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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
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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applications
Historical Flood Analysis Tool
With this tool, variable risk for floods and potentially for droughts can be found with identification of areas particularly prone to such disasters. This information can help with preparedness for prevention and response to flood disasters. 
Mekong Drought and Crop Watch
The system can be used to assist local governments and the agricultural sector with seasonal drought forecasting and in implementing short and long-term mitigation measures during and in advance of droughts. 
Risk Assessment Platform
The Risk Assessment Platform is an online tool that is designed to be used to perform risk assessment using the Spatial Multi-criteria Evaluation (SMCE) method. With the facilities to upload or import datasets and creating custom criteria by defining parameters and assigning weights, the tool can be utilized in different sectors. The web application uses a powerful computational resource in the background, the Google Earth Engine, to perform spatial overlay analysis using the custom criteria set by users. 
Regional Land Cover & Monitoring System
This system guides users in applying peer-reviewed methods and cloud computing power to produce a wide variety of high-quality land cover information products that can be updated regularly and consistently. 
Sahana Alerting and Messaging Broker
We make use of an International warning standard to bridge the last mile and bring efficiency to early warning practices. 
Sentiel 1 Pre-processing pipeline using Sentinel Application Platform (SNAP) Graph Processing Tool (GPT) 7.0
Using Sentinel-1 SNAP GPT to download and preprocess Sentinel 1 Radar Images, and push it to the Google Cloud Bucket to import in the Google Earth Engine (GEE). The Pre-processing included applying orbit file, thermal noise removel, border noise removal, calibration, multilook correction, radiometric terrain flattening, and DEM assisted co-registration, speckle filtering, and Range-Doppler Terrain Correction. Read more here. 
Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine
We investigate two methods of automatic data labeling: 1. the Joint Research Centre (JRC) surface water maps; 2. an Edge-Otsu dynamic threshold approach. We deployed a U-Net convolutional neural network to map surface water from Sentinel-1 Synthetic Aperture Radar (SAR) data and tested the model performance using different hyperparameter tuning combinations to identify the optimal learning rate and loss function. Read more here. 
Satellite Radar-derived Virtual Rain and Stream Gauge Data Service
This service provides near real-time rainfall and stream height data from publicly available satellite measurements by creation of a virtual network of rain gauges and stream gauges at points widely distributed over the entire Lower Mekong Region. 
publications
ITU X.1303 International Warning Standard: Lessons from an Asian Implementation.
Published in Journal of ICT Standardization, 2017
Recommended citation: Waidyanatha, Nuwan, Biplov Bhandari, and Lutz Frommberger. "ITU X. 1303 International Warning Standard: Lessons from an Asian Implementation." Journal of ICT Standardization 4, no. 3 (2017): 177-198. https://doi.org/10.13052/jicts2245-800X.431
An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale.
Published in MDPI Remote Sensing, 2018
Recommended citation: Poortinga, Ate, Nicholas Clinton, David Saah, Peter Cutter, Farrukh Chishtie, Kel N. Markert, Eric R. Anderson et al. "An operational before-after-control-impact (BACI) designed platform for vegetation monitoring at planetary scale." Remote Sensing 10, no. 5 (2018): 760. https://doi.org/10.3390/rs10050760
Annual continuous fields of woody vegetation structure in the Lower Mekong region from 2000‐2017 Landsat time-series.
Published in Remote Sensing of Environment, 2019
Recommended citation: Potapov, P., A. Tyukavina, S. Turubanova, Y. Talero, A. Hernandez-Serna, M. C. Hansen, D. Saah et al. "Annual continuous fields of woody vegetation structure in the Lower Mekong region from 2000‐2017 Landsat time-series." Remote Sensing of Environment 232 (2019): 111278. https://doi.org/10.1016/j.rse.2019.111278
Primitives as building blocks for constructing land cover maps.
Published in International Journal of Applied Earth Observation and Geoinformation, 2019
Recommended citation: Saah, David, Karis Tenneson, Ate Poortinga, Quyen Nguyen, Farrukh Chishtie, Khun San Aung, Kel N. Markert et al. "Primitives as building blocks for constructing land cover maps." International Journal of Applied Earth Observation and Geoinformation 85 (2020): 101979. https://doi.org/10.1016/j.jag.2019.101979
Land Cover Mapping in Data Scarce Environments: Challenges and Opportunities.
Published in Frontiers in Environmental Science, 2019
Recommended citation: Saah, David, Karis Tenneson, Mir Matin, Kabir Uddin, Peter Cutter, Ate Poortinga, Quyen H. Nguyen et al. "Land cover mapping in data scarce environments: challenges and opportunities." Frontiers in Environmental Science 7 (2019): 150. https://doi.org/10.3389/fenvs.2019.00150
Linking Earth Observations for Assessing the Food Security Situation in Vietnam: A Landscape Approach.
Published in Frontiers in Environmental Science, 2019
Recommended citation: Poortinga, Ate, Quyen Nguyen, Karis Tenneson, Austin Troy, David Saah, Biplov Bhandari, Walter L. Ellenburg et al. "Linking earth observations for assessing the food security situation in Vietnam: A landscape approach." Frontiers in Environmental Science (2019): 186. https://doi.org/10.3389/fenvs.2019.00186
Operational Flood Risk Index Mapping for Disaster Risk Reduction Using Earth Observations and Cloud Computing Technologies: A Case Study on Myanmar.
Published in Frontiers in Environmental Science, 2019
Recommended citation: Phongsapan, Kittiphong, Farrukh Chishtie, Ate Poortinga, Biplov Bhandari, Chinaporn Meechaiya, Thannarot Kunlamai, Khun San Aung et al. "Operational flood risk index mapping for disaster risk reduction using Earth Observations and cloud computing technologies: A case study on Myanmar." Frontiers in Environmental Science (2019): 191. https://doi.org/10.3389/fenvs.2019.00191
Predictive Analytics for Identifying Land Cover Change Hotspots in the Mekong Region.
Published in MDPI Remote Sensing, 2020
Recommended citation: Poortinga, Ate, Aekkapol Aekakkararungroj, Kritsana Kityuttachai, Quyen Nguyen, Biplov Bhandari, Nyein Soe Thwal, Hannah Priestley et al. "Predictive analytics for identifying land cover change hotspots in the mekong region." Remote Sensing 12, no. 9 (2020): 1472. https://doi.org/10.3390/rs12091472
Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine.
Published in MDPI Remote Sensing, 2020
Recommended citation: Markert, Kel N., Amanda M. Markert, Timothy Mayer, Claire Nauman, Arjen Haag, Ate Poortinga, Biplov Bhandari et al. "Comparing sentinel-1 surface water mapping algorithms and radiometric terrain correction processing in southeast asia utilizing google earth engine." Remote Sensing 12, no. 15 (2020): 2469. https://doi.org/10.3390/rs12152469
Mapping sugarcane in Thailand using transfer learning, a lightweight convolutional neural network, NICFI high resolution satellite imagery and Google Earth Engine.
Published in ISPRS Open Journal of Photogrammetry and Remote Sensing, 2021
Recommended citation: Poortinga, Ate, Nyein Soe Thwal, Nishanta Khanal, Timothy Mayer, Biplov Bhandari, Kel Markert, Andrea P. Nicolau et al. "Mapping sugarcane in Thailand using transfer learning, a lightweight convolutional neural network, NICFI high resolution satellite imagery and Google Earth Engine." ISPRS Open Journal of Photogrammetry and Remote Sensing 1 (2021): 100003. https://doi.org/10.1016/j.ophoto.2021.100003
Automatic Detection of Impervious Surfaces from Remotely Sensed Data Using Deep Learning.
Published in MDPI Remote Sensing, 2021
Recommended citation: Parekh, Jash R., Ate Poortinga, Biplov Bhandari, Timothy Mayer, David Saah, and Farrukh Chishtie. "Automatic Detection of Impervious Surfaces from Remotely Sensed Data Using Deep Learning." Remote Sensing 13, no. 16 (2021): 3166. https://doi.org/10.3390/rs13163166
Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine.
Published in ISPRS Open Journal of Photogrammetry and Remote Sensing, 2021
Recommended citation: Mayer, Timothy, Ate Poortinga, Biplov Bhandari, Andrea P. Nicolau, Kel Markert, Nyein Soe Thwal, Amanda Markert et al. "Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine." ISPRS Open Journal of Photogrammetry and Remote Sensing 2 (2021): 100005. https://doi.org/10.1016/j.ophoto.2021.100005
talks
Sahana Eden Training
Published:
Read the blog post here.
The role of Sahana Alerting and Messaging Broker (SAMBRO) as cross-agency situational-awareness platform for Disaster Risk Management
Published:
View the presentation here.
The role of SAMBRO as Cross-Agency Situational-Awareness Platform for Disaster Risk Management
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Sahana Disaster Management System
Published:
More information about the conference here Read the blog post here
Building capacity on Common Alerting Protocol for Nepal.
Published:
Read my blog post here.
Bias Correction of Global Streamflow Product Using Machine Learning
Published:
More information here
Data-driven approach for Rating Curve generation utilizing publicly available Hydrological dataset.
Published:
More information here.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.