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Relevant bibliographies by topics / Forests and forestry Aerial photography in forestry

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Academic literature on the topic 'Forests and forestry Aerial photography in forestry'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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Journal articles on the topic "Forests and forestry Aerial photography in forestry"

1

Koch, Barbara. "Stand und Perspektiven der Nutzung neuer Fernerkundungstechnologien im Waldbereich | Status and perspectives of the application of new remote sensing technologies in forestry." Schweizerische Zeitschrift fur Forstwesen 162, no. 6 (June 1, 2011): 156–63. http://dx.doi.org/10.3188/szf.2011.0156.

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Remote sensing has been used in forestry for a long time. Aerial photography has mainly been used to support national and operational inventories and medium resolution satellite data for large area inventories. Today through the availability of new technologies there are greatly extended possibilities for remote sensing in the forestry sector. The major change is the better availability of 3-D information, which allows a much better modelling of forests and forest attributes. The paper presents an overview of the newest remote sensing technologies, such as the systems carried by satellite which can be used to record changes or degradation in the area covered by forest for the global forestry resources assessment of the UN World Food and Agriculture Organisation or are examined in connection with the United Nations REDD program. Besides these, other small scale applications are presented based on optical or laser systems carried by aircraft. The article finishes with an outlook on expected developments in the near future. It is expected that the future of forestry remote sensing will be characterized above all by the combination of information obtained from diverse sources, such as data based on terrestrial and on remotely sensed sources.

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Martin, Maxence, Nicole J. Fenton, and Hubert Morin. "Boreal old-growth forest structural diversity challenges aerial photographic survey accuracy." Canadian Journal of Forest Research 50, no. 2 (February 2020): 155–69. http://dx.doi.org/10.1139/cjfr-2019-0177.

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The erosion of old-growth forests in boreal managed landscapes is a major issue currently faced by forest managers; however, resolving this problem requires accurate surveys. The intention of our study was to determine if historic operational aerial forest surveys accurately identified boreal old-growth forests in Quebec, Canada. We first compared stand successional stages (even-aged vs. old-growth) in two aerial surveys performed in 1968 (preindustrial aerial survey) and 2007 (modern aerial survey) on the same 2200 km2 territory. Second, we evaluated the accuracy of the modern aerial survey by comparing its results with those of 74 field plots sampled in the study territory between 2014 and 2016. The two aerial surveys differed significantly; 80.8% of the undisturbed stands that were identified as “old-growth” in the preindustrial survey were classified as “even-aged” in the modern survey, and 60% of the stands identified as “old-growth” by field sampling were also erroneously identified as “even-aged” by the modern aerial survey. The scarcity of obvious old-growth attributes in boreal old-growth forests, as well as poorly adapted modern aerial survey criteria (i.e., criteria requiring high vertical stratification and significant changes in tree species composition along forest succession), were the main factors explaining these errors. It is therefore likely that most of Quebec’s boreal old-growth forests are currently not recognized as such in forest inventories, challenging the efficacy of sustainable forest management policies.

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BERGEN, KATHLEEN, ZHENZHEN ZHANG, GERALD TYRRELL, KAREN VON KLUGE, and JACOB RUMSCHLAG. "Mapping Forest and Surrounding Landscape Changes 1949-2015 at the University of Michigan's Historic Forestry Education Properties." Michigan Academician 45, no. 2 (January 1, 2018): 241–64. http://dx.doi.org/10.7245/0026-2005-45.2.241.

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ABSTRACT Three forested properties owned by the University of Michigan and near to Ann Arbor were the sites of some of the earliest forestry field education in the USA. No longer managed solely for this purpose after the mid-1960s, and at the same time nested within a rapidly developing area of Michigan, current planning for the properties focuses on melding their historic legacy with renewed ecologically and sustainably sound uses. We developed new maps and knowledge of forest and land change within and surrounding the properties between 1949 and 2015. We acquired aerial photography at 5-10 year intervals, created land-cover/land-use and change data, and identified key trajectories of change. Results within Saginaw Forest (established 1904) showed a consistent amount of forest area, but transitions in some observed overstory composition from coniferous to mixed forest between 1949 and 2015. Within the present-day extent of Stinchfield Woods and the Newcomb Tract (established 1925-1955), forest area increased from 68% to 98% and 51% to 93% respectively between 1949 and 2015, as forest plantations and other regrowth replaced former cleared lands. In 0.5 km-wide buffer areas surrounding the properties, agriculture decreased, and urban uses increased dramatically between 1949 and 2015 for all three sites. Forested land cover has also increased on the surrounding landscapes, again replacing agriculture and grassland. The properties today still display the legacies of their historic forestry education and research, and are living laboratories of natural succession in planted forests. The properties now also represent some of the most protected local lands while the landscapes surrounding them continue to change.

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Gillis, Mark D., and Donald G. Leckie. "Forest inventory update in Canada." Forestry Chronicle 72, no. 2 (April 1, 1996): 138–56. http://dx.doi.org/10.5558/tfc72138-2.

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Modern forest management presents ever increasing demands for accurate and up-to-date forest inventory information. The process of inventory update is critical. Inventory update in Canada is examined including update for harvest, burns, insect and disease, silviculture, roads and other changes. The magnitude and requirements of the update task are documented. The procedures used are described and summarized by province in table form. Usage, advantages and disadvantages of current methods (e.g. conventional 9 × 9 aerial photography, supplemental aerial photography, satellite imagery, and aerial reconnaissance) are examined, new methods discussed and trends highlighted. Also outlined are issues related to the incorporation of silviculture and insect and disease information into inventories and the structure and responsibilities for update. Key words: forest inventory, inventory update, harvest, burns, insect and disease, blowdown, silviculture, aerial photography, satellite imagery, Global Positioning System, aerial reconnaissance, video

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Spencer, Ray D. "Small format aerial photography: methods and achievements in Australian forestry." Australian Forestry 61, no. 4 (January 1998): 267–74. http://dx.doi.org/10.1080/00049158.1998.10674751.

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Morgan, Jessica L., and Sarah E. Gergel. "Automated analysis of aerial photographs and potential for historic forest mapping." Canadian Journal of Forest Research 43, no. 8 (August 2013): 699–710. http://dx.doi.org/10.1139/cjfr-2012-0492.

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Historic information regarding forest status is essential to management and conservation. Manual interpretation of aerial photography has long been the standard for forest inventory; however, manual interpretation can be subjective, inconsistent, and labor-intensive. This research compares automated techniques with manual interpretation results. First, we used an automated process (called segmentation) to delineate homogeneous stands of forests (or objects), analogous to the goal of manually delineating of polygons. Second, we used classification and regression tree (CART) analysis to classify polygons into the forest and terrain schemes used in British Columbia. Most characteristics of objects created via segmentation were similar to manually delineated polygons, as >70% of attributes were statistically similar across local, polygon, and landscape-level comparisons. Using manual interpretations for comparative reference, automated classifications produced overall accuracies ranging from 62% to 86% with per-class accuracies ranging from 0% to 96%. Automated methods yielded classifications meeting provincial overlap accuracy targets and helped identify classifications most suited to automation. Automated procedures have potential for aiding swift utilization of extensive historical photography archives with several caveats for future consideration. While automated techniques may never replicate all aspects of forest inventory classification, automated techniques may be valuable in assisting different phases of the process.

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Kamioka, Hisaaki, and Nobuyuki Abe. "Estimating Stand Structure Using Digitalized Aerial Photography." Journal of Forest Research 4, no. 2 (May 1999): 75–78. http://dx.doi.org/10.1007/bf02762229.

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Gering, Lawrence R., and Dennis M. May. "Point-Sampling of Tree Crowns Using Aerial Photographs for Forest Inventory." Southern Journal of Applied Forestry 21, no. 1 (February 1, 1997): 28–36. http://dx.doi.org/10.1093/sjaf/21.1.28.

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Abstract Aerial-photo angle-gauges were designed and constructed for developing a procedure for using variable-radius plot sampling for forest inventory of natural stands in Hardin and Wayne Counties, Tennessee. Data were obtained during the 1989 USDA Southern Forest Experiment Station survey of the forests of Tennessee, with supplemental aerial photographic measurements. Photo-based cruises of the two counties were made on 9 x 9 in. color aerial photographs (with a nominal scale of 1:4,800) taken during the fall color season. Photo cruises were compared to traditional ground-based cruises, and great differences were observed in number of trees, basal area, and merchantable volume. Evaluation of empirical diameter distributions revealed that the photo-based inventory failed to tally many of the smaller diameter trees. The development of the angle-gauge is theoretically sound, but results from its use are questionable due to differences with corresponding ground-based inventories. South. J. Appl. For. 21(1):28-36.

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Lister, Andrew J., Hans Andersen, Tracey Frescino, Demetrios Gatziolis, Sean Healey, Linda S. Heath, Greg C. Liknes, et al. "Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory." Forests 11, no. 12 (December 19, 2020): 1364. http://dx.doi.org/10.3390/f11121364.

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Globally, forests are a crucial natural resource, and their sound management is critical for human and ecosystem health and well-being. Efforts to manage forests depend upon reliable data on the status of and trends in forest resources. When these data come from well-designed natural resource monitoring (NRM) systems, decision makers can make science-informed decisions. National forest inventories (NFIs) are a cornerstone of NRM systems, but require capacity and skills to implement. Efficiencies can be gained by incorporating auxiliary information derived from remote sensing (RS) into ground-based forest inventories. However, it can be difficult for countries embarking on NFI development to choose among the various RS integration options, and to develop a harmonized vision of how NFI and RS data can work together to meet monitoring needs. The NFI of the United States, which has been conducted by the USDA Forest Service’s (USFS) Forest Inventory and Analysis (FIA) program for nearly a century, uses RS technology extensively. Here we review the history of the use of RS in FIA, beginning with general background on NFI, FIA, and sampling statistics, followed by a description of the evolution of RS technology usage, beginning with paper aerial photography and ending with present day applications and future directions. The goal of this review is to offer FIA’s experience with NFI-RS integration as a case study for other countries wishing to improve the efficiency of their NFI programs.

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Blinn, Charles R., Al Lyons, and Edward R. Buckner. "Color Aerial Photography for Assessing the Need for Fertilizers in Loblolly Pine Plantations." Southern Journal of Applied Forestry 12, no. 4 (November 1, 1988): 270–73. http://dx.doi.org/10.1093/sjaf/12.4.270.

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Abstract Color aerial photography was used to assess crown color classes in loblolly pine (Pinus taeda L.) plantations. Three distinct Munsell color classes were delineated on the resulting photographs. Foliar N levels and, to a lesser degree, foliar K levels were directly related to color. Significant relationships between color and site index and color and basal area were shown. Application of color aerial photography, combined with Munsell color coding, could expedite land classification and also make possible more efficient use of fertilizers. South J. Appl. For. 12(4):270-273.

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Dissertations / Theses on the topic "Forests and forestry Aerial photography in forestry"

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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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Pacurari, Doru I. "Evaluation of the use of remotely sensed images to speciate mixed Appalachian forests." Morgantown, W. Va. : [West Virginia University Libraries], 2000. http://etd.wvu.edu/templates/showETD.cfm?recnum=1550.

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Thesis (M.S.)--West Virginia University, 2000.
Title from document title page. Document formatted into pages; contains x, 128 p. : ill. (some col.), maps (some col.) Vita. Includes abstract. Includes bibliographical references (p. 116-121).

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Metzler, Jacob W. "Use of Multi-temporal IKONOS and LANDSAT ETM+ Satellite Imagery to Determine Forest Stand Conditions in Northern Maine." Fogler Library, University of Maine, 2004. http://www.library.umaine.edu/theses/pdf/MetzlerJW2004.pdf.

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Korpela, Ilkka. "Individual tree measurements by means of digital aerial photogrammetry." Helsinki : Finnish Forest Research Institute, Finnish Society of Forest Science, 2004. http://catalog.hathitrust.org/api/volumes/oclc/55872310.html.

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Johnson, Ryan L., and University of Lethbridge Faculty of Arts and Science. "Airborne remote sensing of forest leaf area index in mountainous terrain." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2000, 2000. http://hdl.handle.net/10133/90.

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Leaf area index (LAI) provides forestry information that is important for regional scale ecological models and in studies of global change. This research examines the effects of mountainous terrain on the radiometric properties of multispectral CASI imagery in estimating ground-based optical measurements of LAI, obtained using the TRAC and LAI- 2000 systems. Field and image data were acquired summer 1998 in Kananaskis, Alberta, Canada. To account for the influence of terrain a new modified approach using the Li and Strahler Geometric Optical Mutual Shadowing (GOMS) model in 'multiple forward mode' (MFM) was developed. This new methodology was evaluated against four traditional radiometric corrections used in comination with spectral mixture analysis (SMA) and NDVI. The MFM approach provided the best overall predictions of LAI measured with ground-based optical instruments, followed by terrain normalized SMA, SMA without terrain normalization and NDVI.
xiv, 151 leaves : ill. (some col.), map ; 29 cm.

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Bleier, Mary F. "Use of prior distributions from aerial photographs in forest inventory." Thesis, Virginia Tech, 1986. http://hdl.handle.net/10919/41543.

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Bayesian estimates of gross cubic- foot volume per acre were computed for four stand types (plantation pine, natural pine. hardwood. and mixed wood stands) using aerial photo volume tables as the prior information source. Aerial photographs provided a reliable source of information even though most photographs were nearly five years old. For a given level of precision within a particular stand, Bayesian methods reduced the required field sample size up to 50% using all or half of the prior information available. Those priors which utilized a regression or a regression/topographic correction in the estimation of photo heights required less field information for the given precision level than those priors which used uncorrected or topographic corrected photo heights. In order to obtain meaningful gains in sample size reduction corrections to the estimated photo heights should be made. Although the uncorrected prior produced generally less biased estimates. the reduction in sample size was not as large as that observed using other prior types. Greater gains were attributed to the better accuracy of the prior distribution. Although Bayesian methods are biased, it appeared that these methods tempered severely biased prior distributions. In the hardwood stand for example, the average bias present in the photo volume data amounted to -140%. After combining the prior with the field sample, the greatest average bias was -50%. Bayesian methods performed better than the traditional estimation methods in terms of precision. In a one to one comparison. the Bayes standard error was consistently less than its non-Bayes counterpart. The one exception to this trend was the regression prior from the hardwood stand. The poor performance of the prior was due to the weak height regression correction equation. Modal priors utilized were not subject to the extreme input values for prior distribution development as their conservative empirical prior counterparts were. Less overall variation was observed 1n the estimated values. Under the conditions for mode selection set forth in this project, modal priors provided another good source of prior information.
Master of Science

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Holt, Ryan Samuel. "Three enabling technologies for vision-based, forest-fire perimeter surveillance using multiple unmanned aerial systems /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1894.pdf.

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Pilger, Neal, and University of Lethbridge Faculty of Arts and Science. "Canopy reflectance modeling of forest stand volume." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2004, 2004. http://hdl.handle.net/10133/230.

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Three-dimensional canopy relectance models provide a physical-structural basis to satellite image analysis, representing a potentially more robust, objective and accurate approach for obtaining forest cover type and structural information with minimal ground truth data. The Geometric Optical Mutual Shadowing (GOMS) canopy relectance model was run in multiple-forward-mode (MFM) using digital multispectral IKONOS satellite imagery to estimate tree height and stand volume over 100m2 homogeneous forest plots in mountainous terrain, Kananaskis, Alberta. Height was computed within 2.7m for trembling aspen and 1.8m fr lodgepole pine, with basal area estimated within 0.05m2. Stand volume, estimated as the product of mean tree height and basal area, had an absolute mean difference from field measurements of 0.85m3/100m2 and 0.61m3/100m2 for aspen and pine, respectively.
xiii, 143 leaves : ill. (some col.) ; 29 cm.

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Soenen, Scott, and University of Lethbridge Faculty of Arts and Science. "Remote sensing of montane forest structure and biomass : a canopy relectance model inversion approach." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2006, 2006. http://hdl.handle.net/10133/281.

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The multiple-forward-mode (MFM) inversion procedure is a set of methods for indirect canopy relectance model inversion using look-up tables (LUT). This thesis refines the MFM technique with regard to: 1) model parameterization for the MFM canopy reflectance model executions and 2) methods for limiting or describing multiple solutions. Forest stand structure estimates from the inversion were evaluated using 40 field validation sites in the Canadian Rocky Mountains. Estimates of horizontal and vertical crown radius were within 0.5m and 0.9m RMSE for both conifer and deciduous species. Density estimates were within 590 stems/ha RMSE for conifer and 310 stems/ha RMSE for deciduous. The most effective inversion method used a variable spectral domain with constrained, fine increment LUTs. A biomass estimation method was also developed using empirical relationships with crown area. Biomass density estimates using the MFM method were similar to estimates produced using other multispectral analysis methods (RMSE=50t/ha).
xvi, 156 leaves : ill. (some col.), maps ; 29 cm.

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Wiles, Steven Jay. "Evaluation of photographic properties for area estimation." Thesis, Virginia Tech, 1988. http://hdl.handle.net/10919/44695.

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From the known image positional errors on aerial photographs, this thesis computes and evaluates acreage estimation errors. Four hypothetical tracts were used in simulating aerial photographs with 104 different camera orientation combinations. Flying heights of 4000 and 6000 feet, focal lengths of 24 and 50 millimeters with and without lens distortion, and tilts of 0, 3, 6, and 12 degrees were simulated. The 416 photographs were all simulated with the camera exposure station centered above the midpoint of the respective tract's bounding rectangle. The topographic relief of the tracts ranged from 19 feet in the Coastal Plain to 105 feet in the Piedmont.

It was found that lens focal length did not have an independent effect on the acreage estimates. Relief error, the lowest, averaged -0.080%. In comparison, small errors in calculating scale were shown to be larger than relief errors. Tilt was recommended to be limited to six degrees, averaging +1.6% error at six degrees tilt. Because of its positive exponential nature when the tracts are centered, tilt can induce large biases. including tilts from zero to six degrees,the average was 0.634%. Lens distortion error averaged -0.686%. Overall, the average acreage error was 0.363% for simulations up to and including six degrees of tilt with and without lens distortion. This result is for centered tracts, and it was felt many of the errors were compensating given this situation. In conclusion, the photographic images can estimate areas to $1%, however, additional errors are imparted during actual measurement of the photographs.
Master of Science

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Books on the topic "Forests and forestry Aerial photography in forestry"

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Setzer, Theodore S. Verification of aerial photo stand volume tables for southeast Alaska. Portland, Or: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 1988.

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Arnup, R. W. Predicting the abundance of advance growth in black spruce forests in Northeastern Ontario: An aerial photograph interpretive key. Sault Ste. Marie, Ont: Great Lakes Forestry Centre, 1996.

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Stellingwerf, Donald A. Applications of aerial photographs and other remote sensing imagery in forestry (tropical regions). Enschede, Netherlands: International Institute for Aerospace Survey and Earth Sciences, 1986.

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Treitz, P. Remote sensing for forest ecosystem characterization: A review. [Sault Ste. Marie, Ont.?]: NODA/EDNO, 1996.

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Treitz, Paul Michael. Remote sensing for forest ecosystem characterization: A review. Sault Ste. Marie, Ont: Great Lakes Forestry Centre, 1996.

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Ciesla, William M. Color-IR aerial photos for assessment of dieback and mortality in northern hardwood forests. Fort Collins, Colo: U.S. Dept. of Agriculture, Forest Service, Forest Pest Management, Methods Application Group, 1985.

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Farber, S. K. Lesnye izmerenii͡a︡ po srednemasshtabnym aėrosnimkam. Krasnoi͡a︡rsk: Izd-vo SO RAN, 1997.

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Mondragón, Raúl Cancino. Bibliografía temática sobre fotografías aéreas e imágenes remotas de aplicación al subsector forestal. México, D.F: Instituto Nacional de Investigaciones Forestales, 1985.

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Matejek, Sébastien. Méthode de mise à jour des cartes forestières en forêt privée à l'aide des images LANDSAT TM. Québec: Gouvernement du Québec, Ministère des ressources naturelles, Direction de la recherche forestière, 1997.

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Bélouard, Thierry. Forest landscapes: Beyond what meets the eye. Edited by Boureau Jean-Guy, Guéro Marie-Claire, and Vidal Claude 1951-. Paris: Editions de Monza, 2003.

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Book chapters on the topic "Forests and forestry Aerial photography in forestry"

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Halverson, Howard G. "Urban Forest Cover and Aggregation from High-Altitude Aerial Photographs." In The Forest-Atmosphere Interaction, 337–48. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5305-5_21.

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Sedykh, V. N. "Using Aerial Photography and Satellite Imagery to Monitor Forest Cover in Western Siberia." In Boreal Forests and Global Change, 499–507. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-017-0942-2_47.

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Hall, Ronald J. "The Roles of Aerial Photographs in Forestry Remote Sensing Image Analysis." In Remote Sensing of Forest Environments, 47–75. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0306-4_3.

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Ying-ji, Yin, and Wang Ni-hong. "Expert System for Forest Type Interpretation on Aerial Photographs." In Proceedings of the 2012 International Conference on Communication, Electronics and Automation Engineering, 519–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31698-2_74.

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Pekkarinen, A., and S. Tuominen. "Stratification of a Forest Area for Multisource Forest Inventory by Means of Aerial Photographs and Image Segmentation." In Advances in Forest Inventory for Sustainable Forest Management and Biodiversity Monitoring, 111–23. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0649-0_9.

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Trichon, Valérie. "Crown typology and the identification of rain forest trees on large-scale aerial photographs." In Tropical Forest Canopies: Ecology and Management, 301–12. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-017-3606-0_24.

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Kentsch, Sarah, Savvas Karatsiolis, Andreas Kamilaris, Luca Tomhave, and Maximo Larry Lopez Caceres. "Identification of Tree Species in Japanese Forests Based on Aerial Photography and Deep Learning." In Progress in IS, 255–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61969-5_18.

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"Forestry." In Aerial Photography and Image Interpretation, 405–27. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118110997.ch21.

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Česnulevičius, Algimantas, Artūras Bautrėnas, Linas Bevainis, and Donatas Ovodas. "Classical and Modern Remote Mapping Methods for Vegetation Cover." In Vegetation Index and Dynamics [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97427.

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Plant classification is quite complex and multilevel. All living organisms are divided into domains, kingdoms, types, classes, ranks, families, tribes, and species. This classification complexity is also reflected in the classification of biogeographic maps, which is much simpler. Based on floristic dependence, vegetation is grouped by connecting it into spatial (territorial) complexes. This paper presents the interfaces of mapping methods with taxonomic vegetation types at different hierarchical levels. At the same time, examples of vegetation mapping techniques from national and thematic atlases of different countries are presented in this article. UAV aerial photographs are widely used for local mapping of vegetation areas. The authors of this article propose a new methodology that can be used to assess the ecological condition of young trees and the volume of mature forest wood. The methodology is based on the separation of tree crown areas in UAV aerial photographs and photo color analysis. For automated area calculation of young trees, a PixRGB software has been developed to determine the area of pixels of the same color in aerial photographs. The software is based on the comparison of young tree crown area calculations in AutoCAD software and area measurements of individual color spectrum pixels. In the initial stage, aerial photographs are transformed to the exact size of the photographed area. Transformations were performed with an error of less than 2–3 cm. The transformation of the spectrum of aerial photographs allowed to concentrate the color of the image of young trees in a relatively narrow color range. Studies performed in 2019–2020 to assess the ecological condition of trees and the amount of wood using UAV INSPIRE 1 and PixRGB color analysis software showed the effectiveness of the applied methodology.

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"A hybrid method using aerial photograph to extract forest land area." In Computational Intelligence in Industrial Application, 135–40. CRC Press, 2015. http://dx.doi.org/10.1201/b18590-27.

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Conference papers on the topic "Forests and forestry Aerial photography in forestry"

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KARLOVSKA, Amanda, Inga GRĪNFELDE, Ina ALSIŅA, Gints PRIEDĪTIS, and Daina ROZE. "PLANT REFLECTED SPECTRA DEPENDING ON BIOLOGICAL CHARACTERISTICS AND GROWTH CONDITIONS." In Rural Development 2015. Aleksandras Stulginskis University, 2015. http://dx.doi.org/10.15544/rd.2015.045.

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Sustainable and economically based forestry needs modern inventory and monitoring techniques. One of the most common technologies for identification of forest tree species and monitoring of forest growth conditions is the hyperspectral remote sensing. This technology gives an opportunity to economize human resources and time for data collecting and processing. The spectral behaviour of plant leaves depends on number of factors, including environmental background. The aim of this study was to assess the tree reflectance spectra in relation to the growth conditions to take into account potential differences for increasing precision of species identification in Latvian forests and for estimating of forest growth conditions. Remote sensing data were obtained using a specialized aircraft (Pilatus PC-6), which is equipped with a high-performance airborne VNIR pushbroom hyperspectral system (AisaEAGLE). The study area was flown at 1000 m altitude. Data was recorded in the 400–970 nm spectral range, spectral resolution was 3.3 nm, ground resolution 0.5 m. Data processing consisted of manually selecting trees with a recognizable tree crowns in the airborne images. Tree centres were adjusted by putting them in the accurate position according to the situation in aerial photography. All trees with a diameter at breast height DBH of more than 5 cm were measured and for each tree coordinates, its species, height, DBH, crown width and length were recorded. Differentially corrected Global Positioning System measurements were used to determine the position of each plot centre. Data from different hyperspectral bands were compared using ANOVA at confidence level 95 %. Four species: Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst), silver birch (Betula pendula Roth), and European aspen (Populus tremula L.) – were examined in distinct forest site types. The spectral response of studied species was 1) different between species and 2) different between site types within each species, correlating with soil fertility gradient and soil moisture gradient. Differences between species occurred most in the intensity of reflected electromagnetic radiation rather than distinctive locations of maximums or minimums in spectrum curve, and near infrared (NIR) region of spectrum showed more differences between species than visible light zone. Most informative wavebands for distinguishing differences between site types were 805 nm and 644 nm.

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Petrova, M. S., K. T. Protasov, and S. N. Velisevich. "Recognition and evaluation of cedar forests from aerial photography data." In SPIE Proceedings, edited by Gelii A. Zherebtsov and Gennadii G. Matvienko. SPIE, 2006. http://dx.doi.org/10.1117/12.675878.

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Barbezat, Vincent, Philippe Kreiss, Armin Sulzmann, and Jacques Jacot. "Automated recognition of forest patterns using aerial photographs." In Photonics East '96, edited by George E. Meyer and James A. DeShazer. SPIE, 1996. http://dx.doi.org/10.1117/12.262870.

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Hyyppae, Juha M., Hannu Hyyppae, Mikko Inkinen, Mathias Schardt, and Michaela Ziegler. "Forest inventory based on laser scanning and aerial photography." In AeroSense 2000, edited by Gary W. Kamerman, Upendra N. Singh, Christian Werner, and Vasyl V. Molebny. SPIE, 2000. http://dx.doi.org/10.1117/12.397783.

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de Vogels, M. F. A., S. M. de Jong, G. Sterk, and E. A. Addink. "A semi-automatic cropland mapping approach using GEOBIA and random forests on black-and-white aerial photography." In GEOBIA 2016 : Solutions and Synergies. University of Twente Faculty of Geo-Information and Earth Observation (ITC), 2016. http://dx.doi.org/10.3990/2.462.

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Naimeng, Cang, Yu Wanjun, and Wu Xiaoyu. "Smoke detection for early forest fire in aerial photography based on GMM background and wavelet energy." In 2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA). IEEE, 2021. http://dx.doi.org/10.1109/icpeca51329.2021.9362647.

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Johnston, Katherine, Betsy Waddington, Mark Leir, and Corey Kenny. "Re-Introducing the Benefits of Terrain Mapping for Pipeline Routing and Design." In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64285.

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Terrain mapping is the process of the interpretation of aerial photographs, LiDAR and satellite imagery plus field based ground truthing to delineate and characterize terrain polygons with similar surficial materials, landforms and geological processes [1]. For new pipeline projects, detailed terrain mapping is usually completed at a map scale of 1:20,000 corresponding to ground accuracy, at best, of 20 m. Although typically used to support the forestry industry in planning and developing forestry operations in British Columbia, Canada [2], and despite the rapid advancements of remote sensing technology, the art and science of terrain mapping continues to be an essential. albeit somewhat forgotten, tool for new and existing pipeline projects in a variety of terrain settings. For new pipeline projects, a quality terrain mapping product has been be used to characterize ground conditions and support the estimation of design inputs for numerous aspects of pipeline routing and design [3,4]. It is the backbone of most terrain and geohazard related tasks on a pipeline project and it is useful through many stages of a project’s development [5]. At routing and feasibility stages of a project, terrain mapping can be used to efficiently identify geohazards to avoid and to allow comparison of the terrain between different corridor options. Later on at the early design stages, terrain mapping can be used to develop and maintain a geohazard inventory to support geohazard risk assessment and design through geohazards that could not be avoided [6], delineate areas of shallow groundwater where buoyancy control and construction dewatering maybe required, help estimate soil spring parameters to support pipe stress analysis, delineate areas of shallow bedrock to support construction cost estimates and planning [8], and to identify sources of sands and gravels that maybe used for pipeline construction. This paper is intended to re-introduce the ongoing benefits of terrain mapping for new pipeline projects and describe how terrain mapping can cost-effectively support a pipeline project through its lifecycle of feasibility, design, and construction. Examples of the benefits of terrain mapping for routing and design of two proposed transmission pipelines in northern BC are presented. This work will be of interest to project managers, engineers, scientists and regulators involved with routing, design, and construction of new pipelines projects.

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Lateb, Mustapha, Chariton Kalaitzidis, Maria Tompoulidou, and Ioannis Gitas. "Development of an object-based classification model for mapping mountainous forest cover at high elevation using aerial photography." In Fourth International Conference on Remote Sensing and Geoinformation of the Environment, edited by Kyriacos Themistocleous, Diofantos G. Hadjimitsis, Silas Michaelides, and Giorgos Papadavid. SPIE, 2016. http://dx.doi.org/10.1117/12.2240738.

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Reports on the topic "Forests and forestry Aerial photography in forestry"

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Lannom, Keith B., David L. Evans, and Zhiliang Zhu. Comparison of AVHRR classification and aerial photography interpretation for estimation of forest area. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1995. http://dx.doi.org/10.2737/so-rp-292.

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