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Commercialising radar-based detection of deforestation and forest degradation

将基于雷达的毁林和森林退化检测商业化

基本信息

批准号：
NE/M021998/1
负责人：
Edward Mitchard
金额：
$ 24.7万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FM021998%2F1
关键词：
Commercialising radar based detection deforestation

项目摘要

Keywords: carbon credits; classification; deforestation; forest degradation; radar; REDD+; satellite data; tropical forestDeforestation is accelerating across tropical forests and woodlands. As much as 20% of man-made greenhouse gas emissions come from tropical forest loss, ten times the emissions from air travel. However some damage to forest is hard to detect or quantify: in particular small-scale deforestation and degradation. Examples of this include a slash-and-burn farmer clearing a small field, orwhere some trees are taken from a forest but it remains forest - e.g. selective logging for high value trees. This makes it very difficult to accurately estimate the area of forest destroyed by people each year. It similarly makes it hard to measure the success of projects that aim to halt or reverse forest loss. When looking to monitor deforestation and degradation, pretty much the only available data source used is optical satellite data. Effectively these sensors are advanced digital cameras collecting images every time they pass over an area. Images are mostly available for free at resolutions of up to about 30 metre pixel size, with an image at this resolution typically taken everywhere in the planet every few weeks. However, there are two major problems:1. Much of the tropics is cloudy most of the time. For some tropical forest areas, good cloud-free images are only available once every few years. 2. Optical satellite data can only see the top of the canopy, and can confuse trees with grass and shrubs. This means small-scale deforestation and degradation can often be missed.We have produced a potential solution using a different type of satellite data: radar data. Radar can 'see through' cloud cover and the top of the canopy to discover the three dimensional structure of forests, solving the above problems. We know that long wavelength radar data can be used to map changes, but before our innovation it was not known that this could also be done with short wavelength data. There is no guaranteed provision of long wavelength radar data, just a collection of one-off satellites with data policies that do not allow commercial use without a significant charge. However, short wavelength data is far more readily available: the European Union has just funded a satellite series called Sentinel-1, which commits to providing consistent short-wavelength radar data into the 2030's from a number of satellites, and with the data provided free of charge for commercial use. NERC research at the University of Edinburgh has led to an algorithm that can use this data successfully. On completion of this project we will be able to create maps of deforestation and forest degradation every quarter at a 20 m resolution. There is no comparable product available from optical data, and we have submitted a patent for this radar-based technology, so we mean to start the only company able to sell the most reliable forest change product available.We have commissioned market research suggesting there are a wide number of potential users. Our primary market would be project developers that are generating carbon credits by protecting forest areas that were threatened with destruction: managers need satellite products to demonstrate historical rates of forest loss and to monitor the success of their projects. Such developers are already spending millions of dollars a year on inferior products.We would also aim to sell to large multinational companies who are trying to remove deforestation from their supply chains: large companies such as Nestle and Unilever have already committed to this, but need to provide evidence of this to their customers. Finally there are opportunities to sell the product to timber companies (who may need to prove the source of their timber is sustainable for certification purposes), and biofuel producers, including those providing wood pellets to an increasing number of power stations.

保留字：碳信用额;分类;砍伐森林;森林退化;雷达; REDD+;卫星数据;热带森林热带森林和林地的砍伐正在加速。多达20%的人为温室气体排放来自热带森林的损失，是航空旅行排放量的十倍。然而，对森林的某些损害难以发现或量化：特别是小规模的毁林和退化。这方面的例子包括刀耕火种的农民清理一块小田地，或者从森林中砍伐一些树木，但它仍然是森林--例如选择性砍伐高价值树木。这使得很难准确估计每年被人类破坏的森林面积。同样，这也使得难以衡量旨在阻止或扭转森林损失的项目的成功程度。在监测森林砍伐和退化时，几乎唯一可用的数据来源是光学卫星数据。实际上，这些传感器是先进的数码相机，每次经过一个区域时都会收集图像。大多数图像都是免费的，分辨率高达30米像素大小，通常每隔几周就会在地球上的任何地方拍摄一张这种分辨率的图像。然而，存在两个主要问题：1。大部分热带地区大部分时间多云。对于一些热带森林地区，好的无云图像每隔几年才能获得一次。2.光学卫星数据只能看到树冠的顶部，并且可能将树木与草和灌木混淆。这意味着小规模的森林砍伐和退化往往会被忽略。我们已经使用不同类型的卫星数据产生了一个潜在的解决方案：雷达数据。雷达可以“看穿”云层和树冠的顶部，发现森林的三维结构，解决了上述问题。我们知道长波长雷达数据可以用来绘制变化，但在我们的创新之前，人们不知道这也可以用短波长数据来完成。没有保证提供长波长雷达数据，只是收集一次性卫星，其数据政策不允许在不收取大量费用的情况下进行商业使用。然而，短波长数据更容易获得：欧盟刚刚资助了一个名为Sentinel-1的卫星系列，该系列致力于从一些卫星提供一致的短波长雷达数据到2030年代，并免费提供数据用于商业用途。爱丁堡大学的NERC研究已经产生了一种可以成功使用这些数据的算法。该项目完成后，我们将能够以20米的分辨率每季度制作一次森林砍伐和退化地图。目前还没有可与光学数据相媲美的产品，我们已经为这项基于雷达的技术申请了专利，因此我们打算创办唯一一家能够销售最可靠的森林变化产品的公司。我们委托进行了市场调查，表明有大量的潜在用户。我们的主要市场将是通过保护受到破坏威胁的森林地区来产生碳信用额的项目开发商：管理人员需要卫星产品来展示历史森林损失率并监测其项目的成功。这些开发商每年已经在劣质产品上花费了数百万美元。我们的目标也是向那些试图从供应链中消除森林砍伐的大型跨国公司出售产品：雀巢和联合利华等大型公司已经承诺这样做，但需要向客户提供证据。最后，还有机会向木材公司（这些公司可能需要证明其木材的来源是可持续的，以便进行认证）和生物燃料生产商（包括向越来越多的发电站提供木屑颗粒的生产商）出售产品。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Assessing Forest/Non-Forest Separability Using Sentinel-1 C-Band Synthetic Aperture Radar

DOI：
10.3390/rs12111899
发表时间：
2020-06
期刊：
Remote. Sens.
影响因子：
0
作者：
Johannes N. Hansen;E. Mitchard;Stuart King
通讯作者：
Johannes N. Hansen;E. Mitchard;Stuart King

A small subset of protected areas are a highly significant source of carbon emissions.

DOI：
10.1038/srep41902
发表时间：
2017-02-10
期刊：
Scientific reports
影响因子：
4.6
作者：
Collins MB;Mitchard ET
通讯作者：
Mitchard ET

Spatial Wavelet Statistics of SAR Backscatter for Characterizing Degraded Forest: A Case Study From Cameroon

用于表征退化森林的 SAR 后向散射空间小波统计：喀麦隆案例研究

DOI：
10.1109/jstars.2015.2420596
发表时间：
2015
期刊：
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
影响因子：
5.5
作者：
De Grandi E
通讯作者：
De Grandi E

Congo Basin peatlands: threats and conservation priorities