共查询到19条相似文献，搜索用时 281 毫秒
1.
基于DRNN和ARIMA模型的森林火灾面积时空综合预测方法 总被引：1，自引：0，他引：1
森林火灾是一个跨空间发展的动态过程,不易被传统的分析方法和静态神经网络有效处理.提出一种基于动态回归神经网络(DRNN)和自回归集成移动平均(ARIMA)组合模型的森林火灾时空综合预测方法.该方法先用ARIMA对时空数据的时序进行预测,再用DRNN捕获时空数据间隐藏的空间相关,最后用统计回归将时间和空间预测结果组合起来,得到时空综合预测结果.以广东省森林火灾面积预测为例,说明其原理和建模过程,并对预测结果的精度进行验证.结果表明:由于考虑了数据间的空间关系,该时空综合预测模型可以对森林火灾面积进行较准确有效的预测,比单纯应用ARIMA模型预测精度高,是预测森林火灾等跨空间动态变化问题的有效工具. 相似文献
2.
森林经理学与人工智能 总被引：3，自引：0，他引：3
从森林经理的复杂性、系统性、综合性入手,阐述了森林经理与人工智能的关系.人工智能能够用于预测和模拟森林系统中的非线性行为和许多复杂问题,是现代森林经理工作的一种应用工具;总结了人工智能应用于森林类型分类、图像信息采集与制图、林火监控、规划设计等方面,为森林经理工作提供了一定的应用基础. 相似文献
3.
基于人工神经网络预测广东省森林火灾的发生 总被引：7，自引：0，他引：7
应用人工神经网络建立热带森林火灾发生情况预测的多层神经网络模型,并将林火发生影响因子的历史数据作为样本值,输入模型进行训练。结果表明:利用所选取的输入因子作为样本的人工神经网络,可以对林火的发生发展作出准确有效的预测。文中还对模型的准确性和训练精度进行讨论,进而分析人工神经网络在林火预测中的可行性,证明人工神经网络在林火预测中的应用价值。 相似文献
4.
基于人工智能的木材缺陷检测研究进展 总被引：1，自引：1，他引：0
木材缺陷检测是木制品加工前的重要步骤,为了提高检测效率和经济效益,木材缺陷检测也从传统的人工方法向智能化方向转变。随着计算机技术的不断提高,人工智能得到快速发展,人工智能在木材缺陷检测中的应用也进一步增加。目前,人工智能主要通过机器学习、人工神经网络、深度学习等算法实现对木材缺陷的预处理和检测。文中阐述部分常用人工智能算法在木材缺陷检测中的应用,包括相关算法的原理、特点;综合分析算法优缺点,并对人工智能技术在木材缺陷检测中的研究进行了展望。 相似文献
5.
地理信息系统在林业中的应用、问题及前景(英文) 总被引：7，自引：0，他引：7
森林经营决策必须建立在现在和未来森林资源的时空分布信息基础上 ,而跟踪和获得森林资源信息的变化极具挑战性 ,因为森林资源是一个处于持续不断变化的动态生态系统 ,它的不定性和复杂性决定了森林经营需要更有用的和更及时的信息 ,因此时空信息是进行有效森林决策的基石 .现有的传统技术已满足不了大规模的森林规划和经营的需求 .地理信息系统是基于计算机基础之上的分析工具 ,能为森林经理提供复杂的空间信息 ,并建立定量模型 .本文综述了地理信息系统在森林经营方面的应用 ;指出了地理信息系统在林业中的效益、问题和局限 ;分析了地理信息系统在同其它空间技术如遥感、全球定位系统、人工智能建模、决策支持系统等方面的最新进展与发展方向 相似文献
6.
该文综述了近年来国内外有关蛋白质结构预测的方法,并阐述了人工神经网络方法在蛋白质结构预测中的应用。借鉴蛋白质结构预测方法,叙述了如何用人工神经网络方法对林木蛋白质结构进行预测及预测过程中可能存在的问题和如何提高预测精度,提出了用相同的人工神经网络方法对林木蛋白质结构进行预测的精度要比蛋白质结构预测精度好并分析其原因。 相似文献
7.
应用人工神经网络方法分别建立土地资源预测、森林蓄积量预测、各龄组蓄积量预测三层前馈反向传播神经网络模型对森林资源进行预测模拟.预测结果表明在小样本条件下,森林资源预测神经网络模型预测精度较高,开辟了森林资源预测新途径. 相似文献
8.
传统的森林病虫害监测方法已经不能满足对森林健康保护的需求.随着物联网技术的发展, 利用物联网进行森林病虫害监测成为研究热点, 具有很好的发展前景.文中介绍了利用物联网进行森林病虫害监测的原理, 并结合物联网在果树和农业病虫害监测中的研究现状阐述了物联网在森林病虫害监测中的研究现状以及如何构建森林病虫害监测物联网, 同时对其效益进行了分析; 在指出目前基于物联网架构的森林病虫害监测存在问题的基础上, 提出对未来应用的展望, 以期通过推广物联网技术应用来提高病虫害预测预报的及时性和准确性. 相似文献
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10.
人工神经网络在林业上的应用研究进展 总被引：2，自引：1，他引：1
在目前的林业生产中,林业作业机械化、自动化与智能化的程度存在着一定的不足,在林业作业中借助人工神经网络技术优化作业系统可以有效地提高作业效率和精度。文中概述了国内外人工神经网络在林业作业应用中的研究现状以及人工神经网络在林业作业应用中的优势,介绍了人工神经网络在植树造林、森林监测、森林采伐、木材加工4个方面的应用现状,在分析林业作业应用人工神经网络存在问题的基础上,提出了人工神经网络在林业作业应用中未来的发展方向,以期提高林业作业的智能性和准确性。 相似文献
11.
Naomi Radke Rasoul Yousefpour Roderich von Detten Stefan Reifenberg Marc Hanewinkel 《Annals of Forest Science》2017,74(2):43
Key message
Multi-objective robust decision making is a promising decision-making method in forest management under climate change as it adequately considers deep uncertainties and handles the long-term, inflexible, and multi-objective character of decisions. This paper provides guidance for application and recommendation on the design.Context
Recent studies have promoted the application of robust decision-making approaches to adequately consider deep uncertainties in natural resource management. Yet, applications have until now hardly addressed the forest management context.Aims
This paper seeks to (i) assemble different definitions of uncertainty and draw recommendation to deal with the different levels in decision making, (ii) outline those applications that adequately deal with deep uncertainty, and (iii) systematically review the applications to natural resources management in order to (iv) propose adoption in forest management.Methods
We conducted a systematic literature review of robust decision-making approaches and their applications in natural resource management. Different levels of uncertainty were categorized depending on available knowledge in order to provide recommendations on dealing with deep uncertainty. Robust decision-making approaches and their applications to natural resources management were evaluated based on different analysis steps. A simplified application to a hypothetical tree species selection problem illustrates that distinct robustness formulations may lead to different conclusions. Finally, robust decision-making applications to forest management under climate change uncertainty were evaluated and recommendations drawn.Results
Deep uncertainty is not adequately considered in the forest management literature. Yet, the comparison of robust decision-making approaches and their applications to natural resource management provide guidance on applying robust decision making in forest management regarding decision contexts, decision variables, robustness metrics, and how uncertainty is depicted.Conclusion
As forest management is characterized by long decision horizons, inflexible systems, and multiple objectives, and is subject to deeply uncertain climate change, the application of a robust decision-making framework using a global, so-called satisficing robustness metric is recommended. Further recommendations are distinguished depending on the decision context.12.
《Scandinavian Journal of Forest Research》2012,27(6):473-474
Abstract Climatic warming may lead to increased or decreased future forest productivity. However, more frequent heat waves, droughts and storms and accompanying pathogen attacks are also expected for Europe and are considered to be increasingly important abiotic and biotic stress factors for forests. Adaptive forestry can help forest ecosystems to adapt to these new conditions in order to achieve management goals, maintain desired forest ecosystem services and reduce the risks of forest degradation. With a focus on central Europe, this paper presents the following management strategies: (1) conservation of forest structures, (2) active adaptation, and (3) passive adaptation. The feasibility and criteria for application of the different strategies are discussed. Forest adaptation may entail the establishment of “neonative” forests, including the use and intermixing of native and non-native tree species as well as non-local tree provenances that may adapt better to future climate conditions. An integrative adaptive management concept is proposed that combines (1) species suitability tests and modelling activities at the international scale, (2) priority mapping of adaptation strategies at the national to regional scale, and (3) implementation at the local scale. To achieve this, an international experimental trial system is required to test suitable adaptive measures throughout Europe and worldwide. 相似文献
13.
Guangyu Wang Tongli Wang Haijun Kang Shari Mang Brianne Riehl Brad Seely Shirong Liu Futao Guo Qinglin Li John L. Innes 《林业研究》2016,27(3):469-488
Climate change is a threat to the stability and productivity of forest ecosystems throughout the Asia-Pacific region. The loss of forests due to climate-induced stress will have extensive adverse impacts on biodiversity and an array of ecosystem services that are essential for the maintenance of local economies and public health. Despite their importance, there is a lack of decision-support tools required to evaluate the potential effects of climate change on Asia-Pacific ecosystems and economies and to aid in the development of regionally appropriate adaptation and mitigation strategies. The project Adaptation of Asia-Pacific Forests to Climate Change, summarized herein, aims to address this lack of knowledge and tools and to provide support for regional managers to develop effective policy to increase the adaptive capacity of Asia-Pacific forest ecosystems. This objective has been achieved through the following activities: (1) development of a high-resolution climate downscaling model, ClimateAP, applicable to any location in the region; (2) development of climate niche models to evaluate how climate change might affect the distribution of suitable climatic conditions for regionally important tree species; (3) development and application of forest models to assess alternative management strategies in the context of management objectives and the projected impacts of climate change; (4) evaluation of models to assess forest fire risk and the relationship between forest fire and climate change; (5) development of a technique to assess ecosystem carbon storage using LiDAR; and (6) evaluation of how vegetation dynamics respond to climate change using remote sensing technology. All project outputs were developed with a focus on communication and extension to facilitate the dissemination of results to regional forest resource managers to support the development of effective mitigation and adaptation policy. 相似文献
14.
Estimating aboveground biomass of Pinus densata-dominated forests using Landsat time series and permanent sample plot data 总被引：3，自引：0，他引：3
Southwest China is one of three major forest regions in China and plays an important role in carbon sequestration.Accurate estimations of changes in aboveground biomass are critical for understanding forest carbon cycling and promoting climate change mitigation.Southwest China is characterized by complex topographic features and forest canopy structures,complicating methods for mapping aboveground biomass and its dynamics.The integration of continuous Landsat images and national forest inventory data provides an alternative approach to develop a long-term monitoring program of forest aboveground biomass dynamics.This study explores the development of a methodological framework using historical national forest inventory plot data and Landsat TM timeseries images.This method was formulated by comparing two parametric methods:Linear Regression for Multiple Independent Variables(MLR),and Partial Least Square Regression(PLSR);and two nonparametric methods:Random Forest(RF)and Gradient Boost Regression Tree(GBRT)based on the state of forest aboveground biomass and change models.The methodological framework mapped Pinus densata aboveground biomass and its changes over time in Shangri-la,Yunnan,China.Landsat images and national forest inventory data were acquired for 1987,1992,1997,2002 and 2007.The results show that:(1)correlation and homogeneity texture measures were able to characterize forest canopy structures,aboveground biomass and its dynamics;(2)GBRT and RF predicted Pinus densata aboveground biomass and its changes better than PLSR and MLR;(3)GBRT was the most reliable approach in the estimation of aboveground biomass and its changes;and,(4)the aboveground biomass change models showed a promising improvement of prediction accuracy.This study indicates that the combination of GBRT state and change models developed using temporal Landsat and national forest inventory data provides the potential for developing a methodological framework for the long-term mapping and monitoring program of forest aboveground biomass and its changes in Southwest China. 相似文献
15.
3S技术及其在林业上的应用 总被引：10，自引：0，他引：10
随着社会经济的发展，传统的森林资源调查方法因存许多局限性而难以满足现代林业发展的需要。3S技术的发展与应用，一方面可以弥补传统调查方法的不足；另一方面作业项技术手段，在森林资源监测、野生动物调查、植被调查、病虫害预报、林业信息管理、林业专题图编制和森林经营经营管理等方面将发挥重要的作用。 相似文献
16.
Mapping dead wood distribution in a temperate hardwood forest using high resolution airborne imagery
Dead wood, in the form of coarse woody debris and standing dead wood, or snags, is an essential structural component of forest ecosystems. It plays a key role in nutrient cycling, ecosystem functions and provision of habitat for a wide variety of species. In order to manage dead wood in a temperate hardwood forest, an understanding of its availability and spatial distribution is important. This research evaluates airborne digital camera remote sensing for mapping temperate forest dead wood across an area within Gatineau Park, Canada. Two approaches were evaluated: (1) direct detection and mapping of canopy dead wood (dead branches and tall snags) through the combination of three techniques in a hybrid classification: ISODATA clustering, object-based classification, and spectral unmixing, and (2) indirect modelling of coarse woody debris and snags using spectral and spatial predictor variables extracted from the imagery. Indirect modelling did not provide useful results while direct detection was successful with field validation showing 94% accuracy for detected canopy level dead wood objects (i.e. 94% of validation sites with canopy dead wood were detected correctly) and 90% accuracy for control sites (i.e. 90% of validation sites with no canopy level dead wood were identified correctly). The procedures presented in this paper are repeatable and could be used to monitor dead wood over time, potentially contributing to applications in forest carbon budget estimation, biodiversity management, and forest inventory. 相似文献
17.
竹林是我国重要的森林资源,竹林资源的实时监测是竹林经营管理的重要依据,同时作为陆地生态系统的重要组成部分,其在缓解气候变化方面发挥着重要作用。遥感技术以其大范围、周期性、自动化等优点可以用来提供空间明确和定量的信息,适用于竹林资源的动态监测,也可用于竹林相关参数的提取。本文主要介绍了遥感技术在竹林资源监测和竹林相关参数提取中的应用,分析了该技术的优缺点,并对其未来应用前景进行了展望。 相似文献
18.
Advances in modelling and decision support systems for vegetation management in young forest plantations 总被引：1，自引：0，他引：1
The two most common forest vegetation management objectivesare to (1) minimize resource competition, and (2) to developmethods for managing specific weed species. This paper reviewsrelevant models and decision support systems for assisting inachieving these objectives. The aim of reducing resource competitionis to increase crop-tree growth and survival. Several modellingapproaches have been applied to this problem and these generallyestimate crop survival and growth benefits following some formof generalized weed control. Linkages with models of older treecrops are needed for comparing vegetation management strategiesin the context of complete silvicultural regimes. More refinedindividual tree models use competition indices to estimate thequantity of weed vegetation within the growing space aroundeach tree. The indices reflect resource use by the weeds andare sensitive to changes in weed growth over time and to theapplication of specific vegetation management treatments. Hybridand process-based models have the potential to provide moregeneralized models of inter-specific competition, but theirusefulness for forest practitioners has yet to be proven. Someforest vegetation management problems require a more detailedunderstanding of the biology and ecology of a specific species.In this case, different modelling approaches that consider overallweed population dynamics, distribution or spread may be appropriate. 相似文献