Hasil untuk "Forestry"

T. Adão, Jonás Hruska, L. Pádua et al.

Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors’ ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectral sensors plays a center role—is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing—by isolating the common user from the processes’ mathematical complexity—several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper’s conclusions.

I. Noble, M. Apps, R. Houghton et al.

Pete Smith, M. Bustamante, Helal Ahammad et al.

R. Cavatassi

Jakob Iglhaut, Carlos Cabo, Stefano Puliti et al.

Purpose of ReviewThe adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and practical considerations of this technology and show opportunities that SfM photogrammetry offers for forest practitioners and researchers.Recent FindingsOur examples of key research indicate the successful application of SfM photogrammetry in forestry, in an operational context and in research, delivering results that are comparable to LiDAR surveys. Reviewed studies have identified possibilities for the extraction of biophysical forest parameters from airborne and terrestrial SfM point clouds and derived 2D data in area-based approaches (ABA) and individual tree approaches. Additionally, increases in the spatial and spectral resolution of sensors available for SfM photogrammetry enable forest health assessment and monitoring. The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels.SummaryWe highlight the potential of using unmanned aerial vehicles (UAVs) and consumer-grade cameras for terrestrial SfM-based surveys in forestry. Offering several spatial products from a single sensor, the SfM workflow enables foresters to collect their own fit-for-purpose RS data. With the broad availability of non-expert SfM software, we provide important practical considerations for the collection of quality input image data to enable successful photogrammetric surveys.

F. Pendrill, U. M. Persson, Javier Godar et al.

Abstract Deforestation, the second largest source of anthropogenic greenhouse gas emissions, is largely driven by expanding forestry and agriculture. However, despite agricultural expansion being increasingly driven by foreign demand, the links between deforestation and foreign demand for agricultural commodities have only been partially mapped. Here we present a pan-tropical quantification of carbon emissions from deforestation associated with the expansion of agriculture and forest plantations, and trace embodied emissions through global supply chains to consumers. We find that in the period 2010–2014, expansion of agriculture and tree plantations into forests across the tropics was associated with net emissions of approximately 2.6 gigatonnes carbon dioxide per year. Cattle and oilseed products account for over half of these emissions. Europe and China are major importers, and for many developed countries, deforestation emissions embodied in imports rival or exceed emissions from domestic agriculture. Depending on the trade model used, 29–39% of deforestation-related emissions were driven by international trade. This is substantially higher than the share of fossil carbon emissions embodied in trade, indicating that efforts to reduce greenhouse gas emissions from land-use change need to consider the role of international demand in driving deforestation. Additionally, we find that deforestation emissions are similar to, or larger than, other emissions in the carbon footprint of key forest-risk commodities. Similarly, deforestation emissions constitute a substantial share (˜15%) of the total carbon footprint of food consumption in EU countries. This highlights the need for consumption-based accounts to include emissions from deforestation, and for the implementation of policy measures that cross these international supply-chains if deforestation emissions are to be effectively reduced.

F. Fassnacht, Joanne C. White, M. Wulder et al.

Remote sensing has developed into an omnipresent technology in the scientific field of forestry and is also increasingly used in an operational fashion. However, the pace and level of uptake of remote sensing technologies into operational forest inventory and monitoring programs varies notably by geographic region. Herein, we highlight some key challenges that remote sensing research can address in the near future to further increase the acceptance, suitability and integration of remotely sensed data into operational forest inventory and monitoring programs. We particularly emphasize three recurrent themes: (1) user uptake, (2) technical challenges of remote sensing related to forest inventories and (3) challenges related to map validation. Our key recommendations concerning these three thematic areas include (1) a need to communicate and learn from success stories in those geographic regions where user uptake was successful due to multi-disciplinary collaborations supported by administrative incentives, (2) a shift from regional case studies towards studies addressing ‘real world’ problems focusing on forest attributes that match the spatial scales and thematic information needs of end users and (3) an increased effort to develop, communicate, and apply best-practices for map and model validation including an effort to inform current and future remote sensing scientists regarding the need for and the functionalities of these best practices. Finally, we present information regarding the use of remote sensing for forest inventory and monitoring, combined with recommendations where possible, and highlighting areas of opportunity for additional investigation.

Lara A. Roman, Tenley M. Conway, T. Eisenman et al.

A. Rehman, Hengyun Ma, Munir Ahmad et al.

Abstract Global warming is an important issue from the last few decades and causing climate change due to carbon dioxide emission and greenhouse gases emission. The present study's key aim is to decouple the carbon dioxide emission influence on forestry production, crops production, livestock production, energy usage, population growth, temperature and rainfall in Pakistan. Time series data was utilized ranging from 1970 to 2017, and stationarity of the data was verified by using the unit root tests, while vector autoregressive model was applied to demonstrate the dynamic interaction amid study variables. Furthermore, the Granger causality test was applied to check the causal relation amid variables. The long-run dynamics results through the vector autoregressive model show that forestry production, rainfall, and temperature have a constructive effect on carbon dioxide emission, while crops production, livestock production, energy use, and population growth have a negative effect on carbon dioxide emission. Short-run analysis outcomes also demonstrate that forestry production, crops production, livestock production, population growth, rainfall, and the temperature have a positive effect on carbon dioxide emission, while energy usage has an adverse impact on carbon dioxide emission in Pakistan. Similarly, Granger causality test results also exposed that all variables have a unidirectional association. The Pakistani government needs to take the requisite measures to curb carbon dioxide emission in order to improve agricultural production.

Nathalie Guimarães, L. Pádua, P. Marques et al.

Currently, climate change poses a global threat, which may compromise the sustainability of agriculture, forestry and other land surface systems. In a changing world scenario, the economic importance of Remote Sensing (RS) to monitor forests and agricultural resources is imperative to the development of agroforestry systems. Traditional RS technologies encompass satellite and manned aircraft platforms. These platforms are continuously improving in terms of spatial, spectral, and temporal resolutions. The high spatial and temporal resolutions, flexibility and lower operational costs make Unmanned Aerial Vehicles (UAVs) a good alternative to traditional RS platforms. In the management process of forests resources, UAVs are one of the most suitable options to consider, mainly due to: (1) low operational costs and high-intensity data collection; (2) its capacity to host a wide range of sensors that could be adapted to be task-oriented; (3) its ability to plan data acquisition campaigns, avoiding inadequate weather conditions and providing data availability on-demand; and (4) the possibility to be used in real-time operations. This review aims to present the most significant UAV applications in forestry, identifying the appropriate sensors to be used in each situation as well as the data processing techniques commonly implemented.

Duo Wang, Peikun Jiang, Haibo Zhang et al.

Biochar is a product of biomass thermochemical conversion. Its yield and quality vary significantly with the production technology and process parameters, which also affect its performance in agro and forestry systems. In this review, biochar production technologies including slow pyrolysis, fast pyrolysis, gasification, and torrefaction were compared. The yield of biochar was found to decrease with faster heating rate or more oxygen available. The benefits of biochar application to agro and forestry systems were discussed. Improvements in soil health, plant growth, carbon sequestration, and greenhouse gas mitigation are apparent in many cases, but opposite results do exist, indicating that the beneficial aspect of biochar are limited to particular conditions such as the type of biochar used, the rate of application, soil type, climate, and crop species. Limitations of current studies and future research needed on biochar are also discussed. Specifically, the relationships among biochar production technologies, biochar properties, and biochar performance in agro and forestry systems must be better understood.

Lei Zhang, P. Sun, F. Huettmann et al.

As a nature‐based and cost‐effective solution, forestation plays a crucial role in combating global warming, biodiversity collapse, environmental degradation, and global well‐being. Although China is acknowledged as a global leader of forestation and has achieved considerable overall success in environmental improvements through mega‐forestation programs, many negative effects have also emerged at local scales due to the planting of maladapted tree species. To better help achieve carbon neutrality and the new vision of an ecological civilization, China has committed to further increase forestation. However, where forestation lands and such efforts should really be located is not so well understood yet and agreed upon, especially in the face of rapid climate change. Based on an ensemble‐learning machine, we predicted the spatial habitats (ecological niche) of the forest, grassland, shrubland, and desert under present and future climate conditions based on the natural climax vegetation distribution across China. We show that the potential forestation lands are mainly located in eastern China, which is east of the Hu Line (also known as the Heihe‐Tengchong Line). Under future climate change, forests will shift substantially in the latitudinal, longitudinal, and elevational distribution. Potential forestation lands will increase by 33.1 million hectares through the 2070s, mainly due to the conversions of shrub and grassland to forests along the Hu Line. Our prediction map also indicates that grassland rehabilitation is the universal optimal vegetation restoration strategy in areas west of the Hu Line. This analysis is consistent with much of the observed evidence of forestation failures and recent climate‐change‐induced forest range shifts. Our results provide an overview and further show the importance of adaptive science‐based forestation planning and forest management.

W. Mason, J. Diaci, J. Carvalho et al.

There is increasing interest across Europe in adopting forest management strategies, which promote species and structural diversity through the use of irregular silvicultural systems, an approach often described as continuous cover forestry (CCF). However, there is little information about the proportion of CCF practised across the continent or about the knowledge gaps and other obstacles that limit its use. A survey of respondents in 33 European countries sought to address these issues. The results indicated that the silvicultural systems associated with CCF were single stem, group selection and irregular shelterwood. Rotational forest management (RFM) was more frequent than CCF in about 66 per cent of countries, whereas in 25 per cent the reverse was true. We estimated that between 22 and 30 per cent of European forests are managed through CCF, although good data are lacking. The main knowledge gaps were: uncertainties arising from climate change (e.g. appropriate species choice, carbon storage in CCF), using CCF to increase forest resilience, deployment of mechanized harvesting systems, lack of knowledge about CCF amongst professional foresters and better information on economic implications of this approach. Major obstacles included: little awareness of CCF amongst forest owners, limited competence in CCF within the forestry profession and a scarcity of skilled forest workers to implement this approach, high ungulate populations damaging natural regeneration, a sawmilling sector geared to processing medium-sized logs, subsidy regimes favouring practices associated with RFM and a lack of experience in transforming plantation forests to more diverse structures. Better information on the use of different silvicultural systems is essential to allow policymakers and other stakeholders to monitor progress in diversifying forests. Establishment of a continental network of long-term operational trials (e.g. expanding the existing Association Futaie Irrégulière network) would improve professional understanding of CCF, would demonstrate this approach to forest owners and other stakeholders and could provide a valuable platform for supporting research.

Fitri Rahmafitria, Heri Puspito Diyah Setiyorini, Purna Hindayani et al.

This study explores how destination attributes, such as accessibility, natural attractions, facilities, and disaster knowledge, influence tourists' risk perceptions, ultimately shaping their travel preparedness. Data were collected through questionnaires distributed to 806 tourists visiting a tsunami-prone beach destination in Indonesia. Partial Least Squares Structural Equation Modeling (PLS-SEM) was implemented in the analysis. The findings indicate that accessibility and well-developed tourist facilities tend to lower tourists’ perceived risk, while disaster knowledge heightens it, leading to improved preparedness. Tourists generally feel safer when destinations offer accessible amenities and infrastructure, yet this sense of security may inadvertently decrease their readiness for disasters. This situation creates a paradox: While enhanced accessibility and high-quality amenities contribute to visitor satisfaction, they can unintentionally lower risk perception and preparedness levels. The study challenges the conventional view that accessibility and amenities are inherently beneficial, highlighting the importance of balancing these attributes with proactive risk management strategies. Destination providers, destination management organizations (DMOs), and governments should enhance tourists’ disaster awareness through well-crafted guidelines, educational campaigns, and community engagement programs; these efforts help equip tourists with the necessary knowledge to respond effectively in emergency situations. At the same time, they contribute to the development of safer and more enjoyable tourist destinations.  

Andreas Holzinger, J. Schweier, Christoph Gollob et al.

Recent technological innovations in Artificial Intelligence (AI) have successfully revolutionized many industrial processes, enhancing productivity and sustainability, under the paradigm of Industry 5.0. It offers opportunities for the forestry sector such as predictive analytics, automation, and precision management, which could transform traditional forest operations into smart, effective, and sustainable practices. The paper sets forth to outline the evolution from Industry 5.0 and its promising transition into Forestry 5.0. The purpose is to elucidate the status of these developments, identify enabling technologies, particularly AI, and uncover the challenges hindering the efficient adoption of these techniques in forestry by presenting a framework. However, the gap between potential and practical implementation is primarily due to logistical, infrastructural, and environmental challenges unique to the forestry sector. The solution lies in Human-Centered AI, which, unlike the Industry 4.0 paradigm, aims to integrate humans into the loop rather than replace them, thereby fostering safe, secure, and trustworthy Human-AI interactions. The paper concludes by highlighting the need for Human-Centered AI development for the successful transition to Forestry 5.0 – where the goal is to support the human workers rather than substituting them. A multidisciplinary approach involving technologists, ecologists, policymakers, and forestry practitioners is essential to navigate these challenges, leading to a sustainable and technologically advanced future for the forestry sector. In this transformation, our focus remains on ensuring a balance between increased productivity, nature conservation and social licence, worker safety and satisfaction.

P. J. Verkerk, R. Costanza, L. Hetemäki et al.

To achieve the objectives of the Paris Climate Agreement, a significant reduction in carbon dioxide emissions is needed, as well as increased removals by carbon sinks. In this context, we argue that Climate-Smart Forestry is a necessary, but still missing component in national strategies for implementing actions under the Paris Agreement. Climate-Smart Forestry is needed to (a) increase the total forest area and avoid deforestation, (b) connect mitigation with adaption measures to enhance the resilience of global forest resources, and (c) use wood for products that store carbon and substitute emission-intensive fossil and non-renewable products and materials. Successful Climate-Smart Forestry has important policy implications on finding the right balance between short and long-term goals, as well as between the need for wood production, the protection of biodiversity and the provision of other important ecosystem services. CSF thus can provide important co-benefits that are increasingly being recognized as essential for sustainable well-being.

Y. Diez, Sarah Kentsch, M. Fukuda et al.

Forests are the planet’s main CO2 filtering agent as well as important economical, environmental and social assets. Climate change is exerting an increased stress, resulting in a need for improved research methodologies to study their health, composition or evolution. Traditionally, information about forests has been collected using expensive and work-intensive field inventories, but in recent years unoccupied autonomous vehicles (UAVs) have become very popular as they represent a simple and inexpensive way to gather high resolution data of large forested areas. In addition to this trend, deep learning (DL) has also been gaining much attention in the field of forestry as a way to include the knowledge of forestry experts into automatic software pipelines tackling problems such as tree detection or tree health/species classification. Among the many sensors that UAVs can carry, RGB cameras are fast, cost-effective and allow for straightforward data interpretation. This has resulted in a large increase in the amount of UAV-acquired RGB data available for forest studies. In this review, we focus on studies that use DL and RGB images gathered by UAVs to solve practical forestry research problems. We summarize the existing studies, provide a detailed analysis of their strengths paired with a critical assessment on common methodological problems and include other information, such as available public data and code resources that we believe can be useful for researchers that want to start working in this area. We structure our discussion using three main families of forestry problems: (1) individual Tree Detection, (2) tree Species Classification, and (3) forest Anomaly Detection (forest fires and insect Infestation).

Euan Bowditch, G. Santopuoli, F. Binder et al.

Abstract Climate-Smart Forestry (CSF) is an emerging branch of sustainable forest management that aims to manage forests in response to climate change. Specific CSF strategies are viewed as a way forward for developing suitable management responses and enhancing the provision of ecosystem services. However, there is currently a lack of comprehensive and cohesive assessment to implement CSF. This paper describes the step-by-step process that developed a comprehensive and shared definition of CSF, and the process for selecting indicators that assess the “climate-smartness” of forest management. Adaptation, mitigation and social dimensions are the core focus of the CSF definition, which recognises the need to integrate and avoid development of these aspects in isolation. An iterative participatory process was used with a range of experts in forest-related fields from the CLIMO project, this was subsequently supported by a network analysis to identify sustainable forest management indicators important to CSF. The definition developed here, is an important first step in to promote CSF that will aid practice in the forestry sector. It can be used as a template across Europe, tailored to local contexts. Further work communicating CSF to practitioners and policy-makers will create a CSF practice and culture that will help to safeguard future forest economies and communities.

Lishi Zeng, Xuemei Jiang

Agriculture and forestry are fundamental industries. With the development of the ESG concept, stakeholders are increasingly concerned about the relationship between ESG and agricultural and forestry corporate performance. This paper examines 156 listed agricultural and forestry companies to explore the impact of ESG on corporate performance, both theoretically and empirically, using two-stage least squares. Heterogeneity is explored from the perspective of three sub-dimensions of ESG and industry comparison, respectively. Finally, the impact mechanism of ESG is analyzed from three perspectives: government, market, and company. Results indicate that (1) ESG and corporate performance are significantly and positively correlated, and higher ESG ratings are beneficial to corporate performance improvement. (2) Compared with E performance, S and G performance are more conducive to promoting corporate performance growth. (3) There is no significant difference in the effect of ESG on corporate performance between listed companies in agriculture and forestry. (4) Tax incentives and the regional marketization degree have a negative moderating effect, but the proportion of female executives plays a positive moderating role. These findings provide useful insights for listed companies in agriculture and forestry to improve ESG performance and, consequently, corporate performance, and also promote listed companies to play a greater leading role in green development.

Siddharth Singh, Mickey Mecon Dalbehera, S. Maiti et al.

Production of burnt clay bricks, cement and burning of agricultural/forestry wastes are responsible for major greenhouse gases emission. The present work investigate the effect of treated rice straw and forestry leaves in alkali-activated fly ash bricks with construction & demolition wastes for non-load bearing partitions walls at elevated temperature of 800 °C. 1-4 wt% incorporated agro-forestry wastes fly ash bricks with 10 and 20 wt% ground granulated blast slag (GGBFS) addition shows compressive strength ranging from 8 to 15 MPa. The thermal conductivity of the panels with 1-4 wt% agro-forestry addition varies from 0.4 to 0.5 W/m.K. The sound transmission class (STC) of 20 mm thick agro-forestry waste fly ash samples depict moderate sound insulation properties over the range of 24 to 37 dB. The wallette units of burnt clay bricks and agro-forestry based fly ash bricks show load carrying capacity of 360 kN, 273 kN and 195 kN, 110 kN at temperatures of 35 °C and 800 °C respectively. The present study shows a potential green solution toward sustainable building materials in construction sector leading to reduced depletion of fertile soil used in production of burnt clay bricks.