Relevant bibliographies by topics / Aerial sample plot

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers
  4. Reports

Academic literature on the topic 'Aerial sample plot'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Aerial sample plot"

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Hoxha, Besim. "Two-phased inventory of standing volume in mountain forests with the use of aerial photographs." Folia Forestalia, Series A - Forestry 54(2) (July 1, 2012): 123–33. https://doi.org/10.5281/zenodo.30736.

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This study aimed to elaborate and develop the existing methods used in inventorying lowland forest and adapt them for mountainous forests. The inventory of mountain forests with the use of CIR aerial photographs in this study relied on the implementation of the 3D (three-dimensional) methods and it was characterised by two phases. In the 1st p hase the auxiliary variables (e.g. crown cover, height of dominant trees, density) were measured on the aerial photographs (355 circular plots). Variable of interest (standing volume) was recorded during the terrestrial survey on the corresponding ground
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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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Tuominen, Sakari, Stuart Fish, and Simo Poso. "Combining remote sensing, data from earlier inventories, and geostatistical interpolation in multisource forest inventory." Canadian Journal of Forest Research 33, no. 4 (2003): 624–34. http://dx.doi.org/10.1139/x02-199.

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Multisource forest inventory with two-phase sampling offers several advantages in the forest management planning when compared with the traditional visual inventory by stands. For example, by combining data from remote sensing imagery with field measurements, it is possible to estimate the forest characteristics of large areas at a more reasonable cost than by using the traditional visual inventory by stands. In this study, the k-nearest-neighbours estimation (k-nn), stand inventory data, and geostatistical interpolation were combined for estimation of five forest variables (mean diameter, mea
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Leboeuf, Antoine, Martin Riopel, Dave Munger, Marie-Soleil Fradette, and Jean Bégin. "Modeling Merchantable Wood Volume Using Airborne LiDAR Metrics and Historical Forest Inventory Plots at a Provincial Scale." Forests 13, no. 7 (2022): 985. http://dx.doi.org/10.3390/f13070985.

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So far, large-scale projects aiming to map forest attributes using aerial LiDAR data have been developed using ground sample plots acquired synchronously with LiDAR. No large projects have been developed using aerial LiDAR acquired independent of ground sample plot datasets. The goal of this study was to develop and validate large-scale parametric merchantable wood volume estimation models using existing historical ground sample plots. The models can be applied to large LiDAR datasets to map merchantable wood volume as a 10 × 10 m raster. The study demonstrated that a relative density index (R
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Packalé n, Petteri, and Matti Maltamo. "Predicting the Plot Volume by Tree Species Using Airborne Laser Scanning and Aerial Photographs." Forest Science 52, no. 6 (2006): 611–22. http://dx.doi.org/10.1093/forestscience/52.6.611.

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Abstract Several studies have indicated that forest characteristics can be accurately predicted using airborne laser scanner (ALS) data, but there are very few studies in which species-specific forest characteristics have been estimated. This article compares two approaches for determining species-specific volumes at plot level by combining ALS data with aerial photographs. The first approach consists of two stages: (1) prediction of total volume using ALS data, and (2) assignment of this total volume to tree species by fuzzy classification and aerial photographs, in which three fuzzy classifi
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Pfannenstiel, R. S., R. L. Meagher, and R. R. Saldana. "Aerial Insecticide Evaluation Against Mexican Rice Borer on Sugarcane, 1989." Insecticide and Acaricide Tests 15, no. 1 (1990): 291. http://dx.doi.org/10.1093/iat/15.1.291.

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Abstract Foliar spray concentrates were applied aerially to a field of 4th ratoon sugarcane in Cameron Co., near Bluetown, TX. The field was sectioned in plots consisting of 33 rows (60-inch centers) × 1530 ft, with the 11 treated rows in the center, and 11 buffer rows on either side. Insecticide treatments were randomly assigned to plots in a complete block design with 4 replications. Each spray was applied to the crop canopy on 55-ft swath widths (11 rows) at a rate of 5 gal finished formulation (material + water)/acre. Prespray counts of above-ground bored internodes and stalks containing i
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Patterson, Paul L., and Michael S. Williams. "Effects of Registration Errors Between Remotely Sensed and Ground Data on Estimators of Forest Area." Forest Science 49, no. 1 (2003): 110–18. http://dx.doi.org/10.1093/forestscience/49.1.110.

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Abstract The estimation of area by land cover type is a key component of most large-scale forest inventories. Historically, these estimates were derived from a large sample of points, taken from aerial photos, followed by a smaller sample of ground points, which were used to correct errors in the classification of the aerial photo points. There has been interest in replacing aerial photography with satellite imagery. One problem with using satellite imagery is the registration errors between a pixel and a plot or a point on the ground. The estimators and modes of inference can differ substanti
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Pereira, Janielle Souza, Gabriel Araújo e. Silva Ferraz, and Lucas Santos Santana. "Aerial images to monitor grapevine vegetative growth." Revista Engenharia na Agricultura - REVENG 30 (June 20, 2022): 166–74. http://dx.doi.org/10.13083/reveng.v30i1.13390.

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Images obtained by Remotely Piloted Aircraft (RPA) used to monitor the crop can help evaluate leaf mass, plant formation, and plant population. In this context, the objectives of this study were to analyze plant growth in a grapevine crop trained in the trellis system, detect failures and determine the plant covered area using images obtained by RPA. The flight was parameterized with frontal overlap of 75%, lateral overlap of 70%, Ground Sample Distance (GSD) of 60 m, and flight speed of 5 m.s-1, using a sensor in the visible range. Processed images showed a stand 3% smaller than projected, an
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Zeng, Guanzhong, Jiaqi Xu, Wei Zhang, and Bin Wang. "Tree species identification and health assessment of forest sample plots based on UAV hyperspectral remote sensing technology." Journal of Physics: Conference Series 2621, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1742-6596/2621/1/012001.

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Abstract National forest resource information is an important part of national basic information in many countries, sample plot survey is the main means to obtain this information. With the progress of science and technology and social development, the demand for cost saving and scientific and technological innovation has led to the wide application of UAV remote sensing in forest resource survey. This study introduced the practice of UAV hyperspectral remote sensing survey in Yicheng, Hubei Province, described in detail how to realize tree species identification and health assessment in fores
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MacLean, David A., and Wayne E. MacKinnon. "Accuracy of aerial sketch-mapping estimates of spruce budworm defoliation in New Brunswick." Canadian Journal of Forest Research 26, no. 12 (1996): 2099–108. http://dx.doi.org/10.1139/x26-238.

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The accuracy of aerial sketch-mapping estimates of spruce budworm (Choristoneurafumiferana (Clem.)) defoliation was evaluated from 1984 to 1993 in 222–325 sample plots in spruce (Picea sp.)–balsam fir (Abiesbalsamea (L.) Mill.) stands in New Brunswick. Operational aerial defoliation estimates were used, wherein all productive forest in known budworm infestation zones was surveyed each year from small aircraft with flight lines 2–5 km apart, and rated in classes of nil (0–10%), light (11–30%), moderate (31–70%), and severe (71–100%). Aerial defoliation estimates were compared with ground-based
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Dissertations / Theses on the topic "Aerial sample plot"

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Holmström, Hampus. "Data acquisition for forestry planning by remote sensing based sample plot imputation /." Umeå : Swedish Univ. of Agricultural Sciences (Sveriges lantbruksuniv.), 2001. http://epsilon.slu.se/avh/2001/91-576-6086-7.pdf.

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Conference papers on the topic "Aerial sample plot"

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Zhu, Jinxia, Ke Wang, Jinsong Deng, and Tom Harmon. "Quantifying Nitrogen Status of Rice Using Low Altitude UAV-Mounted System and Object-Oriented Segmentation Methodology." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87107.

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Nitrogen deficiency can seriously reduce yield, while over-fertilization can result problems such as excess nutrient runoff and groundwater pollution. Hence, efficient methods for assessing crop nitrogen status are needed to enable more optimal fertilizer management. The ability to quantify the different nitrogen application rates by crops using digital images taken from an unmanned aerial vehicle (UAV) was investigated in comparison with ground-based hyperspectral reflectance and chlorophyll content data from 140 plots on a managed field. This research utilized new UAV system, comprised of re
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Asenova, Maria, Georgi Donchev, and Evgeni Evangelov. "PERSONAL LASER SCANNING TECHNOLOGY FOR 3D MAPPING AND FOREST INVENTORY." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/2.1/s10.41.

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LiDAR technology expands the possibilities for forest inventory using aerial and terrestrial scanning. A technological scheme for terrestrial personal laser scanning (PLS) has been developed in order to extract numerical tree parameters. The aim of the paper is to determine the characteristics of individual trees and average taxation indicators of forest stands via terrestrial PLS method. The PLS system includes Sensor Ouster OS1-16, mounted on a folding monopod and mini PC for control and recording of primary raw data, the base of creation of the 3D cloud of points. Google Cartographer is a s
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Reports on the topic "Aerial sample plot"

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Ley, Matt, Tom Baldvins, Hannah Pilkington, David Jones, and Kelly Anderson. Vegetation classification and mapping project: Big Thicket National Preserve. National Park Service, 2024. http://dx.doi.org/10.36967/2299254.

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The Big Thicket National Preserve (BITH) vegetation inventory project classified and mapped vegetation within the administrative boundary and estimated thematic map accuracy quantitatively. National Park Service (NPS) Vegetation Mapping Inventory Program provided technical guidance. The overall process included initial planning and scoping, imagery procurement, vegetation classification field data collection, data analysis, imagery interpretation/classification, accuracy assessment (AA), and report writing and database development. Initial planning and scoping meetings took place during May, 2
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Ley, Matt, Tom Baldvins, David Jones, Hanna Pilkington, and Kelly Anderson. Vegetation classification and mapping: Gulf Islands National Seashore. National Park Service, 2023. http://dx.doi.org/10.36967/2299028.

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The Gulf Islands National Seashore (GUIS) vegetation inventory project classified and mapped vegetation on park-owned lands within the administrative boundary and estimated thematic map accuracy quantitatively. The project began in June 2016. National Park Service (NPS) Vegetation Mapping Inventory Program provided technical guidance. The overall process included initial planning and scoping, imagery procurement, field data collection, data analysis, imagery interpretation/classification, accuracy assessment (AA), and report writing and database development. Initial planning and scoping meetin
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McManamay, Rachel, and Wendy Wright. Vegetation mapping at Cumberland Island National Seashore. National Park Service, 2017. https://doi.org/10.36967/2243967.

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The Southeast Coast Network (SECN), with the support of the National Park Service (NPS) Vegetation Mapping Inventory Program, described and mapped vegetation at Cumberland Island National Seashore (CUIS). This mapping effort was accomplished through collaboration with the Southeast regional office of NatureServe (Raleigh/Durham, N.C.). The mapping area was 15,163.4 hectares (ha), encompassing the entire boundary of the seashore plus an additional buffered area. NatureServe ecologists identified plant associations for the seashore and a remote sensing specialist from the Southeast Coast Network
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