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市场调查报告书
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1881344

全球野火探测系统市场：依组件、技术、应用和地区划分 - 市场规模、行业趋势、机会分析和预测（2025-2033 年）

Global Forest Wildfire Detection System Market: By Component, Technology, Application, Region - Market Size, Industry Dynamics, Opportunity Analysis and Forecast For 2025-2033
出版日期: | 出版商: Astute Analytica | 英文 197 Pages | 商品交期: 最快1-2个工作天内

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简介目录

全球野火侦测系统市场正经历显着成长，反映出全球对高效火灾监测和管理解决方案的需求日益增长。 2024 年，该市场规模约为 7.7264 亿美元，这得益于野火风险的增加和先进探测技术的广泛应用，市场基础稳固。展望未来，预计该市场将继续稳定成长，到 2033 年将超过 13.3899 亿美元。 2025 年至 2033 年的复合年增长率 (CAGR) 为 6.30%，这印证了野火探测系统在全球范围内的持续扩张及其日益增长的重要性。

推动市场成长的关键因素有很多，其中最主要的是气候变迁导致野火发生的频率和严重程度不断增加。气温上升、长期干旱和气候模式变化加剧了野火的发生，使得早期发现和快速反应比以往任何时候都更加重要。世界各国政府正在透过实施旨在提高野火防范和缓解能力的严格法规来应对这项挑战，从而推动了对更先进探测系统的需求。技术的快速进步也在市场转型中发挥关键作用。

市场趋势

野火探测系统市场竞争格局瞬息万变，既有成熟企业，也有创新新创公司，它们透过技术突破和全面的服务组合来争夺市场领导地位。这种多元化的市场参与者正在推动快速创新，并扩大解决方案的范围，以应对日益严重的全球野火威胁。哥伦比亚于2025年11月启动了一项基于卫星的国家野火探测计划，就是这一趋势的一个显着例证。这项开创性的措施在拉丁美洲尚属首例，它得益于国家灾害风险管理部门（UNGRD）与OroraTech的策略合作，并得到了当地经销商GeoSpatial的支持。

另一个重大进展是，以色列航空航太工业公司 (IAI) 和 Fire Free Forest (3F) 于 2025 年 7 月签署了一份战略谅解备忘录 (MOU)，共同开发先进的空中灭火平台。此次合作旨在利用尖端技术和作战能力来应对日益严重的全球野火威胁。该平台基于 IAI 的 767BDSF，这是一款经过大幅改装的 BEDEK 特种运输机，专为灭火任务而设计。这款创新空中系统旨在增强快速反应能力，并能够更有效地从空中控制和扑灭野火。

核心成长驱动因子

人工智慧 (AI) 和机器学习 (ML) 的融合已成为野火探测系统市场的决定性因素，这标誌着其从理论可能性转变为实用且必不可少的技术。这些先进技术不再是未来概念，而是发展成为现代探测系统的关键组成部分，从根本上改变了野火的识别和管理方式。人工智慧演算法拥有无与伦比的能力，能够即时处理和分析来自卫星、无人机和地面感测器等各种来源的大量数据。这使得它们能够检测到人类操作员无法快速准确识别的复杂模式和细微异常。

新兴机会

野火侦测的未来越来越注重精确预测潜在火灾的位置和时间，这标誌着管理方式从被动回应向主动出击的重大转变。这一发展趋势得益于将先进的人工智慧 (AI) 和机器学习演算法与各种资料来源（包括历史野火记录、当前天气状况以及来自各种感测器的即时输入）相结合。透过整合这些多样化的资料集，企业正在建立先进的风险评估模型，这些模型能够分析复杂模式，并以前所未有的精度预测野火风险。

优化障碍

由于部署先进探测技术成本高昂，野火探测系统市场的成长面临巨大的挑战。 人工智慧摄影机、无人机、卫星影像和大型感测器网路等先进系统需要大量的资金投入，不仅包括初始购置和安装成本，还包括持续的维护、资料处理和基础设施更新。这些成本可能成为一大障碍，尤其对于预算有限的小型市政当局和地区而言，会减缓尖端侦测解决方案的普及应用。

目录

第一章：研究架构

  • 研究目标
  • 产品概述
  • 市场区隔

第二章：研究方法

  • 质性研究
    • 一手和二手资料来源
  • 量化研究
    • 一手和二手资料来源
  • 依地区划分的原始调查受访者
  • 研究假设
  • 市场规模估算
  • 资料三角验证

第三章：摘要整理：全球森林火灾侦测系统市场

第四章：全球森林火灾侦测系统市场概论

  • 产业价值链分析
    • 服务提供者
    • 最终用户
  • 行业展望
    • 关键统计数据概述
  • PESTLE 分析
  • 波特五力分析
    • 供应商议价能力
    • 买方议价能力
    • 替代品威胁
    • 新进入者威胁
    • 竞争强度
  • 市场动态与趋势
    • 成长推动因素
    • 阻碍因素
    • 挑战
    • 主要趋势
  • COVID-19 对市场成长趋势的影响评估
  • 市场成长与展望
    • 市场收入预测及预测（2019-2032）
  • 竞争格局概览
    • 市场集中度
    • 公司竞争占有率分析（价值，2023 年）
    • 竞争格局图

第五章：全球森林火灾侦测系统市场依组件分析

  • 主要见解
  • 市场规模及预测（2019-2032 年）
    • 软体
    • 硬体
    • 服务

第六章：全球森林火灾侦测系统市场依技术分析

  • 主要见解
  • 市场规模及预测（2019-2032 年）
    • 感测器网路和监控
    • 卫星影像
    • 无人机
    • 人工智慧 (AI) 与机器学习
    • 其他

第七章 全球森林火灾侦测系统市场依应用领域分析

  • 主要见解
  • 市场规模及预测 (2019-2032)
    • 早期预警系统
    • 火灾监控与控制
    • 环境监测
    • 研究与保护

第八章 全球森林火灾侦测系统市场依应用领域分析

  • 主要见解
  • 市场规模及预测 (2019-2032)
    • 公园
    • 森林

第九章 全球森林火灾侦测系统市场依应用领域分析

  • 主要洞察
  • 市场规模及预测，2019-2032
    • 北美
    • 欧洲
    • 亚太
    • 中东和非洲
    • 南美

第十章：北美森林火灾侦测系统市场分析

第十一章：欧洲森林火灾侦测系统市场分析

第十二章：亚太森林火灾侦测系统市场分析

第十三章：中东与非洲森林火灾侦测系统市场分析

第十四章：南美洲森林火灾侦测系统市场分析

第十五章：韩国森林火灾侦测系统市场分析

第十六章 公司简介

  • 罗伯特博世有限公司
  • Dryad Networks GmbH
  • Insight Robotics
  • IQ FireWatch
  • Orora Technologies
  • Paratronic
  • SmokeD
  • 其他主要厂商

第一章：研究架构

  • 研究目标
  • 产品概述
  • 市场区隔

第二章：研究架构与研究方法

  • 质性研究
    • 一手和二手资料来源
  • 量化研究
    • 一手和二手资料来源
  • 依地区划分的原始调查受访者
  • 研究假设
  • 市场规模估算
  • 数据三角测量

第三章：摘要整理：全球森林火灾侦测系统市场

第四章：全球森林火灾侦测系统市场概论

  • 产业价值链分析
    • 服务提供者
    • 最终用户
  • 行业展望
    • 关键统计数据概述
  • PESTLE 分析
  • 波特五力分析
    • 供应商议价能力
    • 买方议价能力
    • 替代品威胁
    • 新进入者威胁
    • 竞争强度
  • 市场动态与趋势
    • 成长推动因素
    • 阻碍因素
    • 挑战
    • 主要趋势
  • 新冠疫情对市场成长趋势的影响评估
  • 市场成长与展望
    • 市场收入估计与预测（2019-2032）
  • 竞争格局概览
    • 市场集中度
    • 公司竞争占有率分析（价值，2023）
    • 竞争格局图

第五章 全球森林火灾侦测系统市场依组件分析

  • 主要见解
  • 市场规模与预测2019-2032
    • 软体
    • 硬体
    • 服务

第六章：全球森林火灾侦测系统市场依技术划分的分析

  • 主要见解
  • 市场规模及预测（2019-2032）
    • 感测器网路和监控
    • 卫星影像
    • 无人机
    • 人工智慧 (AI) 与机器学习
    • 其他

第七章：全球森林火灾侦测系统市场依应用划分的分析

  • 主要见解
  • 市场规模及预测（2019-2032）
    • 早期预警系统
    • 火灾监测与管理
    • 环境监测
    • 研究与保护

第八章：全球森林火灾侦测系统市场区域分析

  • 主要见解
  • 市场规模及预测（2019-2032）
    • 公园
    • 森林

第九章：全球森林火灾侦测系统市场区域分析

  • 主要见解
  • 市场规模及预测（2019-2032）
    • 北美
    • 欧洲
    • 亚太地区
    • 中东和非洲
    • 南美

第十章：北美森林火灾侦测系统市场分析

第十一章：欧洲森林火灾侦测系统市场分析

第十二章：亚太地区森林火灾侦测系统市场分析

第十三章：中东与非洲森林火灾侦测系统市场分析

第十四章：南美洲森林火灾侦测系统市场分析

第十五章：韩国森林火灾侦测系统市场分析

第十六章：公司简介

  • 罗伯特博世有限公司
  • Dryad Networks GmbH
  • Insight Robotics
  • IQ FireWatch
  • Orora Technologies
  • Paratronic
  • SmokeD
  • 其他主要厂商
简介目录
Product Code: AA0923620

The global forest wildfire detection system market is undergoing substantial growth, reflecting the escalating need for effective wildfire monitoring and management solutions worldwide. In 2024, the market was valued at approximately US$ 772.64 million, demonstrating a strong foundation driven by escalating wildfire risks and the increasing adoption of advanced detection technologies. Looking ahead, the market is projected to grow steadily, with valuations expected to surpass US$ 1,338.99 million by 2033. This growth represents a compound annual growth rate (CAGR) of 6.30% over the forecast period from 2025 to 2033, underscoring the sustained expansion and rising importance of wildfire detection systems on a global scale.

Several key factors contribute to this market growth, foremost among them being the increasing incidence and severity of wildfires fueled by climate change. Rising temperatures, prolonged droughts, and changing weather patterns have intensified wildfire occurrences, making early detection and rapid response more critical than ever. Governments worldwide are responding by implementing stringent regulations aimed at improving wildfire preparedness and mitigation, which in turn drives demand for more sophisticated detection systems. Additionally, rapid technological advancements have played a pivotal role in transforming the market.

Noteworthy Market Developments

The competitive landscape in the wildfire detection system market is highly dynamic, characterized by a blend of well-established corporations and innovative startups vying to lead through technological breakthroughs and comprehensive service portfolios. This mix of players is driving rapid innovation and expanding the scope of solutions available to address the growing threat of wildfires worldwide. A notable example of this dynamic occurred in November 2025, when Colombia became the first country in Latin America to implement a national wildfire detection program utilizing satellite technology. This groundbreaking initiative was made possible through a strategic partnership between the National Unit for Disaster Risk Management (UNGRD) and OroraTech, with support from the local representative GeoSpatial.

In another significant development, Israel Aerospace Industries (IAI) and Fire Free Forests (3F) entered into a strategic Memorandum of Understanding in July 2025 to jointly develop an advanced airborne firefighting platform. This collaboration aims to address the escalating global wildfire threat with cutting-edge technology and operational capabilities. The platform will be based on the 767BDSF, an extensively modified version of IAI's BEDEK Special Freighter aircraft, specially adapted for firefighting missions. This innovative airborne system is designed to enhance rapid response capabilities, enabling more effective containment and suppression of wildfires from the air.

Core Growth Drivers

The integration of Artificial Intelligence (AI) and Machine Learning (ML) has become a defining characteristic of the wildfire detection system market, reflecting a shift from theoretical potential to practical, indispensable technology. These advanced technologies are no longer futuristic concepts but have evolved into critical elements of modern detection systems, fundamentally transforming how wildfires are identified and managed. AI algorithms have the remarkable capability to process and analyze enormous volumes of data gathered from diverse sources such as satellites, drones, and ground-based sensors in real-time. This allows for the detection of intricate patterns and subtle anomalies that would be impossible for human operators to recognize quickly or accurately.

Emerging Opportunity Trends

The future of wildfire detection is increasingly focused on the ability to precisely predict the location and timing of potential fires, marking a significant shift from reactive responses to proactive management. This evolution is driven by the integration of advanced artificial intelligence (AI) and machine learning algorithms with a broad spectrum of data sources, including historical wildfire records, current weather conditions, and real-time inputs from various sensors. By combining these diverse datasets, companies are creating sophisticated risk assessment models capable of analyzing complex patterns and forecasting wildfire risks with greater accuracy than ever before.

Barriers to Optimization

The growth of the wildfire detection system market faces notable challenges due to the high costs associated with implementing advanced detection technologies. Sophisticated systems such as AI-powered cameras, drones, satellite imaging, and extensive sensor networks require significant financial investment not only in the initial purchase and installation but also in ongoing maintenance, data processing, and infrastructure upgrades. These expenses can be prohibitive, especially for smaller municipalities or regions with limited budgets, potentially slowing the widespread adoption of cutting-edge detection solutions.

Detailed Market Segmentation

By Technology, Satellite imaging technology holds a dominant position in the forest wildfire detection system market, generating over 34.2% of the total revenue and maintaining its leadership role through ongoing advancements and investments. This technology's prominence is due to its unparalleled ability to monitor vast and often inaccessible forest areas from space, providing early warnings and detailed data critical for effective wildfire management. Currently, both public and private sectors are investing heavily in next-generation satellite constellations that enhance wildfire detection resolution, speed, and accuracy, allowing faster response times and informed decision-making.

By Component, the hardware segment is rapidly establishing itself as a crucial component in the global forest wildfire detection system market, expected to generate over 56.6% of the total revenue. This segment includes a diverse array of essential equipment, such as ground-based sensors, AI-powered cameras, and drones, all of which play a vital role in early wildfire detection and monitoring. The advancements in hardware technology have significantly enhanced the ability to identify fires at their inception, allowing for quicker response times and potentially reducing the devastating impacts of wildfires on both natural ecosystems and human communities.

By End Use, the forest segment holds a commanding dominance in the forest wildfire detection system market, accounting for over 62.20% of the total market share. This predominance is largely driven by the extensive and often remote nature of forested landscapes, which are highly vulnerable to wildfires. The sheer vastness of these areas presents unique challenges for early detection and monitoring, making specialized wildfire detection systems essential for effective management and mitigation.

By Application, Early warning and alert systems dominate the wildfire detection system market, capturing the largest share of 45.38%. As a result of this significant market share, these systems are essential for rapidly disseminating vital information among the public and emergency responders. In the event of a wildfire, their ability to provide timely alerts and warnings is essential for minimising damage, protecting lives, and allowing swift response actions. The effectiveness of these systems in communication and coordination has made them indispensable components of modern wildfire management strategies.

Segment Breakdown

By Technology

  • Sensor Network & Surveillance
  • Camera (Vision) Systems
  • Infrared (IR) Camera or Thermal Imaging Camera
  • IR spectrometers
  • LIDAR
  • Satellite Imaging
  • Drones
  • AI and Machine Learning
  • Others

By End Use

  • Park
  • Forest

By Component

  • Software
  • Hardware
  • Services

By Application

  • Early Warning and Alert Systems
  • Fire Monitoring and Management
  • Environmental Monitoring
  • Research and Conservation

By Region

  • North America
  • The US
  • Canada
  • Mexico
  • Europe
  • The U.K.
  • Germany
  • France
  • Spain
  • Poland
  • Belgium
  • Finland
  • Netherlands
  • Portugal
  • Sweden
  • Switzerland
  • Rest of Europe
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia & New Zealand
  • ASEAN
  • South Korea
  • Rest of Asia Pacific
  • Middle East & Africa
  • UAE
  • Saudi Arabia
  • Qatar
  • South Africa
  • Morocco
  • Rest of MEA
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Chile
  • Peru
  • Rest of South America

Geography Breakdown

  • North America firmly holds the position as the leading region in the forest wildfire detection system market, commanding a commanding share of over 41% globally. This dominant standing is a direct result of significant investments spurred by the increasing frequency and intensity of wildfires across the continent. Growing awareness of the devastating impacts these fires have on ecosystems, communities, and economies has prompted governments and private entities alike to prioritize early detection and rapid response technologies.
  • Within North America, the United States spearheads this market, with its wildfire detection system market projected to reach US$ 235.19 million in 2024. This growth is underpinned by a strong commitment at the federal level, exemplified by a substantial US$ 1.6 billion allocation dedicated to wildland fire management in 2025. Such significant funding reflects the urgency placed on enhancing wildfire monitoring infrastructure and improving emergency response capabilities. The financial support is enabling widespread adoption and deployment of cutting-edge detection technologies designed to identify wildfire outbreaks swiftly, minimizing damage and enhancing public safety.

Leading Market Participants

  • Robert Bosch GmbH
  • Dryad Networks GmbH
  • Insight Robotics
  • IQ FireWatch
  • Orora Technologies
  • Paratronic
  • SmokeD
  • Other Prominent Players

Table of Content

Chapter 1. Research Framework

  • 1.1 Research Objective
  • 1.2 Product Overview
  • 1.3 Market Segmentation

Chapter 2. Research Methodology

  • 2.1 Qualitative Research
    • 2.1.1 Primary & Secondary Sources
  • 2.2 Quantitative Research
    • 2.2.1 Primary & Secondary Sources
  • 2.3 Breakdown of Primary Research Respondents, By Region
  • 2.4 Assumption for the Study
  • 2.5 Market Size Estimation
  • 2.6. Data Triangulation

Chapter 3. Executive Summary: Global Forest Wildfire Detection System Market

Chapter 4. Global Forest Wildfire Detection System Market Overview

  • 4.1. Industry Value Chain Analysis
    • 4.1.1. Service Provider
    • 4.1.2. End User
  • 4.2. Industry Outlook
    • 4.2.1. Overview of key statistics
  • 4.3. PESTLE Analysis
  • 4.4. Porter's Five Forces Analysis
    • 4.4.1. Bargaining Power of Suppliers
    • 4.4.2. Bargaining Power of Buyers
    • 4.4.3. Threat of Substitutes
    • 4.4.4. Threat of New Entrants
    • 4.4.5. Degree of Competition
  • 4.5. Market Dynamics and Trends
    • 4.5.1. Growth Drivers
    • 4.5.2. Restraints
    • 4.5.3. Challenges
    • 4.5.4. Key Trends
  • 4.6. Covid-19 Impact Assessment on Market Growth Trend
  • 4.7. Market Growth and Outlook
    • 4.7.1. Market Revenue Estimates and Forecast (US$ Mn), 2019 - 2032
  • 4.8. Competition Dashboard
    • 4.8.1. Market Concentration Rates
    • 4.8.2. Company Market Share Analysis (Value %), 2023
    • 4.8.3. Competitor Mapping

Chapter 5. Global Forest Wildfire Detection System Market Analysis, By Component

  • 5.1. Key Insights
  • 5.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 5.2.1. Software
    • 5.2.2. Hardware
    • 5.2.3. Services

Chapter 6. Global Forest Wildfire Detection System Market Analysis, By Technology

  • 6.1. Key Insights
  • 6.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 6.2.1. Sensor Network & Surveillance
      • 6.2.1.1. Camera (Vision) Systems
      • 6.2.1.2. Infrared (IR) Camera or Thermal Imaging Camera
      • 6.2.1.3. IR spectrometers
      • 6.2.1.4. LIDAR
    • 6.2.2. Satellite Imaging
    • 6.2.3. Drones
    • 6.2.4. AI and Machine Learning
    • 6.2.5. Others

Chapter 7. Global Forest Wildfire Detection System Market Analysis, By Application

  • 7.1. Key Insights
  • 7.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 7.2.1. Early Warning and Alert Systems
    • 7.2.2. Fire Monitoring and Management
    • 7.2.3. Environmental Monitoring
    • 7.2.4. Research and Conservation

Chapter 8. Global Forest Wildfire Detection System Market Analysis, By End Use

  • 8.1. Key Insights
  • 8.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 8.2.1. Parks
    • 8.2.2. Forest

Chapter 9. Global Forest Wildfire Detection System Market Analysis, By Region

  • 9.1. Key Insights
  • 9.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 9.2.1. North America
      • 9.2.1.1. The U.S.
      • 9.2.1.2. Canada
      • 9.2.1.3. Mexico
    • 9.2.2. Europe
      • 9.2.2.1. Western Europe
        • 9.2.2.1.1. The UK
        • 9.2.2.1.2. Germany
        • 9.2.2.1.3. France
        • 9.2.2.1.4. Italy
        • 9.2.2.1.5. Spain
        • 9.2.2.1.6. Rest of Western Europe
      • 9.2.2.2. Eastern Europe
        • 9.2.2.2.1. Poland
        • 9.2.2.2.2. Russia
        • 9.2.2.2.3. Rest of Eastern Europe
    • 9.2.3. Asia Pacific
      • 9.2.3.1. China
      • 9.2.3.2. India
      • 9.2.3.3. Japan
      • 9.2.3.4. South Korea
      • 9.2.3.5. Australia & New Zealand
      • 9.2.3.6. ASEAN
      • 9.2.3.7. Rest of Asia Pacific
    • 9.2.4. Middle East & Africa
      • 9.2.4.1. UAE
      • 9.2.4.2. Saudi Arabia
      • 9.2.4.3. South Africa
      • 9.2.4.4. Rest of MEA
    • 9.2.5. South America
      • 9.2.5.1. Argentina
      • 9.2.5.2. Brazil
      • 9.2.5.3. Rest of South America

Chapter 10. North America Forest Wildfire Detection System Market Analysis

  • 10.1. Key Insights
  • 10.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 10.2.1. By Component
    • 10.2.2. By Technology
    • 10.2.3. By Application
    • 10.2.4. By End Use
    • 10.2.5. By Country

Chapter 11. Europe Forest Wildfire Detection System Market Analysis

  • 11.1. Key Insights
  • 11.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 11.2.1. By Component
    • 11.2.2. By Technology
    • 11.2.3. By Application
    • 11.2.4. By End Use
    • 11.2.5. By Country

Chapter 12. Asia Pacific Forest Wildfire Detection System Market Analysis

  • 12.1. Key Insights
  • 12.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 12.2.1. By Component
    • 12.2.2. By Technology
    • 12.2.3. By Application
    • 12.2.4. By End Use
    • 12.2.5. By Country

Chapter 13. Middle East & Africa Forest Wildfire Detection System Market Analysis

  • 13.1. Key Insights
  • 13.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 13.2.1. By Component
    • 13.2.2. By Technology
    • 13.2.3. By Application
    • 13.2.4. By End Use
    • 13.2.5. By Country

Chapter 14. South America Forest Wildfire Detection System Market Analysis

  • 14.1. Key Insights
  • 14.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 14.2.1. By Component
    • 14.2.2. By Technology
    • 14.2.3. By Application
    • 14.2.4. By End Use
    • 14.2.5. By Country

Chapter 15. South Korea Forest Wildfire Detection System Market Analysis

  • 15.1. Key Insights
  • 15.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 15.2.1. By Component
    • 15.2.2. By Technology
    • 15.2.3. By Application
    • 15.2.4. By End Use

Chapter 16. Company Profile (Company Overview, Financial Matrix, Key Product landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

  • 16.1. Robert Bosch GmbH
  • 16.2. Dryad Networks GmbH
  • 16.3. Insight Robotics
  • 16.4. IQ FireWatch
  • 16.5. Orora Technologies
  • 16.6. Paratronic
  • 16.7. SmokeD
  • 16.8. Other Prominent Players

Chapter 1. Research Framework

  • 1.1 Research Objective
  • 1.2 Product Overview
  • 1.3 Market Segmentation

Chapter 2. Research Methodology

  • 2.1 Qualitative Research
    • 2.1.1 Primary & Secondary Sources
  • 2.2 Quantitative Research
    • 2.2.1 Primary & Secondary Sources
  • 2.3 Breakdown of Primary Research Respondents, By Region
  • 2.4 Assumption for the Study
  • 2.5 Market Size Estimation
  • 2.6. Data Triangulation

Chapter 3. Executive Summary: Global Forest Wildfire Detection System Market

Chapter 4. Global Forest Wildfire Detection System Market Overview

  • 4.1. Industry Value Chain Analysis
    • 4.1.1. Service Provider
    • 4.1.2. End User
  • 4.2. Industry Outlook
    • 4.2.1. Overview of key statistics
  • 4.3. PESTLE Analysis
  • 4.4. Porter's Five Forces Analysis
    • 4.4.1. Bargaining Power of Suppliers
    • 4.4.2. Bargaining Power of Buyers
    • 4.4.3. Threat of Substitutes
    • 4.4.4. Threat of New Entrants
    • 4.4.5. Degree of Competition
  • 4.5. Market Dynamics and Trends
    • 4.5.1. Growth Drivers
    • 4.5.2. Restraints
    • 4.5.3. Challenges
    • 4.5.4. Key Trends
  • 4.6. Covid-19 Impact Assessment on Market Growth Trend
  • 4.7. Market Growth and Outlook
    • 4.7.1. Market Revenue Estimates and Forecast (US$ Mn), 2019 - 2032
  • 4.8. Competition Dashboard
    • 4.8.1. Market Concentration Rates
    • 4.8.2. Company Market Share Analysis (Value %), 2023
    • 4.8.3. Competitor Mapping

Chapter 5. Global Forest Wildfire Detection System Market Analysis, By Component

  • 5.1. Key Insights
  • 5.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 5.2.1. Software
    • 5.2.2. Hardware
    • 5.2.3. Services

Chapter 6. Global Forest Wildfire Detection System Market Analysis, By Technology

  • 6.1. Key Insights
  • 6.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 6.2.1. Sensor Network & Surveillance
      • 6.2.1.1. Camera (Vision) Systems
      • 6.2.1.2. Infrared (IR) Camera or Thermal Imaging Camera
      • 6.2.1.3. IR spectrometers
      • 6.2.1.4. LIDAR
    • 6.2.2. Satellite Imaging
    • 6.2.3. Drones
    • 6.2.4. AI and Machine Learning
    • 6.2.5. Others

Chapter 7. Global Forest Wildfire Detection System Market Analysis, By Application

  • 7.1. Key Insights
  • 7.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 7.2.1. Early Warning and Alert Systems
    • 7.2.2. Fire Monitoring and Management
    • 7.2.3. Environmental Monitoring
    • 7.2.4. Research and Conservation

Chapter 8. Global Forest Wildfire Detection System Market Analysis, By End Use

  • 8.1. Key Insights
  • 8.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 8.2.1. Parks
    • 8.2.2. Forest

Chapter 9. Global Forest Wildfire Detection System Market Analysis, By Region

  • 9.1. Key Insights
  • 9.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 9.2.1. North America
      • 9.2.1.1. The U.S.
      • 9.2.1.2. Canada
      • 9.2.1.3. Mexico
    • 9.2.2. Europe
      • 9.2.2.1. Western Europe
        • 9.2.2.1.1. The UK
        • 9.2.2.1.2. Germany
        • 9.2.2.1.3. France
        • 9.2.2.1.4. Italy
        • 9.2.2.1.5. Spain
        • 9.2.2.1.6. Rest of Western Europe
      • 9.2.2.2. Eastern Europe
        • 9.2.2.2.1. Poland
        • 9.2.2.2.2. Russia
        • 9.2.2.2.3. Rest of Eastern Europe
    • 9.2.3. Asia Pacific
      • 9.2.3.1. China
      • 9.2.3.2. India
      • 9.2.3.3. Japan
      • 9.2.3.4. South Korea
      • 9.2.3.5. Australia & New Zealand
      • 9.2.3.6. ASEAN
      • 9.2.3.7. Rest of Asia Pacific
    • 9.2.4. Middle East & Africa
      • 9.2.4.1. UAE
      • 9.2.4.2. Saudi Arabia
      • 9.2.4.3. South Africa
      • 9.2.4.4. Rest of MEA
    • 9.2.5. South America
      • 9.2.5.1. Argentina
      • 9.2.5.2. Brazil
      • 9.2.5.3. Rest of South America

Chapter 10. North America Forest Wildfire Detection System Market Analysis

  • 10.1. Key Insights
  • 10.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 10.2.1. By Component
    • 10.2.2. By Technology
    • 10.2.3. By Application
    • 10.2.4. By End Use
    • 10.2.5. By Country

Chapter 11. Europe Forest Wildfire Detection System Market Analysis

  • 11.1. Key Insights
  • 11.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 11.2.1. By Component
    • 11.2.2. By Technology
    • 11.2.3. By Application
    • 11.2.4. By End Use
    • 11.2.5. By Country

Chapter 12. Asia Pacific Forest Wildfire Detection System Market Analysis

  • 12.1. Key Insights
  • 12.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 12.2.1. By Component
    • 12.2.2. By Technology
    • 12.2.3. By Application
    • 12.2.4. By End Use
    • 12.2.5. By Country

Chapter 13. Middle East & Africa Forest Wildfire Detection System Market Analysis

  • 13.1. Key Insights
  • 13.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 13.2.1. By Component
    • 13.2.2. By Technology
    • 13.2.3. By Application
    • 13.2.4. By End Use
    • 13.2.5. By Country

Chapter 14. South America Forest Wildfire Detection System Market Analysis

  • 14.1. Key Insights
  • 14.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 14.2.1. By Component
    • 14.2.2. By Technology
    • 14.2.3. By Application
    • 14.2.4. By End Use
    • 14.2.5. By Country

Chapter 15. South Korea Forest Wildfire Detection System Market Analysis

  • 15.1. Key Insights
  • 15.2. Market Size and Forecast, 2019 - 2032 (US$ Mn)
    • 15.2.1. By Component
    • 15.2.2. By Technology
    • 15.2.3. By Application
    • 15.2.4. By End Use

Chapter 16. Company Profile (Company Overview, Financial Matrix, Key Product landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

  • 16.1. Robert Bosch GmbH
  • 16.2. Dryad Networks GmbH
  • 16.3. Insight Robotics
  • 16.4. IQ FireWatch
  • 16.5. Orora Technologies
  • 16.6. Paratronic
  • 16.7. SmokeD
  • 16.8. Other Prominent Players