Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
Page not in menu
This is a page not in th emain menu
Posts
blog
letters
2015
Published:
2016
Published:
2017
Published:
2018
Published:
2019
Published:
2020
Published:
projects
Fire Prediction in Southeast Asia using Machine Learning
Published:
Detecting fire occurence in Southeast Asia using satellite remote sensing and machine learning 
Fix the Jet
Published:
Make images and figures colorblind friendly by swapping their colormaps 
Can We Infer Seasons by Looking at Nature?
Published:
Live season detector using a network of cameras across North America 
Flood Mapper: Automated Flood Detection System
Published:
Near-realtime global flood mapper using automated, localized change-detection 
Leafnet: Species identification using leaf images
Published:
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:
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:
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:
DamageMap is a system composed of rapid buildings damage assessment and a convenient user interface for result visualization. 
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
talks
Stormwater drainage
Published:
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-
- New culverts at frequently-flooded areas with high traffic
- Stormwater drainage basin to control overflow from the campus lake
- Sustainable stormwater drainage elements such as swales, greenroofs, etc.
Satellite-Based Vegetation Optical Depth as an Indicator of Drought-driven Tree Mortality
Published: