Modelling of a construction pit

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.

scholarly journals Integrated Archaeological Research: Archival Resources, Surveys, Geophysical Prospection and Excavation Approach at an Execution and Burial Site: The German Nazi Labour Camp in Treblinka

Geosciences ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 336
Author(s):  
Sebastian Różycki ◽  
Rafał Zapłata ◽  
Jerzy Karczewski ◽  
Andrzej Ossowski ◽  
Jacek Tomczyk
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Archaeological Research ◽  
Burial Site ◽  
Sensing Data ◽  
Non Invasive ◽  
Geophysical Surveys ◽  
Forced Labour ◽  
Labour Camp

This article presents the results of multidisciplinary research undertaken in 2016–2019 at the German Nazi Treblinka I Forced Labour Camp. Housing 20,000 prisoners, Treblinka I was established in 1941 as a part of a network of objects such as forced labour camps, resettlement camps and prison camps that were established in the territory of occupied Poland from September 1939. This paper describes archaeological research conducted in particular on the execution site and burial site—the area where the “death pits” have been found—in the so-called Las Maliszewski (Maliszewa Forest). In this area (poorly documented) exhumation work was conducted only until 1947, so the location of these graves is only approximately known. The research was resumed at the beginning of the 21st century using, e.g., non-invasive methods and remote-sensing data. The leading aim of this article is to describe the comprehensive research strategy, with a particular stress on non-invasive geophysical surveys. The integrated archaeological research presented in this paper includes an analysis of archive materials (aerial photos, witness accounts, maps, plans, and sketches), contemporary data resources (orthophotomaps, airborne laser scanning-ALS data), field work (verification of potential objects, ground penetrating radar-GPR surveys, excavations), and the integration, analysis and interpretation of all these datasets using a GIS platform. The results of the presented study included the identification of the burial zone within the Maliszewa Forest area, including six previously unknown graves, creation of a new database, and expansion of the Historical-GIS-Treblinka. Obtained results indicate that the integration and analyses within the GIS environment of various types of remote-sensing data and geophysical measurements significantly contribute to archaeological research and increase the chances to discover previously unknown “graves” from the time when the labour camp Treblinka I functioned.

TECHNOLOGY OF INTEGRATED ASSESSMENT OF WOOD RESOURCES BY REMOTE SENSING METHODS OF THE EARTH

2021 ◽  
pp. 129-138
Author(s):  
V. K. KHLYUSTOV ◽  
◽  
S. A. YURCHUK ◽  
D. V. KHLYUSTOV ◽  
A. M. GANIKHIN
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Aerial Photography ◽  
Laser Scanning ◽  
Forest Canopy ◽  
Remote Sensing Data ◽  
Economic Sectors ◽  
Sensing Data ◽  
The Earth ◽  
Photogrammetric Method

The relevance and significance of the problem of automated forest inventory is dictated by regulatory documents defining the main directions and principles of digitalization of the country’s economic sectors, including the forest sector. The article is devoted to the problem of automated inventory of forests and digitalization of wood resources by technical means of ground-based taxation of stands, as well as remote aerial photography methods, analytical decoding of the forest canopy and determination of the complex of taxation indicators through the use of information and reference systems of multidimensional forest taxation standards. To construct an orthophotoplane and obtain a digital vegetation model, aerial photography works that meet the requirements of the photogrammetric method and the method of air-laser scanning (ALS) are described. The requirements for the parameters of aerial photography using the photogrammetric method, as well as for the parameters in the BOS, are set out. Variants of the technology of inventory of stands are proposed, indicating the appropriate tools for obtaining remote sensing data of the Earth. An assessment of the reliability of contour decoding of the species composition of stands with different spatial resolution of remote sensing data is given. The accuracy of digital vegetation models with different spatial resolution of data, the possibility of evaluating morphometric and volumetric indicators of tree crowns, as well as the resulting indicators of canopy closeness as a result of automation are indicated. An important element of the automated digitalization of wood resources is the allocation and taxation of cutting areas, the assessment of the commodity-monetary potential of stands allocated for logging.

From comprehensive field inventories to remotely sensed wall-to-wall stand attribute data - a brief history of management inventories in the Nordic countries

2020 ◽  
Author(s):  
Matti Maltamo ◽  
Petteri Packalen ◽  
Annika Kangas
Keyword(s):  
Remote Sensing ◽  
Forest Management ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Nordic Countries ◽  
Optical Remote Sensing ◽  
Mixed Stands ◽  
Forest Management Planning ◽  
Sensing Data ◽  
Visual Assessments

Forest Management Inventories (FMIs) provide critical information, usually at the stand level, for forest management planning. A typical FMI includes i) the delineation of the inventory area to stands by applying auxiliary information, ii) the classification of the stands according to categorical attributes, such as age, site fertility, main tree species, stand development, and iii) measurement, modelling and prediction of stand attributes of interest. The emergence of wall-to-wall remote-sensing data has enabled a paradigm change in FMIs from highly subjective, visual assessments to objective, model-based inferences. Previously, optical remote-sensing data were used to complement visual assessments, especially in stand delineation and height measurements. The evolution of airborne laser scanning (ALS) has made objective estimation of forest characteristics with known accuracy possible. New optical and Lidar-based sensors and platforms will allow further improvements of accuracy. However, there are still bottlenecks related to species-specific stand attribute information in mixed stands and assessments of tree quality. Here we concentrate on approaches and methods that have been applied in the Nordic countries in particular.

scholarly journals The utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland

2020 ◽  
Vol 77 (4) ◽  
Author(s):  
Ranjith Gopalakrishnan ◽  
Petteri Packalen ◽  
Veli-Pekka Ikonen ◽  
Janne Räty ◽  
Ari Venäläinen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Wind Damage ◽  
Sensing Data ◽  
Wind Speeds ◽  
Airborne Laser ◽  
Forested Areas ◽  
Risk Maps ◽  
Damage Risk

Abstract Key message The potential of airborne laser scanning (ALS) and multispectral remote sensing data to aid in generating improved wind damage risk maps over large forested areas is demonstrated. This article outlines a framework to generate such maps, primarily utilizing the horizontal structural information contained in the ALS data. Validation was done over an area in Eastern Finland that had experienced sporadic wind damage. Context Wind is the most prominent disturbance element for Finnish forests. Hence, tools are needed to generate wind damage risk maps for large forested areas, and their possible changes under planned silvicultural operations. Aims (1) How effective are ALS-based forest variables (e.g. distance to upwind forest stand edge, gap size) for identifying high wind damage risk areas? (2) Can robust estimates of predicted critical wind speeds for uprooting of trees be derived from these variables? (3) Can these critical wind speed estimates be improved using wind multipliers, which factor in topography and terrain roughness effects? Methods We first outline a framework to generate several wind damage risk–related parameters from remote sensing data (ALS + multispectral). Then, we assess if such parameters have predictive power. That is, whether they help differentiate between damaged and background points. This verification exercise used 42 wind damaged points spread over a large area. Results Parameters derived from remote sensing data are shown to have predictive power. Risk models based on critical wind speeds are not that robust, but show potential for improvement. Conclusion Overall, this work described a framework to get several wind risk–related parameters from remote sensing data. These parameters are shown to have potential in generating wind damage risk maps over large forested areas.

scholarly journals Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

2021 ◽  
Vol 13 (20) ◽  
pp. 4092
Author(s):  
Marsel Vagizov R. ◽  
Eugenie Istomin P. ◽  
Valerie Miheev L. ◽  
Artem Potapov P. ◽  
Natalya Yagotinceva V.
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Forest Inventory ◽  
Three Dimensional ◽  
Remote Sensing Data ◽  
Digital Model ◽  
Inventory Data ◽  
Forest Model ◽  
Sensing Data ◽  
Forest Inventory Data

This article discusses the process of creating a digital forest model based on remote sensing data, three-dimensional modeling, and forest inventory data. Remote sensing data of the Earth provide a fundamental tool for integrating subsequent objects into a digital forest model, enabling the creation of an accurate digital model of a selected forest quarter by using forest inventory data in educational and experimental forestry, and providing a valuable and extensive database of forest characteristics. The formalization and compilation of technologies for connecting forest inventory databases and remote sensing data with the construction of three-dimensional tree models for a dynamic display of changes in forests provide an additional source of data for obtaining new knowledge. The quality of forest resource management can be improved by obtaining the most accurate details of the current state of forests. Using machine learning and regression analysis methods as part of a digital model, it is possible to visually assess the course of planting growth, changes in species composition, and other morphological characteristics of forests. The goal of digital, interactive forest modeling is to create virtual simulations of the future status of forests using a combination of predictive forest inventory models and machine learning technology. The research findings provide a basic idea and technique for developing local digital forest models based on remote sensing and data integration technologies.

ANALYSIS OF REMOTE SENSING DATA FOR DETERMINATION OF SPATIAL CHANGES IN ORCHARDS

2020 ◽  
Author(s):  
Vita Celmina ◽  
Vivita Pukite
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Nutrient Content ◽  
Future Research ◽  
Surface Model ◽  
Tree Crown ◽  
Sensing Data ◽  
Spatial Changes

Aim of the paper is to explore the application possibilities of remote sensing data for determination of spatial changes in orchards from 1995 to 2019. In Latvia, many fruit-growing companies have been established around the turn of the century and today have established a solid production base. Although many farms achieve good yields, the average level of productivity in orchards is insufficient. Often the yields are different in the same garden in different places. Remote sensing technology provides tree crown size data. Evaluating garden data would identify sectors with lower increments. When you see specific sectors on the map, they will be surveyed by gardeners looking for factors that have influenced tree growth (soil nutrient content, moisture content, abundant fruit yield, etc.). As a result, average productivity may increase by at least 10%, but in the longer term (5-6 years) by 20-30% Using Latvian Geospatial Information Agency’s available orthophoto and digital surface model (DSM) data, were examined three land units - orchards, where the spatial changes could be observed. The spatial changes can be observed over a longer period of time, therefore there were compared several orthophoto maps, each taken in different period of time. This study is an initial analysis of the data to determine the spatial changes. Future research will further investigate orchards with aerial laser scanning to determine accurate tree crown volumes and develop digital surface models.

scholarly journals Creating a digital model of regional relief using GIS technologies to evaluate degradation processes

2021 ◽  
Vol 258 ◽  
pp. 03025
Author(s):  
Dilrabo Kadirova ◽  
Matlyuba Usmanova ◽  
Munisa Saidova ◽  
Gulnora Djalilova ◽  
Normamat Namozov
Keyword(s):  
Remote Sensing ◽  
At Risk ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Remote Sensing Data ◽  
Geographic Information ◽  
Digital Model ◽  
Sensing Data ◽  
Gis Technologies ◽  
Degradation Processes

This paper presents the results of research on the creation of a digital model of relief by processing remote sensing data using geographic information systems to identify and assess areas at risk of degradation. According to the results of the study, the relief of the region is important in the occurrence and acceleration of degradation processes.

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