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Posts

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projects

Fire Prediction in Southeast Asia using Machine Learning

Published: June 12, 2017

Detecting fire occurence in Southeast Asia using satellite remote sensing and machine learning

Fix the Jet

Published: December 03, 2017

Make images and figures colorblind friendly by swapping their colormaps

Can We Infer Seasons by Looking at Nature?

Published: December 12, 2017

Live season detector using a network of cameras across North America

Flood Mapper: Automated Flood Detection System

Published: February 12, 2018

Near-realtime global flood mapper using automated, localized change-detection

Leafnet: Species identification using leaf images

Published: March 12, 2018

Identify species of a tree using an image of its leaf. Model powered by deep learning and hosted as a chatbot.

Stormwater Rate Simulator for New York City

Published: March 03, 2019

A simulator which allocates stormwater-associated costs based on user inputs for several different rate structures and incentives.

FireNet: Wildfire Risk Forecaster for Social Equality

Published: December 12, 2019

A deep learning system saving you from falling into the trap of wildfire risk and social inequality

DamageMap: A Post-Wildfire Damaged Building Detector

Published: May 01, 2020

DamageMap is a system composed of rapid buildings damage assessment and a convenient user interface for result visualization.

AIRGAP: Assessing Inequality in Risk from Global Air Pollution

Published: November 03, 2020

AIRGAP: Assessing Inequality in Risk from Global Air Pollution tool allows for the exploration and analysis of near-real time air quality and income inequality around the world based on sattelite data.

publications

Satellite-based vegetation optical depth as an indicator of drought-driven tree mortality

Published in Remote Sensing of Environment, 2019

This paper is about developing a scalable plant drought stress indicator using vegetation optical depth.

Recommended citation: Rao, K., Anderegg, W.R.L., Sala, A., Martínez-Vilalta, J. & Konings, A.G. (2019). Satellite-based vegetation optical depth as an indicator of drought-driven tree mortality. Remote Sens. Environ., 227, 125–136. https://www.sciencedirect.com/science/article/pii/S0034425719301208

Macro to micro: microwave remote sensing of plant water content for physiology and ecology

Published in New Phytologist, 2019

This paper presents a short review for the use of microwave remote sensing of plant water.

Recommended citation: Konings, A.G., Rao, K. & Steele‐Dunne, S.C. (2019). Macro to Micro: Microwave Remote Sensing of Plant Water Content for Physiology and Ecology. New Phytol., nph.15808. https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.15808

SAR-enhanced mapping of live fuel moisture content

Published in Remote Sensing of Environment, 2020

This paper presents a deep learning-based solution to rapidly estimate forest dryness across western USA.

Recommended citation: Rao, K., Williams, A.P., Fortin, J. & Konings, A.G. (2020). SAR-enhanced mapping of live fuel moisture content. Remote Sens. Environ., 245. https://www.sciencedirect.com/science/article/pii/S003442572030167X

Drainage canals in Southeast Asian peatlands increase carbon emissions

Published in AGU Advances, 2021

This paper presents a novel convolutional neural network to detect canals and study the effect of canals on land subsidence.

Recommended citation: Dadap, N. C., Hoyt, A. M., Cobb, A. R., Oner, D., Kozinski, M., Fua, P. V., Rao, K., Harvey, C. F., & Konings, A. G. (2021). Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions. AGU Advances, 2(1), e2020AV000321. https://doi.org/10.1029/2020AV000321 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020AV000321

Interannual Variations of Vegetation Optical Depth Are Due to Both Water Stress and Biomass Changes

Published in Geophysical Research Letters, 2021

This paper re-examines the commonly held assumption that VOD interannual variations are proportional to interannual variations in biomass, and shows that the assumption for the most part, is invalid.

Recommended citation: Konings, A. G., Holtzman, N. M., Rao, K., Xu, L., & Saatchi, S. S. (2021). Interannual Variations of Vegetation Optical Depth are Due to Both Water Stress and Biomass Changes. Geophysical Research Letters, 48(16), e2021GL095267. https://doi.org/10.1029/2021gl095267 https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021GL095267

DamageMap: A post-wildfire damaged buildings classifier

Published in International Journal of Disaster Risk Reduction, 2021

This paper presents an AI-based method to classify damaged buildings using post-wildfire images only.

Recommended citation: Galanis, M., Rao, K., Yao, X., Tsai, Y.-L., Ventura, J., & Fricker, G. A. (2021). DamageMap: A post-wildfire damaged buildings classifier. International Journal of Disaster Risk Reduction, 102540. https://doi.org/10.1016/j.ijdrr.2021.102540 https://www.sciencedirect.com/science/article/pii/S221242092100501X

Plant-water sensitivity regulates wildfire vulnerability

Published in Nature Ecology & Evolution, 2022

We show that an ecosystem’s sensitivity to drought affects fire hazard.

Recommended citation: Rao, K., Williams, A.P., Diffenbaugh N.S., Yebra, M., & Konings, A.G. (2022). Plant-water sensitivity regulates wildfire vulnerability. Nature Ecology & Evolution, 6, 332–339 (2022) https://www.nature.com/articles/s41559-021-01654-2

talks

Stormwater drainage

Published: June 01, 2014

This talk presented retrofitting measures for the storwater drainage system of the IIT Madras campus. The 650-acre campus’ stormwater drainage network is more than 50 years old fails frequently during big storms. The talk focussed on presenting a 3-phase expansion plan to include-