Robust and Efficient Analysis Approaches of Remote Imagery for Assessing Population and Forest Health in India

印度面临着巨大的社会和生态挑战。城市正在发展，随之而来的是人口的增加和交通的增加。印度城市的交通在空气污染和大量道路交通死亡中扮演着重要角色。与此同时，虽然印度的森林覆盖率平均在增加，但目前还不清楚这在多大程度上是种植造成的，而不是天然林，这一知识差距可能正在危及印度森林的生物多样性。标准化收集的印度遥感数据提供了一个很好的机会，可以量化这些因素的现状，并将其转变为生态和健康模型，为帮助应对这些挑战的新政府政策提供信息。在这个项目中，我们将开发新的数学方法，这些方法可以释放遥感数据中包含的丰富信息，重点是改善印度面临的两个挑战：交通管理和森林保护。我们将重点开发新的图像分析方法来量化按交通方式分层的交通流量，即汽车、公交车、突克、洛里、自行车、行人等。我们的分析将集中在印度一些人口最稠密和污染最严重的城市，如德赫里、孟买和班加卢市，使用从卫星获得的图像数据，并结合更本地化的交通摄像头数据。该项目开发的算法以及从数据中得出的相关统计数据将向公众提供，并将传达给印度的相关利益攸关方。在森林保护的背景下，我们的项目将开发从卫星数据绘制印度森林不同树种的新算法。在一个由来自学术界和工业界以及来自印度和剑桥的研究人员和利益相关者组成的跨学科项目团队的支持下，通过将遥感数据的新数学方法的开发与知识转移紧密结合起来，我们的项目旨在为改善印度的交通和森林政策决策提供一个步骤

India faces tremendous societal and ecological challenges. Cities are growing which is accompanied by an increase in population and consequently traffic. Transport in India's cities plays an important role in air pollution and a large volume of road traffic fatalities. At the same time, while India's forest cover is on average increasing, it is not clear how much of this is due to plantation in contrast to natural forest, a knowledge gap that is possibly endangering biodiversity of India's forests. Standardly collected remote sensing data of India offers a great opportunity for quantifying the status quo of these factors and turning them into ecological and health models that can inform new government policies to help tackle these challenges. In this project, we will develop novel mathematical methods that can unlock the wealth of information contained in remote sensing data, with a focus on improving upon two of India's challenges: traffic management and forest conservation. We will focus on the development of novel image analysis methods for quantifying traffic volume stratified with respect to traffic mode, i.e. car, bus, tuk tuk, lory, bicycle, pedestrian etc. Our analysis will focus on some of the most populated and polluted cities in India such as Dehli, Mumbai and Bengaluru, using image data obtained from satellites combined with more localised traffic camera data. Algorithms developed in the project as well as associated statistics drawn from the data will be made available to the general public as well as communicated to relevant stakeholders in India. In the context of forest conservation, our project will develop new algorithms for mapping different tree species from India's forests from satellite data.Supported by an interdisciplinary project team of researchers and stakeholders from academia and industry, and from India and Cambridge, and by tightly combining the development of novel mathematical methods for remote sensing data with knowledge transfer, our project aims to provide a step change towards improved decision making in traffic and forest policies in India