scholarly journals Age structure, carbonate production and shell loss rate in an Early Miocene reef of the giant oyster <i>Crassostrea gryphoides</i>

2016 ◽  
Vol 13 (4) ◽  
pp. 1223-1235 ◽  
Author(s):  
Mathias Harzhauser ◽  
Ana Djuricic ◽  
Oleg Mandic ◽  
Thomas A. Neubauer ◽  
Martin Zuschin ◽  
...  

Abstract. We present the first analysis of population structure and cohort distribution in a fossil oyster shell bed based on 1121 shells of the giant oyster Crassostrea gryphoides (von Schlotheim, 1813). Data derive from terrestrial laser scanning of a Lower Miocene shell bed covering 459 m2. Within two transects, individual shells were manually outlined on a digital surface model and cross-checked based on high-resolution orthophotos, resulting in accurate information on center line length and area of exposed shell surface. A growth model was calculated, revealing this species as the fastest growing and largest Crassostrea known so far. Non-normal distribution of size, area and age data hints at the presence of at least four distinct recruitment cohorts. The rapid decline of frequency amplitudes with age is interpreted to be a function of mortality and shell loss. The calculated shell half-lives range around a few years, indicating that oyster reefs were geologically short-lived structures, which could have been fully degraded on a decadal scale. Crassostrea gryphoides reefs were widespread and common along the Miocene circum-Tethyan coasts. Given its enormous growth performance of  ∼  150 g carbonate per year this species has been an important carbonate producer in estuarine settings. Yet, the rapid shell loss impeded the formation of stable structures comparable to coral reefs.

2015 ◽  
Vol 12 (18) ◽  
pp. 15867-15900 ◽  
Author(s):  
M. Harzhauser ◽  
A. Djuricic ◽  
O. Mandic ◽  
T. A. Neubauer ◽  
M. Zuschin ◽  
...  

Abstract. We present the first analysis of population structure and cohort distribution in a fossil oyster reef based on more than 1121 shells of the giant oyster Crassostrea gryphoides (Schlotheim, 1813). Data derive from Terrestrial Laser Scanning of a Lower Miocene shell bed covering 459 m2. Within two transects, individual shells were manually outlined on a digital surface model and cross-checked based on high-resolution orthophotos, resulting in accurate information on center line length and area of exposed shell surface. A growth model was calculated, revealing this species as the fastest growing and largest Crassostrea known so far. Non-normal distribution of size, area and age data hints at the presence of at least four distinct recruitment cohorts. The rapid decline of frequency amplitudes with age is interpreted to be a function of mortality and shell loss. The calculated shell half-lives range around few years, indicating that oyster reefs were geologically short-lived structures, which could have been fully degraded on a decadal scale. Crassostrea gryphoides reefs were widespread and common along the Miocene circum-Tethyan coasts. Given its enormous growth performance of ~ 150 g carbonate per year this species has been an important carbonate producer in estuarine settings. Yet, the rapid shell loss impeded the formation of stable structures comparable to coral reefs.


Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 835
Author(s):  
Ville Luoma ◽  
Tuomas Yrttimaa ◽  
Ville Kankare ◽  
Ninni Saarinen ◽  
Jiri Pyörälä ◽  
...  

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.


Drones ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Geonung Park ◽  
Kyunghun Park ◽  
Bonggeun Song

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.


Author(s):  
Leena Matikainen ◽  
Juha Hyyppä ◽  
Paula Litkey

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.


Author(s):  
M. A. Altyntsev ◽  
S. A. Arbuzov ◽  
R. A. Popov ◽  
G. V. Tsoi ◽  
M. O. Gromov

A dense digital surface model is one of the products generated by using UAV aerial survey data. Today more and more specialized software are supplied with modules for generating such kind of models. The procedure for dense digital model generation can be completely or partly automated. Due to the lack of reliable criterion of accuracy estimation it is rather complicated to judge the generation validity of such models. One of such criterion can be mobile laser scanning data as a source for the detailed accuracy estimation of the dense digital surface model generation. These data may be also used to estimate the accuracy of digital orthophoto plans created by using UAV aerial survey data. The results of accuracy estimation for both kinds of products are presented in the paper.


2021 ◽  
Vol 10 (10) ◽  
pp. 665
Author(s):  
Xukai Zhang ◽  
Xuelian Meng ◽  
Chunyan Li ◽  
Nan Shang ◽  
Jiaze Wang ◽  
...  

Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation.


Author(s):  
V. Yilmaz ◽  
C. Serifoglu ◽  
O. Gungor

In Turkey, forest management plans are produced by terrestrial surveying techniques for 10 or 20 year periods, which can be considered quite long to maintain the sustainability of forests. For a successful forest management plan, it is necessary to collect accurate information about the stand parameters and store them in dynamic and robust databases. The position, number, height and closure of trees are among the most important stand parameters required for a forest management plan. Determining the position of each single tree is challenging in such an area consisting of too many interlocking trees. Hence, in this study, an object-based tree detection methodology has been developed in MATLAB programming language to determine the position of each tree top in a highly closed area. The developed algorithm uses the Canopy Height Model (CHM), which is computed from the Digital Terrain Model (DTM) and Digital Surface Model (DSM) generated by using the point cloud extracted from the images taken from a UAS (Unmanned Aerial System). The heights of trees have been determined by using the CHM. The closure of the trees has been determined with the written MATLAB script. The results show that the developed tree detection methodology detected more than 70% of the trees successfully. It can also be concluded that the stand parameters may be determined by using the UAS-based point clouds depending on the characteristics of the study area. In addition, determination of the stand parameters by using point clouds reduces the time needed to produce forest management plans.


2013 ◽  
Vol 778 ◽  
pp. 350-357 ◽  
Author(s):  
Clara Bertolini-Cestari ◽  
Filiberto Chiabrando ◽  
Stefano Invernizzi ◽  
Tanja Marzi ◽  
Antonia Spanò

Nowadays, there is an increasing demand for detailed geometrical representation of the existing cultural heritage, in particular to improve the comprehension of interactions between different phenomena and to allow a better decisional and planning process. The LiDAR technology (Light Detection and Ranging) can be adopted in different fields, ranging from aerial applications to mobile and terrestrial mapping systems. One of the main target of this study is to propose an integration of innovative and settled inquiring techniques, ranging from the reading of the technological system, to non-destructive tools for diagnosis and 3D metric modeling of buildings heritage. Many inquiring techniques, including Terrestrial Laser Scanner (TLS) method, have been exploited to study the main room of the Valentino Castle in Torino. The so-called “Salone delle Feste”, conceived in the XVIIth century under the guidance of Carlo di Castellamonte, has been selected as a test area. The beautiful frescos and stuccoes of the domical vault are sustained by a typical Delorme carpentry, whose span is among the largest of their kind. The dome suffered from degradation during the years, and a series of interventions were put into place. A survey has revealed that the suspender cables above the vault in the region close to the abutments have lost their tension. This may indicate an increase of the vault deformation; therefore a structural assessment of the dome is mandatory. The high detailed metric survey, carried out with integrated laser scanning and digital close range photogrammetry, reinforced the structural hypothesis of damages and revealed the deformation effects. In addition, the correlation between the survey-model of the intrados and of the extrados allowed a non-destructive and extensive determination of the dome thickness. The photogram-metrical survey of frescos, with the re-projection of images on vault surface model (texture mapping), is purposed to exactly localize formers restoration and their signs on frescos continuity. The present paper illustrates the generation of the 3D high-resolution model and its relations with the results of the structural survey; both of them support the Finite Element numerical simulation of the dome.


Author(s):  
Motohei Kanayama ◽  
Masataka Akashi ◽  
Masami Ohtsubo ◽  
Takahiro Higashi

2020 ◽  
Vol 50 (10) ◽  
pp. 1012-1024
Author(s):  
Meimei Wang ◽  
Jiayuan Lin

Individual tree height (ITH) is one of the most important vertical structure parameters of a forest. Field measurement and laser scanning are very expensive for large forests. In this paper, we propose a cost-effective method to acquire ITHs in a forest using the optical overlapping images captured by an unmanned aerial vehicle (UAV). The data sets, including a point cloud, a digital surface model (DSM), and a digital orthorectified map (DOM), were produced from the UAV imagery. The canopy height model (CHM) was obtained by subtracting the digital elevation model (DEM) from the DSM removed of low vegetation. Object-based image analysis was used to extract individual tree crowns (ITCs) from the DOM, and ITHs were initially extracted by overlaying ITC outlines on the CHM. As the extracted ITHs were generally slightly shorter than the measured ITHs, a linear relationship was established between them. The final ITHs of the test site were retrieved by inputting extracted ITHs into the linear regression model. As a result, the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean relative error (MRE) of the retrieved ITHs against the measured ITHs were 0.92, 1.08 m, 0.76 m, and 0.08, respectively.


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