Construction remote sensing, building blackbox, and 3-D laser scanning applications Liang Y. Liu, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

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

Remote Sensing ◽

10.3390/rs13030507 ◽

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.

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Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales

Remote Sensing ◽

10.3390/rs13020257 ◽

2021 ◽

Vol 13 (2) ◽

pp. 257 ◽

Cited By ~ 1

Author(s):

Shaun R. Levick ◽

Tim Whiteside ◽

David A. Loewensteiner ◽

Mitchel Rudge ◽

Renee Bartolo

Keyword(s):

Remote Sensing ◽

Vegetation Structure ◽

Laser Scanning ◽

Canopy Cover ◽

Structural Diversity ◽

Point Clouds ◽

Large Area ◽

Calibration And Validation ◽

Savanna Vegetation ◽

Landscape Scales

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.

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Remote Sensing for Land Administration

Remote Sensing ◽

10.3390/rs12152497 ◽

2020 ◽

Vol 12 (15) ◽

pp. 2497

Author(s):

Rohan Bennett ◽

Peter van Oosterom ◽

Christiaan Lemmen ◽

Mila Koeva

Keyword(s):

Remote Sensing ◽

Land Tenure ◽

Laser Scanning ◽

Poverty Reduction ◽

Spatial Information ◽

Cost Effective ◽

Terrestrial Lidar ◽

Land Administration ◽

Tools And Techniques ◽

Vertical Development

Land administration constitutes the socio-technical systems that govern land tenure, use, value and development within a jurisdiction. The land parcel is the fundamental unit of analysis. Each parcel has identifiable boundaries, associated rights, and linked parties. Spatial information is fundamental. It represents the boundaries between land parcels and is embedded in cadastral sketches, plans, maps and databases. The boundaries are expressed in these records using mathematical or graphical descriptions. They are also expressed physically with monuments or natural features. Ideally, the recorded and physical expressions should align, however, in practice, this may not occur. This means some boundaries may be physically invisible, lacking accurate documentation, or potentially both. Emerging remote sensing tools and techniques offers great potential. Historically, the measurements used to produce recorded boundary representations were generated from ground-based surveying techniques. The approach was, and remains, entirely appropriate in many circumstances, although it can be timely, costly, and may only capture very limited contextual boundary information. Meanwhile, advances in remote sensing and photogrammetry offer improved measurement speeds, reduced costs, higher image resolutions, and enhanced sampling granularity. Applications of unmanned aerial vehicles (UAV), laser scanning, both airborne and terrestrial (LiDAR), radar interferometry, machine learning, and artificial intelligence techniques, all provide examples. Coupled with emergent societal challenges relating to poverty reduction, rapid urbanisation, vertical development, and complex infrastructure management, the contemporary motivation to use these new techniques is high. Fundamentally, they enable more rapid, cost-effective, and tailored approaches to 2D and 3D land data creation, analysis, and maintenance. This Special Issue hosts papers focusing on this intersection of emergent remote sensing tools and techniques, applied to domain of land administration.

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Modelling of a construction pit

10.33920/sel-04-2102-10 ◽

2021 ◽

pp. 144-149

Author(s):

G. G. Bickbulatova ◽

E. N. Kupreeva

Keyword(s):

Remote Sensing ◽

Point Cloud ◽

Laser Scanning ◽

Remote Sensing Data ◽

Digital Model ◽

Geodetic Measurement ◽

Sensing Data

There are various programs for processing geodetic measurement and remote sensing data. This article discusses the use of Cyclone software for building a digital model of a construction pit surface based on a point cloud based on laser scanning and calculating the volume of earthworks.

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Airborne Laser Scanning in Poland - Between Science and Practice

Archives of Photogrammetry, Cartography and Remote Sensing ◽

10.2478/apcrs-2019-0008 ◽

2019 ◽

Vol 31 (1) ◽

pp. 105-133

Author(s):

Zdzisław Kurczyński

Keyword(s):

Remote Sensing ◽

Retrospective Analysis ◽

Laser Scanning ◽

Airborne Laser Scanning ◽

Production Potential ◽

Development Trends ◽

The Past ◽

Airborne Laser ◽

National Production ◽

Research Centres

Abstract The article is a retrospective analysis of the development of airborne laser scanning technology in the country in the past twenty years, i.e. from the beginnings of this technique use in Poland to the present day. The emphasis in the text is placed on development trends and scientific and application problems in the field of technology undertaken by national research centres. The review is based on numerous publications in this field, which have been released over two decades mainly in the “Archive of Photogrammetry, Cartography and Remote Sensing”. Therefore, the article is a presentation of the progress in the area of airborne laser scanning through an attempt to systematize and review national publications in this scope. It also presents the development of the national production potential and the level of the country’s coverage with data and products derived from airborne laser scanning.

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Construction remote sensing, building blackbox, and 3-D laser scanning applications

Structures and Infrastructures - Frontier Technologies for Infrastructures Engineering ◽

10.1201/9780203875599.ch18 ◽

2009 ◽

Author(s):

Liang Liu

Keyword(s):

Remote Sensing ◽

Laser Scanning

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PREFACE – ISPRS Geospatial Week 2019

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w5-1-2019 ◽

2019 ◽

Vol IV-2/W5 ◽

pp. 1-1

Author(s):

G. Vosselman ◽

S. J. Oude Elberink ◽

M. Y. Yang

Keyword(s):

Remote Sensing ◽

Data Quality ◽

Spatial Data ◽

Laser Scanning ◽

Spatial Information ◽

Smart Cities ◽

International Workshop ◽

Crowd Sourcing ◽

Spatial Data Quality ◽

Information Sciences

Abstract. The ISPRS Geospatial Week 2019 is a combination of 13 workshops organised by 30 ISPRS Working Groups active in areas of interest of ISPRS. The Geospatial Week 2019 is held from 10–14 June 2019, and is convened by the University of Twente acting as local organiser. The Geospatial Week 2019 is the fourth edition, after Antalya Turkey in 2013, La Grande Motte France in 2015 and Wuhan China in 2017.The following 13 workshops provide excellent opportunities to discuss the latest developments in the fields of sensors, photogrammetry, remote sensing, and spatial information sciences: <ul> <li>C3M&amp;GBD – Collaborative Crowdsourced Cloud Mapping and Geospatial Big Data</li> <li>CHGCS – Cryosphere and Hydrosphere for Global Change Studies</li> <li>EuroCow-M3DMaN – Joint European Calibration and Orientation Workshop and Workshop onMulti-sensor systems for 3D Mapping and Navigation</li> <li>HyperMLPA – Hyperspectral Sensing meets Machine Learning and Pattern Analysis</li> <li>Indoor3D</li> <li>ISSDQ – International Symposium on Spatial Data Quality</li> <li>IWIDF – International Workshop on Image and Data Fusion</li> <li>Laser Scanning</li> <li>PRSM – Planetary Remote Sensing and Mapping</li> <li>SarCon – Advances in SAR: Constellations, Signal processing, and Applications</li> <li>Semantics3D – Semantic Scene Analysis and 3D Reconstruction from Images and ImageSequences</li> <li>SmartGeoApps – Advanced Geospatial Applications for Smart Cities and Regions</li> <li>UAV-g – Unmanned Aerial Vehicles in Geomatics</li> </ul> Many of the workshops are part of well-established series of workshops convened in the past. They cover topics like UAV photogrammetry, laser scanning, spatial data quality, scene understanding, hyperspectral imaging, and crowd sourcing and collaborative mapping with applications ranging from indoor mapping and smart cities to global cryosphere and hydrosphere studies and planetary mapping.In total 143 full papers and 357 extended abstracts were submitted by authors from 63 countries. 1250 reviews have been delivered by 295 reviewers. A total of 81 full papers have been accepted for the volume IV-2/W5 of the International Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Another 289 papers are published in volume XLII-2/W13 of the International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences.The editors would like to thank all contributing authors, reviewers and all workshop organizers for their role in preparing and organizing the Geospatial Week 2019. Thanks to their contributions, we can offer an excessive and varying collection in the Annals and the Archives.We hope you enjoy reading the proceedings.George Vosselman, Geospatial Week Director 2019, General Chair Sander Oude Elberink, Programme Chair Michael Ying Yang, Programme Chair

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Geomorphological mapping based on DEMs and GIS: A review

Abstracts of the ICA ◽

10.5194/ica-abs-1-275-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-1

Author(s):

Takashi Oguchi

Keyword(s):

Remote Sensing ◽

Laser Scanning ◽

Aerial Photographs ◽

Topographic Maps ◽

Formation Processes ◽

Geomorphological Mapping ◽

Topographic Data ◽

Aerial Photogrammetry ◽

Landform Classification ◽

Shape Characteristics

Abstract. Geomorphology is a scientific discipline dealing with the characteristics, origin, and evolution of landforms. It utilizes topographic data such as spot height information, contour lines on topographic maps, and DEMs (Digital Elevation Models). Topographic data were traditionally obtained by ground surveying, but introduction of aerial photogrammetry in the early 20th century enabled more efficient data acquisition based on remote sensing. In recent years, active remote sensing methods including airborne and terrestrial laser scanning and applications of satellite radar have also been employed, and aerial photogrammetry has become easier and popular thanks to drones and a new photogrammetric method, SfM (Structure from Motion). The resultant topographic data especially raster DEMs are combined with GIS (Geographic Information Systems) to obtain derivatives such as slope and aspect as well as to conduct efficient geomorphological mapping. Resultant maps can depict various topographic characteristics based on surface height and DEM derivatives, and applications of advanced algorithms and some heuristic reasoning permit semi-automated landform classification. This quantitative approach differs from traditional and more qualitative methods to produce landform classification maps using visual interpretation of analogue aerial photographs and topographic maps as well as field observations.For scientific purposes, landforms need to be classified based on not only shape characteristics but also formation processes and ages. Among them, DEMs only represent shape characteristics, and understanding formation processes and ages usually require other data such as properties of surficial deposits observed in the field. However, numerous geomorphological studies indicate relationships between shapes and forming-processes of landforms, and even ages of landforms affect shapes such as a wider distribution of dissected elements within older landforms. Recent introduction of artificial intelligence in geomorphology including machine learning and deep learning may permit us to better understand the relationships of shapes with processes and ages. Establishing such relationships, however, is still highly challenging, and at this moment most geomorphologists think landform classification maps based on the traditional methods are more usable than those from the DEM-based methods. Nevertheless, researchers of some other fields such as civil engineering more appreciate the DEM-based methods because they can be conducted without deep geomorphological knowledge. Therefore, the methods should be developed for interdisciplinary understanding. This paper reviews and discusses such complex situations of geomorphological mapping today in relation to historical development of methodology.

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Remote Sensing based investigation of secondary mining deformation processes in a postglacial landscape of the Muzakow Arch Geopark (Western Poland) – preliminary results

10.5194/egusphere-egu21-2458 ◽

2021 ◽

Author(s):

Jan Blachowski ◽

Miłosz Becker ◽

Anna Buczyńska ◽

Natalia Bugajska ◽

Dominik Janicki ◽

...

Keyword(s):

Remote Sensing ◽

Laser Scanning ◽

Raw Materials ◽

Ground Level ◽

Slope Instability ◽

Opencast Mining ◽

Ongoing Research ◽

Preliminary Results ◽

Underground Workings ◽

Sink Hole

The area of the present day Muzalkow Arch Geopark located on the border of Poland and Germany was subjected to a long term mining of lignite and other rock raw materials that ceased in the 70&#8217;ties of the 20th Century. The present-day geomorphological landscape of the research area is characterised by numerous and differentiated forms of anthropogenic origin (e.g. artificial lakes, subsidence troughs, sink holes, waste heaps) associated with underground and subsequently opencast mining of lignite in complex geological and tectonic conditions that result from glaciotectonic processes of subsequent stages of accumulation and weathering. It is thought that the area is presently subjected to geodynamic processes associated with weathering of exposed areas (lignite outcrops and waste heaps), destruction of shallow underground workings (subsidence troughs, sink holes) and changing hydrogeological conditions of the rock mass. The scale of these secondary deformations is presently unknown and these processes pose a threat the present day tourist development of the area, such as: sudden development of discontinuous terrain deformations, slope instability, flooding and subsequent dying of vegetation, etc. Geodetic surveying and remote sensing (terrestrial, aerial and satellite) observations have been employed, apart from other in-situ investigations (geophysical and geological prospecting), to study the processes in one of the former coal mining fields in the geopark. In this study preliminary results of selected geodetic field investigations, i.e. terrestrial laser scanning of a sink hole that showed on the surface in Autumn 2019 and UAV photogrammetric monitoring of an artificial waste rock tips have been reported. It has been found, based on mapping of old mining maps in GIS, that the sink hole is directly related to old shallow underground workings. Maximum depth of the analysed sink hole below ground level is &#160;5.5 m and volume of subsidence is 35 m3. The location is being monitored to check if the geometry changes in time. Whereas, comparison of digital elevation models of the investigated waste heap (one of three measured so far) showed development of gully erosion and downward movement of the weathered material. The deposition of material at the bottom of the heap averaged over a dozen cm and maximum of over 50 cm for a half year Summer period (from 15.05.2020 to 07.11.2020). The presented results constitute a first approximation of 3D mapping and modelling the post-mining deformations in glaciotectonic landscape and constitute part of an ongoing research project financed from the Polish National Science Centre OPUS funds (no 2019/33/B/ST10/02975).

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