Developing statistically driven eco-engineering designs from LiDAR and structure from motion surveys for marine artificial structures.

2020 ◽  
Author(s):  
Peter Lawrence ◽  
Ally Evans ◽  
Paul Brooks ◽  
Tim D'Urban Jackson ◽  
Stuart Jenkins ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Habitat Loss ◽  
Structure From Motion ◽  
Laser Scanning ◽  
Large Scale ◽  
Spatial Scales ◽  
Coastal Development ◽  
Ecological Design ◽  
Artificial Structures ◽  
Engineering Research

<p>Coastal ecosystems are threatened by habitat loss and anthropogenic “smoothing” as hard engineering approaches to sea defence, such as sea-walls, rock armouring, and offshore reefs, become common place. These artificial structures use homogenous materials (e.g. concrete or quarried rock) and as a result, lack the surface heterogeneity of natural rocky shoreline known to play a key role in niche creation and higher species diversity. Despite significant investment and research into soft engineering and ecologically sensitive approaches to coastal development, there are still knowledge gaps, particularly in relation to how patterns that are observed in nature can be utilised to improve artificial shores.</p><p>Given the technical improvements and significant reductions in cost within the portable remote sensing field (structure from motion and laser scanning), we are now able to plug gaps in our understanding of how habitat heterogeneity can influence overall site diversity. These improvements represent an excellent opportunity to improve our understanding of the spatial scales and complexity of habitats that species occur within and ultimately improve the ecological design of engineered structures in areas experiencing “smoothing” and habitat loss.</p><p>In this talk, I will highlight how advances in remote sensing techniques can be applied to context-specific ecological problems, such as low diversity and loss of rare species within marine infrastructure. I will describe our approach to combining large-scale ecological, 3D geophysical and engineering research to design statistically-derived ecologically-inspired solutions to smooth artificial surfaces. We created experimental concrete enhancement units and deployed them at a number of coastal locations. I will present preliminary ecological results, provide a workflow of unit development and statistical approaches, and finally discuss how these advances may improve future ecological intervention and design options.</p>

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 Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence

2019 ◽  
pp. 201900278 ◽  
Author(s):  
Troy S. Magney ◽  
David R. Bowling ◽  
Barry A. Logan ◽  
Katja Grossmann ◽  
Jochen Stutz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Spatial Scales ◽  
Gross Primary Production ◽  
Canopy Structure ◽  
Operating Efficiency ◽  
Conifer Forest ◽  
Spatiotemporal Resolution ◽  
Evergreen Forests ◽  
Spectrometer System

Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO2 but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated (R2 = 0.62–0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution.

scholarly journals Radar vision in the mapping of forest biodiversity from space

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Soyeon Bae ◽  
Shaun R. Levick ◽  
Lea Heidrich ◽  
Paul Magdon ◽  
Benjamin F. Leutner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
External Validation ◽  
Predictive Ability ◽  
Radar Data ◽  
Forest Regions ◽  
Local Species ◽  
Spatio Temporal ◽  
Derived Data

Abstract Recent progress in remote sensing provides much-needed, large-scale spatio-temporal information on habitat structures important for biodiversity conservation. Here we examine the potential of a newly launched satellite-borne radar system (Sentinel-1) to map the biodiversity of twelve taxa across five temperate forest regions in central Europe. We show that the sensitivity of radar to habitat structure is similar to that of airborne laser scanning (ALS), the current gold standard in the measurement of forest structure. Our models of different facets of biodiversity reveal that radar performs as well as ALS; median R² over twelve taxa by ALS and radar are 0.51 and 0.57 respectively for the first non-metric multidimensional scaling axes representing assemblage composition. We further demonstrate the promising predictive ability of radar-derived data with external validation based on the species composition of birds and saproxylic beetles. Establishing new area-wide biodiversity monitoring by remote sensing will require the coupling of radar data to stratified and standardized collected local species data.

scholarly journals Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest

2021 ◽  
Vol 13 (11) ◽  
pp. 2063
Author(s):  
Luka Jurjević ◽  
Mateo Gašparović ◽  
Xinlian Liang ◽  
Ivan Balenović
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
Deciduous Forest ◽  
Information Source ◽  
Data Sources ◽  
Pedunculate Oak ◽  
Absolute Deviation ◽  
Close Range ◽  
Remote Sensing Techniques

Digital terrain models (DTMs) are important for a variety of applications in geosciences as a valuable information source in forest management planning, forest inventory, hydrology, etc. Despite their value, a DTM in a forest area is typically lower quality due to inaccessibility and limited data sources that can be used in the forest environment. In this paper, we assessed the accuracy of close-range remote sensing techniques for DTM data collection. In total, four data sources were examined, i.e., handheld personal laser scanning (PLShh, GeoSLAM Horizon), terrestrial laser scanning (TLS, FARO S70), unmanned aerial vehicle (UAV) photogrammetry (UAVimage), and UAV laser scanning (ULS, LS Nano M8). Data were collected within six sample plots located in a lowland pedunculate oak forest. The reference data were of the highest quality available, i.e., total station measurements. After normality and outliers testing, both robust and non-robust statistics were calculated for all close-range remote sensing data sources. The results indicate that close-range remote sensing techniques are capable of achieving higher accuracy (root mean square error < 15 cm; normalized median absolute deviation < 10 cm) than airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) data that are generally understood to be the best data sources for DTM on a large scale.

scholarly journals Estimating Floodplain Vegetative Roughness Using Drone-Based Laser Scanning and Structure from Motion Photogrammetry

2021 ◽  
Vol 13 (13) ◽  
pp. 2616
Author(s):  
Elizabeth M. Prior ◽  
Charles A. Aquilina ◽  
Jonathan A. Czuba ◽  
Thomas J. Pingel ◽  
W. Cully Hession
Keyword(s):  
Structure From Motion ◽  
Laser Scanning ◽  
Spatial Scales ◽  
High Flow ◽  
Model Simulations ◽  
Hydraulic Roughness ◽  
Vegetation Height ◽  
Large Trees ◽  
Patch Scale

Vegetation heights derived from drone laser scanning (DLS), and structure from motion (SfM) photogrammetry at the Virginia Tech StREAM Lab were utilized to determine hydraulic roughness (Manning’s roughness coefficients). We determined hydraulic roughness at three spatial scales: reach, patch, and pixel. For the reach scale, one roughness value was set for the channel, and one value for the entire floodplain. For the patch scale, vegetation heights were used to classify the floodplain into grass, scrub, and small and large trees, with a single roughness value for each. The roughness values for the reach and patch methods were calibrated using a two-dimensional (2D) hydrodynamic model (HEC-RAS) and data from in situ velocity sensors. For the pixel method, we applied empirical equations that directly estimated roughness from vegetation height for each pixel of the raster (no calibration necessary). Model simulations incorporating these roughness datasets in 2D HEC-RAS were validated against water surface elevations (WSE) from seventeen groundwater wells for seven high-flow events during the Fall of 2018 and 2019, and compared to marked flood extents. The reach method tended to overestimate while the pixel method tended to underestimate the flood extent. There were no visual differences between DLS and SfM within the pixel and patch methods when comparing flood extents. All model simulations were not significantly different with respect to the well WSEs (p > 0.05). The pixel methods had the lowest WSE RMSEs (SfM: 0.136 m, DLS: 0.124 m). The other methods had RMSE values 0.01–0.02 m larger than the DLS pixel method. Models with DLS data also had lower WSE RMSEs by 0.01 m when compared to models utilizing SfM. This difference might not justify the increased cost of a DLS setup over SfM (~150,000 vs. ~2000 USD for this study), though our use of the DLS DEM to determine SfM vegetation heights might explain this minimal difference. We expect a poorer performance of the SfM-derived vegetation heights/roughness values if we were using a SfM DEM, although further work is needed. These results will help improve hydrodynamic modeling efforts, which are becoming increasingly important for management and planning in response to climate change, specifically in regions were high flow events are increasing.

scholarly journals Three-dimensional digital mapping of ecosystems: a new era in spatial ecology

2020 ◽  
Vol 287 (1920) ◽  
pp. 20192383 ◽  
Author(s):  
Tim D'Urban Jackson ◽  
Gareth J. Williams ◽  
Guy Walker-Springett ◽  
Andrew J. Davies
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Structure From Motion ◽  
Spatial Ecology ◽  
Laser Scanning ◽  
Multiple Scales ◽  
3D Structure ◽  
Three Dimensional ◽  
Ecosystem Structure ◽  
New Era

Ecological processes occur over multiple spatial, temporal and thematic scales in three-dimensional (3D) ecosystems. Characterizing and monitoring change in 3D structure at multiple scales is challenging within the practical constraints of conventional ecological tools. Remote sensing from satellites and crewed aircraft has revolutionized broad-scale spatial ecology, but fine-scale patterns and processes operating at sub-metre resolution have remained understudied over continuous extents. We introduce two high-resolution remote sensing tools for rapid and accurate 3D mapping in ecology—terrestrial laser scanning and structure-from-motion photogrammetry. These technologies are likely to become standard sampling tools for mapping and monitoring 3D ecosystem structure across currently under-sampled scales. We present practical guidance in the use of the tools and address barriers to widespread adoption, including testing the accuracy of structure-from-motion models for ecologists. We aim to highlight a new era in spatial ecology that uses high-resolution remote sensing to interrogate 3D digital ecosystems.

GIS of the chora of Cyrene: fortifications and Christian buildings in Late Antiquity

2016 ◽  
Vol 47 ◽  
pp. 31-66 ◽  
Author(s):  
A. Abdalrahim Sheriff Saad ◽  
S. Farag Abdel Hati ◽  
Sonia Antonelli ◽  
Oliva Menozzi ◽  
Veronica Petraccia ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Late Antiquity ◽  
Laser Scanning ◽  
Large Scale ◽  
Landscape Archaeology ◽  
Local Economy ◽  
Gis Mapping ◽  
Differential Gps ◽  
Non Invasive ◽  
Traditional Research

AbstractThe project of mapping the chora of Cyrene, for the team of Chieti University, started between 1999 and 2001 as a layer of a ‘macro-GIS’ of the area to the east of Cyrene, that is, the transect between Cyrene and El-Gubba/Qubbah. Because of the large scale of the area and the monumentality of the sites, the team is composed of several research units based around a large number of scholars and technicians. The project employs a suite of traditional methodologies for the study of landscape archaeology (surveys, GIS mapping, differential GPS, excavations), in combination with technologies integrating the knowledge of the territory (remote sensing on HD satellite photos, geomorphological reconstruction, laser scanning, archaeometric analysis, non-invasive geophysical prospection and infrared diagnostic analysis). The large quantity of data coming from this wide approach has been organised into a flexible and multilayer GIS. A joint team of Libyan and Italian archaeologists and technicians is testing a common protocol for monitoring the monuments and sites in the territory, using surveys and remote sensing analysis, which has intensified during these problematic periods, and regularly analysing satellite sets over the past four years.The project aims to map and document as much as possible in this territory, to identify the location of the region's so-called ‘minor sites’, which are numerous and almost unknown. They were, from the Late Classical to the Islamic periods, vital sites for the management of the local economy. This paper presents the main issues relating to settlements and sites in Late Antiquity, concentrating mainly on fortifications along the limes and basilicas within the area of the transect. Moreover, in the presentation of the data, the GIS approach has been integrated here with data coming both from the remote sensing and from more traditional research approaches, such as planimetrical and typological analysis of the buildings, study of the sources and detailed mapping of the building techniques.

scholarly journals A Review of Quantifying pCO2 in Inland Waters with a Global Perspective: Challenges and Prospects of Implementing Remote Sensing Technology

2021 ◽  
Vol 13 (23) ◽  
pp. 4916
Author(s):  
Zhidan Wen ◽  
Yingxin Shang ◽  
Lili Lyu ◽  
Sijia Li ◽  
Hui Tao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Biological Activities ◽  
Spatial Scales ◽  
Measurement Data ◽  
Global Perspective ◽  
Published Data ◽  
Inland Waters ◽  
Rivers And Streams ◽  
Temporal And Spatial

The traditional field-based measurements of carbon dioxide (pCO2) for inland waters are a snapshot of the conditions on a particular site, which might not adequately represent the pCO2 variation of the entire lake. However, these field measurements can be used in the pCO2 remote sensing modeling and verification. By focusing on inland waters (including lakes, reservoirs, rivers, and streams), this paper reviews the temporal and spatial variability of pCO2 based on published data. The results indicate the significant daily and seasonal variations in pCO2 in lakes. Rivers and streams contain higher pCO2 than lakes and reservoirs in the same climatic zone, and tropical waters typically exhibit higher pCO2 than temperate, boreal, and arctic waters. Due to the temporal and spatial variations of pCO2, it can differ in different inland water types in the same space-time. The estimation of CO2 fluxes in global inland waters showed large uncertainties with a range of 1.40–3.28 Pg C y−1. This paper also reviews existing remote sensing models/algorithms used for estimating pCO2 in sea and coastal waters and presents some perspectives and challenges of pCO2 estimation in inland waters using remote sensing for future studies. To overcome the uncertainties of pCO2 and CO2 emissions from inland waters at the global scale, more reliable and universal pCO2 remote sensing models/algorithms will be needed for mapping the long-term and large-scale pCO2 variations for inland waters. The development of inverse models based on dissolved biogeochemical processes and the machine learning algorithm based on measurement data might be more applicable over longer periods and across larger spatial scales. In addition, it should be noted that the remote sensing-retrieved pCO2/the CO2 concentration values are the instantaneous values at the satellite transit time. A major technical challenge is in the methodology to transform the retrieved pCO2 values on time scales from instant to days/months, which will need further investigations. Understanding the interrelated control and influence processes closely related to pCO2 in the inland waters (including the biological activities, physical mixing, a thermodynamic process, and the air–water gas exchange) is the key to achieving remote sensing models/algorithms of pCO2 in inland waters. This review should be useful for a general understanding of the role of inland waters in the global carbon cycle.

Structure-level fuel load assessment in the wildland–urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies

2016 ◽  
Vol 25 (5) ◽  
pp. 547 ◽  
Author(s):  
Nicholas S. Skowronski ◽  
Scott Haag ◽  
Jim Trimble ◽  
Kenneth L. Clark ◽  
Michael R. Gallagher ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
Unit Area ◽  
Airborne Laser Scanning ◽  
Fuel Load ◽  
Spatial Averaging ◽  
Fuel Reduction ◽  
Wildland Urban Interface ◽  
Airborne Laser

Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland–urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels in the WUI at the scale of individual structures by integrating aerial photography, airborne laser scanning and cadastral datasets into a hazard assessment framework. This methodology is appropriate for informing zoning policy questions, targeting presuppression planning and fuel reduction treatments, and assisting in prioritising structure defence during suppression operations. Our results show increased variability in fuel loads with decreasing analysis unit area, indicating that fine-scale differences exist that may be omitted owing to spatial averaging when using a coarser, grid-based approach. Analyses using a local parcel database indicate that approximately 75% of the structures in this study have ownership of less than 50% of the 30 m buffer around their building, illustrating the complexity of multiple ownerships when attempting to manage fuels in the WUI. Our results suggest that our remote-sensing approach could augment, and potentially improve, ground-based survey approaches in the WUI.

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