Digital Aerial Photographs Research Articles

A low-cost alternative to LiDAR for site index models: applying repeated digital aerial photogrammetry data in the modelling of forest top height growth

Abstract Environmental and forest structural information derived from remote sensing data has been found suitable for modelling forest height growth and site index and therefore forest productivity assessment, with the advances in airborne laser scanning (ALS) playing a major role in this development. While there is growing interest in the use of ALS-derived point clouds, point clouds from high-resolution digital aerial photography (DAP) are also often used for mapping and estimating forest ecosystem properties due to their lower acquisition costs. In this study, we document the applicability of bi-temporal DAP data for developing top height (TH) growth models for Scots pine stands. Our results indicate that DAP data can function as an alternative to traditional TH measurements used in growth modelling when corrected based on a limited sample of field-measured reference TH values. As the correction cannot be constant for each DAP dataset due to the different parameters during data acquisition, we propose a straightforward method for the bias correction of DAP-derived TH estimates. By undertaking iterative random sampling, we were able to find the minimum number of reference measurements needed to calculate the TH correction in order to achieve the desired accuracy of the TH estimations based on DAP. Here, we used ALS data as the reference data; however, the ALS measurements can be replaced by any other reliable source of TH values. The presented method for determining TH can be used not only for site index and forest growth modelling but also in forest inventories.

Aerial SfM–MVS Visualization of Surface Deformation along Folds during the 2024 Noto Peninsula Earthquake (Mw7.5)

This study aimed to map and analyze the spatial pattern of the surface deformation associated with the 2024 Noto Peninsula earthquake (Mw7.5) using structure-from-motion/multi-view-stereo (SfM–MVS), an advanced photogrammetric technique. The analysis was conducted using digital aerial photographs with a ground pixel dimension of 0.2 m (captured the day after the earthquake). Horizontal locations of GCPs were determined using pre-earthquake data to remove the wide-area horizontal crustal deformation component. The elevations of the GCPs were corrected by incorporating quasi-vertical values derived from a 2.5-dimensional analysis of synthetic aperture radar (SAR) results. In the synclinorium structure area, where no active fault had previously been identified, we observed a 5 km long uplift zone (0.1 to 0.2 km in width), along with multiple scarps that reached a maximum height of 2.2 m. The area and shape of the surface deformation suggested that the induced uplift and surrounding landslides were related to fold structures and their growth. Thus, our study shows the efficacy of SfM–MVS with respect to accurately mapping earthquake-induced deformations, providing crucial data for understanding seismic activity and informing disaster-response strategies.

Innovative educational and research center for monitoring forest resources of Siberia based on laser and microwave aerospace imaging

The possibilities of creating an innovative educational and scientific center for monitoring forest resources in Siberia on the basis of the Department of Space Facilities and Technologies of the Siberian State University of Science and Technology named after Mikhail Fedorovich Reshetnev are discussed, with the aim of training highly qualified engineering personnel and conducting promising scientific research in the field of monitoring, modeling, forecasting and management of forest resources. Methodological solutions and algorithms for three-dimensional modeling of forest structure and dynamics based on laser scanning data, digital aerial and space photography are proposed. These methods contribute to operational monitoring and can significantly reduce the cost of monitoring the condition and use of forest resources over the vast territory of Siberia. Remote sensing data is presented in the form of a geotransformed database and digital photo map, compatible in formats with computer-aided design systems and with the main geographic information systems – ArcView, ArcINFO, MapINFO. The innovative monitoring center will be used for operational state control and monitoring of forest management, the state of forest lands, forest management and forest inventory, solving problems of ecology and environmental management, geoecology, formation of a forest resource inventory, aerospace methods for studying natural resources and territories, information technology. Solving these problems will allow for the training of highly qualified specialists. The center's specialists plan to create information technologies for remote sensing of natural objects with the aim of import substitution of foreign software products. The main scientific directions of the created center: development and research of methods for system analysis of large-scale multidimensional remote sensing data based on nonparametric decision-making algorithms and parallel computing technologies; testing hypotheses about the distributions of large-volume remote sensing data based on nonparametric nuclear-type pattern recognition algorithms; detection of compact groups of large-volume remote sensing data corresponding to unimodal fragments of the joint probability density of multivariate random variables.

Application of the Digital Aerial Photography Method in the Construction of a Multifunctional Cargo Area

Recently, digital aerial photography has been increasingly used to obtain data on the surface of the earth and those real estate objects that are located on it. So, using the example of engineering and geodetic surveys conducted on the territory of the Makarovsky district of the Sakhalin region, we will consider what methods and what equipment are currently used to obtain information that will be necessary for construction in the future.

DBH Estimation for Individual Tree: Two-Dimensional Images or Three-Dimensional Point Clouds?

Accurate forest parameters are crucial for ecological protection, forest resource management and sustainable development. The rapid development of remote sensing can retrieve parameters such as the leaf area index, cluster index, diameter at breast height (DBH) and tree height at different scales (e.g., plots and stands). Although some LiDAR satellites such as GEDI and ICESAT-2 can measure the average tree height in a certain area, there is still a lack of effective means for obtaining individual tree parameters using high-resolution satellite data, especially DBH. The objective of this study is to explore the capability of 2D image-based features (texture and spectrum) in estimating the DBH of individual tree. Firstly, we acquired unmanned aerial vehicle (UAV) LiDAR point cloud data and UAV RGB imagery, from which digital aerial photography (DAP) point cloud data were generated using the structure-from-motion (SfM) method. Next, we performed individual tree segmentation and extracted the individual tree crown boundaries using the DAP and LiDAR point cloud data, respectively. Subsequently, the eight 2D image-based textural and spectral metrics and 3D point-cloud-based metrics (tree height and crown diameters) were extracted from the tree crown boundaries of each tree. Then, the correlation coefficients between each metric and the reference DBH were calculated. Finally, the capabilities of these metrics and different models, including multiple linear regression (MLR), random forest (RF) and support vector machine (SVM), in the DBH estimation were quantitatively evaluated and compared. The results showed that: (1) The 2D image-based textural metrics had the strongest correlation with the DBH. Among them, the highest correlation coefficient of −0.582 was observed between dissimilarity, variance and DBH. When using textural metrics alone, the estimated DBH accuracy was the highest, with a RMSE of only 0.032 and RMSE% of 16.879% using the MLR model; (2) Simply feeding multi-features, such as textural, spectral and structural metrics, into the machine learning models could not have led to optimal results in individual tree DBH estimations; on the contrary, it could even reduce the accuracy. In general, this study indicated that the 2D image-based textural metrics have great potential in individual tree DBH estimations, which could help improve the capability to efficiently and meticulously monitor and manage forests on a large scale.

Моделирование объектов трубопроводного транспорта по данным дистанционного зондирования

The author considers the results of geospatial modeling of a production facility based on data from various types of surveys obtained during monitoring. The essence is to combine it in a single coordinate space for subsequent modeling with remote methods. The technological solutions are described; they enable performing geospatial modeling of pipeline transport objects on the basis of a single coordinate space due to the data from various types of remote studies. The site of the oil refinery, where reconstruction must have been carried out, was chosen as the object of the research. The remote sensing data were obtained through ground-based laser scanning and digital aerial photography using a drone. A scheme for remote sensing, information preprocessing and geospatial modeling of pipeline transportation facilities is provided. As a methodological basis for geospatial modeling, constructive methods are used, assuming the finiteness of the elements and the use of its basic components as an information unit.

Changes in landscape structure and ecosystem services since 1850 analyzed using landscape metrics in two German municipalities

Land use has fundamentally altered landscape structure and ecosystem service provision over the last century in central Europe and worldwide. In this study, we analyzed long-term changes in landscape structures and ecosystem services in two case study areas in Germany in 1850 and 2018. First, we reconstructed land use changes using historical and current serial cadastral maps, historical documents, and digital aerial photographs. Second, we analyzed landscape structure by calculating select landscape metrics for several land-use types in both case study areas and time steps. Land use analysis for the first case study in the intensively used agricultural area of Jesewitz (Saxony) showed a significantly decreased percentage of grassland from 9.2% (in 1850) to 3.9% (in 2018) and an increase in built-up areas from 1.2% to 3.8%. For the second study area, located in the mountainous region of Ilsenburg, Harz (Saxony-Anhalt), the analysis revealed a stable forest area of 78% at both time steps. Grasslands dominated the non-forest areas and showed a significant decrease in area from 53.2% (in 1850) to 19.6% (in 2018). The settlement area increased markedly from 1.8% to 16.4%. Business and industrial areas also increased significantly from 0.9% to 10.0%. The present study shows that the risk of soil degradation caused by erosion has increased significantly since 1850. Furthermore, the risk of biodiversity loss has increased significantly owing to habitat degradation and devastation of vegetation structures. Moreover, the results showed that changes in landscape structure adversely affected the availability and quality of ecosystem services.

Ефективність застосування безпілотних літальних апаратів для підготовчого етапу оціночних робіт

The Purpose. The purpose of the study is to prove the effectiveness of the use of unmanned aerial vehicles for the preparatory stage of evaluation works. In the process of development of modern methods of remote sensing of the territory of populated areas, the problem of using unmanned aerial vehicles for real estate evaluation is gaining relevance. Aerial surveying has been an effective tool for geodetic work, geophysical research and various types of monitoring for several decades. Modern technologies for creating topographic and cadastral plans are based precisely on the use of digital aerial photography materials [Burshtynska H., Stankevich S., 2013]. However, the cost of using airplanes and helicopters for local large-scale shooting is an order of magnitude higher and therefore. an alternative solution is to use UAVs for property valuation. The Methodology. The methodology is based on the need to use UAVs to assess the market value of real estate. The creation of large-scale plans of rural settlements based on data obtained with the help of UAVs is necessary for the design of master plans [Glotov V., Korduba Yu., 2011; Glotov V., Gunina A., 2014]. And this, in turn, is connected with land accounting and setting boundaries in a certain region, as well as the need to assess the market value of real estate. Unmanned aerial vehicles are widely used for aerial photography, as they are an inexpensive alternative to traditional filming from airplanes, helicopters, hang gliders, and satellites. In addition to high economic efficiency, i.e. a tenfold decrease in price, UAVs have additional advantages compared to traditional aerial and space shooting. The Results. The conducted studies prove the importance of using UAVs in real estate evaluation. The purpose of using a UAV is to obtain images of the territory with given characteristics. It is known that aerial photography, as a type of remote sensing of the earth, is an economically and technologically justified way of collecting spatial information, the basis for creating cadastral plans and maps, three-dimensional models of the terrain and terrain [Glotov V., Tserklevych A., etc., 2014]. It is proven that the efficiency of the proposed method exceeds by 36% the traditional methods of real estate evaluation. Scientific Innovation and Practical Significance. For the first time, research was carried out related to the possibility of using UAVs to estimate the market value of real estate. The article proves that the use of unmanned aerial vehicles at the stage of collection and analysis of initial data will make it possible to reduce the cost of determining the geometric characteristics of the object of evaluation by ten times compared to traditional geodetic methods, as well as speed up the process of selecting similar objects for the purpose of building mathematical models determining the market value of the relevant real estate segment. It has been proven that unmanned aerial vehicles have significant advantages compared to traditional methods of filming, namely: the possibility of obtaining ultra-high resolution (units and tenths of a centimeter) on the terrain; the possibility of detailed filming of small objects and small areas where it is completely unprofitable or technically impossible to do it in other ways, for example, in the conditions of urban development; mobility; high efficiency; environmental cleanliness of flights; high economic efficiency (decreasing the cost of work tenfold), etc.

Individual tree segmentation and biomass estimation based on UAV Digital aerial photograph

Individual tree segmentation and biomass estimation based on UAV Digital aerial photograph

Using UAV to create digital doubles of reality and BIM

Computer technology is widely developed and implemented. Many companies use unmanned aerial vehicles (UAVs) to obtain information about buildings and facilities for construction or renovation. The following methods can be used to provide data from UAVs: laser scanning or digital aerial photography. Each of them has its own advantages. The distinctive feature of laser scanning is the high speed of data acquisition and processing, as well as the ability to work at any time, regardless of the light. Digital aerial photography, in its turn, is characterised by high productivity and inexpensive equipment. Given the development of data acquisition and processing methods, the creation of digital copies of buildings and structures has recently become widespread. Today this process has become more accessible and convenient. This article deals with the acquisition of data from unmanned aerial vehicles. A digital twin is a digital copy of an object that is used to realistically represent a physical model. It can be a digital twin of a single object or a global model of processes affecting hundreds of thousands of people. Digital twin technology and BIM-technology are related to each other, but have a number of features that distinguish them from each other. The article compares information modelling and the technology of creating a digital twin of buildings. The aim of the paper is to identify and analyse the problems that can be encountered when creating a digital twin and to find their solutions.

Multilevel integrated studies and monitoring of natural and technical objects of Kola region

The relevance of research, diagnostics and study of natural and technical objects belonging to I–II hazard classes is shown. Methodological approaches to the application of interdisciplinary methods for a complex of observations and observation of such objects are proposed: visual observations and photodocumentation, geophysical survey, hydrological measurements, geomechanics methods, satellite geodesy, digital photography using UAVs, remote sensing, hydrogeomechanical modeling. Comprehensive natural observations of various incidents on the earth's surface: underground, explosive, high-altitude and satellite. The underground level includes hydrological measurements, seismic tomography and georadar sounding. At the surface level, geodetic surveys, horizontal and vertical measurements, geodetic referencing and precise positioning of objects are performed. Various types of digital aerial photography are used for the high-altitude level. The basis of the satellite level is the processing and analysis of multispectral and radar images (ERS). The data obtained as a result of field studies are used to develop hydrogeomechanical 3D models, with the help of which scenario modeling of various hydrogeological and geomechanical conditions is performed. Such an approach to solving monitoring problems, which consists in integrating interdisciplinary studies at various levels, makes it possible to control a natural and technical object in a hierarchy: from a structure as a whole to its individual structural elements and local sections. A description is given of examples of the application of multilevel integrated research and monitoring of natural and technical objects of mining enterprises in the Kola region.

АЛГОРИТМ ФОРМУВАННЯ НАБОРУ АПРІОРНИХ ДАНИХ НЕЙРОННОЇ МЕРЕЖІ ДЛЯ ОБРОБКИ ЦИФРОВИХ АЕРОЗНІМКІВ

Analysis of the use of unmanned aerial systems in the combat zone indicates a constant increase in the requirements for intelligence data. One of the ways to increase the effectiveness of UaV application is the use of artificial intelligence methods. The basis for building a reliable neural network model is a large amount of various data, which helps to more accurately summarize information about the given task. The article considers an approach for increasing the accuracy of object image classification by convolutional neural networks based on data augmentation, which differs from existing ones in its adaptation to shooting factors and the specificity of aerial reconnaissance objects. An important and most time-consuming step in building an accurate machine learning model is finding and annotating the data that will be used to train and test the accuracy of the neural network. The accuracy and stability of the network in real conditions depends on the amount of collected data. To date, such methods of object image augmentation as geometric transformations, color correction, and spatial image filtering have been well described and analyzed. The possibilities of optimal combinations of data augmentation methods to achieve the desired generalization of poorly visible invariant features of objects remain unexplored at the moment. Taking into account the conducted research, an approach was proposed for the formation of a set of a priori data of a neural network for object recognition on digital aerial photographs, which will significantly reduce the complexity of the process of collecting the necessary data and replace it with magnification methods that are much simpler, consume less computing resources, and increase the accuracy of work convolutional neural networks, simulation of the use of the proposed approach was carried out. Keywords: unmanned aerial vehicle; convolutional neural network; data augmentation; automated processing of digital aerial photographs.

Создание растров высокой информативности по данным лазерного сканирования и аэрофотосъемки

The paper is focused on scenario and terrain modeling using the results of aerial laser scanning combined with digital aerial photography. The advantages and disadvantages of these technologies are discussed in regard to the construction of large-scale topographic maps. The generalized sequence of cameral processing aerial survey data is investigated. Based on our research, we believe that developing a combined technique of presenting Lidar survey and aerial photography materials is feasible; it could simplify and speed up the operator`s (cartographer`s) work. The novelty of the research is the formation of algorithms for creating original raster images containing more information on the terrain in each section than the orthophotoplane familiar to the interested user. The criteria for the object composition of materials are worked out taking into account the specifics of the methods under consideration, variants of information combinations are formulated for broader opportunities of analyzing and interpreting the data on the territory. Various approaches to the implementation of these ideas are shown. Examples of testing developments are given.

MODERN PROGRAMS FOR PROCESSING DATA OF GEODESIC DIMENSIONS

Modern software used for processing field geodetic surveys was studied. Every year, geodetic production faces new tasks that require a quick and correct solution. The modern level of automation of geodetic work is characterized by the widespread distribution of electronic total stations and satellite receivers, digital aerial photography complexes, field portable computers, as well as multifunctional software packages. This requires the use of new technologies and an automated information processing system, which includes the availability of a software complex for processing field measurement materials, means of automated data entry and graphical information, programs for processing graphics and automated drawing, devices for outputting graphic and textual information. The software for processing the received data of geodetic measurements should be such that the most complex tasks are performed, and at the same time it is easy to use. The development of software tools for processing geodetic measurements will help to reduce the time for camera data processing. The article evaluates the software in terms of the possibility of their practical implementation in the field of geodesy, as well as in terms of accessibility, comprehensibility and the presence of additional functions. An analysis of the functionality of the most widespread in Ukraine modern software complexes for processing the results of ground surveying, such as: CADdy, FieldWorks, Topograd, Topocad, and CREDO, designed for processing the results of geodetic measurements and designing the construction, reconstruction, repair of highways and transport interchanges, was carried out. including public roads, city streets and roads of all technical categories. Based on the analysis of the functionality of modern software complexes designed to process the results of geodetic measurements and the design, reconstruction and capital repair of highways, appropriate conclusions were formed.

ГЕОДЕЗІЯ, КАРТОГРАФІЯ І АЕРОФОТОЗНІМАННЯ

The aim of this work. This article is devoted to the study of geodynamic processes in the Tysza River basin within the Transcarpathian region with an analysis of geodetic observations obtained over the past decade. Method. Karst monitoring began with the identification of the most dangerous areas of the earth's surface that are subject to vertical displacements. After the detection of the most dangerous areas the local geodetic monitoring was carried out at facilities within the urban settlement to prevent possible accidents: Solotvyno, Dilove and Bila Tserkva. A collection of archival aerial photography was also used to develop a methodology for identifying changes in landscapes and landforms under the influence of geodynamic processes. Results. UAVs were used to remove karsts. On the basis of digital aerial photography data were created: orthophotos and digital terrain models. Digital aerial photography was carried out in accordance with the requirements of regulatory documents. To determine the dynamics of landslides and karst the digital aerial photography must be repeated several times at certain intervals. Aerial photography work was carried out in two stages in 2020 and 2021 Contour points were selected for identification marks. They are recognized on aerial photography and the terrain with an accuracy of at least 0.1 mm on the scale of the created plan. Mathematical processing of geodetic GPS measurements was performed using Trimble Geomatics Office software. After photogrammetric processing, the quality control of the obtained results was performed and digital surface models using DEM and TIN methods. Orthophotomaps on a scale of 1:1000 were made from raster images of aerial photographs, taking into account the created digital terrain model. There is a need for monitoring work to update information on the state of modern karst formations and areas with exogenous processes in Solotvyno and Bila Tserkva, Tyachiv district and the village Dilove, Rakhiv district, Transcarpathian region. The technology of topographic and geodetic works with the use of UAVs and GPS measurements in mountainous areas has been developed and tested. The results of aerial photography were used to visualize the study objects and to convey information regarding the deformation processes to local governments. For processes of natural or man-made nature (displacement, landslides, karst) requires the development of individual approaches to the use of UAVs. With the mass use of UAV images, a data bank is formed, which cannot be obtained by other methods. The study made it possible to create the method of complex determination of movements in exogenous and technogenic areas in mountainous areas with the use of the latest technologies. It allows quick establishing a plan-altitude basis of the required accuracy in the reference coordinate system in solving a number of applied geodesy problems using satellite technologies and UAVs for observations by objects.

IMPROVED METHODOLOGIES FOR THE REVISION OF A TRADITIONAL TOPOGRAPHIC MAP SERIES

Abstract. Conventional topographic maps are still important for many applications, such as land planning, but require frequent updates, which involve high costs and are not easy to accomplish. There are however many advances in Photogrammetry that are not always exploited to their full potential in a real map production environment. The traditional process involves aerial triangulation with ground control points, stereo restitution in digital photogrammetric workstations and field completion. The process is very time-consuming and expensive and map update is many times not done with the frequency required by users.This paper describes the implementation of an improved methodology for very frequent revision of the Portuguese map series of scale 1:25,000 making use of conventional digital aerial photography, which now is acquired on a regular basis for all the country. Vector features are digitised in monoscopic mode, in a GIS environment, over true orthophotos. These can be produced in a largely automated manner, using direct georeferencing data, and with minimal ground control only for vertical adjustments. Revision time and cost can be significantly reduced, keeping acceptable accuracy standards. That will satisfy the users that require the traditional high standards of the topographic map series for land panning.Additionally, for the task of field data collection of information that cannot be obtained from aerial photographs, a method is being applied to make use of video data collected in the field along roads with action cameras, with GPS. Operators can confirm or identify attributes of objects along, or near roads, such as power lines.

Creation of control network for aerial surveys in open-pit workings using UAV

To assess the condition of the instrument array at the Aksu field, the earth's surface has been monitored since 2018. The territory of the mining and technical facilities of the Aksu deposit is characterized by a varying degree of complexity of the relief and a variety of the structure of the composing rocks. At the first stage, instrumental geodetic monitoring was organized to identify active deformations on the object under study using observation profile lines located in the zone of Earth surface movements. Based on the monitoring results, an assessment of the condition of the instrument array of the deposit was carried out and decisions were made on systematic observations of the movement of the Earth's surface using digital aerial photography. A deformation monitoring program has been developed at the site under study, including a project for creating a geometric pattern of signs and a zone of possible and existing deformations has been determined. Aerial photography was carried out with the help of UAVs at intervals every half a year starting in 2020. According to the results of aerial survey, local zones of new deformations on the earth's surface were obtained, as a result of mining underground work at the Aksu mine. Monitoring continues, the next flight of aerial photography is planned for May-June 2022.

Predictive Mapping of Low-Density Juniper Stands in Prairie Landscapes of the Northern Great Plains

Expanding distributions of native juniper species have had significant ecological and economic impacts on prairie ecosystems of the Great Plains. Juniper encroachment reduces rangeland production by decreasing herbaceous biomass and affecting natural ecosystem functions as it alters other native plant communities, microclimates, and soils. Juniper distribution maps are needed to support proactive management, but they often underestimate the extent of low-density juniper stands. Our objectives were to extend a previous juniper mapping study by 1) fitting a predictive ecological model for low-density (< 15% fractional cover) juniper stands and assessing the classification accuracy, 2) determining the habitat variables that had the strongest associations with low-density juniper, and 3) applying the model to map low-density juniper stands, where proactive management has the greatest potential for stopping further juniper encroachment. The study area included counties bordering the Missouri River in southeastern South Dakota and northeastern Nebraska covering approximately 23 000 km2. Environmental predictors included seed source distance and density, as well as topography, climate, soils, and land use variables. Areas of low-density juniper were identified by visual interpretation of sample plots from digital aerial photography. We used a machine-learning approach to classify low-density juniper with the random forests algorithm. Model accuracy was high with an area under the receiver operating characteristic curve of 0.884. Variables related to seed sources were the most important predictors, and precipitation, slope angle, and the local intensity of human land use also had substantial influences. A previous map based on Landsat imagery identified 209 968 acres (84 971 ha) as juniper with in the study area, and this study found an additional 430 648 acres (174 277 ha) classified as low-density juniper stands. These results can provide agencies and land managers with more accurate information about the distribution of juniper, and the underlying techniques can be extended to map woody plant encroachment in other areas.

Расчет категорий проходимости растительности для техники по данным лазерного сканирования

Determining the categories of vegetation passability for vehicles (in forested areas) is a very popular and technically difficult task. Its complexity increases as the area of the territory increases, while duration of works and their cost should decrease. The passability of forests is influenced by elementary characteristics such as the species composition, the diameter of the trunks, the average distance between the trunks, etc. An example of such work is the construction of vegetation passability maps for vehicles by category. This task is in high demand during the construction of new facilities (pipelines, roads, railways) and the development of new deposits in the forest zone. One of the most promising methods of information support for solving this problem is airborne laser scanning and digital aerial photography. The disadvantage of this method (as well as all methods of remote sensing) is the practical impossibility of direct instrumental measurement of a number of vegetation parameters (despite 25 years of progress in the development of the lidar method), such as the diameter of the trunk, or its exact location. Increasing scan density, combined with the use of UAVs surveying at high angles to the vertical, allows these characteristics to be obtained at the cost of a significant decrease in productivity, an exponential increase in the cost of surveying and data processing, with little confidence in the obtained vegetation characteristics. This paper proposes an alternative approach based on the identification of relationships between characteristics that can be directly measured from low-density laser scanning data (crown height, coverage density, range of distribution of points of laser reflections in height relative to the ground) and vegetation passability categories measured in the field conditions. The obtained results show high reliability. A positive feature of this approach is the low cost and high productivity in determining the categories of terrain passability.

Using canopy height model derived from UAV imagery as an auxiliary for spectral data to estimate the canopy cover of mixed broadleaf forests.

Canopy cover is an important structural trait that is frequently used in forest inventories to assess sustainability as well as many other important aspects of forest stands. Remote sensing data is more effective and suitable for canopy cover estimating than traditional field measurements such as sample plots, especially at broad scales. Measurement and mapping this attribute in fine-scale is a difficult task. Aerial imagery using unmanned aerial vehicle (UAV) has been recognized as an excellent tool to estimate canopy attributes. In this study, we compared the potential of using digital hemispherical photography (DHP), digital cover photography (DCP), UAV RGB data, and canopy height model (CHM) for estimation of canopy cover of mix broad-leaved forest on seven different stands. The canopy cover was measured from two digital canopy photographic methods, including DHP (as the reference method) and DCP. The stand orthophotos were segmented using a multi-resolution image segmentation method. Afterward, the classification in two classes of the canopy cover and the non-canopy cover was conducted using minimum distance classification to estimate canopy cover. The CHM layer was generated based on the SfM algorithm and utilized in the canopy cover estimation in each stand as auxiliary data. The results showed a slight improvement when we used the CHM as auxiliary data. Overall, the results showed that the efficiency of the ground digital canopy photographic methods (zenith view) in multi-storied and dense forests is the lowest. In return, our method for digital aerial canopy photography (object-based canopy segmentation and classification) is simple, quick, efficient, and cost-effective.