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

Lead Research Organisation: University of Cambridge
Department Name: Applied Maths and Theoretical Physics

Abstract

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

Planned Impact

Our project aims to benefit policy making in climate change, healthcare and environment conservation in India. We will develop and make available new mathematical algorithms which allow to quantify, in an accurate and highly stratified way, the status quo of traffic in India's cities and the composition of India's forests. Equipped with a picture of the current situation, the Indian Government will be better informed when making policy decisions, ultimately benefiting the whole of society in India.

India has some of the noisiest and most polluted cities in the world, with a growing burden of traffic deaths and an increase in non-communicable disease associated with lack of physical activity. Having accurate knowledge as well as an overall picture of the traffic quantity in cities around India will help the government to better target and assess the impact of intervention policies in transport and health, benefiting the local inhabitants. Directly from this project, the current status will be established in the cities of Delhi, Jaipur, Chennai, Bengaluru, Kolkata and Mumbai. However, the project has inbuilt mechanisms to enable local partners and stakeholders to take up the novel methods developed to continue to monitor change and roll out to the entire country.

India is one of the megadiverse countries, but its large population and development objectives are putting huge pressure on forests. In particular there is not a clear picture of how much of the current forest is plantation as opposed to natural forest. Our species level mapping will be able to alert as to the extent of plantation cover and hence inform future decisions to minimise loss in forest quality and biodiversity, ultimately benefiting local communities who depend on the forests for fuel, food and livelihoods. Naturally, ecological conservation benefits the country as a whole. Via this project information will be obtained on the status of forests in the states of Sikkim, Assam and Madhya Pradesh, but here again the methods will be able to be subsequently extended to other states.

Both of the above actions will also help mitigate climate change, via maintenance of natural forest cover and reductions in carbon emissions from vehicles, and help the Indian economy via transportation and environmental policies that reduce damage to health and the environment.

Publications

10 25 50

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Toader B (2022) Image Reconstruction in Light-Sheet Microscopy: Spatially Varying Deconvolution and Mixed Noise. in Journal of mathematical imaging and vision

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Tan H (2023) Data-Driven Mirror Descent with Input-Convex Neural Networks in SIAM Journal on Mathematics of Data Science

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Sellars P (2022) LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification. in IEEE transactions on neural networks and learning systems

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Sabaté Landman M (2023) On Krylov methods for large-scale CBCT reconstruction. in Physics in medicine and biology

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Lunz S (2021) On Learned Operator Correction in Inverse Problems in SIAM Journal on Imaging Sciences

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Kotzagiannidis M (2022) Semi-Supervised Superpixel-Based Multi-Feature Graph Learning for Hyperspectral Image Data in IEEE Transactions on Geoscience and Remote Sensing

 
Description 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 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 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 are made available to the general public as well as communicated to relevant stakeholders in India.

In the context of forest conservation, our project develops 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.
Exploitation Route - Open source algorithms for the analysis of hyper spectral imaging data - in particular for the classification of forest cover into different tree species. This is in collaboration with IORA - a major conservation provider in India and the Forest Survey of India, which is the Indian government's forest conservation agency. Through this tight link between software development and relevant conservation stakeholders in India translation to remote sensing data from India, integration of ground-truth labels (provided by IORA) and education of India's conservationists in the use of the software are seamless.

- Open source algorithms for the analysis of traffic video data - in particular for the detection, classification and tracking of different modes of transport (pedestrians, cycles, cares, rickshaws, trucks etc). This is in collaboration with Kritikal, who are providing access to traffic video data from India and are supporting the project through their experience with their software called TRACER (prototype software for detecting cars in traffic videos). Again, through having this Indian AI company on board, which is a spin-off of IIT in Delhi, the translation into user-friendly software will be supported. Also, with C40 on board, relevant stakeholders from India's government offices related to transport and wellbeing will be involved in the translation of our algorithms.
Sectors Digital/Communication/Information Technologies (including Software),Environment,Healthcare,Leisure Activities, including Sports, Recreation and Tourism,Transport

URL https://sites.google.com/view/remote-sens-research-for-india/
 
Description Our collaboration with KritiKal is resulting into two main non-academic advances: 1. The Trazer software, see https://kritikalsolutions.com/products/trazer/ , that KritiKal has been developing for vehicle detection and classification from traffic camera data, has been upgraded to a new, extended version, that can now detect and classify a large class of vehicles, including motor bikes and bicycles. This software will be available for continuation research. 2. A fully labelled traffic camera dataset that will be openly available to academic and non-profit use. This dataset will be extremely valuable for future algorithm development, both for training and benchmarking of algorithms.
First Year Of Impact 2022
Sector Environment,Transport
Impact Types Societal,Economic,Policy & public services

 
Description Cambridge Mathematics of Information in Healthcare (CMIH)
Amount £1,295,778 (GBP)
Funding ID EP/T017961/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 08/2020 
End 08/2023
 
Description Combining Knowledge And Data Driven Approaches to Inverse Imaging Problems
Amount £1,240,288 (GBP)
Funding ID EP/V029428/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 06/2021 
End 05/2026
 
Description rapiD and secuRe AI imaging based diaGnosis, stratification, fOllow-up, and preparedness for coronavirus paNdemics (DRAGON)
Amount € 11,542,642 (EUR)
Funding ID Grant Agreement (GA) No: 101005122 
Organisation European Commission 
Department Innovative Medicines Initiative (IMI)
Sector Public
Country Belgium
Start 10/2020 
End 09/2023
 
Description 21st ECMI Conference on Industrial and Applied Mathematics (ECMI 2021) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The series of European Consortium for Mathematics in Industry (ECMI) conferences are devoted to enforcing the interaction between academy and industry, leading to innovations in both fields. These events have attracted leading experts from business, science, and academia, and have promoted the application of novel mathematical technologies to industry. We hope that ECMI 2021 will further enhance multidisciplinary research and development both in academia and industry, leading to the formulation of challenging real-life problems, where mathematics may provide significant new insights and at the same time may be inspired by those interactions.
Year(s) Of Engagement Activity 2021
URL https://ecmiindmath.org/2020/11/22/21st-ecmi-conference-on-industrial-and-applied-mathematics/
 
Description 91st GAMM Annual Meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The Annual Meeting of the International Association of Applied Mathematics and Mechanics, the GAMM 2020@21.
Year(s) Of Engagement Activity 2021
URL https://jahrestagung.gamm-ev.de/jahr2020-2021/annual-meeting/
 
Description BIRS Women in Inverse Problems 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The objective of this workshop is to bring together women in the broad and vibrant field of Inverse Problems. Both established as well as early career researchers will come together to discuss their recent research achievements. This workshop will facilitate professional networking and create mentoring opportunities for women researchers. The ultimate goal is to help broaden female participation in research careers in particular in the field of Inverse Problems, as well as to create new research collaborations.
Year(s) Of Engagement Activity 2021
URL https://www.birs.ca/events/2021/5-day-workshops/21w5035
 
Description CANADIAN APPLIED AND INDUSTRIAL MATHEMATICS SOCIETY 2021 Annual Meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Each year CAIMS/SCMAI hosts an annual meeting for all members. This meeting is one of the central activities of CAIMS and has been held for over 30 years. The annual meeting covers all areas of applied and industrial mathematics with high profile speakers invited to give keynote addresses on currently active thematic areas.
Year(s) Of Engagement Activity 2021
URL https://uwaterloo.ca/canadian-applied-industrial-math-society-annual-meeting-2021/
 
Description Computational Mathematics and Machine Learning 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The aim of this workshop is to formulate a plan for future developments within the area of computational science and engineering (CSE) making use of machine learning techniques. We will discuss the impact that machine learning has already made or will make on computational mathematics, and how the ideas from computational mathematics, particularly numerical analysis, can be used to help understanding and better formulating machine learning models. In the annex, the state of the art is provided in more detail. The question is: which research directions are most promising? What should we concentrate on? How can we combine physics-based and data-based techniques? Can we formulate joint projects? Or maybe a joint organisation for the discussion and dissemination of new developments?

In this workshop, we will address the following two very important questions: (1) How machine learning has already impacted and will further impact computational mathematics, scienti?c computing and computational science? (2) How computational mathematics, particularly numerical analysis, can impact machine learning? To accomplish the aforementioned aim, in this workshop, we review what has been learned on these two issues.

We will discuss some of the most important progress that has been made on the foregoing two issues, and where new developments should take place. This workshop will be considered a success if we have been able to put things into a perspective that will help to integrate machine learning with computational mathematics, and produced (at the end of the workshop) a sound plan for future research directions in several of the areas mentioned in Section 4. We will identify the most promising research directions, networking activities, as well as building of new collaborations between participants.
Year(s) Of Engagement Activity 2021
URL https://www.lorentzcenter.nl/computational-mathematics-and-machine-learning.html
 
Description Deep Learning and Inverse Problems (NeurIPS Workshop) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact This virtual workshop aims at bringing together theoreticians and practitioners in order to chart out recent advances and discuss new directions in deep learning-based approaches for solving inverse problems in the imaging sciences and beyond.
Year(s) Of Engagement Activity 2021
URL https://deep-inverse.org/index.html
 
Description Eighth International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact SSVM is a biannual meeting within the area of Computer Vision and Image Analysis. SSVM focuses especially on multiscale analysis of image content, partial differential equations, geometric and level-set methods, variational methods, and optimization.
Year(s) Of Engagement Activity 2021
URL https://ssvm2021.sciencesconf.org/
 
Description IEEE International Symposium on Biomedical Imaging 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging.
Year(s) Of Engagement Activity 2021
URL https://biomedicalimaging.org/2021/
 
Description INTERACT 2021 "Sense, Feel, Design" 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The theme of INTERACT 2021 "Sense, Feel, Design" highlights the new challenges of interaction design. Technology is today more and more widespread, pervasive and blended in the world we live in. On one side, devices that sense humans' activities have the potential to provide an enriched interaction. On the other side, the user experience can be further enhanced by exploiting multisensorial technologies. Not only the traditional human senses of vision and hearing, but also senses of touch, smell, and taste, as well as emotions are to be taken into account when designing for future interactions.
INTERACT 2021 represents the right venue to debate such new challenges. Another hot topic of this edition is Human-AI Interaction, focusing on the design of human-centered intelligent systems.
Year(s) Of Engagement Activity 2021
URL https://www.interact2021.org/
 
Description Mathematics of deep learning 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Aiming to derive a mathematical foundation of deep learning, this programme addresses theoretical questions in two realms:
(1) Theoretical foundations of deep learning independent of a particular application.
(2) Theoretical analysis of the potential and the limitations of deep learning for mathematical methodologies, in particular, for inverse problems and partial differential equations.

The main goal of this programme is to achieve substantial progress in developing a theoretical foundation of deep learning. For this, the programme will for the first time gather the top experts from various areas of mathematics and of the theory of machine learning, including computer scientists, physicists, and statisticians in one place, initiating collaborations across intra- and interdisciplinary boundaries and thereby generating unprecedented research dynamics.
Year(s) Of Engagement Activity 2021
URL https://www.newton.ac.uk/event/mdl/
 
Description Mathematisches Forschungsinstitut Oberwolfach - Geometric Numerical Integration 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The topics of the workshop included interactions between geometric numerical integration and numerical partial differential equations; geometric aspects of stochastic differential equations; interaction with optimisation and machine learning; new applications of geometric integration in physics; problems of discrete geometry, integrability, and algebraic aspects.
Year(s) Of Engagement Activity 2021
URL https://publications.mfo.de/handle/mfo/3860
 
Description Mathematisches Forschungsinstitut Oberwolfach - Mini-Workshop: Deep Learning and Inverse Problems 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Machine learning and in particular deep learning offer several
data-driven methods to amend the typical shortcomings of purely analytical approaches. The mathematical research on these combined models is
presently exploding on the experimental side but still lacking on the theoretical point of view. This workshop addresses the challenge of developing
a solid mathematical theory for analyzing deep neural networks for inverse
problems.
Year(s) Of Engagement Activity 2021
URL https://publications.mfo.de/handle/mfo/3633
 
Description Woudschoten Conference 2021 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The Woudschoten conference has a long and rich history, dating back to the first edition in 1976, and it has featured many of the great names in numerical analysis and scientific computing. Since its establishment in the early days of `approximation and discretization' - the two themes of the first edition of the conference -- the Woudschoten conference has provided an introduction to and overview of groundbreaking developments in scientific computing and numerical analysis. The conference is attended by essentially all Dutch and Flemish researchers in numerical analysis and scientific computing, from PhD students to full professors, and including industrial researchers. By virtue of its unique format and its informal setting, the conference does not only provide insight and inspiration to the Dutch-Flemish numerical-mathematics community, but it also plays a central role in retaining coherence in the community.
Year(s) Of Engagement Activity 2021
URL https://wsc.project.cwi.nl/woudschoten-conferences/2021-conference