People

My research focuses on remote sensing and its applications spanning flood mapping, water resource management and crop mapping, with a particular interest in raster analytics using satellite image time series combined with deep neural networks. These include design of high-performance models for improved recognition tasks (e.g. semantic segmentation and object detection), generative models for gap filling, and advanced augmentation.

My research lies at the intersection of remote sensing, modeling, and environmental analytics. I apply advanced methods, including deep learning, spatial programming, geo-statistics, and multi-scale data integration, to Earth Observation data to assess the health of crops and other vegetation, monitor forest die-back, and predict ecological changes.

I am a Professor in the Graduate School of Geography at Clark University, and the PI of the Agricultural Impacts Research Group. I am an environmental scientist who uses new Earth Observation technologies and modeling techniques to investigate the drivers and impacts of agricultural change, with a particular focus on Africa.

I am interested in agricultural development and food security in Sub-Saharan Africa. I use GIS, remote sensing, and agricultural modeling technology to map changes in cropland coverage and productivity across African countries. Additionally, I collaborate with economists and ecologists to understand the interactions between socio-economic and environmental factors and the changes in cropland coverage and productivity.

Dr. Lei Song is AIRG’s first PhD graduate (May 2023). Lei uses remotely sensed data, novel statistical models, and visualization tools to conduct research in biodiversity conservation, landscape connectivity, land cover change, and human disturbances (e.g. agriculture). She is an Assistant Professor of Geography at Rutgers University, and was previously a postdoctoral research scholar at University of California Santa Barbara in the SCALE Lab on the BioFI project. Her current work focuses on the ecological impacts of climate change and human disturbances on ecosystems and biodiversity at various temporal and spatial scales.

Dr. Sam Khallaghi's (PhD, 2024) research interests lie in the field of computational geography, with a specific focus on satellite image processing, spatio-temporal modeling, and geospatial machine learning. He is particularly intrigued by the development and application of deep artificial neural network (ANN) models within this domain. Sam is now a post-doctoral researcher at Clark's Center for Geospatial Analytics.

Dr. Mike Cecil (PhD, 2024) works at the intersection of crop modeling, multi-sensor data integration, and smallholder farmer decision-making. He combines combine ground-based radiometric sensors with satellite sensors to understand the effectiveness of smallholder management decisions under different soil-weather constraints. He is also interested in applications of deep learning for Earth Observation. Mike currently works as a post-doctoral research at NASA HARVEST.