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

2021 ◽  
Vol 13 (2) ◽  
pp. 257 ◽  
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.

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 Entwicklungen im Bereich der Fernerkundung für forstliche Anwendungen

2017 ◽  
Vol 168 (3) ◽  
pp. 118-126
Author(s):  
Christian Ginzler ◽  
Lars T. Waser
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
Near Infrared ◽  
National Level ◽  
Point Clouds ◽  
Aerial Image ◽  
High Temporal Resolution ◽  
Large Area ◽  
Daily Work

Progress in remote sensing for forestry applications Over the past ten years significant advances have been made in remote sensing data and methods for forestry applications. In many cases datasets are no longer limited to use for case studies or the development of methods, but are available for large area applications, often with high temporal resolution. Aerial image acquisition, including in near infrared, has become standard thanks to the use of digital cameras. Colour infrared orthophotos are easily embedded into GIS applications at the cantonal and national level. Aerial laser scanning data has almost become the norm for many applications. Tools integrated into common working environments are available which allow for the efficient analysis of 3-D point clouds and the realisation of valuable products describing forested areas. Terrestrial laser scanning is also nearing operational applicability for many purposes. Remote sensing is continually developing into a practical instrument for daily work. As long as users are aware of the possibilities and also the limitations, remote sensing offers substantial potential to support and optimise terrestrial inventory and for the generation of additional large-scale values.

scholarly journals Fusing Sentinel-2 Imagery and ALS Point Clouds for Defining LULC Changes on Reclaimed Areas by Afforestation

2019 ◽  
Vol 11 (5) ◽  
pp. 1251 ◽  
Author(s):  
Marta Szostak ◽  
Kacper Knapik ◽  
Piotr Wężyk ◽  
Justyna Likus-Cieślik ◽  
Marcin Pietrzykowski
Keyword(s):  
Laser Scanning ◽  
Canopy Cover ◽  
Point Clouds ◽  
Test Site ◽  
Vegetation Growth ◽  
Landsat 7 ◽  
Forested Areas ◽  
Primary Focus ◽  
Year 2000 ◽  
Sentinel 2

The study was performed on two former sulphur mines located in Southeast Poland: Jeziórko, where 216.5 ha of afforested area was reclaimed after borehole exploitation and Machów, where 871.7 ha of dump area was reclaimed after open cast strip mining. The areas were characterized by its terrain structure and vegetation cover resulting from the reclamation process. The types of reclamation applied in these areas were forestry in Jeziórko and agroforestry in the Machów post-sulphur mine. The study investigates the possibility of applying the most recent Sentinel-2 (ESA) satellite imageries for land cover mapping, with a primary focus on detecting and monitoring afforested areas. Airborne laser scanning point clouds were used to derive precise information about the spatial (3D) characteristics of vegetation: the height (95th percentile), std. dev. of relative height, and canopy cover. The results of the study show an increase in afforested areas in the former sulphur mines. For the entire analyzed area of Jeziórko, forested areas made up 82.0% in the year 2000 (Landsat 7, NASA), 88.8% in 2009 (aerial orthophoto), and 95.5% in 2016 (Sentinel-2, ESA). For Machów, the corresponding results were 46.1% in 2000, 57.3% in 2009, and 60.7% in 2016. A dynamic increase of afforested area was observed, especially in the Jeziórko test site, with the presence of different stages of vegetation growth.

scholarly journals Individual tree extraction from terrestrial laser scanning data via graph pathing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Di Wang ◽  
Xinlian Liang ◽  
Gislain II Mofack ◽  
Olivier Martin-Ducup
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Tree Level ◽  
Forest Types ◽  
Computationally Efficient ◽  
Large Area ◽  
Individual Tree ◽  
Single Crown ◽  
Tree Extraction

Abstract Background Individual tree extraction from terrestrial laser scanning (TLS) data is a prerequisite for tree-scale estimations of forest biophysical properties. This task currently is undertaken through laborious and time-consuming manual assistance and quality control. This study presents a new fully automatic approach to extract single trees from large-area TLS data. This data-driven method operates exclusively on a point cloud graph by path finding, which makes our method computationally efficient and universally applicable to data from various forest types. Results We demonstrated the proposed method on two openly available datasets. First, we achieved state-of-the-art performance on locating single trees on a benchmark dataset by significantly improving the mean accuracy by over 10% especially for difficult forest plots. Second, we successfully extracted 270 trees from one hectare temperate forest. Quantitative validation resulted in a mean Intersection over Union (mIoU) of 0.82 for single crown segmentation, which further led to a relative root mean square error (RMSE%) of 21.2% and 23.5% for crown area and tree volume estimations, respectively. Conclusions Our method allows automated access to individual tree level information from TLS point clouds. The proposed method is free from restricted assumptions of forest types. It is also computationally efficient with an average processing time of several seconds for one million points. It is expected and hoped that our method would contribute to TLS-enabled wide-area forest qualifications, ranging from stand volume and carbon stocks modelling to derivation of tree functional traits as part of the global ecosystem understanding.

Spatial patterns of vegetation structure and structural diversity across edges between forested wetlands and upland forest in Atlantic Canada

2021 ◽  
Author(s):  
Karen Amanda Harper ◽  
Logan Gray ◽  
Natasha Dazé Querry
Keyword(s):  
Spatial Patterns ◽  
Vegetation Structure ◽  
Canopy Cover ◽  
Forested Wetlands ◽  
Structural Diversity ◽  
Shannon Index ◽  
Forested Wetland ◽  
Atlantic Canada ◽  
Wetland Protection ◽  
Upland Forest

Forested wetlands are an integral but understudied part of heterogeneous landscapes in Atlantic Canada, although they are known to provide habitat for species at risk. Our objectives were to explore patterns of forest structure across edges between forested wetland and upland forest, to locate changes in vegetation structure and to assess multivariate relationships in vegetation structure. Our study sites were in temperate (Acadian) forested wetland landscapes. We sampled trees and recorded canopy cover every 20 m along 120 m long transects. We estimated the cover of trees, saplings, shrubs in three height classes, Sphagnum, other bryophytes, lichens, graminoids, ferns and forbs in contiguous 1 x 1 m quadrats. We calculated structural diversity using the Shannon index and used wavelet analysis to assess spatial patterns. We found few clear patterns except for lower tree structural diversity at the edge of forested wetlands. Structural diversity was not a reliable measure for distinguishing forested wetland from upland forest. Forested wetlands are an integral part of many forested landscapes in Atlantic Canada but their detection and differentiation from surrounding ecosystem can be difficult. Policy should err on the side of caution when mapping forested wetlands and include them in wetland protection.

Development on Filtering Algorithms of Airborne LiDAR Point Clouds

2012 ◽  
Vol 226-228 ◽  
pp. 1892-1898
Author(s):  
Jian Qing Shi ◽  
Ting Chen Jiang ◽  
Ming Lian Jiao
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Filtering Algorithms ◽  
Filtering Algorithm ◽  
Digital Elevation ◽  
City Model ◽  
Elevation Model

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

scholarly journals AUTOMATED STRUCTURAL FOREST CHANGES USING LIDAR POINT CLOUDS AND GIS ANALYSES

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 603-608
Author(s):  
A. Novo ◽  
H. González-Jorge ◽  
J. Martínez-Sánchez ◽  
J. M. Fernández-Alonso ◽  
H. Lorenzo
Keyword(s):  
Spatial Data ◽  
Forest Structure ◽  
Laser Scanning ◽  
Structural Model ◽  
Canopy Cover ◽  
Ground Truth ◽  
Point Clouds ◽  
Forest Community ◽  
Structural Behaviour ◽  
Ground Truth Data

Abstract. Forest spatial structure describes the relationships among different species in the same forest community. Automation in the monitoring of the structural forest changes and forest mapping is one of the main utilities of applications of modern geoinformatics methods. The obtaining objective information requires the use of spatial data derived from photogrammetry and remote sensing. This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for automated mapping and detection changes in vegetation structure during a year of study. The research was conducted in an area of the Ourense Province (NWSpain). The airborne laser scanning (ALS) data, acquired in August 2019 and June of 2020, reveal detailed changes in forest structure. Based on ALS data the vegetation parameters will be analysed.To study the structural behaviour of the tree vegetation, the following parameters are used in each one of the sampling areas: (1) Relationship between the tree species present and their stratification; (2) Vegetation classification in fuel types; (3) Biomass (Gi); (4) Number of individuals per area; and (5) Canopy cover fraction (CCF). Besides, the results were compared with the ground truth data recollected in the study area.The development of a quantitative structural model based on Aerial Laser Scanning (ALS) point clouds was proposed to accurately estimate tree attributes automatically and to detect changes in forest structure. Results of statistical analysis of point cloud show the possibility to use UAV LiDAR data to characterize changes in the structure of vegetation.

scholarly journals The Highest Peaks of the Mountains: Comparing the Use of GNSS, LiDAR Point Clouds, DTMs, Databases, Maps, and Historical Sources

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5731
Author(s):  
Stanisław Szombara ◽  
Marta Róg ◽  
Krystian Kozioł ◽  
Kamil Maciuk ◽  
Bogdan Skorupa ◽  
...  
Keyword(s):  
Spatial Data ◽  
Laser Scanning ◽  
Point Clouds ◽  
Satellite System ◽  
Data Sources ◽  
Data Sets ◽  
Large Area ◽  
Historical Sources ◽  
Spatial Data Sets ◽  
Gnss Measurements

Advances in remote data acquisition techniques have contributed to the flooding of society with spatial data sets and information. Widely available spatial data sets, including digital terrain models (DTMs) from aerial laser scanning (ALS) data, are finding more and more new applications. The article analyses and compares the heights of the 14 highest peaks of the Polish Carpathians derived from different data sources. Global navigation satellite system (GNSS) geodetic measurements were used as reference. The comparison primarily involves ALS data, and selected peaks’ GNSS measurements carried out with Xiaomi Mi 8 smartphones were also compared. Recorded raw smartphone GNSS measurements were used for calculations in post-processing mode. Other data sources were, among others, global and local databases and models and topographic maps (modern and old). The article presents an in-depth comparison of Polish and Slovak point clouds for two peaks. The results indicate the possible use of large-area laser scanning in determining the maximum heights of mountain peaks and the need to use geodetic GNSS measurements for selected peaks. For the Polish peak of Rysy, the incorrect classification of point clouds causes its height to be overestimated. The conclusions presented in the article can be used in the dissemination of knowledge and to improve positioning methods.

scholarly journals CREATING IMMERSIVE AND INTERACTIVE SURVEYING LABORATORIES IN VIRTUAL REALITY: A DIFFERENTIAL LEVELING EXAMPLE

2020 ◽  
Vol V-5-2020 ◽  
pp. 9-15
Author(s):  
D. Bolkas ◽  
J. Chiampi ◽  
J. Chapman ◽  
J. Fioti ◽  
V. F. Pavill IV
Keyword(s):  
Remote Sensing ◽  
Virtual Reality ◽  
Laser Scanning ◽  
Point Clouds ◽  
Theoretical Concepts ◽  
Undergraduate Instruction ◽  
Student Comprehension ◽  
Penn State ◽  
Dense Point ◽  
Academic Plan

Abstract. Surveying engineering education includes several outdoor laboratories that complement and enhance theoretical concepts taught in class. In addition, outdoor laboratories develop student skills with instruments and surveying techniques. These laboratories are often affected by weather, leading to cancelled laboratories, which reduce the time students spend with instruments and disrupt/delay the academic plan. Furthermore, terrain characteristics are important in surveying, as each terrain and project introduce unique surveying challenges. However, training often takes places in one location, thus, limiting student comprehension and experience on how to use the same instrument and techniques in different terrain conditions. Virtual reality constantly gains ground in education, as it overcomes restrictions of physical laboratories and enhances student learning. This study discusses the development of a leveling laboratory in immersive and interactive virtual reality, as well as the challenges encountered. We have replicated a part of the Penn State Wilkes-Barre campus, where students conduct many of their physical laboratories, in virtual reality with geometric and photorealistic fidelity using remote sensing and photogrammetric methods. Dense point clouds derived from terrestrial laser scanning and small unmanned aerial surveys are used for terrain and man-made object modeling. In addition, we have developed software that simulates surveying instruments, their properties, and user/student interaction with the instrument (e.g., moving the tripod, leveling the level instrument and leveling rod, etc.). This paper demonstrates that by utilizing cutting-edge remote sensing and virtual reality technologies, we can create realistic laboratories that can supplement physical outdoor laboratories and improve/enhance undergraduate instruction of surveying students.

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