A detailed assessment of the accuracy of the TanDEM-X derived WorldDEM digital elevation models with reference to airborne lidar data was performed for a quarter degree tile located to the west of ...Rapid City, SD, USA. In addition to assessing the accuracy under standard conditions (uniform unvegetated terrain) analyses on the effects of vegetation height and terrain slope were conducted. Results for standard conditions and even in unvegetated terrain with slopes ranging from 0° to 80° are in agreement with the TanDEM-X accuracy specifications. The accuracy of canopy height (canopy heights ≤25 meters) degrades by a factor of at least 1.4 with respect to the bare terrain which is expected because the radar energy propagates through the vegetation canopy before scattering back to the sensor.
The geospatial data acquisition becomes easier than before. It is due to the availability of Unmanned Aerial Vehicle (UAV) or more familiar known as a drone. However, the accuracy is still in doubt. ...Especially data acquired using an optical sensor mounted on the UAV. The American Society of Photogrammetry and Remote Sensing (ASPRS) standards were used for the quality guidance. Fixed-wing type of UAV was employed with the mounted optical sensor. The final result of vertical elevation generated from the optical sensor then compared with the data of terrestrial laser scanner from two different spatial distribution of checkpoint (that is even and uneven) of two different locations (that is active and inactive) of high confidence area. The accuracy assessment found that the even spatial distribution and a higher number of checkpoints of active high confidence area lead to higher vertical elevation error, while the uneven distribution and lower number of checkpoints of inactive confidence area lead to lower vertical elevation error. This study proposed that for vertical accuracy assessment, the user need to find the inactive bare-earth confidence area for quality control of DTM derived from the mounted optical sensor on UAV.
The digital terrain model (DTM) is a complex object of the Primary Database for The Geographic Information System (PD GIS). PD GIS is a component of the Automated Information System of Geodesy, ...Cartography and Cadastre. The EC initiative INSPIRE defines DTM as one basic element of the National Spatial Data Infrastructure (NSDI). The creation of NSDI is a task of the Action Plan of the Strategy of the Slovak Information Society. The range of the DTM vertical accuracy is described through the metadata. The metadata describes a product in a complex way. The GCCA SR will offer metadata and the solo product of DTM through its organization, the Geodetic and Cartographic Institute in Bratislava (GCI), via the Internet. For this purpose the GCI meaningfuly build a webmap service, GCCA SR Geoportal, which is nearly related with the NSDI concept as well as with the projects of the Eurogeographics association. The paper describes the creation of DMR50, DTM of Slovakia, with the 50x50 meter grid. DMR50 was created by the data processing of the contour lines model from the Basic Map of the Slovak Republic 1:50 000. The testing of the DMR50 vertical accuracy was carried out by the set of geodetic points from the State Levelling Network. DMR50 is a suitable contribution of Slovakia to the creation of the EuroGeographics or INSPIRE–coordinated pan-European products.
Digitalni model reljefa (DTM, engl. Digital Terrain Model) ima široku i važnu primjenu u mnogim djelatnostima, uključujući i šumarstvo. Međutim, precizno modeliranje terena, odnosno izrada DTM-a u ...šumama, bilo korištenjem terenskih metoda ili metoda daljinskih istraživanja, izazovan je i vrlo zahtjevan zadatak. U većini razvijenih zemalja svijeta, zračno lasersko skeniranje (ALS, engl. Airborne Laser Scanning) bazirano na LiDAR (engl. Light Detection and Ranging) tehnologiji trenutno predstavlja glavnu metodu za izradu DTM-a. Uslijed mogućnosti laserskog zračenja da penetrira kroz krošnje drveća, LiDAR tehnologija se pokazala kao efektivna i brza metoda za izradu DTM-a u šumskim područjima s vrlo velikom točnošću. Međutim, u mnogim zemljama svijeta, uključujući i Hrvatsku, zračno lasersko skeniranje nije u potpunosti provedeno, tj. samo su manji dijelovi zemlje pokriveni s podacima zračnog laserskog skeniranja. U tim slučajevima, DTM temeljen na stereo-fotogrametrijskoj izmjeri aerosnimaka potpomognut s terenskim podacima najčešće predstavlja glavni izvor informacija za izradu DTM-a. Poznato je da tako izrađen DTM u šumskim predjelima ima manju točnost od DTM-a dobivenog na temelju zračnog laserskog skeniranja zbog pokrivenosti terena vegetacijom. Također, u okviru nedavno provedenog istraživanja (Balenović i dr., 2018) utvrđeno je da takvi službeni fotogrametrijski digitalni podaci terena u šumskim predjelima sadrže određen broj tzv. grubih grešaka, koje mogu značajno utjecati na točnost izrađenog DTM-a. Nakon vizualnog detektiranja i manualnog uklanjanja tih pogrešaka, Balenović i dr. (2018) utvrdili su značajno poboljšanje točnosti fotogrametrijskog DTM-a.Stoga je glavni cilj ovoga rada razviti automatsku metodu za detekciju i eliminaciju vertikalnih pogrešaka u fotogrametrijskim digitalnim podacima terena te na taj način poboljšati točnost fotogrametrijskog DTM-a u nizinskim šumskim područjima Hrvatske. Ideja je razviti brzu, jednostavnu i učinkovitu metodu koja će biti primjenjiva i za druga šumska područja sličnih karakteristika, a za koja ne postoje DTM dobiven zračnim laserskim skeniranjem. Istraživanje je provedeno u nizinskim šumama na području gospodarske jedinice Jastrebarski lugovi, u neposrednoj blizini Jastrebarskog (Slika 1). Istraživanjem je obuhvaćena površina od 2.005,74 ha, na kojoj su u najvećoj mjeri zastupljene jednodobne sastojine hrasta lužnjaka (Quercus robur L.), a u manjoj mjeri jednodobne sastojine poljskog jasena (Fraxinus angustifolia L.) te jednodobne sastojine običnoga graba (Carpinus betulus L.). Nadmorska visina područja istraživanja kreće se u rasponu od 105 do 121 m.Fotogrametrijski DTM (DTMPHM) je izrađen iz digitalnih vektorskih podataka terena (prijelomnice, linije oblika, markantne točke terena i pravokutne mreže visinskih točaka) nabavljenih iz Državne geodetske uprave (Slika 2). Ti podaci predstavljaju nacionalni standard i jedini su dostupni podaci za izradu DTM-a u Hrvatskoj. Detaljan opis vektorskih podataka dan je u radu Balenović i dr. (2018). Prvo je iz digitalnih terenskih podataka izrađena nepravilna mreža trokuta, koja je potom linearnom interpolacijom pretvorena u rasterski DTMPHM prostorne rezolucije (veličine piksela) 0,5 m. Automatska metoda za detekciju i eliminaciju vertikalnih pogrešaka fotogrametrijskog DTM-a u nizinskim šumskim područjima razvijena je u slobodnom programskom paketu Grass GIS (Slika 3). Kombinacijom vrijednosti nagiba i tangencijalne zakrivljenosti terena rasterskog DTMPHM (Slika 4), automatskom metodom su detektirane 91 grube greške (engl. outliers). Drugim riječima, utvrđeno je da 91 točkasti vektorski objekt pogrešno prikazuje stvarnu visinu terena. Navedeni broj čini 3,2 % od ukupnog broja točkastih objekata korištenih za izradu DTMPHM-a. Nakon eliminacije detektiranih pogrešaka izrađen je novi, korigirani fotogrametrijski DTM (DTMPHMc). Za ocjenu vertikalne točnosti izvornog (DTMPHM) i korigiranog DTM-a (DTMPHMc) korišten je visoko precizni DTM dobiven zračnim laserskim skeniranjem (DTMLiD). U tu svrhu su izrađeni rasteri razlika između DTMPHM i DTMLiD, te između DTMPHMc i DTMLiD. Kako je preliminarnom analizom utvrđeno da vertikalne razlike između DTMPHM i DTMLiD nisu normalno distribuirane (Slika 5), za ocjenu točnosti su uz normalne mjere točnosti korištene i tzv. robusne mjere točnosti (Tablica 2). Dobiveni rezultati ukazuju na poboljšanje vertikalne točnosti fotogrametrijskog DTM-a primjenom razvijene automatske metode. To je posebice uočljivo na podpodručjima 2 i 3 (Slika 6 i 7) u kojima se nakon uklanjanja detektiranih grešaka, korijen srednje kvadratne pogreške (RMSE, engl. root mean square error) smanjio za 8 % odnosno 50 % (Tablica 2). Na temelju dobivenih rezultata i usporedbe s DTMLiD, može se zaključiti da predložena metoda uspješno detektira i eliminira vertikalne pogreške fotogrametrijskog DTM-a u nizinskim šumskim područjima, te slijedom toga poboljšava njegovu vertikalnu točnost.
The Global DEM (GDEM) product is being generated from Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) data by Japan's Ministry of Economy, Trade, and Industry (METI) and the ...National Aeronautics and Space Administration (NASA). It is a snapshoot of the reflective surface of the earth during the time period of the mission, and is about 100 times more detailed than existing global elevation data, such as GTOPO 301 and GLOBE2 and nine times more detailed than the existing SRTM3, 4. Up to now, only limited evaluation has been performed of the GDEM dataset. From what is known about the processing methodology it is expected that the Aster GDEM contains a significant number of anomalies that prevents immediate use for a wide range of applications.
Public Land Mobile Network (PLMN) or cellular network location based services use multiple positioning methods in order to fulfill requirements in terms of availability, response time and accuracy. ...This is needed since no single method performs uniformly best, for all services at all locations. Very often more than one positioning method needs to be applied in a fallback manner, or in LTE in parallel, to arrive at a good enough User Equipment (UE) positioning result. At the beginning of this positioning sequence, no measured data exist and hence the evolved serving mobile location center (eSMLC) needs to compare the requested QoS from the end user with prior performance capabilities of the available positioning methods, to find the best positioning method sequence for the request. The paper proposes new techniques for on-line estimation and adaptation of this prior performance information. The proposed algorithms also provide detailed information on the confidence of the prior information, i.e. the probability that the terminal is actually located in the estimated region. The need for and the effect of transformations between reporting formats are also discussed and two such shape conversions are derived.
Every iOS device has the ability to determine where in the world it is using a framework called Core Location. There are actually three technologies that Core Location can leverage to do this: GPS, ...cell tower triangulation, and Wi-Fi Positioning Service (WPS). GPS is the most accurate of the three but is not available on first-generation iPhones, iPod touches, or Wi-Fi-only iPads; in short, any device with a 3G data connection also contains a GPS unit. GPS reads microwave signals from multiple satellites to determine the current location.
Your iPhone has the ability to determine where in the world it is using a framework called Core Location. There are actually three technologies that Core Location can leverage to do this: GPS, cell ...tower triangulation, and Wi-Fi Positioning Service (WPS). GPS is the most accurate of the three but is not available on first-generation iPhones. GPS reads microwave signals from multiple satellites to determine the current location. Cell tower triangulation determines the current location by doing a calculation based on the locations of the cell towers in the phone’s range. Cell tower triangulation can be fairly accurate in cities and other areas with a high cell tower density but becomes less accurate in areas where there is a greater distance between towers. The last option, WPS, uses the IP address from iPhone’s Wi-Fi connection to make a guess at your location by referencing a large database of known service providers and the areas they service. WPS is imprecise and can be off by many miles.
This paper describes the vertical accuracies achievable using Low-power, Mass-market, Multifrequency, Multi-constellation GNSS (LM3GNSS) receivers, and antennas, and evaluates the results as a ...precursor to providing alternatives to high-end GNSS hardware on emerging remotely operated and unmanned systems, such as autonomous surface vehicles (ASV), small unmanned aircraft systems (sUAS), and offshore GNSS buoys. The LM3GNSS receivers are relatively new in the market, and they are affordable (243 - 2,670). Given their low-power characteristics, they readily fulfill the power budget requirement aboard marine systems. In the first round of our studies, we conducted five experiments in a minivan, which traveled at approximately 80 km per hour (50 mph) with matching pairs of receivers and antennas. We assume that the results should be comparable to solutions aboard a marine vessel at typical hydrographic survey speeds (10 - 20 km per hour {5 - 10 knots}). The matching pairs of receivers include four LM3GNSS hardware, Trimble NetR9 receiver, and Zephyr3 antenna. The results show that LM3GNSS receivers are capable of achieving vertical positioning uncertainties that are within 10 cm of the geodetic results (95% confidence level).
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