scholarly journals A COMPARISON OF UAV AND TLS DATA FOR SOIL ROUGHNESS ASSESSMENT

2016 ◽  
Vol III-5 ◽  
pp. 145-152
Author(s):  
M. Milenković ◽  
W. Karel ◽  
C. Ressl ◽  
N. Pfeifer
Keyword(s):  
Correlation Length ◽  
Measurement Errors ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Reference Method ◽  
Bundle Adjustment ◽  
Surface Model ◽  
Surface Geometry ◽  
Roughness Assessment ◽  
Uav Images

Soil roughness represents fine-scale surface geometry which figures in many geophysical models. While static photogrammetric techniques (terrestrial images and laser scanning) have been recently proposed as a new source for deriving roughness heights, there is still need to overcome acquisition scale and viewing geometry issues. By contrast to the static techniques, images taken from unmanned aerial vehicles (UAV) can maintain near-nadir looking geometry over scales of several agricultural fields. This paper presents a pilot study on high-resolution, soil roughness reconstruction and assessment from UAV images over an agricultural plot. As a reference method, terrestrial laser scanning (TLS) was applied on a 10 m x 1.5 m subplot. The UAV images were self-calibrated and oriented within a bundle adjustment, and processed further up to a dense-matched digital surface model (DSM). The analysis of the UAV- and TLS-DSMs were performed in the spatial domain based on the surface autocorrelation function and the correlation length, and in the frequency domain based on the roughness spectrum and the surface fractal dimension (spectral slope). The TLS- and UAV-DSM differences were found to be under ±1 cm, while the UAV DSM showed a systematic pattern below this scale, which was explained by weakly tied sub-blocks of the bundle block. The results also confirmed that the existing TLS methods leads to roughness assessment up to 5 mm resolution. However, for our UAV data, this was not possible to achieve, though it was shown that for spatial scales of 12 cm and larger, both methods appear to be usable. Additionally, this paper suggests a method to propagate measurement errors to the correlation length.

scholarly journals A COMPARISON OF UAV AND TLS DATA FOR SOIL ROUGHNESS ASSESSMENT

2016 ◽  
Vol III-5 ◽  
pp. 145-152 ◽  
Author(s):  
M. Milenković ◽  
W. Karel ◽  
C. Ressl ◽  
N. Pfeifer
Keyword(s):  
Correlation Length ◽  
Measurement Errors ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Reference Method ◽  
Bundle Adjustment ◽  
Surface Model ◽  
Surface Geometry ◽  
Roughness Assessment ◽  
Uav Images

Soil roughness represents fine-scale surface geometry which figures in many geophysical models. While static photogrammetric techniques (terrestrial images and laser scanning) have been recently proposed as a new source for deriving roughness heights, there is still need to overcome acquisition scale and viewing geometry issues. By contrast to the static techniques, images taken from unmanned aerial vehicles (UAV) can maintain near-nadir looking geometry over scales of several agricultural fields. This paper presents a pilot study on high-resolution, soil roughness reconstruction and assessment from UAV images over an agricultural plot. As a reference method, terrestrial laser scanning (TLS) was applied on a 10 m x 1.5 m subplot. The UAV images were self-calibrated and oriented within a bundle adjustment, and processed further up to a dense-matched digital surface model (DSM). The analysis of the UAV- and TLS-DSMs were performed in the spatial domain based on the surface autocorrelation function and the correlation length, and in the frequency domain based on the roughness spectrum and the surface fractal dimension (spectral slope). The TLS- and UAV-DSM differences were found to be under ±1 cm, while the UAV DSM showed a systematic pattern below this scale, which was explained by weakly tied sub-blocks of the bundle block. The results also confirmed that the existing TLS methods leads to roughness assessment up to 5 mm resolution. However, for our UAV data, this was not possible to achieve, though it was shown that for spatial scales of 12 cm and larger, both methods appear to be usable. Additionally, this paper suggests a method to propagate measurement errors to the correlation length.

scholarly journals 3D Reconstruction of Power Lines Using UAV Images to Monitor Corridor Clearance

2020 ◽  
Vol 12 (22) ◽  
pp. 3698
Author(s):  
Elżbieta Pastucha ◽  
Edyta Puniach ◽  
Agnieszka Ścisłowicz ◽  
Paweł Ćwiąkała ◽  
Witold Niewiem ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Laser Scanning ◽  
Power Line ◽  
Power Lines ◽  
Spatial Distance ◽  
Surface Model ◽  
Verification Methods ◽  
Comparison Results ◽  
Uav Images

Regular power line inspections are essential to ensure the reliability of electricity supply. The inspections of overground power submission lines include corridor clearance monitoring and fault identification. The power lines corridor is a three-dimensional space around power cables defined by a set distance. Any obstacles breaching this space should be detected, as they potentially threaten the safety of the infrastructure. Corridor clearance monitoring is usually performed either by a labor-intensive total station survey (TS), terrestrial laser scanning (TLS), or expensive airborne laser scanning (ALS) from a plane or a helicopter. This paper proposes a method that uses unmanned aerial vehicle (UAV) images to monitor corridor clearance. To maintain the adequate accuracy of the relative position of wires in regard to surrounding obstacles, the same data were used both to reconstruct a point cloud representation of a digital surface model (DSM) and a 3D power line. The proposed algorithm detects power lines in a series of images using decorrelation stretch for initial image processing, the modified Prewitt filter for edge enhancement, random sample consensus (RANSAC) with additional parameters for line fitting, and epipolar geometry for 3D reconstruction. DSM points intruding into the corridor are then detected by calculating the spatial distance between a reconstructed power line and the DSM point cloud representation. Problematic objects are localized by segmenting points into voxels and then subsequent clusterization. The processing results were compared to the results of two verification methods—TS and TLS. The comparison results show that the proposed method can be used to survey power lines with an accuracy consistent with that of classical measurements.

scholarly journals Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Parameter Extraction ◽  
Airborne Lidar ◽  
Special Focus ◽  
Vegetation Parameter

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

scholarly journals Spatio-Temporal Change Monitoring of Outside Manure Piles Using Unmanned Aerial Vehicle Images

Drones ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Geonung Park ◽  
Kyunghun Park ◽  
Bonggeun Song
Keyword(s):  
Point Source ◽  
Laser Scanning ◽  
Image Data ◽  
Surface Model ◽  
Point Source Pollution ◽  
Efficient Management ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Agricultural Areas ◽  
Water Quality Deterioration

Water quality deterioration due to outdoor loading of livestock manure requires efficient management of outside manure piles (OMPs). This study was designed to investigate OMPs using unmanned aerial vehicles (UAVs) for efficient management of non-point source pollution in agricultural areas. A UAV was used to acquire image data, and the distribution and cover installation status of OMPs were identified through ortho-images; the volumes of OMP were calculated using digital surface model (DSM). UAV- and terrestrial laser scanning (TLS)-derived DSMs were compared for identifying the accuracy of calculated volumes. The average volume accuracy was 92.45%. From April to October, excluding July, the monthly average volumes of OMPs in the study site ranged from 64.89 m3 to 149.69 m3. Among the 28 OMPs investigated, 18 were located near streams or agricultural waterways. Establishing priority management areas among the OMP sites distributed in a basin is possible using spatial analysis, and it is expected that the application of UAV technology will contribute to the efficient management of OMPs and other non-point source pollutants.

scholarly journals Development of a Long Period Fiber Grating Interrogation System Using a Multimode Laser Diode

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 749
Author(s):  
Luís Henrique Silva ◽  
Paulo Santos ◽  
Luís C. C. Coelho ◽  
Pedro Jorge ◽  
José Manuel Baptista
Keyword(s):  
Laser Diode ◽  
Measurement Errors ◽  
Laser Scanning ◽  
Fiber Grating ◽  
Light Sources ◽  
Fiber Gratings ◽  
Multimode Laser ◽  
Central Wavelength ◽  
Long Period ◽  
Multimode Laser Diode

Optical fiber gratings have long shown their sensing capabilities. One of the main challenges, however, is the interrogation method applied, since typical systems tend to use broadband light sources with optical spectrum analyzers, laser scanning units or CCD (Charged Coupled Device) spectrometers. The following paper presents the development of an interrogation system, which explores the temperature response of a multimode laser diode, in order to interrogate long period fiber gratings. By performing a spectral sweep along one of its rejection bands, a discrete attenuation spectrum is created. Through a curve fitting technique, the original spectrum is restored. The built unit, while presenting a substantially reduced cost compared with typical interrogation systems, is capable of interrogating along a 10 nm window with measurement errors reaching minimum values as low as 0.4 nm, regarding the grating central wavelength, and 0.4 dB for its attenuation. Given its low cost and reduced dimensions, the developed system shows potential for slow-changing field applications.

scholarly journals A low-cost technique to measure bank erosion proces ses along middle-size river reaches

2018 ◽  
Author(s):  
Gonzalo Duró ◽  
Alessandra Crosato ◽  
Maarten G. Kleinhans ◽  
Wim S. J. Uijttewaal
Keyword(s):  
Laser Scanning ◽  
Spatial Scales ◽  
Low Cost ◽  
Bank Erosion ◽  
Water Levels ◽  
Small Scale ◽  
Observation Distance ◽  
River Bank ◽  
Erosion Processes ◽  
Rtk Gps

Abstract. Diverse methods are currently available to measure river bank erosion at broad-ranging temporal and spatial scales. Yet, no technique provides low-cost and high-resolution to survey small-scale bank processes along a river reach. We investigate the capabilities of Structure-from-Motion photogrammetry applied with imagery from an Unmanned Aerial Vehicle (UAV) to describe the evolution of riverbank profiles in middle-size rivers. The bank erosion cycle is used as a reference to assess the applicability of different techniques. We surveyed 1.2 km of a restored bank of the Meuse River eight times within a year, combining different photograph perspectives and overlaps to identify an efficient UAV flight to monitor banks. The accuracy of the Digital Surface Models (DSMs) was evaluated compared with RTK GPS points and an Airborne Laser Scanning (ALS) of the whole reach. An oblique perspective with eight photo overlaps was sufficient to achieve the highest relative precision to observation distance of ~1:1400, with 10 cm error range. A complementary nadiral view increased coverage behind bank toe vegetation. The DSM and ALS had comparable accuracies except on banks, where the latter overestimates elevations. Sequential DSMs captured signatures of the erosion cycle such as mass failures, slump-block deposition, and bank undermining. Although this technique requires low water levels and banks without dense vegetation, it is a low-cost method to survey reach-scale riverbanks in sufficient resolution to quantify bank retreat and identify morphological features of the bank failure and erosion processes.

scholarly journals Remotely Sensed Single Tree Data Enable the Determination of Habitat Thresholds for the Three-Toed Woodpecker (Picoides tridactylus)

2018 ◽  
Vol 10 (12) ◽  
pp. 1972 ◽  
Author(s):  
Katarzyna Zielewska-Büttner ◽  
Marco Heurich ◽  
Jörg Müller ◽  
Veronika Braunisch
Keyword(s):  
Bark Beetles ◽  
Laser Scanning ◽  
Positive Relationship ◽  
Spatial Scales ◽  
Keystone Species ◽  
Remote Sensing Data ◽  
Individual Tree ◽  
Substrate Quality ◽  
Dead Trees ◽  
Negative Effect

Forest biodiversity conservation requires precise, area-wide information on the abundance and distribution of key habitat structures at multiple spatial scales. We combined airborne laser scanning (ALS) data with color-infrared (CIR) aerial imagery for identifying individual tree characteristics and quantifying multi-scale habitat requirements using the example of the three-toed woodpecker (Picoides tridactylus) (TTW) in the Bavarian Forest National Park (Germany). This bird, a keystone species of boreal and mountainous forests, is highly reliant on bark beetles dwelling in dead or dying trees. While previous studies showed a positive relationship between the TTW presence and the amount of deadwood as a limiting resource, we hypothesized a unimodal response with a negative effect of very high deadwood amounts and tested for effects of substrate quality. Based on 104 woodpecker presence or absence locations, habitat selection was modelled at four spatial scales reflecting different woodpecker home range sizes. The abundance of standing dead trees was the most important predictor, with an increase in the probability of TTW occurrence up to a threshold of 44–50 dead trees per hectare, followed by a decrease in the probability of occurrence. A positive relationship with the deadwood crown size indicated the importance of fresh deadwood. Remote sensing data allowed both an area-wide prediction of species occurrence and the derivation of ecological threshold values for deadwood quality and quantity for more informed conservation management.

scholarly journals Large but decreasing effect of ozone on the European carbon sink

2018 ◽  
Vol 15 (13) ◽  
pp. 4245-4269 ◽  
Author(s):  
Rebecca J. Oliver ◽  
Lina M. Mercado ◽  
Stephen Sitch ◽  
David Simpson ◽  
Belinda E. Medlyn ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Primary Productivity ◽  
Carbon Sink ◽  
Spatial Scales ◽  
Stomatal Closure ◽  
Regional Scale ◽  
Surface Model ◽  
Background Concentrations ◽  
Tropospheric O3 ◽  
The Impact

Abstract. The capacity of the terrestrial biosphere to sequester carbon and mitigate climate change is governed by the ability of vegetation to remove emissions of CO2 through photosynthesis. Tropospheric O3, a globally abundant and potent greenhouse gas, is, however, known to damage plants, causing reductions in primary productivity. Despite emission control policies across Europe, background concentrations of tropospheric O3 have risen significantly over the last decades due to hemispheric-scale increases in O3 and its precursors. Therefore, plants are exposed to increasing background concentrations, at levels currently causing chronic damage. Studying the impact of O3 on European vegetation at the regional scale is important for gaining greater understanding of the impact of O3 on the land carbon sink at large spatial scales. In this work we take a regional approach and update the JULES land surface model using new measurements specifically for European vegetation. Given the importance of stomatal conductance in determining the flux of O3 into plants, we implement an alternative stomatal closure parameterisation and account for diurnal variations in O3 concentration in our simulations. We conduct our analysis specifically for the European region to quantify the impact of the interactive effects of tropospheric O3 and CO2 on gross primary productivity (GPP) and land carbon storage across Europe. A factorial set of model experiments showed that tropospheric O3 can suppress terrestrial carbon uptake across Europe over the period 1901 to 2050. By 2050, simulated GPP was reduced by 4 to 9 % due to plant O3 damage and land carbon storage was reduced by 3 to 7 %. The combined physiological effects of elevated future CO2 (acting to reduce stomatal opening) and reductions in O3 concentrations resulted in reduced O3 damage in the future. This alleviation of O3 damage by CO2-induced stomatal closure was around 1 to 2 % for both land carbon and GPP, depending on plant sensitivity to O3. Reduced land carbon storage resulted from diminished soil carbon stocks consistent with the reduction in GPP. Regional variations are identified with larger impacts shown for temperate Europe (GPP reduced by 10 to 20 %) compared to boreal regions (GPP reduced by 2 to 8 %). These results highlight that O3 damage needs to be considered when predicting GPP and land carbon, and that the effects of O3 on plant physiology need to be considered in regional land carbon cycle assessments.

scholarly journals Spatial scales, patterns, and positivity trends of SARS-CoV-2 pandemics in mass rapid antigen testing in Slovakia

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256669
Author(s):  
Katarína Boďová ◽  
Richard Kollár
Keyword(s):  
Correlation Length ◽  
Spatial Scales ◽  
Mean Reversion ◽  
Spatial Trend ◽  
Geographical Data ◽  
Mean Reversion Process ◽  
Data Surveillance ◽  
Direct Guidance ◽  
Epidemic Response ◽  
Antigen Testing

We study geographical epidemic scales and patterns and positivity trends of SARS-CoV-2 pandemics in mass antigen testing in Slovakia in 2020. The observed test positivity was exponentially distributed with a long scale exponential spatial trend, and its characteristic correlation length was approximately 10 km. Spatial scales also play an important role in test positivity reduction between two consecutive testing rounds. While test positivity decreased in all counties, it increased in individual municipalities with low test positivity in the earlier testing round in a way statistically different from a mean-reversion process. Also, non-residents testing influences the mass testing results as test positivity of non-residents was higher than of residents when testing was offered only in municipalities with the highest positivity in previous rounds. Our results provide direct guidance for pandemic geographical data surveillance and epidemic response management.

scholarly journals MULTISPECTRAL AIRBORNE LASER SCANNING FOR AUTOMATED MAP UPDATING

2016 ◽  
Vol XLI-B3 ◽  
pp. 323-330 ◽  
Author(s):  
Leena Matikainen ◽  
Juha Hyyppä ◽  
Paula Litkey
Keyword(s):  
Change Detection ◽  
Laser Scanning ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Sensor Technology ◽  
Classification Error ◽  
Surface Model ◽  
Airborne Laser ◽  
Map Updating

During the last 20 years, airborne laser scanning (ALS), often combined with multispectral information from aerial images, has shown its high feasibility for automated mapping processes. Recently, the first multispectral airborne laser scanners have been launched, and multispectral information is for the first time directly available for 3D ALS point clouds. This article discusses the potential of this new single-sensor technology in map updating, especially in automated object detection and change detection. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from a random forests analysis suggest that the multispectral intensity information is useful for land cover classification, also when considering ground surface objects and classes, such as roads. An out-of-bag estimate for classification error was about 3% for separating classes asphalt, gravel, rocky areas and low vegetation from each other. For buildings and trees, it was under 1%. According to feature importance analyses, multispectral features based on several channels were more useful that those based on one channel. Automatic change detection utilizing the new multispectral ALS data, an old digital surface model (DSM) and old building vectors was also demonstrated. Overall, our first analyses suggest that the new data are very promising for further increasing the automation level in mapping. The multispectral ALS technology is independent of external illumination conditions, and intensity images produced from the data do not include shadows. These are significant advantages when the development of automated classification and change detection procedures is considered.

Sign in / Sign up

Export Citation Format

Share Document