Integrated Segmentation Approach with Machine Learning Classifier in Detecting and Mapping Post Selective Logging Impacts Using UAV Imagery

Selective logging can cause significant impacts on the residual stands, affecting biodiversity and leading to environmental changes. Proper monitoring and mapping of the impacts from logging activities, such as the stumps, felled logs, roads, skid trails, and forest canopy gaps, are crucial for sustainable forest management operations. The purpose of this study is to assess the indicators of selective logging impacts by detecting the individual stumps as the main indicators, evaluating the performance of classification methods to assess the impacts and identifying forest gaps from selective logging activities. The combination of forest inventory field plots and unmanned aerial vehicle (UAV) RGB and overlapped imaged were used in this study to assess these impacts. The study area is located in Ulu Jelai Forest Reserve in the central part of Peninsular Malaysia, covering an experimental study area of 48 ha. The study involved the integration of template matching (TM), object-based image analysis (OBIA), and machine learning classification—support vector machine (SVM) and artificial neural network (ANN). Forest features and tree stumps were classified, and the canopy height model was used for detecting forest canopy gaps in the post selective logging region. Stump detection using the integration of TM and OBIA produced an accuracy of 75.8% when compared with the ground data. Forest classification using SVM and ANN methods were adopted to extract other impacts from logging activities such as skid trails, felled logs, roads and forest canopy gaps. These methods provided an overall accuracy of 85% and kappa coefficient value of 0.74 when compared with conventional classifier. The logging operation also caused an 18.6% loss of canopy cover. The result derived from this study highlights the potential use of UAVs for efficient post logging impact analysis and can be used to complement conventional forest inventory practices.

Distribution attributes of natural canopy gaps in the Hyrcanian mixed-oriental beech forests

One of the most important issues indicating the quality and quantity of forest ecosystems is the distribution of natural disturbances resulting in canopy gaps (CGs). The present study was conducted in one of the Hyrcanian beech forests in northern Iran in summer 2018. The gap areas were classified into small (< 200 m²), medium (200‒500 m²) and large gaps (500–1 000 m²) on the basis of full inventory. The univariate Ripley’s L-function was used for introducing the CG spatial pattern. Furthermore, mark correlation function (MCF) and density function (DC) in turns were used for verifying the correlation and frequency of CG size classes in each pattern. The results showed patterns of the gaps in each size class and integrated by the three size classes, they were random and cluster, respectively. Furthermore, the MCF revealed that the gap size classes were independently located in the clusters. The total frequency of the small, medium and large gaps in turns was 32, 49 and 19%, respectively. Although the density share of medium and small gaps in turns was more frequent than the large gap density in the study forest, the results of DC indicated that the frequency of each gap size class was random within each cluster, regardless of their density share. Based on the natural gap aggregations, the base circular mosaic with an area of 5 000 m² can be introduced for monitoring and specifying the forest stand dynamics.

Seasonal Dynamics of Tropical Forest Vegetation in Ngoc Linh Nature Reserve, Vietnam Based on UAV Data

Seasonal dynamics in tropical forests are closely related to the variation in forest canopy gaps. The canopy gaps change continuously in shape and size between the rainy and dry seasons, leading to the variation in the vegetative indicators. To monitor the variation of the canopy gaps, UAVs were used to collect datas in the mentioned tropical forests at an altitude of over 1,000m in Ngoc Linh Nature Reserve, Vietnam with a post-processing image resolution of about 8cm, which allows the detection of relatively small gaps. The analysis results at 10 squares of 1 ha showed a decrease in the area of ​​ canopy gaps from the rainy season in September 2019 to the dry season of May 2020. The mixed broad-leaved or broadleaf forest dominates with a greater variation, when the area of ​​the gaps decreases significantly. The variation in forest canopy gaps and vegetative indicators are closely related to the high differentiation of terrain, the seasonal and the dry season climatic characteristics. The fluctuation of the vegetation cover affects the habitats of the species under the forest canopy such as animals, birds and soil fauna. This is one of the scientific bases that contributes to the management and conservation of flora and fauna biodiversity, especially in mountainous tropical forests such as Ngoc Linh Nature Reserve.

Tree mortality and regeneration of Euphrates poplar riparian forests along the Tarim River, Northwest China

Background Tree mortality and regeneration (seedling and sapling recruitment) are essential components of forest dynamics in arid regions, especially where subjected to serious eco-hydrological problems. In recent decades, the mortality of the Euphrates poplar (Populus euphratica) along the Tarim River in Northwest China has increased. However, few studies have quantified the causes of mortality and regeneration in this azonal riparian forest type. Methods The present study describes the annual hydrological response of tree mortality and regeneration in forest gaps. A total of 60 canopy gaps were investigated in six replicate grid plots (50 m × 50 m) and the annual runoff and water consumption data during the period of 1955–2016 were collected from hydrological stations in the middle reaches of the Tarim River. We compared the regeneration density of seedlings and saplings within the canopy gap areas (CGAs), undercanopy areas (UCAs), and uncovered riverbank areas (RBAs) through detailed field investigation. Results Our study found that the mortality of young and middle-aged gap makers has increased remarkably over recent decades, particularly since the year 1996. The main results indicated that regional water scarcity was the primary limiting factor for long-term changes in tree mortality, as shown by a significant correlation between the diameter at breast height (DBH) of dead trees and the annual surface water. The average density (or regeneration rate) of seedlings and saplings was highest in the RBAs, intermediate in the CGAs, and lowest in the UCAs. Compared with the UCAs, the CGAs promote tree regeneration to some extent by providing favorable conditions for the survival and growth of seedlings and saplings, which would otherwise be suppressed in the understory. Furthermore, although the density of seedlings and saplings in the CGAs was not as high as in the RBAs, the survival rate was higher in the CGAs than in the RBAs. Conclusion Forest canopy gaps in floodplain areas can play a decisive role in the long-term germination and regeneration of plant species. However, as a typical phreatophyte in this hyper-arid region, the ecosystem structure, functions and services of this fragile P. euphratica floodplain forests are threatened by a continuous decrease of water resources, due to excessive water use for agricultural irrigation, which has resulted in a severe reduction of intact poplar forests. Furthermore, the survival of seedlings and saplings is influenced by light availability and soil water at the regional scale. Our findings suggest that policymakers may need to reconsider the restoration and regeneration measures implemented in riparian P. euphratica forests to improve flood water efficiency and create canopy gaps. Our results provide with valuable reference information for the conservation and sustainable development of floodplain forest ecosystems.