scholarly journals Effects of Percent Tree Canopy Density and DEM Misregistration on SRTM/NED Vegetation Height Estimates

2009 ◽  
Vol 1 (2) ◽  
pp. 36-49 ◽  
Author(s):  
George Miliaresis ◽  
Demitris Delikaraoglou
Keyword(s):  
Tree Canopy ◽  
Canopy Density ◽  
Vegetation Height ◽  
Height Estimates

Spray Volume, Canopy Density, and Other Factors Involved in Thinner Efficacy

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 553d-553
Author(s):  
C.R. Unrath
Keyword(s):  
Tree Height ◽  
Tree Canopy ◽  
Tree Size ◽  
Water Volume ◽  
Canopy Density ◽  
The North ◽  
Run Off ◽  
Tree Canopies ◽  
Average Water ◽  
Water Volumes

Historically, most airblast chemical applications to apple orchards used a single “average” water volume, resulting in variability of coverage with tree size and also the greatest variable in chemical thinning. This coverage variability can be eliminated by properly quantifying the tree canopy, as tree row volume (TRV), and relating that volume to airblast water rate for adequate coverge. Maximum typical tree height, cross-row limb spread, and between-row spacing are used to quantify the TRV. Further refinement is achieved by adjusting the water volume for tree canopy density. The North Carolina TRV model allows a density adjustment from 0.7 gal/1000 ft3 of TRV for young, very open tree canopies to 1.0 gal/1000 ft3 of TRV for large, thick tree canopies to deliver a full dilute application for maximum water application (to the point of run-off). Most dilute pesticide applications use 70% of full dilute to approach the point of drip (pesticide dilute) to not waste chemicals and reduce non-target environmental exposure. From the “chemical load” (i.e., lb/acre) calculated for the pesticide dilute application, the proper chemical load for lower (concentrate) water volumes can be accurately determined. Another significant source of variability is thinner application response is spray distribution to various areas of the tree. This variability is related to tree configuration, light, levels, fruit set, and natural thinning vs. the need for chemical thinning. Required water delivery patterns are a function of tree size, form, spacing, and density, as well as sprayer design (no. of nozzles and fan size). The TRV model, density adjustments, and nozzle patterns to effectively hit the target for uniform crop load will be addressed.

Structure and Regeneration of Sal (Shorea robusta Gaertn. f.) Forests in Shiwalik Region of Kumaun Himalaya, India

2017 ◽  
Vol 40 (1) ◽  
pp. 1-8
Author(s):  
Bhawna Adhikari ◽  
◽  
Bhawana Kapkoti ◽  
Neelu Lodhiyal ◽  
L.S. Lodhiyal ◽  
...  
Keyword(s):  
Tree Species ◽  
Basal Area ◽  
Tree Canopy ◽  
Canopy Density ◽  
Kumaun Himalaya ◽  
Shorea Robusta ◽  
Canopy Trees ◽  
Dense Forest ◽  
Open Forest ◽  
Sal Forest

Present study was carried out to assess the structure and regeneration of Sal forests in Shiwalik region of Kumaun Himalaya. Vegetation analysis and tree canopy density was determined by using quadrat and densitometer, respectively. Density of seedlings, saplings and trees was 490-14067, 37-1233, and 273-863 ind.ha-1 respectively. The basal area was 0.12-5.44 m2 ha-1 reported for saplings and 25.4-77.6 m2 ha-1 for trees. Regeneration of Sal was found good in Sal mixed dense forest followed by Sal open forest and Sal dense forest, respectively. Regeneration of Sal was assisted by the presence of associated tree species as well as the sufficient sunlight availability on ground due to adequate opening of canopy trees in Sal forest. Thus it is concluded that the density of tree canopy, sunlight availability and also associated tree species impacted the regeneration of Sal in the region.

scholarly journals Accuracy Assessment of GEDI Terrain Elevation and Canopy Height Estimates in European Temperate Forests: Influence of Environmental and Acquisition Parameters

2020 ◽  
Vol 12 (23) ◽  
pp. 3948
Author(s):  
Markus Adam ◽  
Mikhail Urbazaev ◽  
Clémence Dubois ◽  
Christiane Schmullius
Keyword(s):  
Laser Scanning ◽  
Temperate Forests ◽  
Accuracy Assessment ◽  
Canopy Cover ◽  
Global Scale ◽  
Canopy Height ◽  
Ecosystem Dynamics ◽  
Vegetation Height ◽  
Height Estimates ◽  
Terrain Elevation

Lidar remote sensing has proven to be a powerful tool for estimating ground elevation, canopy height, and additional vegetation parameters, which in turn are valuable information for the investigation of ecosystems. Spaceborne lidar systems, like the Global Ecosystem Dynamics Investigation (GEDI), can deliver these height estimates on a near global scale. This paper analyzes the accuracy of the first version of GEDI ground elevation and canopy height estimates in two study areas with temperate forests in the Free State of Thuringia, central Germany. Digital terrain and canopy height models derived from airborne laser scanning data are used as reference heights. The influence of various environmental and acquisition parameters (e.g., canopy cover, terrain slope, beam type) on GEDI height metrics is assessed. The results show a consistently high accuracy of GEDI ground elevation estimates under most conditions, except for areas with steep slopes. GEDI canopy height estimates are less accurate and show a bigger influence of some of the included parameters, specifically slope, vegetation height, and beam sensitivity. A number of relatively high outliers (around 9–13% of the measurements) is present in both ground elevation and canopy height estimates, reducing the estimation precision. Still, it can be concluded that GEDI height metrics show promising results and have potential to be used as a basis for further investigations.

scholarly journals COMPARISON OF MODEL ACCURACY IN TREE CANOPY DENSITY ESTIMATION USING SINGLE BAND, VEGETATION INDICES AND FOREST CANOPY DENSITY (FCD) BASED ON LANDSAT-8 IMAGERY (CASE STUDY: PEAT SWAMP FOREST IN RIAU PROVINCE)

2018 ◽  
Vol 15 (1) ◽  
pp. 81 ◽  
Author(s):  
Faisal Ashaari ◽  
Muhammad Kamal ◽  
Dede Dirgahayu
Keyword(s):  
Remote Sensing ◽  
Forest Canopy ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Single Band ◽  
Tree Canopy ◽  
Landsat 8 ◽  
Swamp Forest ◽  
Canopy Density ◽  
Forest Canopy Density

Identification of a tree canopy density information may use remote sensing data such as Landsat-8 imagery. Remote sensing technology such as digital image processing methods could be used to estimate the tree canopy density. The purpose of this research was to compare the results of accuracy of each method for estimating the tree canopy density and determine the best method for mapping the tree canopy density at the site of research. The methods used in the estimation of the tree canopy density are Single band (green, red, and near-infrared band), vegetation indices (NDVI, SAVI, and MSARVI), and Forest Canopy Density (FCD) model. The test results showed that the accuracy of each method: green 73.66%, red 75.63%, near-infrared 75.26%, NDVI 79.42%, SAVI 82.01%, MSARVI 82.65%, and FCD model 81.27%. Comparison of the accuracy results from the seventh methods indicated that MSARVI is the best method to estimate tree canopy density based on Landsat-8 at the site of research. Estimation tree canopy density with MSARVI method showed that the canopy density at the site of research predominantly 60-70% which spread evenly.

scholarly journals Vegetation height and cover fraction between 60° S and 60° N from ICESat GLAS data

2012 ◽  
Vol 5 (2) ◽  
pp. 413-432 ◽  
Author(s):  
S. O. Los ◽  
J. A. B. Rosette ◽  
N. Kljun ◽  
P. R. J. North ◽  
L. Chasmer ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Climate Models ◽  
Soil Cover ◽  
Bare Soil ◽  
Ecological Models ◽  
Tree Cover ◽  
Data Sets ◽  
Vegetation Height ◽  
Height Estimates ◽  
Global Vegetation

Abstract. We present new coarse resolution (0.5° × 0.5°) vegetation height and vegetation-cover fraction data sets between 60° S and 60° N for use in climate models and ecological models. The data sets are derived from 2003–2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70 m in 0.5 m intervals for each 0.5° × 0.5°. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r = 0.33 to r = 0.78, decreases the root-mean-square error by a factor 3 to about 6 m (RMSE) or 4.5 m (68% error distribution) and decreases the bias from 5.7 m to −1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5–6 m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r = 0.67); the GLAS tree-cover fraction is compared with the MODIS tree-cover fraction (r = 0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well. The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface.

scholarly journals Relationship Between Xerophyllum tenax and Canopy Density in the Southern Cascades of Washington

2004 ◽  
Vol 19 (2) ◽  
pp. 82-87 ◽  
Author(s):  
Keith Blatner ◽  
Stewart Higgins ◽  
Becky K. Kerns ◽  
Alexis Worthington
Keyword(s):  
Large Scale ◽  
Basal Area ◽  
The United States ◽  
Dry Mass ◽  
Tree Canopy ◽  
Silver Fir ◽  
Canopy Density ◽  
Long Term Study ◽  
The Pacific ◽  
Xerophyllum Tenax

Abstract Large-scale commercial harvest of beargrass (Xerophyllum tenax) has been taking place in the Cascades of Washington and Oregon for the past 15 to 20 years. The long, slender leaves are either used fresh or dried and dyed for use in the floral industries in the United States and Europe. Our objectives were to develop a better understanding of beargrass production under different tree canopy (overstory) densities in the Pacific silver fir/big huckleberry/beargrass and the mountain hemlock/big huckleberry/beargrass plant associations in and around the Cispus Adaptive Management Area. We examined differences in beargrass production for different overstory canopy conditions on 10 sites in each association. Results indicated that beargrass quality is not of commercial grade under open canopies (<60% overstory density). For medium and high densities, the interaction between plant association and overstory density was significant for all response variables except harvestable dry mass. Harvestable dry mass of beargrass did not differ between the two associations, but was greater under medium- compared with high-density conditions. For the Pacific silver fir association, the high-overstory-density class had greater basal area of beargrass per site, and plants were larger with longer leaves compared to medium-canopy-density sites. We did not find this relationship for the mountain hemlock association, except for the longest leaf variable. It is unclear why basal area and size of beargrass were more closely related to overstory conditions for the Pacific silver fir association. Evaluation of the sustainability of beargrass as a nontimber forest product will require long-term study of the relationships among environmental variables, beargrass productivity, and beargrass population dynamics. West. J. Appl. For. 19(2):82–87.

scholarly journals Comparing 3D Point Cloud Data from Laser Scanning and Digital Aerial Photogrammetry for Height Estimation of Small Trees and Other Vegetation in a Boreal–Alpine Ecotone

2021 ◽  
Vol 13 (13) ◽  
pp. 2469
Author(s):  
Erik Næsset ◽  
Terje Gobakken ◽  
Marie-Claude Jutras-Perreault ◽  
Eirik Ramtvedt
Keyword(s):  
Laser Scanning ◽  
Monitoring Program ◽  
Ground Vegetation ◽  
Unmanned Aerial Systems ◽  
Height Estimation ◽  
Vegetation Height ◽  
Height Estimates ◽  
Aerial Photogrammetry ◽  
3D Data ◽  
Pioneer Trees

Changes in vegetation height in the boreal-alpine ecotone are expected over the coming decades due to climate change. Previous studies have shown that subtle changes in vegetation height (<0.2 m) can be estimated with great precision over short time periods (~5 yrs) for small spatial units (~1 ha) utilizing bi-temporal airborne laser scanning (ALS) data, which is promising for operation vegetation monitoring. However, ALS data may not always be available for multi-temporal analysis and other tree-dimensional (3D) data such as those produced by digital aerial photogrammetry (DAP) using imagery acquired from aircrafts and unmanned aerial systems (UAS) may add flexibility to an operational monitoring program. There is little existing evidence on the performance of DAP for height estimation of alpine pioneer trees and vegetation in the boreal-alpine ecotone. The current study assessed and compared the performance of 3D data extracted from ALS and from UAS DAP for prediction of tree height of small pioneer trees and evaluated how tree size and tree species affected the predictive ability of data from the two 3D data sources. Further, precision of vegetation height estimates (trees and other vegetation) across a 12 ha study area using 3D data from ALS and from UAS DAP were compared. Major findings showed smaller regression model residuals for vegetation height when using ALS data and that small and solitary trees tended to be smoothed out in DAP data. Surprisingly, the overall vegetation height estimates using ALS (0.64 m) and DAP data (0.76 m), respectively, differed significantly, despite the use of the same ground observations for model calibration. It was concluded that more in-depth understanding of the behavior of DAP algorithms for small scattered trees and low ground vegetation in the boreal-alpine ecotone is needed as even small systematic effects of a particular technology on height estimates may compromise the validity of a monitoring system since change processes encountered in the boreal-alpine ecotone often are subtle and slow.

scholarly journals Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

2020 ◽  
Vol 12 (24) ◽  
pp. 4042
Author(s):  
Shashi Kumar ◽  
Himanshu Govil ◽  
Prashant K. Srivastava ◽  
Praveen K. Thakur ◽  
Satya P. S. Kushwaha
Keyword(s):  
Forest Canopy ◽  
Linear Regression Analysis ◽  
Tree Canopy ◽  
Canopy Height ◽  
Ecosystem Dynamics ◽  
Amplitude Inversion ◽  
Vegetation Height ◽  
Model Based ◽  
Forest Height ◽  
L Band

Spaceborne and airborne polarimetric synthetic-aperture radar interferometry (PolInSAR) data have been extensively used for forest parameter retrieval. The PolInSAR models have proven their potential in the accurate measurement of forest vegetation height. Spaceborne monostatic multifrequency data of different SAR missions and the Global Ecosystem Dynamics Investigation (GEDI)-derived forest canopy height map were used in this study for vegetation height retrieval. This study tested the performance of PolInSAR complex coherence-based inversion models for estimating the vegetation height of the forest ranges of Doon Valley, Uttarakhand, India. The inversion-based forest height obtained from the three-stage inversion (TSI) model had higher accuracy than the coherence amplitude inversion (CAI) model-based estimates. The vegetation height values of GEDI-derived canopy height map did not show good relation with field-measured forest height values. It was found that, at several locations, GEDI-derived forest height values underestimated the vegetation height. The statistical analysis of the GEDI-derived estimates with field-measured height showed a high root mean square error (RMSE; 5.82 m) and standard error (SE; 5.33 m) with a very low coefficient of determination (R2; 0.0022). An analysis of the spaceborne-mission-based forest height values suggested that the L-band SAR has great potential in forest height retrieval. TSI-model-based forest height values showed lower p-values, which indicates the significant relation between modelled and field-measured forest height values. A comparison of the results obtained from different SAR systems is discussed, and it is observed that the L-band-based PolInSAR inversion gives the most reliable result with low RMSE (2.87 m) and relatively higher R2 (0.53) for the linear regression analysis between the modelled tree height and the field data. These results indicate that higher wavelength PolInSAR datasets are more suitable for tree canopy height estimation using the PolInSAR inversion technique.

Development of a LiDAR-guided section-based tree canopy density measurement system for precision spray applications

2021 ◽  
Vol 182 ◽  
pp. 106053
Author(s):  
Md Sultan Mahmud ◽  
Azlan Zahid ◽  
Long He ◽  
Daeun Choi ◽  
Grzegorz Krawczyk ◽  
...  
Keyword(s):  
Measurement System ◽  
Density Measurement ◽  
Tree Canopy ◽  
Canopy Density ◽  
Spray Applications
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