Preliminary assessment of ironwood (Eusideroxylon zwageri Teijsm. & Binnend.) stand on the KPPN Bulian of the District VIII of PT. Wirakarya Sakti, Jambi as seed source candidate

Applications of lidar in ecosystem conservation and management continue to expand as technology has rapidly evolved. An accounting of relative accuracy and errors among lidar platforms within a range of forest types and structural configurations was needed. Within a ponderosa pine forest in northern Arizona, we compare vegetation attributes at the tree-, plot-, and stand-scales derived from three lidar platforms: fixed-wing airborne (ALS), fixed-location terrestrial (TLS), and hand-held mobile laser scanning (MLS). We present a methodology to segment individual trees from TLS and MLS datasets, incorporating eigen-value and density metrics to locate trees, then assigning point returns to trees using a graph-theory shortest-path approach. Overall, we found MLS consistently provided more accurate structural metrics at the tree- (e.g., mean absolute error for DBH in cm was 4.8, 5.0, and 9.1 for MLS, TLS and ALS, respectively) and plot-scale (e.g., R2 for field observed and lidar-derived basal area, m2 ha−1, was 0.986, 0.974, and 0.851 for MLS, TLS, and ALS, respectively) as compared to ALS and TLS. While TLS data produced estimates similar to MLS, attributes derived from TLS often underpredicted structural values due to occlusion. Additionally, ALS data provided accurate estimates of tree height for larger trees, yet consistently missed and underpredicted small trees (≤35 cm). MLS produced accurate estimates of canopy cover and landscape metrics up to 50 m from plot center. TLS tended to underpredict both canopy cover and patch metrics with constant bias due to occlusion. Taking full advantage of minimal occlusion effects, MLS data consistently provided the best individual tree and plot-based metrics, with ALS providing the best estimates for volume, biomass, and canopy cover. Overall, we found MLS data logistically simple, quickly acquirable, and accurate for small area inventories, assessments, and monitoring activities. We suggest further work exploring the active use of MLS for forest monitoring and inventory.

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ACCURACY ASSESSMENT OF CROWN DELINEATION METHODS FOR THE INDIVIDUAL TREES USING LIDAR DATA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-585-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 585-588

Author(s):

K. T Chang ◽

C. Lin ◽

Y. C. Lin ◽

J. K. Liu

Keyword(s):

Forest Canopy ◽

Accuracy Assessment ◽

Tree Height ◽

Experimental Results ◽

Estimation Methods ◽

Surface Model ◽

Individual Tree ◽

Free Process ◽

Crown Shape ◽

Individual Trees

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

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Individual Tree Detection and Qualitative Inventory of a Eucalyptus sp. Stand Using UAV Photogrammetry Data

Remote Sensing ◽

10.3390/rs13183655 ◽

2021 ◽

Vol 13 (18) ◽

pp. 3655

Author(s):

André Almeida ◽

Fabio Gonçalves ◽

Gilson Silva ◽

Adriano Mendonça ◽

Maria Gonzaga ◽

...

Keyword(s):

Point Cloud ◽

Digital Terrain Model ◽

Tree Height ◽

Northeastern Brazil ◽

Maximum Height ◽

Individual Tree ◽

Terrain Model ◽

Aerial Photogrammetry ◽

Individual Trees

Digital aerial photogrammetry (DAP) data acquired by unmanned aerial vehicles (UAV) have been increasingly used for forest inventory and monitoring. In this study, we evaluated the potential of UAV photogrammetry data to detect individual trees, estimate their heights (ht), and monitor the initial silvicultural quality of 1.5-year-old Eucalyptus sp. stand in northeastern Brazil. DAP estimates were compared with accurate tree locations obtained with real time kinematic (RTK) positioning and direct height measurements obtained in the field. In addition, we assessed the quality of a DAP-UAV digital terrain model (DTM) derived using an alternative ground classification approach and investigated its performance in the retrieval of individual tree attributes. The DTM built for the stand presented an RMSE of 0.099 m relative to the RTK measurements, showing no bias. The normalized 3D point cloud enabled the identification of over 95% of the stand trees and the estimation of their heights with an RMSE of 0.36 m (11%). However, ht was systematically underestimated, with a bias of 0.22 m (6.7%). A linear regression model, was fitted to estimate tree height from a maximum height metric derived from the point cloud reduced the RMSE by 20%. An assessment of uniformity indices calculated from both field and DAP heights showed no statistical difference. The results suggest that products derived from DAP-UAV may be used to generate accurate DTMs in young Eucalyptus sp. stands, detect individual trees, estimate ht, and determine stand uniformity with the same level of accuracy obtained in traditional forest inventories.

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Seed Source Variation in Medicinal Tree – Azadirachta indica A. Juss. (Neem)

Journal of Non Timber Forest Products ◽

10.54207/bsmps2000-2016-ln5l92 ◽

2016 ◽

Vol 23 (3) ◽

pp. 135-138

Author(s):

U. Parmar ◽

Bimal Desai ◽

J. Chavda ◽

M. Tandel ◽

S. Jha

Keyword(s):

Azadirachta Indica ◽

Seedling Survival ◽

Tree Height ◽

Dry Weight ◽

Seed Source ◽

Medicinal And Aromatic Plants ◽

Statistical Tool ◽

Medicinal Tree ◽

Trunk Diameter ◽

Seed Sources

Azadirachta indica A. Juss. is a well known medicinal plant with various therapeutic uses. It cures numbers of human as well as animal ailments and it has been used in our ancient systems of medicine. A present study was laid out at Model Nursery on Medicinal and Aromatic Plants, ACHF, NAU, Navsari (AES Zone III) during the July, 2012 to February, 2013. Seeds were collected from the 4 various geographical locations and 10 places Viz. Central Gujarat 02 (Dahod and Kheda), South Gujarat 04 (Vyara, Netrang, Rajpipla and Navsari), North Gujarat 02 (Palanpur and Modasa) and Saurashtra 02 (Amreli and Junagadh) and each districts treated as separate treatment. An investigation was laid out under the CRD as statistical tool. The seed sources of Amreli district was found best for the tree height (23.47 cm), tree trunk diameter (2.55 m), seed diameter (5.02 mm), seed length (20.53 cm), 100 seed weight (24.49 gm) and azadirachtin content (34.33 %). Similarly, seed source of Kheda district showed better response for fresh weight of seedling (17.80 g), dry weight of seedling (6.31 g), germination percentage (85.55 %), seedling survival percentage (81.55 %), root length (14.53 cm) and collar diameter (0.36 mm). However, seed source of Palanpur district was superior over the other seed sources in context to maximum shoot length (26.16 cm) and number of leaves per seedling (24.87). Hence, it can be concluded that the seeds source from different location were shown better performance in context to various morphological character.

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Estimation of crown form for six conifer species of northern California

Canadian Journal of Forest Research ◽

10.1139/x90-151 ◽

1990 ◽

Vol 20 (8) ◽

pp. 1137-1142 ◽

Cited By ~ 33

Author(s):

Greg S. Biging ◽

Lee C. Wensel

Keyword(s):

Sierra Nevada ◽

Tree Height ◽

Wildlife Habitat ◽

Conifer Species ◽

Damage Potential ◽

Cross Sectional ◽

Individual Tree ◽

Crown Volume ◽

Using Data ◽

Individual Trees

Geometric models are presented for the prediction of crown volume and width at any height in the crown of six conifer species in the Sierra Nevada. Crown volume is defined as the geometric space occupied by the crown and is allometrically related to the diameter, height, and crown ratio of individual trees. Crown diameter is derived from crown volume, tree height, and crown ratio. The crown volumes and associated measures can be used to compute indices of individual tree competition such as those used in the CACTOS (California Conifer Timber Output Simulator) system or to compute other measures such as wildlife habitat suitability or insect damage potential. Estimation equations are developed by regression using data collected on crowns of 593 felled trees. The equations use dbh, total height, and crown ratio to estimate total crown volume, crown volume above a specified height, and cumulative crown cross sectional area at a specified height.

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RHYACIONIA BUSHNELLI (LEPIDOPTERA: TORTRICIDAE) DAMAGED TIPS WITHIN PONDEROSA PINE: DISTRIBUTION AND SAMPLING UNIVERSE

The Canadian Entomologist ◽

10.4039/ent114403-5 ◽

1982 ◽

Vol 114 (5) ◽

pp. 403-409 ◽

Cited By ~ 4

Author(s):

Mary Ellen Dix ◽

Daniel T. Jennings

Keyword(s):

Pinus Ponderosa ◽

Ponderosa Pine ◽

Tree Height ◽

Accurate Estimate ◽

Seed Source ◽

Geographic Regions ◽

Individual Trees

AbstractWithin individual trees in an 8-year-old provenance planting of ponderosa pine (Pinus ponderosa var. scopulorum Engelm.) in central Nebraska, the infestation of tips by the western pine tip moth (Rhyacionia bushnelli Busck) generally decreased with increasing tree height and varied with whorl and seed source. Trees from Eastern Plains sources were taller and had fewer infestations than trees from three other geographic regions. Sampling tips on whorls 3 through 6, 4 through 6, or 4 through 7 all give an accurate estimate of damaged tips per tree in trees less than or equal to 3.0 m high.

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Evaluation of Long-Term Shortleaf Pine Progeny Tests in the Ouachita and Ozark National Forests, USA

Forests ◽

10.3390/f12070953 ◽

2021 ◽

Vol 12 (7) ◽

pp. 953

Author(s):

Shaik M. Hossain ◽

Don C. Bragg ◽

Virginia L. McDaniel ◽

Carolyn C. Pike ◽

Barbara S. Crane ◽

...

Keyword(s):

Tree Height ◽

Seed Orchard ◽

The United States ◽

National Forests ◽

Pinus Echinata ◽

Shortleaf Pine ◽

Individual Tree ◽

Full Sibling ◽

Seed Sources ◽

Progeny Tests

Between the late 1970s and the early 1990s, the USDA Forest Service installed 155 shortleaf pine (Pinus echinata Mill.) progeny tests in national forests across the Southern Region of the United States. Using control-pollinated crosses from the Mount Ida Seed Orchard, 84 of these progeny tests were established in the Ouachita and Ozark-St. Francis National Forests in Arkansas and Oklahoma. Each of these 84 test locations had, on average, 33 full-sibling families representing three local geographic seed sources (East Ouachita, West Ouachita, and Ozark). Though largely abandoned years ago, the progeny tests that remain provided an opportunity to determine if significant genetic and genetic × environment variance exists for performance traits (d.b.h., tree height, and survival) decades after installation. In 2018 and 2019, we remeasured d.b.h. and height and determined survival in 15 fully stocked progeny tests. Family variances were significant (p < 0.01) for both d.b.h. and height but not for survival (p > 0.05). Seed sources differed significantly (p < 0.05) for d.b.h., with more pronounced latitudinal differences. Additionally, we determined that individual tree and full-sibling family mean heritabilities were moderate (0.15 and 0.72, respectively, for d.b.h and 0.09 and 0.41, for height), suggesting relatively high genetic to environmental variation and good potential for genetic improvement. We also found that shortleaf pine families were broadly adapted in this region since family-by-test variances were non-significant (p > 0.05).

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Floral Composition and Timber Stock of Forest In The Samar Island Natural Park

Annals of Tropical Research ◽

10.32945/atr3823.2016 ◽

2016 ◽

pp. 30-51

Author(s):

Justino Quimio

Keyword(s):

Species Composition ◽

Tree Height ◽

High Volume ◽

Transect Line ◽

Natural Park ◽

Access Road ◽

Floral Diversity ◽

Tree Layer ◽

Timber Tree ◽

Individual Trees

Samar Island Natural Park (SINP) is the most important biodiversity refuge Samar Island. This assessment characterized floral diversity status in SINP and provided recommendations on how such resources can be better managed and protected against destruction. Five watersheds, namely: Taft, Can-avid, Basey, Suribao and Catubig were sampled. In each watershed, a transect line with 25 plots spaced at 200 m interval was used in the survey. Plot size was 20m x 20m. Trees 10 cm in diameter at breast height (DBH) and bigger were measured for stem diameter, merchantable height and tree height. This was for computation of timber volume. The species composition in 3 vegetative layers, such as tree layer, undergrowth and ground layer, was determined using the standard Braun-Blanquet methodology. The forest stands in the five watersheds was dominated by dipterocarp species. Of the 212 timber tree species in the tree layer, 35 species had diameter of at least 60 cm. Eighty-six percent of individual trees were dipterocarps, in 14 species. Shorea squamata and Shorea polysperma was the most frequent. Non-dipterocarp species dominated in number at the lower DBH range, particularly in the 10-20 cm and 21-40 cm DBH range. The forest of Samar still has high volume of commercial-size timber. Forests in the 5 watersheds differed in species composition and structure. The absence of access roads to interior barangays contributed to the conservation of forests. The transport system, such as presence of access road and connecting transport facilities to the main roads had influence to the degree of poaching activities. Areas that had access only through motorboats in shallow river had lowest incidence of poaching.

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ACCURACY ASSESSMENT OF CROWN DELINEATION METHODS FOR THE INDIVIDUAL TREES USING LIDAR DATA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b8-585-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 585-588

Author(s):

K. T Chang ◽

C. Lin ◽

Y. C. Lin ◽

J. K. Liu

Keyword(s):

Forest Canopy ◽

Accuracy Assessment ◽

Tree Height ◽

Experimental Results ◽

Estimation Methods ◽

Surface Model ◽

Individual Tree ◽

Free Process ◽

Crown Shape ◽

Individual Trees

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

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Supervised Segmentation of Ultra-High-Density Drone Lidar for Large-Area Mapping of Individual Trees

Remote Sensing ◽

10.3390/rs12193260 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3260

Author(s):

Martin Krůček ◽

Kamil Král ◽

KC Cushman ◽

Azim Missarov ◽

James R. Kellner

Keyword(s):

Random Error ◽

Laser Scanning ◽

Tree Height ◽

High Density ◽

Mountain Forest ◽

Large Area ◽

Estimation Errors ◽

Individual Tree ◽

Individual Trees ◽

The Impact

We applied a supervised individual-tree segmentation algorithm to ultra-high-density drone lidar in a temperate mountain forest in the southern Czech Republic. We compared the number of trees correctly segmented, stem diameter at breast height (DBH), and tree height from drone-lidar segmentations to field-inventory measurements and segmentations from terrestrial laser scanning (TLS) data acquired within two days of the drone-lidar acquisition. Our analysis detected 51% of the stems >15 cm DBH, and 87% of stems >50 cm DBH. Errors of omission were much more common for smaller trees than for larger ones, and were caused by removal of points prior to segmentation using a low-intensity and morphological filter. Analysis of segmented trees indicates a strong linear relationship between DBH from drone-lidar segmentations and TLS data. The slope of this relationship is 0.93, the intercept is 4.28 cm, and the r2 is 0.98. However, drone lidar and TLS segmentations overestimated DBH for the smallest trees and underestimated DBH for the largest trees in comparison to field data. We evaluate the impact of random error in point locations and variation in footprint size, and demonstrate that random error in point locations is likely to cause an overestimation bias for small-DBH trees. A Random Forest classifier correctly identified broadleaf and needleleaf trees using stem and crown geometric properties with overall accuracy of 85.9%. We used these classifications and DBH estimates from drone-lidar segmentations to apply allometric scaling equations to segmented individual trees. The stand-level aboveground biomass (AGB) estimate using these data is 76% of the value obtained using a traditional field inventory. We demonstrate that 71% of the omitted AGB is due to segmentation errors of omission, and the remaining 29% is due to DBH estimation errors. Our analysis indicates that high-density measurements from low-altitude drone flight can produce DBH estimates for individual trees that are comparable to TLS. These data can be collected rapidly throughout areas large enough to produce landscape-scale estimates. With additional refinement, these estimates could augment or replace manual field inventories, and could support the calibration and validation of current and forthcoming space missions.

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