Contact Dr Kriti Mukherjee
Background
My passion lies in the realm of remote sensing and geospatial data analysis, where I specialize in leveraging geographic information science, photogrammetry, image processing, data science, and machine learning to explore and model environmental changes and extreme events.
I embarked on my professional journey as a Scientist at the National Technical Research Organization in New Delhi, India, a premier technical intelligence agency under the National Security Advisor. While there, I completed my PhD in hyperspectral remote sensing, where I developed an innovative method for dimensionality reduction of hyperspectral data using fractal mathematics.
My career then took me across the globe, from Germany and Thailand to Canada and the UK, where I refined my expertise in environmental monitoring and geospatial analysis. Throughout this journey, I made substantial contributions to high-impact research projects, focusing on the impacts of climate change, assessments of natural disasters, and agricultural land suitability. These experiences have enriched my understanding of our planet's dynamic systems and have fueled my dedication to using cutting-edge technology to address critical environmental challenges.
Research opportunities
My research investigates the critical intersection of water resources, climate change, and sustainable development, with a focus on understanding how global warming鈥揹riven shifts in temperature and precipitation affect interconnected environmental systems. Climate variability and extremes鈥攚hether manifesting through glacier retreat, changing agricultural suitability, or natural hazards such as floods, droughts, and landslides鈥攃an have profound consequences when underlying processes are not well understood and risks are inadequately assessed.
As climate change drives both gradual trends and increasingly frequent extreme events, the ability to understand, predict, and evaluate their impacts has become ever more crucial. Yet, many existing modelling frameworks struggle to reliably capture these dynamics, particularly in regions where observational data are sparse or unevenly distributed. Addressing these limitations is a core objective of my research.
To bridge these gaps, I integrate dense meteorological observations, remote sensing data, and advanced modelling techniques to improve predictions of climate-driven impacts on both natural and human systems. My work seeks not only to enhance model performance but also to translate scientific insights into practical assessments of risk for populations, agriculture, and infrastructure. Opportunities in this field are substantial, particularly for improving resilience and decision-making in under-observed and highly vulnerable regions where climate impacts are often most severe.
Self-funded students or those with funding from their home country are encouraged to contact me to discuss their research plans. For funded research opportunities, please see the University's current listing (/research/research-degrees/research-opportunities).
Current activities
My research focuses on the comprehensive assessment, mapping, and continuous monitoring of short- and long-term transformations in land resources. A central theme of my work is understanding how land systems respond to climate change and climate extremes. Within the field of cryosphere science, I have a strong interest in high-mountain glacier research, where I use remote sensing and modelling approaches to examine glacier dynamics, their sensitivity to climatic drivers, and their potential to generate natural hazards.
As an active member of the 探花精选 Land Information System (LandIS) team, I play a key role in exploiting extensive soil datasets covering England and Wales. These data underpin the development of England鈥檚 Agricultural Land Classification (ALC) map, which integrates the combined influences of climate, soil, and topography to evaluate land capability for agriculture under current and future conditions.
In parallel, I am investigating the use of satellite imagery to analyse deforestation patterns in Ghana and C么te d鈥橧voire driven by coffee and cocoa expansion. These tropical regions have experienced substantial forest loss in recent decades, resulting in significant environmental impacts. While this represents predominantly human-induced deforestation, I also explore natural landscape disturbances such as landslides, which can similarly alter forested terrain. My work examines how optical and radar satellite data, combined with machine learning techniques, can be leveraged to detect, monitor, and quantify these changes with improved accuracy.
Through close collaboration with leading national and international organisations, my research aims to develop evidence鈥慴ased solutions to mitigate and adapt to climate change, contributing directly to the United Nations Sustainable Development Goals (SDGs). Recently, I completed a secondment with Defra and Natural England, where I contributed to the development of a national soil map for England. This work combined soil profile data collected by Natural England with a suite of environmental covariates to train machine鈥憀earning models capable of predicting soil types across the country. The resulting England Soil Map provides an openly accessible resource to support land鈥憉se planning, environmental policy, soil monitoring, and long鈥憈erm land management. Importantly, it also identifies clear priorities for future data collection, particularly highlighting soil types and regions where labelled observations remain sparse.
Recognizing the significance of disseminating knowledge, I am actively engaged as a lead and co-author in the creation of several impactful publications. I extend my sincere gratitude to my collaborators whose support has played a pivotal role in shaping the aims and outcomes of my research.
In addition to my research, I mentor masters' and PhD students.
Clients
- Environment Agency
- Flood Re
- Department for Environment, Food and Rural Affairs
- Natural Environment Research Council
- Natural England
- RSK ADAS Ltd
