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Journal articles on the topic 'REMOTE SENSING, FOREST INVENTORY, AIRBORNE LASER SCANNING, FOREST'

Author: Grafiati

Published: 10 March 2023

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1

Saukkola, Atte, Timo Melkas, Kirsi Riekki, et al. "Predicting Forest Inventory Attributes Using Airborne Laser Scanning, Aerial Imagery, and Harvester Data." Remote Sensing 11, no. 7 (2019): 797. http://dx.doi.org/10.3390/rs11070797.

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The aim of the study was to develop a new method to use tree stem information recorded by harvesters along operative logging in remote sensing-based prediction of forest inventory attributes in mature stands. The reference sample plots were formed from harvester data, using two different tree positions: harvester positions (XYH) in global satellite navigation system and computationally improved harvester head positions (XYHH). Study materials consisted of 158 mature Norway-spruce-dominated stands located in Southern Finland that were clear-cut during 2015–16. Tree attributes were derived from

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Cristea, Cătălina, and Andreea Florina Jocea. "Applications Of Terrestrial Laser Scanning And GIS In Forest Inventory." Journal of Applied Engineering Sciences 5, no. 2 (2015): 13–20. http://dx.doi.org/10.1515/jaes-2015-0016.

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Abstract During last years the need of knowing the forest in its various aspects, quantitative and qualitative, has enabled the appearance of a new technique forestry geomatics. Named as “the science of future” this technique integrates multiple technologies such as Remote Sensing, Airborne Photogrammetry, LIDAR, Geographic Information System (GIS), Global Positioning Systems (GPS) or classical geodetic technology for data acquisition, data processing, data analysis and data management. The purpose is to provide specific information regarding the evaluation natural forestry resources. In this

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Jurjević, Luka, Mateo Gašparović, Xinlian Liang, and Ivan Balenović. "Assessment of Close-Range Remote Sensing Methods for DTM Estimation in a Lowland Deciduous Forest." Remote Sensing 13, no. 11 (2021): 2063. http://dx.doi.org/10.3390/rs13112063.

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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, FAR

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Sačkov, Ivan. "Forest inventory based on canopy height model derived from airborne laser scanning data." Central European Forestry Journal 68, no. 4 (2022): 224–31. http://dx.doi.org/10.2478/forj-2022-0013.

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Abstract Airborne laser scanning (ALS) has emerged as a remote sensing technology capable of providing data suitable for deriving all types of elevation models. A canopy height model (CHM), which represents absolute height of objects above the ground in metres (e.g., trees), is the one most commonly used within the forest inventory. The aim of this study was to assess the accuracy of forest inventory performed for forest unit covered 17,583 ha (Slovakia, Central Europe) using the CHM derived from ALS data. This objective also included demonstrating the applicability of freely available data an

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Jamal, Juhaida, Nurul Ain Mohd Zaki, Noorfatekah Talib, et al. "Dominant Tree Species Classification using Remote Sensing Data and Object -Based Image Analysis." IOP Conference Series: Earth and Environmental Science 1019, no. 1 (2022): 012018. http://dx.doi.org/10.1088/1755-1315/1019/1/012018.

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Abstract Over the last few decades, forests have been the victims of over logging and deforestation. Uncontrolled of this activity gave an impact to the tree species to be endangered. A detailed inventory of tree species is needed to manage and plan the forest on a sustainable basis. Many techniques had been done to identify the tree species, but in the recent three decades, remote sensing technique was widely used to study the distribution of tree species. In this study, an object-based image analysis (OBIA) with a combination of high-resolution multispectral satellite imagery (WV-2) and airb

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Kotivuori, Eetu, Matti Maltamo, Lauri Korhonen, Jacob L. Strunk, and Petteri Packalen. "Prediction error aggregation behaviour for remote sensing augmented forest inventory approaches." Forestry: An International Journal of Forest Research 94, no. 4 (2021): 576–87. http://dx.doi.org/10.1093/forestry/cpab007.

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Abstract In this study we investigated the behaviour of aggregate prediction errors in a forest inventory augmented with multispectral Airborne Laser Scanning and airborne imagery. We compared an Area-Based Approach (ABA), Edge-tree corrected ABA (EABA) and Individual Tree Detection (ITD). The study used 109 large 30 × 30 m sample plots, which were divided into four 15 × 15 m subplots. Four different levels of aggregation were examined: all four subplots (quartet), two diagonal subplots (diagonal), two edge-adjacent subplots (adjacent) and subplots without aggregation. We noted that the errors

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Holopainen, M., M. Vastaranta, M. Karjalainen, et al. "FOREST INVENTORY ATTRIBUTE ESTIMATION USING AIRBORNE LASER SCANNING, AERIAL STEREO IMAGERY, RADARGRAMMETRY AND INTERFEROMETRY–FINNISH EXPERIENCES OF THE 3D TECHNIQUES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (March 11, 2015): 63–69. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-63-2015.

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Three-dimensional (3D) remote sensing has enabled detailed mapping of terrain and vegetation heights. Consequently, forest inventory attributes are estimated more and more using point clouds and normalized surface models. In practical applications, mainly airborne laser scanning (ALS) has been used in forest resource mapping. The current status is that ALS-based forest inventories are widespread, and the popularity of ALS has also raised interest toward alternative 3D techniques, including airborne and spaceborne techniques. Point clouds can be generated using photogrammetry, radargrammetry an

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Monnet, J. M., C. Ginzler, and J. C. Clivaz. "WIDE-AREA MAPPING OF FOREST WITH NATIONAL AIRBORNE LASER SCANNING AND FIELD INVENTORY DATASETS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 727–31. http://dx.doi.org/10.5194/isprs-archives-xli-b8-727-2016.

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Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean dia

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Monnet, J. M., C. Ginzler, and J. C. Clivaz. "WIDE-AREA MAPPING OF FOREST WITH NATIONAL AIRBORNE LASER SCANNING AND FIELD INVENTORY DATASETS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 727–31. http://dx.doi.org/10.5194/isprsarchives-xli-b8-727-2016.

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Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean dia

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Grafström, Anton, and Anna Hedström Ringvall. "Improving forest field inventories by using remote sensing data in novel sampling designs." Canadian Journal of Forest Research 43, no. 11 (2013): 1015–22. http://dx.doi.org/10.1139/cjfr-2013-0123.

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It is becoming more common that auxiliary information from remote sensing is available at the planning stage of a forest field inventory. Recent developments in sampling theory allows the inclusion of such information in the sampling design to obtain better samples and, hence, improve estimates of common forest attributes. We explain the methodology and evaluate the possibility of including data from airborne laser scanning in the sampling design. The novel designs that we use can select samples that are balanced on a set of auxiliary variables and (or) well spread in a set of auxiliary variab

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Ørka, Hans Ole, Marie-Claude Jutras-Perreault, Jaime Candelas-Bielza, and Terje Gobakken. "Delineation of Geomorphological Woodland Key Habitats Using Airborne Laser Scanning." Remote Sensing 14, no. 5 (2022): 1184. http://dx.doi.org/10.3390/rs14051184.

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Forest ecosystems provide a range of services and function as habitats for many species. The concept of woodland key habitats (WKH) is important for biodiversity management in forest planning standards and certification schemes. The main idea of the WKH is to preserve biodiversity hotspots in the forest landscape. Current methods used in delineating WKH rely on costly field inventories. Furthermore, it is well known that the surveyor introduces an error because of the subjective assessment. Remote sensing may reduce this error in a cost-efficient way. The current study develops automated metho

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White, Joanne C., Hao Chen, Murray E. Woods, Brian Low, and Sasha Nasonova. "The Petawawa Research Forest: Establishment of a remote sensing supersite." Forestry Chronicle 95, no. 03 (2019): 149–56. http://dx.doi.org/10.5558/tfc2019-024.

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The pace of technological change in forest inventory and monitoring over the past 50 years has been remarkable, largely asa result of the increased availability of various forms of remotely sensed data. Benchmarking sites, with the requisite refer-ence and baseline data for evaluating the capacities of new technologies, algorithms, and approaches, can be extremely valu-able for sparking innovation, as well as for enabling transparent and scientifically sound assessments of technologies, newdata streams, and associated information outcomes. Herein we describe the establishment of a remote sensi

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Gao, Linghan, and Xiaoli Zhang. "Above-Ground Biomass Estimation of Plantation with Complex Forest Stand Structure Using Multiple Features from Airborne Laser Scanning Point Cloud Data." Forests 12, no. 12 (2021): 1713. http://dx.doi.org/10.3390/f12121713.

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Accurate forest above-ground biomass (AGB) estimation is important for dynamic monitoring of forest resources and evaluation of forest carbon sequestration capacity. However, it is difficult to depict the forest’s vertical structure and its heterogeneity using optical remote sensing when estimating forest AGB, for the reason that electromagnetic waves cannot penetrate the canopy’s surface to obtain low vegetation information, especially in subtropical and tropical forests with complex layer structure and tree species composition. As an active remote sensing technology, an airborne laser scanne

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Michałowska, Maja, and Jacek Rapiński. "A Review of Tree Species Classification Based on Airborne LiDAR Data and Applied Classifiers." Remote Sensing 13, no. 3 (2021): 353. http://dx.doi.org/10.3390/rs13030353.

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Remote sensing techniques, developed over the past four decades, have enabled large-scale forest inventory. Light Detection and Ranging (LiDAR), as an active remote sensing technology, allows for the acquisition of three-dimensional point clouds of scanned areas, as well as a range of features allowing for increased performance of object extraction and classification approaches. As many publications have shown, multiple LiDAR-derived metrics, with the assistance of classification algorithms, contribute to the high accuracy of tree species discrimination based on data obtained by laser scanning

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Torres, Fernanda Magri, and Antonio Maria Garcia Tommaselli. "A LIGHTWEIGHT UAV-BASED LASER SCANNING SYSTEM FOR FOREST APPLICATION." Boletim de Ciências Geodésicas 24, no. 3 (2018): 318–34. http://dx.doi.org/10.1590/s1982-21702018000300021.

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Abstract Lightweight Unmanned Aerial Vehicles (UAVs) have become a cost effective alternative for studies which use aerial Remote Sensing with high temporal frequency requirements for small areas. Laser scanner devices are widely used for rapid tridimensional data acquisition, mainly as a complementary data source to photogrammetric surveying. Recent studies using laser scanner systems onboard UAVs for forestry inventory and mapping applications have presented encouraging results. This work describes the development and accuracy assessment of a low cost mapping platform composed by an Ibeo Lux

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Lang, Mait, Allan Sims, Kalev Pärna, et al. "Remote-sensing support for the Estonian National Forest Inventory, facilitating the construction of maps for forest height, standing-wood volume, and tree species composition." Forestry Studies 73, no. 1 (2020): 77–97. http://dx.doi.org/10.2478/fsmu-2020-0016.

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Abstract Since 1999, Estonia has conducted the National Forest Inventory (NFI) on the basis of sample plots. This paper presents a new module, incorporating remote-sensing feature variables from airborne laser scanning (ALS) and from multispectral satellite images, for the construction of maps of forest height, standing-wood volume, and tree species composition for the entire country. The models for sparse ALS point clouds yield coefficients of determination of 89.5–94.8% for stand height and 84.2–91.7% for wood volume. For the tree species prediction, the models yield Cohen's kappa values (ta

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Novo-Fernández, Alís, Marcos Barrio-Anta, Carmen Recondo, Asunción Cámara-Obregón, and Carlos A. López-Sánchez. "Integration of National Forest Inventory and Nationwide Airborne Laser Scanning Data to Improve Forest Yield Predictions in North-Western Spain." Remote Sensing 11, no. 14 (2019): 1693. http://dx.doi.org/10.3390/rs11141693.

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The prediction of growing stock volume is one of the commonest applications of remote sensing to support the sustainable management of forest ecosystems. In this study, we used data from the 4th Spanish National Forest Inventory (SNFI-4) and from the 1st nationwide Airborne Laser Scanning (ALS) survey to develop predictive yield models for the three major commercial tree forest species (Eucalyptus globulus, Pinus pinaster and Pinus radiata) grown in north-western Spain. Integration of both types of data required prior harmonization because of differences in timing of data acquisition and diffi

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Gopalakrishnan, Ranjith, Jobriath Kauffman, Matthew Fagan, et al. "Creating Landscape-Scale Site Index Maps for the Southeastern US Is Possible with Airborne LiDAR and Landsat Imagery." Forests 10, no. 3 (2019): 234. http://dx.doi.org/10.3390/f10030234.

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Sustainable forest management is hugely dependent on high-quality estimates of forest site productivity, but it is challenging to generate productivity maps over large areas. We present a method for generating site index (a measure of such forest productivity) maps for plantation loblolly pine (Pinus taeda L.) forests over large areas in the southeastern United States by combining airborne laser scanning (ALS) data from disparate acquisitions and Landsat-based estimates of forest age. For predicting canopy heights, a linear regression model was developed using ALS data and field measurements f

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Imangholiloo, Mohammad, Ninni Saarinen, Markus Holopainen, Xiaowei Yu, Juha Hyyppä, and Mikko Vastaranta. "Using Leaf-Off and Leaf-On Multispectral Airborne Laser Scanning Data to Characterize Seedling Stands." Remote Sensing 12, no. 20 (2020): 3328. http://dx.doi.org/10.3390/rs12203328.

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Information from seedling stands in time and space is essential for sustainable forest management. To fulfil these informational needs with limited resources, remote sensing is seen as an intriguing alternative for forest inventorying. The structure and tree species composition in seedling stands have created challenges for capturing this information using sensors providing sparse point densities that do not have the ability to penetrate canopy gaps or provide spectral information. Therefore, multispectral airborne laser scanning (mALS) systems providing dense point clouds coupled with multisp

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Heinzel, Johannes, and Christian Ginzler. "A Single-Tree Processing Framework Using Terrestrial Laser Scanning Data for Detecting Forest Regeneration." Remote Sensing 11, no. 1 (2018): 60. http://dx.doi.org/10.3390/rs11010060.

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Direct assessment of forest regeneration from remote sensing data is a previously little-explored problem. This is due to several factors which complicate object detection of small trees in the understory. Most existing studies are based on airborne laser scanning (ALS) data, which often has insufficient point densities in the understory forest layers. The present study uses plot-based terrestrial laser scanning (TLS) and the survey design was similar to traditional forest inventory practices. Furthermore, a framework of methods was developed to solve the difficulties of detecting understory t

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Knoke, Thomas, Mengistie Kindu, Thomas Schneider, and Terje Gobakken. "Inventory of Forest Attributes to Support the Integration of Non-provisioning Ecosystem Services and Biodiversity into Forest Planning—from Collecting Data to Providing Information." Current Forestry Reports 7, no. 1 (2021): 38–58. http://dx.doi.org/10.1007/s40725-021-00138-7.

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Abstract Purpose of Review Our review provides an overview of forest attributes measurable by forest inventory that may support the integration of non-provisioning ecosystem services (ES) and biodiversity into forest planning. The review identifies appropriate forest attributes to quantify the opportunity for recreation, biodiversity promotion and carbon storage, and describes new criteria that future forest inventories may include. As a source of information, we analyse recent papers on forest inventory and ES to show if and how they address these criteria. We further discuss how mapping ES c

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Guerra-Hernández, Cosenza, Cardil, et al. "Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data." Forests 10, no. 10 (2019): 905. http://dx.doi.org/10.3390/f10100905.

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Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogr

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Stereńczak, Krzysztof, Rafał Zapłata, Jarosław Wójcik, et al. "ALS-Based Detection of Past Human Activities in the Białowieża Forest—New Evidence of Unknown Remains of Past Agricultural Systems." Remote Sensing 12, no. 16 (2020): 2657. http://dx.doi.org/10.3390/rs12162657.

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The Białowieża Forest (BF), a unique ecosystem of historical significance in central Europe, has a long history of assumed human settlement, with at least 200 known archaeological sites (until 2016). This study uncovers new evidence of the cultural heritage of this unique forest area using Airborne Laser Scanning (ALS) technology combined with traditional archaeological field assessment methods to verify the ALS data interpretations and to provide additional evidence about the function and origin of the newly detected archaeological sites. The results of this study include (1) a scientific app

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Usoltsev, Vladimir А., Ivan S. Tsepordey, and Igor M. Danilin. "Designing a Model of the Picea L. and Abies L. Biomass for Regional Climatic Conditions in Eurasia." Lesnoy Zhurnal (Forestry Journal), no. 6 (December 10, 2022): 38–54. http://dx.doi.org/10.37482/0536-1036-2022-6-38-54.

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Forest ecosystems play a major role in climate stabilization, and continuous monitoring of their biomass is of paramount importance. Airborne laser scanning technology has become widespread in assessing tree biomass by remote sensing of such inventory indices of trees and stands as crown width and projection area, tree and stand height. The work uses the author’s observation database of 1550 model trees of spruce (Picea L.) and 535 model trees of fir (Abies L.) growing in Eurasia. The database provides information on tree height, crown width and length, as well as biomass of trunk, foliage, br

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Krok, Grzegorz, Bartłomiej Kraszewski, and Krzysztof Stereńczak. "Application of terrestrial laser scanning in forest inventory – an overview of selected issues." Forest Research Papers 81, no. 4 (2020): 175–94. http://dx.doi.org/10.2478/frp-2020-0021.

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AbstractPrecise determination of forest resources is one of the most important tasks in conducting sustainable forest management. Accurate information about the forest’s resources allows for a better planning of current and future management as well as conservation activities. Such precise information is needed by both, individual forest managers and for developing the national forest policy. In recent years, interest in the use of remote sensing in forest inventory has significantly increased. Remote sensing allows for non-invasive measurements and the automation of data processing. The most

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Wulder, Michael A., Christopher W. Bater, Nicholas C. Coops, Thomas Hilker, and Joanne C. White. "The role of LiDAR in sustainable forest management." Forestry Chronicle 84, no. 6 (2008): 807–26. http://dx.doi.org/10.5558/tfc84807-6.

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Forest characterization with light detection and ranging (LiDAR) data has recently garnered much scientific and operational attention. The number of forest inventory attributes that may be directly measured with LiDAR is limited; however, when considered within the context of all the measured and derived attributes required to complete a forest inventory, LiDAR can be a valuable tool in the inventory process. In this paper, we present the status of LiDAR remote sensing of forests, including issues related to instrumentation, data collection, data processing, costs, and attribute estimation. Th

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Xu, Dandan, Haobin Wang, Weixin Xu, Zhaoqing Luan, and Xia Xu. "LiDAR Applications to Estimate Forest Biomass at Individual Tree Scale: Opportunities, Challenges and Future Perspectives." Forests 12, no. 5 (2021): 550. http://dx.doi.org/10.3390/f12050550.

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Accurate forest biomass estimation at the individual tree scale is the foundation of timber industry and forest management. It plays an important role in explaining ecological issues and small-scale processes. Remotely sensed images, across a range of spatial and temporal resolutions, with their advantages of non-destructive monitoring, are widely applied in forest biomass monitoring at global, ecoregion or community scales. However, the development of remote sensing applications for forest biomass at the individual tree scale has been relatively slow due to the constraints of spatial resoluti

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Persson, Henrik Jan, and Göran Ståhl. "Characterizing Uncertainty in Forest Remote Sensing Studies." Remote Sensing 12, no. 3 (2020): 505. http://dx.doi.org/10.3390/rs12030505.

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This discussion paper addresses (1) the challenge of concisely reporting uncertainties in forest remote sensing (RS) studies, primarily conducted at plot and stand level, and (2) the influence of reference data errors and how corrections for such errors can be made. Different common ways of reporting uncertainties are discussed, and a parametric error model is proposed as a core part of a comprehensive approach for reporting uncertainties (compared to, e.g., conventional reporting of root mean square error (RMSE)). The importance of handling reference data errors is currently increasing since

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Cameron, H. A., D. Schroeder, and J. L. Beverly. "Predicting black spruce fuel characteristics with Airborne Laser Scanning (ALS)." International Journal of Wildland Fire 31, no. 2 (2021): 124–35. http://dx.doi.org/10.1071/wf21004.

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Wildfire decision support systems combine fuel maps with other fire environment variables to predict fire behaviour and guide management actions. Until recently, financial and technological constraints have limited provincial fuel maps to relatively coarse spatial resolutions. Airborne Laser Scanning (ALS), a remote sensing technology that uses LiDAR (Light Detection and Ranging), is becoming an increasingly affordable and pragmatic tool for mapping fuels across localised and broad areas. Few studies have used ALS in boreal forest regions to describe structural attributes such as fuel load at

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Essery, Richard, Peter Bunting, Aled Rowlands, et al. "Radiative Transfer Modeling of a Coniferous Canopy Characterized by Airborne Remote Sensing." Journal of Hydrometeorology 9, no. 2 (2008): 228–41. http://dx.doi.org/10.1175/2007jhm870.1.

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Abstract Solar radiation beneath a forest canopy can have large spatial variations, but this is frequently neglected in radiative transfer models for large-scale applications. To explicitly model spatial variations in subcanopy radiation, maps of canopy structure are required. Aerial photography and airborne laser scanning are used to map tree locations, heights, and crown diameters for a lodgepole pine forest in Colorado as inputs to a spatially explicit radiative transfer model. Statistics of subcanopy radiation simulated by the model are compared with measurements from radiometer arrays, an

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Hu, Yang, Fayun Wu, Zhongqiu Sun, et al. "The Laser Vegetation Detecting Sensor: A Full Waveform, Large-Footprint, Airborne Laser Altimeter for Monitoring Forest Resources." Sensors 19, no. 7 (2019): 1699. http://dx.doi.org/10.3390/s19071699.

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The use of satellite-borne large-footprint LiDAR (light detection and ranging) systems allows for the acquisition of forest monitoring data. This paper mainly describes the design, use, operating principles, installation and data properties of the new Laser Vegetation Detecting Sensor (LVDS), a LiDAR system designed and developed at the Academy of Forest Inventory and Planning (AFIP) and the Beijing Institute of Telemetry (BIT). Data from LVDS were used to calculate the mean height of forest trees on sample plots using data collected in the Hunan province of China. The results show that the fu

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Lefsky, M. A., W. B. Cohen, and T. A. Spies. "An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon." Canadian Journal of Forest Research 31, no. 1 (2001): 78–87. http://dx.doi.org/10.1139/x00-142.

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This research evaluates the utility of several remote sensing data types for the purpose of mapping forest structure and related attributes at a regional scale. Several sensors were evaluated, including (i) single date Landsat Thematic Mapper (TM); (ii) multitemporal Landsat TM; (iii) Airborne Data Acquisition and Registration (ADAR), a sensor with high spatial resolution; (iv) Airborne Visible-Infrared Imaging Spectrometer (AVIRIS), a sensor with high spectral resolution; and (v) Scanning Lidar Imager Of Canopies By Echo Recovery (SLICER), a lidar sensor that directly measures the height and

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Steinmann, Katharina, Christian Ginzler, and Adrian Lanz. "Kombination von Landesforstinventar- und Fernerkundungsdaten für Kleingebietsschätzungen." Schweizerische Zeitschrift fur Forstwesen 162, no. 9 (2011): 290–99. http://dx.doi.org/10.3188/szf.2011.0290.

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Combining data from the Swiss National Forest Inventory and from remote sensing for small-area estimations in forestry A design-unbiased small estimator was tested in this study. This estimator combines terrestrial data from the Swiss National Forest Inventory (LFI) with ancillary data from stereo aerial images and airborne laser scanner (ALS) data. The estimator was tested for the two target variables: the percentage of forest and the timber volume. The efficiency of the estimator depends on the model precision of the target variable obtained with remote sensing data and other ancillary spati

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Packalén, Petteri, and Matti Maltamo. "Estimation of species-specific diameter distributions using airborne laser scanning and aerial photographs." Canadian Journal of Forest Research 38, no. 7 (2008): 1750–60. http://dx.doi.org/10.1139/x08-037.

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The use of diameter distributions originates from a need for tree-level description of forest stands, which is required, for example, in growth simulators and bucking. Diameter distribution models are usually applied, since measuring empirical diameter distributions in practical forest inventories is too laborious. This study investigated the ability of remote sensing information to predict species-specific diameter distributions. The study was carried out in Finland in a typical managed boreal forest area. The tree species considered were Scots pine ( Pinus sylvestris L.), Norway spruce ( Pic

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Стариков, Aleksandr Starikov, Батурин, and Kirill Baturin. "The use of laser scanning technology of accounting for wood." Forestry Engineering Journal 5, no. 4 (2015): 114–22. http://dx.doi.org/10.12737/17409.

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Now for the decision of tasks of monitoring and evaluation of forest plantations the use of methods and means of laser scanning is one of the most act-sexual and priorities. Laser scanning can be performed independently, or in combination with digital aerial and space photos and video, and can also be carried out ground research on the sample areas. A number of indicators laser scanning is superior to other, currently known, remote evaluation methods qualitative and quantitative characteristics of the forest Fund Laser scanning of forest cover based on the use of modern tech-nologies of digita

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Chi, Dengkai, Jeroen Degerickx, Kang Yu, and Ben Somers. "Urban Tree Health Classification Across Tree Species by Combining Airborne Laser Scanning and Imaging Spectroscopy." Remote Sensing 12, no. 15 (2020): 2435. http://dx.doi.org/10.3390/rs12152435.

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Declining urban tree health can affect critical ecosystem services, such as air quality improvement, temperature moderation, carbon storage, and biodiversity conservation. The application of state-of-the-art remote sensing data to characterize tree health has been widely examined in forest ecosystems. However, such application to urban trees has not yet been fully explored—due to the presence of heterogeneous tree species and backgrounds, severely complicating the classification of tree health using remote sensing information. In this study, tree health was represented by a set of field-assess

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Woods, M., K. Lim, and P. Treitz. "Predicting forest stand variables from LiDAR data in the Great Lakes St. Lawrence forest of Ontario." Forestry Chronicle 84, no. 6 (2008): 827–39. http://dx.doi.org/10.5558/tfc84827-6.

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Models were developed to predict forest stand variables for common species of the Great Lakes – St. Lawrence forest of central Ontario, Canada from light detection and ranging (LiDAR) data. Stands that had undergone various ranges of partial harvesting or initial spacing treatments from multiple geographic sites were considered. A broad forest stratification was adopted and consisted of: (i) natural hardwoods; (ii) natural conifers; and (iii) plantation conifers. Stand top height (R2 = 0.96, 0.98, and 0.98); average height (R2 = 0.86, 0.76, and 0.98); basal area (R2 = 0.80, 0.80, and 0.85); vo

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Varhola, A., G. W. Frazer, P. Teti, and N. C. Coops. "Estimation of forest structure metrics relevant to hydrologic modelling using coordinate transformation of airborne laser scanning data." Hydrology and Earth System Sciences 16, no. 10 (2012): 3749–66. http://dx.doi.org/10.5194/hess-16-3749-2012.

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Abstract. An accurate characterisation of the complex and heterogeneous forest architecture is necessary to parameterise physically-based hydrologic models that simulate precipitation interception, energy fluxes and water dynamics. While hemispherical photography has become a popular method to obtain a number of forest canopy structure metrics relevant to these processes, image acquisition is field-intensive and, therefore, difficult to apply across the landscape. In contrast, airborne laser scanning (ALS) is a remote-sensing technique increasingly used to acquire detailed information on the s

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Varhola, A., G. W. Frazer, P. Teti, and N. C. Coops. "Estimation of forest structure metrics relevant to hydrologic modeling using coordinate transformation of airborne laser scanning data." Hydrology and Earth System Sciences Discussions 9, no. 4 (2012): 5531–73. http://dx.doi.org/10.5194/hessd-9-5531-2012.

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Abstract. Accurate characterizations of the complex and heterogeneous forest architecture are necessary to parameterize physically-based hydrologic models that simulate precipitation interception, energy fluxes and water dynamics. While hemispherical photography has become a popular method to obtain a number of forest canopy structure metrics relevant to these processes, image acquisition is field-intensive and therefore difficult to apply across the landscape. In contrast, airborne laser scanning (ALS) is a remote sensing technique increasingly used to acquire detailed information on the spat

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Orumaa, Argo, Priit Vellak, Mait Lang, Marek Metslaid, Riho Kägo, and Mart Noorma. "How Can Remote Sensing Reduce Required Human Intervention in Robotic Forest Regeneration." Forests 12, no. 12 (2021): 1802. http://dx.doi.org/10.3390/f12121802.

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In this article, we introduce an alternative solution for forest regeneration based on unmanned ground vehicles (UGV) and describe requirements for external data, which could significantly increase the level of automation. Over the past few decades, the global forested area has decreased, and there is a great need to restore and regenerate forests. Challenges such as the lack of labor and high costs demand innovative approaches for forest regeneration. Mechanization has shown satisfactory results in terms of time-efficient planting, although its usage is limited by high operational costs. Inno

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KHLYUSTOV, V. K., S. A. YURCHUK, D. V. KHLYUSTOV, and A. M. GANIKHIN. "TECHNOLOGY OF INTEGRATED ASSESSMENT OF WOOD RESOURCES BY REMOTE SENSING METHODS OF THE EARTH." Prirodoobustrojstvo, no. 4 (2021): 129–38. http://dx.doi.org/10.26897/1997-6011-2021-4-129-138.

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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

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Girardin, Patricia, Osvaldo Valeria, and François Girard. "Measuring Spatial and Temporal Gravelled Forest Road Degradation in the Boreal Forest." Remote Sensing 14, no. 3 (2022): 457. http://dx.doi.org/10.3390/rs14030457.

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Degradation of forest roads in Canada has strong negative effects on access to forestlands, together with economic (e.g., increased maintenance costs), environmental (e.g., erosion of materials and subsequent habitat contamination), and social (e.g., use risks) impacts. Maintaining sustainable and safe access to forestland requires a better understanding and knowledge of forest road degradation over time and space. Our study aimed to identify relevant spatiotemporal variables regarding the state of eastern Canadian forest road networks by (1) building predictive models of gravel forest road de

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Orwig, D. A., P. Boucher, I. Paynter, E. Saenz, Z. Li, and C. Schaaf. "The potential to characterize ecological data with terrestrial laser scanning in Harvard Forest, MA." Interface Focus 8, no. 2 (2018): 20170044. http://dx.doi.org/10.1098/rsfs.2017.0044.

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Contemporary terrestrial laser scanning (TLS) is being used widely in forest ecology applications to examine ecosystem properties at increasing spatial and temporal scales. Harvard Forest (HF) in Petersham, MA, USA, is a long-term ecological research (LTER) site, a National Ecological Observatory Network (NEON) location and contains a 35 ha plot which is part of Smithsonian Institution's Forest Global Earth Observatory (ForestGEO). The combination of long-term field plots, eddy flux towers and the detailed past historical records has made HF very appealing for a variety of remote sensing studi

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Hao, Yuanshuo, Faris Rafi Almay Widagdo, Xin Liu, Ying Quan, Lihu Dong, and Fengri Li. "Individual Tree Diameter Estimation in Small-Scale Forest Inventory Using UAV Laser Scanning." Remote Sensing 13, no. 1 (2020): 24. http://dx.doi.org/10.3390/rs13010024.

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Unmanned aerial vehicle laser scanning (UAVLS) systems present a relatively new means of remote sensing and are increasingly applied in the field of forest ecology and management. However, one of the most essential parameters in forest inventory, tree diameter at breast height (DBH), cannot be directly extracted from aerial point cloud data due to the limitations of scanning angle and canopy obstruction. Therefore, in this study DBH-UAVLS point cloud estimation models were established using a generalized nonlinear mixed-effects (NLME) model. The experiments were conducted using Larix olgensis

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Tóth, Sándor F. "The 17th Symposium on Systems Analysis in Forest Resources: An Introduction and Synthesis." Forest Science 66, no. 4 (2020): 424–27. http://dx.doi.org/10.1093/forsci/fxaa010.

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Abstract The 17th Symposium on Systems Analysis in Forest Resources was held in Suquamish, Washington, United States on August 27–30, 2017. The goal of this international meeting was to bring together operations researchers, remote sensing scientists, and the government to facilitate the exchange and implementation of systems science in forestry and conservation. The essay that follows is a summary of the outcome of the Symposium, as well as an introduction to the eight research articles that were selected for publication in this Special Issue. Each of the papers was presented at the Symposium

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Homolová, Lucie, Růžena Janoutová, Petr Lukeš, et al. "In situ data supporting remote sensing estimation of spruce forest parameters at the ecosystem station Bílý Kříž." Beskydy 10, no. 1-2 (2017): 75–86. http://dx.doi.org/10.11118/beskyd201710010075.

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Remote sensing offers an effective way of mapping vegetation parameters in a spatially continuous manner, at larger spatial scales and repeatedly in time compared to traditional in situ mapping approaches that are typically accurate, but limited to a few distributed location and few repetitions. In case of forest ecosystems, remote sensing allow to assess quantitative parameters or indicators related to forest health status such as leaf area index, leaf pigment content, chlorophyll fluorescence, etc. Development, calibration and validation of remote sensing-based methods, however, still rely o

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Jucker, Tommaso, Gregory P. Asner, Michele Dalponte, et al. "Estimating aboveground carbon density and its uncertainty in Borneo's structurally complex tropical forests using airborne laser scanning." Biogeosciences 15, no. 12 (2018): 3811–30. http://dx.doi.org/10.5194/bg-15-3811-2018.

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Abstract. Borneo contains some of the world's most biodiverse and carbon-dense tropical forest, but this 750 000 km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognizing the ecosystem services they provide, including their ability to store and sequester carbon. Airborne laser scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into statewide assessments of f

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Szporak-Wasilewska, Sylwia, Hubert Piórkowski, Wojciech Ciężkowski, Filip Jarzombkowski, Łukasz Sławik, and Dominik Kopeć. "Mapping Alkaline Fens, Transition Mires and Quaking Bogs Using Airborne Hyperspectral and Laser Scanning Data." Remote Sensing 13, no. 8 (2021): 1504. http://dx.doi.org/10.3390/rs13081504.

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The aim of this study is to evaluate the effectiveness of the identification of Natura 2000 wetland habitats (Alkaline fens—code 7230, and Transition mires and quaking bogs—code 7140) depending on various remotely sensed (RS) data acquired from an airborne platform. Both remote sensing data and botanical reference data were gathered for mentioned habitats in the Lower (LB) and Upper Biebrza (UB) River Valley and the Janowskie Forest (JF) in different seasonal stages. Several different classification scenarios were tested, and the ones that gave the best results for analyzed habitats were indic

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Dobre, Alexandru Claudiu, Ionuț-Silviu Pascu, Ștefan Leca, et al. "Applications of TLS and ALS in Evaluating Forest Ecosystem Services: A Southern Carpathians Case Study." Forests 12, no. 9 (2021): 1269. http://dx.doi.org/10.3390/f12091269.

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Forests play an important role in biodiversity conservation, being one of the main providers of ecosystem services, according to the Economics of Ecosystems and Biodiversity. The functions and ecosystem services provided by forests are various concerning the natural capital and the socio-economic systems. Past decades of remote-sensing advances make it possible to address a large set of variables, including both biophysical parameters and ecological indicators, that characterize forest ecosystems and their capacity to supply services. This research aims to identify and implement existing metho

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Muumbe, Tasiyiwa Priscilla, Jussi Baade, Jenia Singh, Christiane Schmullius, and Christian Thau. "Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas." Remote Sensing 13, no. 3 (2021): 507. http://dx.doi.org/10.3390/rs13030507.

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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 s

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