastra je ostal ZKP nespremenjen, položajno izboljšani podatki pa so vključeni v ZKN, pri čemer se je obstoječi ZKN (pred lokacijsko izboljšavo) dopolnil s podatki izboljšanega ZKP in tako postal zvezen grafični podatkovni sloj, ki se že uporablja v procesih geodetske uprave, kjer se podatki nepremičninskih evidenc določajo na podlagi grafičnih presekov (na primer dejanska raba zemljišč, boniteta zemljišč), v projektu množičnega zajema poseljenih zemljišč (podlaga za vzpostavitev evidence stavbnih zemljišč), v projektu zajema dejanske rabe zemljišč infrastrukturnih objektov (ceste, železnice), kot podlaga v različnih GIS-okoljih. Zapisał: Franc Ravnihar, za Geodetsko upravo RS e-naslov: franc.ravnihar@gov.si PREDLOG ZAKONA O KATASTRU NEPREMICNIN Ministrstvo za okolje in prostor je konec leta 2019 opravilo medresorsko obravnavo osnutka Zakona o katastru nepremičnin, ki ga je pripravila Geodetska uprava Republike Slovenije.
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IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, UL, UM, UPUK
In this paper we present a description of a new multispectral airborne mapping light detection and ranging (lidar) along with performance results obtained from two years of data collection and test ...campaigns. The Titan multiwave lidar is manufactured by Teledyne Optech Inc. (Toronto, ON, Canada) and emits laser pulses in the 1550, 1064 and 532 nm wavelengths simultaneously through a single oscillating mirror scanner at pulse repetition frequencies (PRF) that range from 50 to 300 kHz per wavelength (max combined PRF of 900 kHz). The Titan system can perform simultaneous mapping in terrestrial and very shallow water environments and its multispectral capability enables new applications, such as the production of false color active imagery derived from the lidar return intensities and the automated classification of target and land covers. Field tests and mapping projects performed over the past two years demonstrate capabilities to classify five land covers in urban environments with an accuracy of 90%, map bathymetry under more than 15 m of water, and map thick vegetation canopies at sub-meter vertical resolutions. In addition to its multispectral and performance characteristics, the Titan system is designed with several redundancies and diversity schemes that have proven to be beneficial for both operations and the improvement of data quality.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
•Horizontal LIDAR performance assessed via comparative study without experiment data.•Atmosphere model employed real visibility data and MODTRAN® solar spectral radiance.•Shiina LIDAR had better ...range resolution but inferior maximum detection range.•VAST LIDAR had superior detection and signal quality but very poor laser safety.•Hypothetical setup showed more balanced performance and met case study requirements.
LIDAR performance is often evaluated after assembled prototypes are deployed for field tests. However, this approach is resource-intensive, which necessitates more cost-effective ways to detect flaws and improve LIDAR design. In this work, we present numerical assessment of horizontal scanning LIDAR performance via comparative study method. This assessment method could evaluate LIDAR performance without physically assembling the unit, hence save resources and time. We demonstrate this using a hypothetical atmospheric LIDAR. In our assessment, Python™ was used to develop simulation algorithm based on LIDAR equation, while Koschmieder visibility theory was used in atmosphere modeling. Daytime visibility and MODTRAN® solar spectral radiance data were also incorporated for analysis. We then evaluated LIDAR performance based on signal-to-noise and range-corrected signal profiles. Lastly, we conducted comparative study of this hypothetical LIDAR setup with Shiina (light emitting diode) LIDAR and VAST (ground-based) LIDAR for horizontal distance of 1 km. Numerical analysis showed that hypothetical LIDAR could operate up to 1 km at night. During daytime, detection was limited to 94 m and 220 m for 532 nm and 808 nm channels respectively. Comparative study demonstrated that the hypothetical LIDAR excelled in nighttime detection range with acceptable daytime performance. Overall, the hypothetical LIDAR has met case study requirements. We demonstrate the feasibility of this numerical assessment via comparative study method by identifying possible improvements in laser module without experimental data verification.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Impacts of small‐scale surface irregularities, or surface roughness, of atmospheric ice crystals on lidar backscattering properties are quantified. Geometric ice crystal models with various degrees ...of surface roughness and state‐of‐the‐science light‐scattering computational capabilities are utilized to simulate the single‐scattering properties across the entire practical size parameter range. The simulated bulk lidar and depolarization ratios of polydisperse ice crystals at wavelength 532 nm are strongly sensitive to the degree of surface roughness. Comparisons of these quantities between the theoretical simulations and counterparts inferred from spaceborne lidar observations for cold cirrus clouds suggest a typical surface‐roughness‐degree range of 0.03–0.15 in the cases of compact hexagonal ice crystals, which is most consistent with direct measurements of scanning electron microscopic images. To properly interpret lidar backscattering observations of ice clouds, it is necessary to account for the degree of surface roughness in light‐scattering computations involving ice crystals.
Plain Language Summary
Lidar (Light Detection and Ranging) instruments on satellites use reflected, or backscattered, laser beams to investigate ice clouds in the atmosphere. However, it has long been a challenge to interpret lidar signals, called backscattering properties, to infer ice cloud characteristics accurately. This study uses theoretical simulations to investigate how small‐scale surface irregularities of ice crystals affect the lidar signals associated with ice clouds. These simulations demonstrate the significant impacts of small‐scale surface irregularities of ice crystals on backscattering. Based on comparisons between the theoretical simulations and satellite lidar observations, it is necessary to assume a moderate degree of small‐scale surface irregularities to explain lidar observations of typical ice clouds.
Key Points
The sensitivity of the backscattering properties to the surface roughness of atmospheric ice crystals is theoretically investigated
The depolarization ratio is substantially sensitive to the degree of surface roughness of ice crystals
Compact hexagonal ice models with degrees of surface roughness ranging 0.03–0.15 reasonably explain the Cloud‐Aerosol Lidar with Orthogonal Polarization backscattering signals
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Monitoring the aquatic environment and the life of free‐floating organisms remains on the borderline of our technical capabilities. Therefore, our insights into aquatic habitats, such as, abundance ...and behavior of organisms are limited. In order to improve our understanding of aquatic life, we have developed a low‐cost inelastic hyperspectral lidar with unlimited focal depth and enough sensitivity and spatiotemporal resolution to detect and resolve position and behavior of individual submillimeter organisms. In this work, we demonstrate elastic as well as molecular ranging by using the water Raman band, and by observing fluorescence from chlorophyll and from dye‐tagged organisms. We present an aquatic laser‐diode‐based inelastic light detection and ranging (lidar) system with unprecedented sensitivity, spatiotemporal resolution and number of spectral bands. Our system offers new opportunities for quantitative in situ studies of aquatic organisms, and has the potential to considerably advance our understanding of biological life in aquatic systems.
The Scheimpflug principle allows a first hyperspectral inelastic laser radar to be built with realistic components, such as high‐power, continuous‐wave laser diodes and CCD detectors. Real‐time simultaneous full‐waveform ranging and spectroscopy is accomplished. The method could make inelastic lidars significantly more widespread. Applications for environmental aquatic monitoring are presented.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Light detection and ranging (lidar) data acquired from airborne or spaceborne platforms have revolutionized measurement and mapping of forest attributes. Airborne data are often either acquired using ...multiple overlapped flight lines to provide complete coverage of an area of interest, or using transects to sample a given population. Spaceborne lidar datasets are unique to each sensor and are sample- or profile-based with characteristics driven by acquisition mode and orbital parameters. To leverage the wealth of accurate vegetation structural data from these lidar systems, a number of approaches have been developed to extend these observations over broader areas, from local landscapes to the globe. In this review we examine studies that have utilised modelling approaches to extend air- or space-based lidar data with the aim of communicating methods, outcomes, and accuracies, and offering guidance on linking lidar metrics and lidar-derived forest attributes with broad-area predictors. Modelling approaches are developed for a variety of applications. In some cases, generation of spatially-exhaustive layers may be useful for forest management purposes, driving management and inventory decisions over smaller focus areas or regions. In other cases, outputs are designed for monitoring at regional or global scales, and may be – due to the spatial grain of the structural estimates – insufficiently accurate or reliable for management. From the reviewed studies, we found height, aboveground biomass and volume, derived from either upper proportions of a large-footprint full-waveform lidar profiles, or statistically modelled from discrete return small-footprint lidar point clouds, to be the most commonly extended forest attributes, followed by canopy cover, basal area and stand complexity. Assessment of the accuracy and bias of the extrapolated forest attributes varied with both independent and model-derived estimates. The coefficient of determination (R2) was the most often reported, followed by absolute and relative (i.e., as a proportion of the mean) root mean square error (RMSE and RMSE% respectively). Compilation of the stated accuracies suggested that the variance explained in predictions of forest height ranged from R2 = 0.38 to 0.90 (mean = 0.64), RMSE from 2 to 6m and RMSE% from 12 to 34%. For volume, R2 ranged from 0.25 to 0.72 (mean = 0.53) and RMSE from 60 to 87 m3/ha and for aboveground biomass (AGB) R2 ranged from 0.35 to 0.78 (mean = 0.55) and RMSE from 28 to 44 Mg/ha. There was no consensus on the level of accuracy required to support successful extension over larger areas. Ultimately, the review suggests that the information need motivating the spatial extension over larger areas drives the choice of the type of lidar data, spatial datasets and related grain. We conclude by discussing future directions and the outlook for new approaches including new lidar-derived response variables, advances in modelling approaches, and assessment of change.
•Lidar technologies produce critical data for forest attribute estimation.•We review studies that extend lidar data and associated estimates over large areas.•Height, aboveground biomass, and volume were the attributes most commonly extended.•Spaceborne lidar data enables the extension of attribute estimates for regional/global insights.•Open data for forest change and dynamics, standardized approaches, and best practices are needed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Multiple scattering theory used to analyze horizontal LIDAR data for haze detection.•Modified Platt formulation used to describe PM multiple scattering effects in LIDAR.•Atmosphere model employed ...real visibility data that reflect varying haze levels.•Multiple scattering error was most significant when hypothetical RFOV is 10 mrad.•Ratio of multiple scattering returns indicated haze and sufficed for practical use.
Haze is hazardous to human health. Although horizontal scanning LIDARs have been used to monitor air pollution sources, they have not been used for haze detection. In this work, we present a numerical model for haze detection using horizontal scanning LIDAR by incorporating multiple scattering theory. This model could evaluate whether multiple scattering theory is suitable for analyzing horizontal scanning LIDAR readings to detect haze without assembling LIDARs. We demonstrate this using a hypothetical LIDAR that has maximum horizontal range of 1 km as case study example. In our assessment, Python™ was used to develop simulation algorithm based on single and multiple scattering LIDAR equations. Relative humidity was below 80% which corresponded to potential haze. Visibility data at different haze levels were incorporated for analysis. We then evaluated errors in hypothetical LIDAR readings associated with multiple scattering. Lastly, we calculated ratios of multiple scattering returns in haze relative to clear weather as haze level indicators. Numerical assessment showed that multiple scattering effects were negligible for both wavelength channels (532 nm and 808 nm) at receiver field-of-view (RFOV) of 1.5 mrad, but introduced significant errors when RFOV is 10 mrad. Average ratio of multiple scattering returns evaluated against threshold of 1 could directly reflect the severity of haze. Although this approach was not suitable for heavy and severe haze, it sufficed for practical applications. Overall, the case study demonstrated the feasibility of incorporating multiple scattering theory when analyzing horizontal scanning LIDAR readings to detect haze without experimental verification.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A ground-based tropospheric O3 lidar with unique vertical near-range capabilities was deployed in support of the larger OWLETS 2017 campaign on the Chesapeake Bay Bridge Tunnel, at the mouth of the ...Chesapeake Bay. It was sited in close proximity to a shipping channel with an ensemble of additional instrumentation including Pandora spectrometer systems, ozonesonde launches, and in-situ trace gas monitors – one flying on a drone. This unique combination enabled successful observation of a near-surface maritime ship plume emission event on August 01, 2017. The observations demonstrate an NO2 enhancement coincident with O3 depletion in the low altitude range of lidar data, allowing for quantification of ship plume height behavior as well as the evolution of trace-gas concentrations. The technological improvements enabling the observation are presented and discussed, demonstrating that a single observation platform would not have been able to fully capture and contextualize the emission event. This synergistic ground-based sampling approach shows great promise for future verification and validation of satellite air quality and atmospheric composition measurements.
•A cargo vessel plume event was captured by O3 lidar and Pandora sun-spectrometer.•Emission sources can titrate O3 levels producing simultaneous NO2 enhancements.•Anti-correlated changes agree in O3 to NO2 conversion amounts.•Case study of a new capability to characterize near-range point-source contributions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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