A Radar Satellite Early-Warning System for Tropical Deforestation

热带森林砍伐雷达卫星预警系统

• 批准号: NE/M007839/1
• 负责人: Heiko Balzter
• 金额: $ 1.03万
• 依托单位: University of Leicester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FM007839%2F1
• 关键词: Radar; Satellite; Early; Warning; System

The market assessment research will review potential users of information services on deforestation, patterns of activity, the ways in which they buy and the motivations for purchase of forest monitoring data and analysis. It will provide an overall picture of demand whilst highlighting markets to prioritise and target (based on size, accessibility, demand). In addition, competitors and substitute products will be analysed. The information will be synthesised to create a picture of markets to target and required features of the product and service.The work will inform our understanding of which segments of the market to target (countries, NGOs) it will also inform on the basics details of product & service design and delivery. This will be of vital importance as we decide of the nature of the service, the extent to which the product needs to be refined and developed. At present it is envisaged that a stand-alone commercial entity will be created providing both data and consultancy services to global users of the data. The follow on funding will support the planning for the organisational model and structure for delivery, through the development of a hard evidence base to support decisions on investment and resources allocation. It will subsequently guide the development of a marketing plan.

市场评估研究将审查森林砍伐信息服务的潜在用户、活动模式、购买方式以及购买森林监测数据和分析的动机。它将提供需求的总体情况，同时强调市场的优先顺序和目标(基于规模、可获得性、需求)。此外，还将分析竞争对手和替代产品。这些信息将被综合起来，以创建一幅目标市场的图景以及产品和服务的必要特征。这项工作将使我们了解目标市场的哪些部分(国家、非政府组织)，还将提供产品和服务设计和交付的基本细节。这将是至关重要的，因为我们决定了服务的性质，产品需要改进和开发的程度。目前设想将创建一个独立的商业实体，向数据的全球用户提供数据和咨询服务。后续资金将通过建立支持投资和资源分配决策的确凿证据基础，支持对交付的组织模式和结构的规划。随后，它将指导制定营销计划。

项目成果

Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning

Pyeo：一个 Python 包，用于使用机器学习从地球观测中近乎实时地检测森林覆盖变化

• DOI: 10.1016/j.cageo.2022.105192
• 发表时间: 2022
• 期刊: Computers & Geosciences
• 影响因子: 4.4
• 作者: Roberts J

Near Real-Time Change Detection System Using Sentinel-2 and Machine Learning: A Test for Mexican and Colombian Forests

• DOI: 10.3390/rs14030707
• 发表时间: 2022-02
• 期刊: Remote. Sens.
• 作者: A. M. Pacheco-Pascagaza;Y. Gou;V. Louis;J. Roberts;P. Rodríguez-Veiga;P. C. Bispo;F. Espírito-Santo;C. Robb;C. Upton;G. Galindo;E. Cabrera;Indira Paola Pachón Cendales;M. Castillo-Santiago;Oswaldo Carrillo Negrete;Carmen Meneses;Marco Iñiguez;H. Balzter

Tiger Habitat Quality Modelling in Malaysia with Sentinel-2 and InVEST

• DOI: 10.3390/rs16020284
• 发表时间: 2024-01
• 期刊: Remote. Sens.
• 作者: V. Louis;Susan E. Page;Kevin Tansey;Laurence Jones;Konstantina Bika;H. Balzter