scholarly journals Geodetic mass balance of the western Svartisen ice cap, Norway, in the periods 1968–1985 and 1985–2002

2009 ◽  
Vol 50 (50) ◽  
pp. 119-125 ◽  
Author(s):  
Torborg Haug ◽  
Cecilie Rolstad ◽  
Hallgeir Elvehøy ◽  
Miriam Jackson ◽  
Ivar Maalen-Johansen
Keyword(s):  
Mass Balance ◽  
Drainage Basin ◽  
Digital Terrain Model ◽  
Aerial Photographs ◽  
Outlet Glacier ◽  
Terrain Model ◽  
Ice Cap ◽  
Digital Terrain ◽  
Geodetic Mass Balance ◽  
Snow Thickness

AbstractThe geodetic mass balance of the western Svartisen ice cap in northern Norway is determined, in this work, from photogrammetry on vertical aerial photographs taken in 1968, 1985 and 2002. The existing 1968 digital terrain model (DTM) was generated using analogue photogrammetry, and the 1985 and 2002 DTMs are newly generated using digital photogrammetry. The geodetic mass balance for 1968–85 is –2.6±0.8mw.e., and for 1985–2002 it is –2.0±1.6mw.e. The area of western Svartisen decreased from 190 km2 in 1968, to 187 km2 in 1985 and to 184 km2 in 2002. The outlet glacier Flatisen in the southeast retreated 1700 m over the two periods. The geodetic mass balance is also determined for Engabreen drainage basin, as –2.1±0.9mw.e. for the first period, and –0.3±2.4mw.e. for the second. The results for Engabreen are compared to traditional mass balances, and the large deviations cannot be explained from uncertainties determined for the geodetic method. The assessed errors contributing to the uncertainty in the geodetic mass balance are elevation errors, uncertainties from the applied melt correction, and the use of Sorge’s law, assuming constant snow thickness and density.

Improving the accuracy of forming a digital terrain model along the railway

2021 ◽  
pp. 22-29
Author(s):  
Dmitriy A. Roshchin
Keyword(s):  
High Efficiency ◽  
Digital Terrain Model ◽  
Digital Processing ◽  
Aerial Photographs ◽  
Railway Track ◽  
Technical Solution ◽  
Digital Terrain Models ◽  
Terrain Model ◽  
Digital Terrain ◽  
Terrain Models

The problem of improving the accuracy of digital terrain models created for monitoring and diagnostics of the railway track and the surrounding area is considered. A technical solution to this problem is presented, which includes a method for joint aerial photography and laser scanning, as well as a method for digital processing of the obtained data. The relevance of using this solution is due to the existence of zones of weak reception of signals from the global navigation satellite system, since in these zones the accuracy of constructing digital terrain models using currently used diagnostic spatial scanning systems is reduced. The technical solution is based on the method of digital processing of aerial photographs of the railway track. In this case, as elements of external orientation, the threads of the rail track located at a normalized distance from each other are used. The use of this method made it possible to increase the accuracy of determining the flight path of an aircraft over railway tracks and, as a result, the accuracy of calculating the coordinates of points on the earth's surface. As a result, a digital terrain model was created that is suitable for diagnostics and monitoring the condition of the railway trackbed. During simulation modeling, it was found that the application of the proposed method allowed to reduce to 50 % the confidence interval of the distribution of the error in determining the coordinates of points on the terrain and increase the accuracy of forming a digital terrain model. This promising technical solution for improving the accuracy of digital terrain models for railway track diagnostics is implemented using unmanned aerial vehicles that are part of the mobile diagnostic complex. The advantages of the proposed solution include high efficiency and availability of application.

Google Earth Revisited

2017 ◽  
Vol 1 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Dimitris Kaimaris ◽  
Petros Patias ◽  
Olga Georgoula
Keyword(s):  
Digital Terrain Model ◽  
Google Earth ◽  
Aerial Photographs ◽  
Editorial Team ◽  
Research Activity ◽  
Ongoing Research ◽  
Terrain Model ◽  
Digital Terrain ◽  
The City ◽  
Ongoing Research Activity

The interpretation of photos and the processing of Google Earth imagery which allowed the “random” discovery, as a result of a non-systematical research, of a numerous marks of buried constructions in the wide area of the city of Larisa (Thessaly, Greece) is presented in this project. Additional data as aerial photographs over time, satellite images and the digital terrain model of the same area has been used. From the numerous marks, this project mainly focuses on three positions where the positive marks (soilmarks or/and cropmarks), circular or/and linear, reveal on a satisfying level covered construction of great dimensions. The ongoing research activity of the editorial team along with this research highlights the advantages of using Google Earth imagery in an attempt to “random” mark of unknown covered constructions, or, in the frame of a systematic survey of aerial and remote sensing archaeology, as additional and not exclusive source of information.

scholarly journals Analysis of the current state of unstable geomorphological structures with modern methods

2020 ◽  
Vol 13 (1) ◽  
pp. 195-199
Author(s):  
Vyacheslav V. Dolotov ◽  
Yuri N. Goryachkin ◽  
Andrey V. Dolotov
Keyword(s):  
Time Perspective ◽  
Digital Terrain Model ◽  
Aerial Photographs ◽  
Detailed Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Current State ◽  
The Status ◽  
The Mathematical Model

The paper gives results of the digitization of the status and spatial position of a cliff in the Western Crimea coastal zone. The modern equipment and methods accelerate the survey from the time perspective and improve the quality of the outcomes; namely a high precision GNSS receiver in RTK mode and PHANTOM-3 PRO copter. The digital terrain model was generated with used the Agisoft Photoscan software. The paper shows that the precision of the mathematical model of the relief constructed by aerial photographs provides more detailed data in comparison to those obtained in the field observations. Furthermore, aerial photography makes it possible to calculate the number of spatial characteristics of hazardous for surveying and latent natural objects out of reach for an on-location investigation. As a result, the very detailed data about current condition of dangerous cliff were obtained. The paper also evaluates the linear and volumetric characteristics of cleavages that are prone to collapse.

scholarly journals METHODS FOR THE UPDATE AND VERIFICATION OF FOREST SURFACE MODEL

2016 ◽  
Vol XLI-B4 ◽  
pp. 51-54
Author(s):  
M. Rybansky ◽  
M. Brenova ◽  
P. Zerzan ◽  
J. Simon ◽  
T. Mikita
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Geographic Location ◽  
Canopy Height ◽  
Aerial Photographs ◽  
Surface Model ◽  
Vegetation Growth ◽  
Terrain Model ◽  
Digital Terrain ◽  
Pulse Echo

The digital terrain model (DTM) represents the bare ground earth's surface without any objects like vegetation and buildings. In contrast to a DTM, Digital surface model (DSM) represents the earth's surface including all objects on it. The DTM mostly does not change as frequently as the DSM. The most important changes of the DSM are in the forest areas due to the vegetation growth. Using the LIDAR technology the canopy height model (CHM) is obtained by subtracting the DTM and the corresponding DSM. The DSM is calculated from the first pulse echo and DTM from the last pulse echo data. The main problem of the DSM and CHM data using is the actuality of the airborne laser scanning. <br><br> This paper describes the method of calculating the CHM and DSM data changes using the relations between the canopy height and age of trees. To get a present basic reference data model of the canopy height, the photogrammetric and trigonometric measurements of single trees were used. Comparing the heights of corresponding trees on the aerial photographs of various ages, the statistical sets of the tree growth rate were obtained. These statistical data and LIDAR data were compared with the growth curve of the spruce forest, which corresponds to a similar natural environment (soil quality, climate characteristics, geographic location, etc.) to get the updating characteristics.

scholarly journals Changes in a hydrographic network of the Słowiński National Park in terms of photogrammetric analyses

2017 ◽  
Vol 21 (4) ◽  
pp. 197-204
Author(s):  
Maciej Góraj ◽  
Marcin Kucharski ◽  
Krzysztof Karsznia ◽  
Izabela Karsznia ◽  
Jarosław Chormański
Keyword(s):  
Spatial Data ◽  
National Park ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Aerial Photographs ◽  
Terrain Model ◽  
Digital Terrain ◽  
Protected Natural Area ◽  
Water Courses ◽  
Hydrographic Network

AbstractThe main objective of this study is to evaluate the changes in the hydrographic network of Słowiński National Park. The authors analysed the changes occurring in the drainage network due to limited maintenance in this legally protected natural area. To accomplish this task, elaborations prepared on the basis of aerial photographs were used: an orthophoto map from 1996, hyperspectral imaging from June 2015, and a digital terrain model based on airborne laser scanning (ALS) from June 2015. These spatial data resources enabled the digitisation of the water courses for which selected hydro-morphological features had been defined. As a result of analysing the differences of these features, a quality map was elaborated which was then subjected to interpretation, and the identified changes were quantified in detail.

Google Earth Revisited

2019 ◽  
pp. 724-735
Author(s):  
Dimitris Kaimaris ◽  
Petros Patias ◽  
Olga Georgoula
Keyword(s):  
Digital Terrain Model ◽  
Google Earth ◽  
Aerial Photographs ◽  
Editorial Team ◽  
Research Activity ◽  
Ongoing Research ◽  
Terrain Model ◽  
Digital Terrain ◽  
The City ◽  
Source Of Information

The interpretation of photos and the processing of Google Earth imagery which allowed the “random” discovery, as a result of a non-systematical research, of a numerous marks of buried constructions in the wide area of the city of Larisa (Thessaly, Greece) is presented in this project. Additional data as aerial photographs over time, satellite images and the digital terrain model of the same area has been used. From the numerous marks, this project mainly focuses on three positions where the positive marks (soilmarks or/and cropmarks), circular or/and linear, reveal on a satisfying level covered construction of great dimensions. The ongoing research activity of the editorial team along with this research highlights the advantages of using Google Earth imagery in an attempt to “random” mark of unknown covered constructions, or, in the frame of a systematic survey of aerial and remote sensing archaeology, as additional and not exclusive source of information.

Google Earth Revisited

2020 ◽  
pp. 41-55
Author(s):  
Dimitris Kaimaris ◽  
Petros Patias ◽  
Olga Georgoula
Keyword(s):  
Digital Terrain Model ◽  
Google Earth ◽  
Aerial Photographs ◽  
Research Activity ◽  
Ongoing Research ◽  
Terrain Model ◽  
Digital Terrain ◽  
The City ◽  
Source Of Information ◽  
Ongoing Research Activity

The interpretation of photos and the processing of Google Earth imagery that allowed the “random” discovery as a result of a non-systematical research of numerous marks of buried constructions in the wide area of the city of Larisa (Thessaly, Greece) is presented in this chapter. Additional data as aerial photographs over time, satellite images and the digital terrain model of the same area has been used. From the numerous marks, this chapter mainly focuses on three positions where the positive marks (soil marks or/and crop marks), circular or/and linear, reveal on a satisfying level covered construction of great dimensions. The ongoing research activity of the research team along with this research highlights the advantages of using Google Earth imagery in an attempt to “random” mark of unknown covered constructions, or, in the frame of a systematic survey of aerial and remote sensing archaeology, as additional and not exclusive source of information.

scholarly journals Geodetic mass balance record with rigorous uncertainty estimates deduced from aerial photographs and lidar data – Case study from Drangajökull ice cap, NW Iceland

2016 ◽  
Vol 10 (1) ◽  
pp. 159-177 ◽  
Author(s):  
E. Magnússon ◽  
J. Muñoz-Cobo Belart ◽  
F. Pálsson ◽  
H. Ágústsson ◽  
P. Crochet
Keyword(s):  
High Resolution ◽  
Mass Balance ◽  
Bias Correction ◽  
Aerial Photographs ◽  
Glacier Surface ◽  
Ice Cap ◽  
Uncertainty Estimates ◽  
Lidar Dem ◽  
Geodetic Mass Balance

Abstract. In this paper we describe how recent high-resolution digital elevation models (DEMs) can be used to extract glacier surface DEMs from old aerial photographs and to evaluate the uncertainty of the mass balance record derived from the DEMs. We present a case study for Drangajökull ice cap, NW Iceland. This ice cap covered an area of 144 km2 when it was surveyed with airborne lidar in 2011. Aerial photographs spanning all or most of the ice cap are available from survey flights in 1946, 1960, 1975, 1985, 1994 and 2005. All ground control points used to constrain the orientation of the aerial photographs were obtained from the high-resolution lidar DEM. The lidar DEM was also used to estimate errors of the extracted photogrammetric DEMs in ice- and snow-free areas, at nunataks and outside the glacier margin. The derived errors of each DEM were used to constrain a spherical semivariogram model, which along with the derived errors in ice- and snow-free areas were used as inputs into 1000 sequential Gaussian simulations (SGSims). The simulations were used to estimate the possible bias in the entire glaciated part of the DEM and the 95 % confidence level of this bias. This results in bias correction varying in magnitude between 0.03 m (in 1975) and 1.66 m (in 1946) and uncertainty values between ±0.21 m (in 2005) and ±1.58 m (in 1946). Error estimation methods based on more simple proxies would typically yield 2–4 times larger error estimates. The aerial photographs used were acquired between late June and early October. An additional seasonal bias correction was therefore estimated using a degree-day model to obtain the volume change between the start of 2 glaciological years (1 October). This correction was largest for the 1960 DEM, corresponding to an average elevation change of −3.5 m or approx. three-quarters of the volume change between the 1960 and the 1975 DEMs. The total uncertainty of the derived mass balance record is dominated by uncertainty in the volume changes caused by uncertainties of the SGSim bias correction, the seasonal bias correction and the interpolation of glacier surface where data are lacking. The record shows a glacier-wide mass balance rate of Ḃ  = −0.26 ± 0.04 m w.e. a−1 for the entire study period (1946–2011). We observe significant decadal variability including periods of mass gain, peaking in 1985–1994 with Ḃ  = 0.27 ± 0.11 m w.e. a−1. There is a striking difference when Ḃ  is calculated separately for the western and eastern halves of Drangajökull, with a reduction of eastern part on average  ∼  3 times faster than the western part. Our study emphasizes the need for applying rigorous geostatistical methods for obtaining uncertainty estimates of geodetic mass balance, the importance of seasonal corrections of DEMs from glaciers with high mass turnover and the risk of extrapolating mass balance record from one glacier to another even over short distances.

scholarly journals A new method for determination of Most Likely Initiation Points and the evaluation of Digital Terrain Model scale in terrain stability mapping

2006 ◽  
Vol 3 (2) ◽  
pp. 395-425 ◽  
Author(s):  
P. Tarolli ◽  
D. G. Tarboton
Keyword(s):  
Digital Terrain Model ◽  
Grid Cell ◽  
Stability Index ◽  
Aerial Photographs ◽  
Terrain Model ◽  
Digital Terrain ◽  
Physically Based ◽  
Elevation Data ◽  
Stability Maps ◽  
Physically Based Models

Abstract. Physically-based models have been used previously to map areas of potential instability where shallow landslides may initiate. Here we introduce a new approach for determining the Most Likely Initiation Points (MLIP) for landslides. We identify the location with critical (lowest) stability index from a terrain stability model on each downslope path from ridge to valley. The SINMAP Stability Index (SI) was applied with this method. Only potential initiation points less than a threshold are considered to avoid identification of stable locations on downslope paths that do not contain any unstable locations. Mapped or observed landslides are often used to evaluate the effectiveness of model derived terrain stability maps, but a problem with these observations is that they may demarcate the entire landslide scar, including run out zones, rather than just initiation locations. Comparing such observations to SI does not provide a meaningful way to assess the effectiveness of the SI map because the demarcated area may include considerable area with stable SI values. In this paper we suggest using the relative density of MLIP locations within and outside demarcated landslide areas to assess the discriminating capability of a SI map. This approach was tested using landslides mapped from aerial photographs and airborne laser altimetry (LIDAR) derived elevation data for a small basin located in the Northeastern Region of Italy. Digital Terrain Models (DTMs) were derived from the LIDAR data for a range of grid cell sizes (from 2 to 50 m) and SI and MLIP evaluated for each. We found that the direct comparison of SI within and outside of landslides was not effective. However when MLIP was used we found appreciable differences between the density of MLIP points within and outside mapped landslides with ratios as large as three or more with the highest ratios for a DTM grid cell size of 10 m. This demonstrated the utility of the MLIP approach to quantifying the effectiveness of a terrain stability map when comparisons are to mapped landslides that include runout zones. This also suggests that in this study area, where landslides occurred in complexes that were sometimes more than 100 m wide, a DTM scale of 10 m is optimal. DTM scales larger than 10 m result in loss of resolution, while for DTM scales smaller than 10 m the physical processes responsible for triggering landslides are obscured by smaller scale DTM variability that is resolved.

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