The crown area is a critical metric for evaluating tree growth and supporting various ecological forestry analyses. This study compares three approaches, i.e., unsupervised clustering, region-based, deep learning, to estimate the of Pinus eldarica Medw. using UAV-acquired RGB imagery (2 cm ground sampling distance) high-density point clouds (1.27 points/cm3). first approach applied clustering techniques, such as Mean-shift K-means, directly areas, bypassing top detection. second employed...

Remote sensing technologies like airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) have emerged as efficient tools for detecting analysing canopy gaps (CGs). Comparing these is essential to determine their functionality applicability in various environments. Thus, this study aimed assess CG dynamics the temperate European Białowieża Forest between 2015 2022 by comparing ALS data image-derived point clouds (IPC) from DAP, evaluate respective capabilities describing forest...

Mangrove forests distributed along the coast of southern Iran are an important resource and a vital habitat for species communities local people. In this study, accurate mapping spatiotemporal change detection were conducted on Iran’s mangroves three decades, using Landsat imagery available years 1990, 2000, 2010, 2020. Four general vegetation indices eight mangrove-specific employed mangrove in study sites. Additionally, six landscape metrics implemented to quantify alteration during...

Abstract. Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different methods for delineation tree crowns and recognition various types ecosystems. However, it still is unclear if this widely-used method can have its on unmanned aerial vehicle (UAV) digital images mapping vegetation cover at...

Tree crown attributes are important parameters during the assessment and monitoring of forest ecosystems. Canopy height models (CHMs) derived from airborne laser scanning (ALS) data have proved to be a reliable source for extracting different biophysical characteristics single trees at stand level. However, ALS-derived tree measurements (e.g., mean diameter) can negatively affected by pits that appear in CHMs. Thus, we propose novel method generating pit-free CHMs ALS point clouds estimating...

An approach was developed to construct a percent canopy cover (PCC) map of Zagros semi-arid woodlands, West Iran, using UltraCam-D airborne imagery. We detected crowns Persian oak coppice trees on the imagery by use support vector machine (SVM) classifier optimized via Taguchi method. Then, PCC calculated in raster grids with various block sizes and their accuracy metrics revealed appropriate sizes. Results showed SVM success separating as receiver operating characteristic (ROC) curve...

Tree height is one of the key parameters in forest plantations that plays a crucial role estimation above-ground biomass (AGB) trees and stands. The parameter may be obtained by different methods from airborne remotely sensed datasets such shadow length each tree individual or crown models (CHMs). However, based on might biased considering diverse topography sites. Therefore, this study aims to develop reliable method estimate plantation using UAV imagery. First, heights 151 pine (Pinus...

There are many satellite systems acquiring environmental data on the world. Acquired global remote sensing datasets require ground reference in order to calibrate them and assess their quality. Regarding calibration validation of these with broad geographical extents, it is essential register zones which might be considered as Homogeneous Patches (HPs). Such patches enable an optimal data/sensors, what more important analysis components significantly influence electro-magnetic signals...

Structural complexity and local biodiversity of species-rich tropical forests can be characterized by their spatial patterns, which contribute to species intra- interspecific interactions. Aiming describe patterns at fine scales, we applied the quantitative analyses based on relationships nearest neighbors conspecific heterospecific trees. In a two-hectare plot broadleaved forest stand in central Vietnam with minimal human influence, all tree individuals diameter breast height ≥ 2.5 cm were...

Explaining the high diversity of tree species in tropical forests remains a persistent challenge ecology. The analysis spatial patterns different and their captures variation behaviors from ‘plant’s eye view’ forest community. To measure scale-dependent species-species interactions at neighborhood scales, we applied uni- bivariate pair correlation functions individual area relationships (ISARs) to two fully mapped 2-ha plots evergreen north-central Vietnam. results showed that (1) positive...

Support vector machine (SVM) is a superior learning methodology with great results in classification of remotely sensed data sets. Determination optimal parameters applied SVM technique still vague to some scientists. This study was aimed detect tree crowns on UltraCam-D (UCD), very high spatial resolution aerial imagery Zagros woodlands by optimised Taguchi method. A 500 × 600 m2 plot covered Persian oak (Quercus brantii var. persica) coppice trees selected woodlands, Iran. The UCD the...

Studying spatial patterns and habitat association of plant communities may provide understanding the ecological mechanisms processes that maintain species coexistence. To conduct assessments correlation between community compositions association, we used data from two topographically different plots with 2 ha area in tropical evergreen forests variables recorded via grid systems 10 × m subplots Northern-Central Vietnam. First, tested relationship composition diversity indices considering...