Forest canopy structure analyzed by using aerial photographs

1995 ◽  
Vol 10 (1) ◽  
pp. 13-18 ◽  
Author(s):  
Tohru Nakashizuka ◽  
Toshio Katsuki ◽  
Hiroshi Tanaka
2022 ◽  
Vol 505 ◽  
pp. 119945
Author(s):  
Jian Zhang ◽  
Zhaochen Zhang ◽  
James A. Lutz ◽  
Chengjin Chu ◽  
Jianbo Hu ◽  
...  

Author(s):  
Brady S. Hardiman ◽  
Elizabeth A. LaRue ◽  
Jeff W. Atkins ◽  
Robert T. Fahey ◽  
Franklin W. Wagner ◽  
...  

Forest canopy structure (CS) controls many ecosystem functions and is highly variable across landscapes, but the magnitude and scale of this variation is not well understood. We used a portable canopy lidar system to characterize variation in five categories of CS along N = 3 transects (140–800 m long) at each of six forested landscapes within the eastern USA. The cumulative coefficient of variation was calculated for subsegments of each transect to determine the point of stability for individual CS metrics. We then quantified the scale at which CS is autocorrelated using Moran’s I in an Incremental Autocorrelation analysis. All CS metrics reached stable values within 300 m but varied substantially within and among forested landscapes. A stable point of 300 m for CS metrics corresponds with the spatial extent that many ecosystem functions are measured and modeled. Additionally, CS metrics were spatially autocorrelated at 40 to 88 m, suggesting that patch scale disturbance or environmental factors drive these patterns. Our study shows CS is heterogeneous across temperate forest landscapes at the scale of 10’s of meters, requiring a resolution of this size for upscaling CS with remote sensing to large spatial scales.


2020 ◽  
Vol 12 (15) ◽  
pp. 2489
Author(s):  
Yusuke Yamada ◽  
Toshihiro Ohkubo ◽  
Katsuto Shimizu

Identifying areas of forest loss is a fundamental aspect of sustainable forest management. Global Forest Change (GFC) datasets developed by Hansen et al. (in Science 342:850–853, 2013) are publicly available, but the accuracy of these datasets for small forest plots has not been assessed. We used a forest-wide polygon-based approach to assess the accuracy of using GFC data to identify areas of forest loss in an area containing numerous small forest plots. We evaluated the accuracy of detection of individual forest-loss polygons in the GFC dataset in terms of a “recall ratio”, the ratio of the spatial overlap of a forest-loss polygon determined from the GFC dataset to the area of a corresponding reference forest-loss polygon, which we determined by visual interpretation of aerial photographs. We analyzed the structural relationships of recall ratio with area of forest loss, tree species, and slope of the forest terrain by using linear non-Gaussian acyclic modelling. We showed that only 11.1% of forest-loss polygons in the reference dataset were successfully identified in the GFC dataset. The inferred structure indicated that recall ratio had the strongest relationships with area of forest loss, forest tree species, and height of the forest canopy. Our results indicate the need for careful consideration of structural relationships when using GFC datasets to identify areas of forest loss in regions where there are small forest plots. Moreover, further studies are required to examine the structural relationships for accuracy of land-use classification in forested areas in various regions and with different forest characteristics.


2017 ◽  
Vol 26 (11) ◽  
pp. 963 ◽  
Author(s):  
Michael J. Lacki ◽  
Luke E. Dodd ◽  
Nicholas S. Skowronski ◽  
Matthew B. Dickinson ◽  
Lynne K. Rieske

The extent to which prescribed fires affect forest structure and habitats of vertebrate species is an important question for land managers tasked with balancing potentially conflicting objectives of vegetation and wildlife management. Many insectivorous bats forage for insect prey in forested habitats, serving as the primary predators of nocturnal forest insects, and are potentially affected by structural changes in forests resulting from prescribed fires. We compared forest-stand characteristics of temperate oak–hickory forests, as measured with airborne laser scanning (light detection and ranging, LiDAR), with categorical estimates of burn severity from prescribed fires as derived from Landsat data and field-based Composite Burn Indices, and used acoustic monitoring to quantify activity of insectivorous bats in association with varying degrees of burn severity (unburned habitat, low severity and medium severity). Forest-stand characteristics showed greatest separation between low-severity and medium-severity classes, with gap index, i.e. open-air space, increasing with degree of burn severity. Greater mid-storey density, over-storey density and proportion of vegetation in the understorey occurred in unburned habitat. Activity of bats did not differ with burn severity for high-frequency (clutter-adapted or closed-space foragers) or low-frequency (edge or open-space foragers) bats. Results indicate that differing degrees of burn severity from prescribed fires produced spatial variation in canopy structure within stands; however, bats demonstrated no shifts in activity levels to this variation in canopy structure, suggesting prescribed fire during the dormant season, used as a management practice targeting desired changes in vegetation, is compatible with sustaining foraging habitat of insectivorous bats.


2015 ◽  
Vol 41 (1) ◽  
pp. 169-174 ◽  
Author(s):  
Akira KATO ◽  
Yuma OKITSU ◽  
Nobumitsu TSUNEMATSU ◽  
Tsuyoshi HONJYO ◽  
Tatsuaki KOBAYASHI ◽  
...  

2003 ◽  
Vol 29 (3) ◽  
pp. 388-410 ◽  
Author(s):  
Jean-Michel N Walter ◽  
Richard A Fournier ◽  
Kamel Soudani ◽  
Emmanuel Meyer

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