Forest Monitoring - Science topic

This study evaluates the effectiveness of combining remote sensing techniques with the Random Forest algorithm for estimating the Periodic Annual Increment (PAI) in a dry tropical forest located within the Caatinga biome in northeastern Brazil. The analysis integrates forest inventory data collected from permanent plots monitored between 2011 and 2...

The Atlantic Forest is a global hotspot rich in biodiversity, but highly threatened by deforestation. The study addresses the PRODES Atlantic Forest monitoring system and its remote sensing techniques, as well as the challenges with the adoption of semi-automatic classification algorithms to process time series of images. We highlight the benefits...

Aim Ecological “bright spots” remain resilient following climate events such as marine heatwaves. One explanation for resilience is that small‐scale variability in ocean temperature sustains cooler areas that emerge as local bright spots. In cases where foundational species like kelp thrive through marine heatwaves, the species that rely on kelp fo...

Accurately classifying tree species using remotely sensed data remains a significant challenge, yet it is essential for forest monitoring and understanding ecosystem dynamics over large spatial extents. While light detection and ranging (lidar) has shown promise for species classification, its accuracy typically decreases in complex forests or with...

Tree smuggling, especially of high-value species like sandalwood and teak, poses a significant threat to biodiversity and forest ecosystems. These trees are highly sought after for their commercial value, making them frequent targets of illegal logging operations. This illicit activity not only depletes valuable natural resources but also contribut...

Estimating forest attributes is crucial for understanding forest performance. While forest protection and tree plantations can serve as cost-effective mitigation strategies to address climate change challenges, monitoring natural forests and plantations remains expensive and challenging for a developing nation like Bangladesh, which is highly donor...

In recent years, climate change has forced us to seek solutions to reduce the amount of greenhouse gases in the atmosphere. One of the most widely known methods is the increase of forest areas, making it essential to monitor the health of forests. Forest health has a significant impact on the entire ecosystem. Lidar technology has been used in fore...

The estimation of three-dimensional (3D) vegetation metrics from space-borne LiDAR allows to capture spatio-temporal trends in forest ecosystems. Structural traits from the NASA Global Ecosystem Dynamics Investigation (GEDI) are vital to support forest monitoring, restoration and biodiversity protection. The Mediterranean Basin is home of relict fo...

Accurate estimation of fractional cover of Chinese fir (Cunninghamialanceolata (Lamb.) Hook.) (FCCF) is crucial for forest management and carbon sequestration assessment. Traditional field inventory is time-consuming, labor-intensive, prone to sampling bias, and often mismatched with satellite image resolutions, hindering accurate regional FCCF map...

Global policy frameworks such as the UN Sustainable Development Goals (SDGs) or the Kunming-Montreal Global Biodiversity Framework (KMGBF) as well as numerous EU policies related to species and habitat conservation (e.g. Nature Restoration Law, Birds Directive, Habitats Directive, Water Framework Directive, Marine Strategy Framework Directive), eco...

This study develops a methodological framework combining three spectral indices—Soil Moisture Index (SMI), Leaf Area Index (LAI), and Normalized Difference Vegetation Index (NDVI)— to detect possible ecological changes in the Parangalitsa eLTER site from 2015 to 2024. The indices values are overlayed, and deviations are outlined to look for pattern...

Forest ecosystems provide a wide range of services, including timber production, biodiversity conservation, protection against natural hazards, and human recreation. However, they are increasingly under pressure from direct human interventions and climate change. Strengthening forest resilience to changing environmental conditions requires appropri...

Forests form a major organic carbon reservoir, both above- and belowground. In the course of global change, predicting possible changes in these carbon reservoirs is essential. To this end, the Horizon Europe PathFinder project aims to develop an innovative forest monitoring system allowing consistent EU greenhouse gas reporting of LULUCF (Land Use...

Pine wilt disease poses a significant threat to pine forests worldwide, necessitating efficient and accurate detection of dead pine wood for effective disease control and forest management. Traditional deep learning methods based on supervised closed-set paradigms often struggle to address unknown interfering objects, causing false positives, misse...

Generating long-term ecological data is essential for understanding how ecosystems respond to environmental stressors and is a core motivation of the eLTER research infrastructure. At Lehrforst Rosalia, a forest site in eastern Austria, we conduct ecological monitoring using a heavily instrumented infrastructure, which we will introduce in this pre...

Groundwater recharge is an important ecosystem function of forests. In regions with a negative climatic water balance it shows a distinct annual cycle: in summer, evapotranspiration exceeds the input by precipitation, in the winter, low evapotranspiration allows a rewetting of soils. In times with sufficient water supply, the water moves below the...

Forest ecosystems cover almost 40% of the European land surface and play a vital role in mitigating the ongoing climate crisis. However, increasing climate extremes, such as droughts, heatwaves, and disturbances, pose significant challenges to forest health, ecosystem services, and societal benefits. Rapid and precise forest monitoring is essential...

This research presents a machine learning-based method for estimating individual tree heights using UAV-acquired RGB imagery, focusing on forest monitoring applications. Conducted in the Gosaithan community forest of Nepal, the study utilized high-resolution drone images processed into orthomosaics and 3D models. A Canopy Height Model (CHM) was der...

Sweden, one of the EU’s most heavily forested countries, with 17.5 percent of the EU’s total forest land area, is home to an important part of the EU’s remaining natural forests. These forests are unique environments for biodiversity, with many species associated with old forests, dead wood and tree cover continuity and of different structures and...

Marine protected areas (MPAs) can promote population recovery from climate change impacts by reducing local stressors like fishing. However, with extreme climatic events such as marine heatwaves (MHWs) increasing in frequency and duration, it remains unclear whether MPAs enhance resistance to and recovery from these acute perturbations and how resi...

Forest monitoring through individual tree crown delineation is essential for sustainable management and carbon cycle assessment. This paper presents TreePseCo, an adaptation of the PseCo framework leveraging foundation models for automated tree crown segmentation in aerial imagery. Our approach implements a three-stage pipeline: (1) tree center det...

Remote sensing (RS) imagery is important for applications ranging from land cover and land use (LCLU) mapping to agriculture and forest monitoring. However, there is a limited availability of high-quality labeled data to use as a reference to train supervised learning (SL) models. Semi-supervised learning (SSL) frameworks, such as UniMatch (Yang et...

This study presents a geospatial modeling framework to assess forest resilience on the eastern slopes of Syria’s coastal mountains under dual pressures: drought and conflict-induced disturbances. The model integrates remote sensing–based agricultural and meteorological drought indicators, the vegetation health index (VHI), and the standardized prec...

A R T I C L E I N F O Keywords: Forest aboveground biomass Forest height metrics LiDAR Machine learning Mixed-effects models A B S T R A C T Forest height metrics are vital for predicting aboveground biomass (AGB), a key indicator of carbon dynamics and sustainable forest management. This study explores the comparative performance of tree-based and...

Process-based forest models (PBFMs) are valuable tools for investigating the effects of climate change and alternative forest management strategies. However, they can also be considered tool for monitoring forest conditions over short to extended periods, when ancillary data are scarce and continuous measurements are time-consuming. This study aims...

This study develops an optimized approach for small-scale forest area extraction in mountainous regions by integrating Landsat multispectral and ALOS PALSAR-2 radar data through threshold-based classification methods. The threshold fusion method proposed in this study achieves innovations in three key aspects: First, by integrating Landsat NDVI wit...

Accurate forest data is essential for informed decisions regarding forest policy and management. Traditionally collected through field surveys, this type of data has increasingly been produced with remote sensing (RS). RS provides comprehensive resource maps produced with data from sensors, including airborne laser scanning (ALS) and satellite imag...

Hyperspectral image classification is crucial in remote sensing but faces challenges in forest ecosystem studies due to high-dimensional data, spectral variability, and spatial heterogeneity. Watershed Superpixel Segmentation and Sparse Graph Convolutional Networks (WSSGCN), a novel framework designed for efficient forest image classification, is i...

Forests grow under dynamic conditions influenced by vegetation structure and environmental factors. However, empirical models to enhance growing stock volume GSV) estimation are commonly established based on structural information from airborne laser scanning (ALS) data, raising important questions regarding the models’ performance across time (tem...

Unmanned Aerial Vehicles (UAVs) are increasingly used for reforestation and forest monitoring, including seed dispersal in hard-to-reach terrains. However, a detailed understanding of the forest floor remains a challenge due to high natural variability, quickly changing environmental parameters, and ambiguous annotations due to unclear definitions....

Remote sensing is a tool that enables monitoring forest fires in extensive territories because it allows locating more and less vulnerable regions using satellites, reducing the costs and time for the perception of hot spots. Thus, the objective of this study was to evaluate the distribution of hot spots in the municipality of Nova Timboteua, Pa be...

This article constitutes a socio-technical exploration of how community forest monitoring operates and circulates within indigenous and tropical contexts. Authored collaboratively by a western anthropologist and two indigenous cartographer-activists from Panama, this study meticulously explores the pathways through which a novel form of geospatial...

The demand for spatially explicit and comprehensive forest attribute data has continued to increase. Light detection and ranging (LiDAR) remote sensing, which can measure three-dimensional (3D) forest attributes, plays a significant role. However, only a few studies have used uncrewed aerial vehicle (UAV)-LiDAR to extract the characteristics of the...

Forest cover changes monitoring in Vietnam has been conducted using remote sensing (RS) and geographic information systems (GIS). Given Vietnam’s diverse climate, this study focused on the Thanh Hoa, Kon Tum, and Dong Nai provinces due to their distinct natural conditions and forest structures. Land cover was classified into five categories: broadl...

Societal Impact Statement Ground‐based Inventorying and Monitoring programs are crucial for documenting long‐term forest responses to global change pressures, though there is limited coordination among them. We call for building synergies between different Inventorying and Monitoring programs, as well as community science and stakeholder engagement...

Knowledge of environmental services is still something special. The Mbeliling landscape in Flores Island, West Manggarai Regency, is one of the landscapes rich in Global Threatened Species (GaTS) including the Flores Hawk-eagle and Yellow-crested Cockatoo. In addition, this landscape provides water for most of West Manggarai including Labuan Bajo....

The classification and identification of individual tree species in forest environments are critical for biodiversity conservation, sustainable forestry management, and ecological monitoring. Recent advances in drone technology and artificial intelligence have enabled new methodologies for detecting and classifying trees at an individual level. How...

DETER is the official Brazilian government program responsible for producing warnings of deforestation and degradation of native vegetation in the Brazilian Legal Amazon (ALB). Developed by INPE, DETER has played an important role in forest monitoring in the ALB for over two decades, undergoing methodological updates throughout this period. As a ne...

In recent years, forest areas in Aceh Province, especially in West Aceh Regency, have experienced a significant decline in forest cover. This can negatively impact biodiversity, community quality of life, and natural disaster risk, exacerbating global climate change. The fact that West Aceh is one of the regencies with the highest number of gold an...

The effects of global change pose major challenges for both practical forest management and forest ecological research if European forests are to be managed in such a way that they can continue to provide their many services to people in the future. The number of studies on impacts of global change on forest ecosystems has increased enormously over...

This community service initiative aims to enhance the effectiveness of teak forest monitoring in the Bojonegoro Regional Forestry Branch (CDK) through active community participation and the utilization of technology. Teak forests hold significant economic value, but the high demand for teak wood often leads to illegal logging practices that threate...

Forests play a vital role in maintaining ecological balance, making accurate forest monitoring technologies essential. Remote sensing point cloud data always capture distinctive geometric features of forests, including the cylindrical symmetry of tree trunks and the radial symmetry of canopies. However, the inherent complexity of point cloud data,...

Informed decisions to reduce deforestation, protect biodiversity, and curb carbon emissions require not just knowing where forests are, but understanding their composition. Identifying natural forests, which serve as critical biodiversity hotspots and major carbon sinks, is particularly valuable. We developed a novel global natural forest map for 2...

This review paper explores the potential of open-source remote sensing-based measurement techniques to improve forest data collection and support Reducing Emissions from Deforestation and Forest Degradation (REDD+) monitoring, reporting, and verification framework in Nigeria's terrestrial forests. This study conducts a systematic analysis of four k...

The Western Ghats in India is one of the eight hottest hotspots of biodiversity in the World. Despite its extensive forest cover and rich biodiversity, the region hosts only nine long-term forest monitoring sites, primarily located in evergreen (8) and deciduous (1) forest types. Notably, tropical semi-evergreen forests (TSEF), a critical forest ty...

Virtual laser scanning (VLS) [1] has been used intensively for method development and machine learning in forestry, e.g., for quantification of leaf angle distribution [2], aboveground biomass prediction [3], or leaf-wood segmentation [4]. So far, these applications have been limited to mono-temporal VLS acquisitions where scenes were simplified to...

Many species of wood-inhabiting fungi, particularly in the boreal forests of Nordic countries, face significant extinction risks. The historical impact of commercial forestry has led to fragmented old-growth forests, meaning that species lost from these areas may not naturally return to newly protected habitats. This study investigates the potentia...

Accurate mapping of vegetation canopy height and biomass distribution is essential for effective forest monitoring, climate change mitigation, and sustainable forestry. Here we present high-resolution remote sensing-based canopy height (10 m resolution) and above ground biomass (AGB, 50 m resolution) maps for the forests of the Iberian Peninsula fr...

Producing high-quality local land cover data can be cost-prohibitive, leaving gaps in reliable estimates of forest cover and loss for environmental policy and planning. Remote sensing data (RSD) offer accessible, globally consistent layers for forest mapping. However, being able to produce reliable RSD-based land cover products with high local fide...

Purpose of Review This study aims to systematically examine the application of Remotely Piloted Aircraft Systems (RPAS) for estimating vegetation height in natural and planted forests, aiming to understand the critical challenges encountered by identifying the methods and technologies employed. Recent Findings Since 2018, the use of RPAS for veget...

This study introduces an advanced adaptive sensor clustering technique for environmental monitoring in dynamic forest ecosystems, focusing on optimizing Wireless Sensor Networks (WSNs) for energy efficiency, adaptability, and data accuracy. The framework integrates Quantum Fuzzy C-Means (QFCM) clustering, energy-efficient cluster head selection, an...

Forests offer a diversity of habitats for animals, plants, and fungi. With this they are essential in providing a multitude of ecosystem services such as carbon sequestration, wood provision, clean water, and recreation, as well as, natural hazard protection. Their large genetic diversity and heterogeneity of species and habitats is the foundation...

This study evaluates forest vegetation classification in Binh Chau - Phuoc Buu, Ba Ria - Vung Tau province, using Machine Learning (ML) and Deep Learning (DL) techniques. High-resolution UAV imagery (5×5 cm/pixel) was processed using eCognition and ArcGIS to classify saline forests on sandy soil, evergreen broadleaf forests, plantation forests, and...

Forest structure is key to understanding the resilience of tropical forests (their ability to recover from disturbance) and predicting how these ecosystems will respond to future environmental and climatic fluctuations. Current resilience studies in the Amazon rely on passive and active remote sensing forest cover metrics that offer limited insight...

In the study, analyzed the effectiveness of unmanned aerial vehicles (UAVs) for forest monitoring. Investigated various image processing algorithms aimed at identifying tree species. Revealed the potential of machine learning techniques in automating data analysis. Established a methodology that combines computer vision with UAV imagery for enhance...

Trees outside forests (TOF) are increasingly recognized for their vital contributions to environmental sustainability and socioeconomic development. TOF are undervalued and seldom included in national inventories and international reporting frameworks, particularly in Africa. There is a need to estimate the state, spatial distribution, and future p...

Pre-registered on OSF Pre-registration : https://osf.io/8g5zq 1. Research questions Core Research Questions RQ1: How can an improved DEA framework quantify the trilemma of “energy access-ecological protection-health costs” in developing countries? RQ2: To what extent do crowdsourced localized parameters correct the policy prediction bias of traditi...

Background: Quantifying aboveground biomass (AGB) is crucial for studying the carbon cycle and estimating mitigation potential of climate change. Combining field inventory data and remote sensing such as Landsat imagery, is a common approach for landscape-Level AGB analysis. However, uncertainties in biomass estimations persist, highlighting the ne...

This study proposes PlantViT, a Vision Transformer (ViT)-based framework for high-precision vegetation classification by integrating hyperspectral imaging (HSI) and Light Detection and Ranging (LiDAR) data. The dual-branch architecture optimizes feature fusion across spectral and spatial dimensions, where the LiDAR branch extracts elevation and str...

Climate change has intensified the frequency and severity of forest fires, driving a global increase in fire-induced forest losses. Although extreme forest fires have been extensively studied at regional scales, the global characteristics of extreme fire-induced forest loss (EFFL) remain poorly understood. Here, we used high-resolution remote-sensi...

The National Forest Inventory (NFI) of the Czech Republic provides essential data for forest management but requires significant time and resources. This study highlights the critical role of validating Sentinel-2-based machine learning models against real NFI data to ensure their reliability for forest monitoring. While satellite-based models offe...

This study addresses the need for a cohesive pan-European forest monitoring system by developing a methodological framework to generate and provide spatially explicit and complementary indicators of forest dynamics. Utilizing Copernicus High-Resolution Layer Tree Cover Density data, we operationalize two key indicators—forest extent and condition—e...

Accurate forest monitoring and resource assessment are crucial for sustainable forest management, with tree diameter at breast height (DBH) serving as a key metric for tree growth assessment and carbon storage estimation. In this study, we developed a comprehensive mobile-LiDAR-based point cloud processing pipeline to segment individual trees and e...

This paper investigates tree species classification using the Sentinel-2 multispectral satellite image time series (SITS). Despite its importance for many applications and users, such mapping is often unavailable or outdated. The value of using SITS to classify tree species on a large scale has been demonstrated in numerous studies. However, many m...

The adoption of novel methods in forest management planning requires the incorporation of precise forest and tree data to improve scheduling and meet multi-objective criteria principles. This study evaluates advanced methods for mapping tree structural attributes to create detailed baselines for forest carbon biomass, a key indicator in environment...

Shifting from a coercive to a collaborative approach that engenders equity in processes and outcomes from forest management remains an aspiration in forest governance in many countries. Whereas several studies have analyzed how national policy changes and international developments collectively influence this change, the nature of the subjects crea...

Accurate forest monitoring is critical for achieving the objectives of the European Green Deal. While national forest inventories provide consistent information on the state of forests, their temporal frequency is inadequate for monitoring fast-growing species with 15-year rotations when inventories are conducted every 10 years. However, Earth obse...

Storm Gudrun represents one of the most significant meteorological events in recent Swedish history, causing widespread forest destruction in southern Sweden. Now, 20 years after the storm, it is time to reflect on its impact on the forest sciences. We highlight key research themes that emerged in response to the storm, emphasising the critical rol...

Satellite lidar systems, such as ICESat, GEDI, and ICESat-2, have revolutionized global above-ground biomass (AGB) estimation by providing precise forest height data. These missions highlight the transformative potential of spaceborne lidar in advancing biomass assessment and forest monitoring. The present research effectively utilized spaceborne I...

As large-scale heterogeneous data sets become increasingly available, adapting foundation models at low cost has become a key issue. Seminal works in natural language processing, e.g. Low-Rank Adaptation (LoRA), leverage the low "intrinsic rank" of parameter updates during adaptation. In this paper, we argue that incorporating stronger inductive bi...

Multi-source remote sensing fusion and machine learning are effective tools for forest monitoring. This study aimed to analyze various fusion techniques, their application with machine learning algorithms, and their assessment in estimating forest type and aboveground biomass (AGB). A keyword search across Web of Science, Science Direct, and Google...

Soil erosion and wildfires are frequent natural disasters that threaten the environment. Identifying and zoning susceptible areas are crucial for the implementation of preventive measures. The Šar Mountains are a national park with rich biodiversity and various climate zones. Therefore, in addition to protecting the local population from natural di...

This study reviews research from 2010 to 2023 on the integration of airborne laser scanning (ALS) metrics with satellite and ground-based data for forest monitoring, highlighting the potential of the combined use of ALS and optical remote sensing data in improving the accuracy and the frequency. Following an in-depth screening process, 42 peer-revi...

A bstract Year 2024 marks the 35th anniversary of forest monitoring in Poland. It is the first and only Europe-wide harmonized research programme to assess the health of the forest environment. In this article, we refer to international legal documents and acts of the Polish Parliament, based on which the forest monitoring programme has developed i...

The pine bark beetle is a devastating forest pest, causing significant forest losses worldwide, including 25% of pine forests in Honduras. This study focuses on Dendroctonus frontalis and Ips spp., which have affected four of the seven native pine species in Honduras: Pinus oocarpa, P. caribaea, P. maximinoi, and P. tecunumanii. Artificial intellig...

Kesatuan Pengelola Hutan (KPH) Dolago Tanggunung, as one of the production forest managers in Central Sulawesi, faces serious challenges such as illegal logging, forest encroachment, and a high risk of forest fires. The complexity of managing production forests in this region is further hindered by manual data collection and reporting processes, wh...

To identify early-stage forest fires using ground-based sensing systems, this paper studies the radiation characteristics of smoke particles and interference particles under natural light in different environments based on a rapid dimensional reduction algorithm of forest monitoring images and a multi-dimensional time series signal graph model. It...

RESUM: el present informe recull els resultats de les inspeccions realitzades durant la campanya 2024 de la Xarxa de seguiment de boscos de Catalunya (8x8CAT). Aquesta xarxa permet analitzar les variacions espacials i temporals de la vitalitat forestal mitjançant l’estudi de diferents paràmetres que s’avaluen anualment a tots els arbres de la 8x8CA...

The climatic conditions in southern Italy favor the occurrence and spread of forest fires, with severe long-lasting consequences on the local flora and fauna. On the one hand, biological and chemical in situ measurements are typically used to accurately investigate the evolution of the land affected by fires, with limited spatial coverage. On the o...

A primary objective of forest certification is to ensure that forest management operations and administration provide opportunities for social, economic and environmental development. This mechanism was created to achieve forest sustainability through good forest management practices. It also helps to maintain transparent and accountable processes...

Assessing the functions of forest ecosystems is important for a proper understanding of their role in the natural environment and society. Ecotourism emphasizes minimizing negative impacts on the environment and supports environmental education. Modern information and communication technologies, including forest apps, are helping in this regard. Pr...

Forests play a crucial role in the Earth’s system processes and provide a suite of social and economic ecosystem services, but are significantly impacted by human activities, leading to a pronounced disruption of the equilibrium within ecosystems. Advancing forest monitoring worldwide offers advantages in mitigating human impacts and enhancing our...

Forests are critical ecosystems, supporting biodiversity, economic resources, and climate regulation. The traditional techniques applied in forestry segmentation based on RGB photos struggle in challenging circumstances, such as fluctuating lighting, occlusions, and densely overlapping structures, which results in imprecise tree detection and categ...

Amid warming seas, high rates of pollution and declining fish stocks observed around the UK, the vital role of kelp as ecosystem mediators on our coastlines is increasingly significant; currently estimated at £500 billion. Extensive research on the rapid decline of kelp forests and its potential consequences has prompted the initiation of numerous...