Dr. Dalia B. Kirschbaum is the Chief of the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center, Greenbelt, MD. In this role, she leads an interdisciplinary Earth system science lab at NASA to conduct large-scale hydrological science research using data from NASA’s satellites, land surface models, and fieldwork. Dr. Kirschbaum’s work focuses on rainfall-triggered landslide modeling, monitoring and mapping using remotely sensed information to conduct landslide hazard and risk studies at multiple spatial and temporal scales. Information on landslide modeling, mapping, and citizen science efforts is available at: https://landslides.nasa.gov. Dr. Kirschbaum also serves as the Global Precipitation Measurement (GPM) Mission Deputy Project Scientist for Applications, where she provides scientific leadership for applications activities, communication, and outreach. Dr. Kirschbaum is a Disaster Response Coordinator for the agency, working with other NASA centers as well as domestic and international partners to bring satellite data and products to bear during natural hazard events to improve situational awareness and inform decision making. Dr. Kirschbaum received her M.S. and Ph.D. in Earth and Environmental Sciences from Columbia University with a focus in Natural Hazards and Remote Sensing. She received her A.B. in Geosciences from Princeton University.
Landslide Hazard Modeling
My research interests center on rainfall-triggered landslide modeling, focusing on applying remotely sensed surface and precipitation information to landslide hazard models at multiple spatial and temporal scales. My current research focuses on advancing a regional landslide hazard and forecasting system with more quantitative and deterministic models to improve landslide hazard assessment. I am also developing a web-based interface for visualization of landslide hazard and remote sensing products for improved situational awareness of landslide hazards and reported events. This landslide interface represents the first regional/global interface to access landslide reports and contribute events to a global database. A prototype of our current system can be seen at https://pmm.nasa.gov/precip-apps
Application of remotely sensed precipitation data
This research involves evaluation and application of remotely sensed precipitation data from GPM and analyzing precipitation extremes as they relate to hydrometeorological hazards
Landslide Citizen Science
Dr. Kirschbaum and her team have developed a landslide citizen science system called "Landslide Reporter" that enables anyone to submit a report through the website: https://landslides.nasa.gov. All reports are evaluated and then posted publicly on the Landslide Viewer portal.
Global Landslide Catalog
This work involves developing and maintaining a Global Landslide Catalog focused on rainfall-triggered landslides. Through this effort we are also working to developed a landslide citizen science portal, "Landslide Reporter" that will be an online portal to visualize, export, and edit this catalog and add additional events that is openly available to the public. This site will launch early in 2018.
Slope-stability modeling: sensitivity analysis and applications
This work involves testing a physically-based slope-stability model over local and regional scales for improved assessment of landslide triggering conditions and sensitivity analysis of the inputs required to effectively model these processes.
2004 – 2009 COLUMBIA UNIVERSITY, NEW YORK, NY
Department of Earth and Environmental Sciences
Lamont-Doherty Earth Observatory
Natural Hazards, Geomorphology, Remote Sensing
Dissertation: Multi-Scale Landslide Hazard and Risk Assessment: A Modeling and Multivariate Statistical Approach
Research Advisor: Dr. Arthur Lerner-Lam
Doctoral Degree Received: July 2009
2007 COLUMBIA UNIVERSITY, NEW YORK, NY
M. Phil. Geomorphology, Remote Sensing, Climate
2006 COLUMBIA UNIVERSITY, NEW YORK, NY
M.A. Earth and Environmental Sciences
2000 – 2004 PRINCETON UNIVERSITY, PRINCETON, NJ
A.B. Geosciences and Environmental Policy
Advisors: Dr. S. George Philander, Dr. Gregory van der Vink
Thesis: A Comparative Analysis of Drought and Famine in the Sahel and India
1/2011
-
Present
Research Physical Scientist
NASA Goddard Space Flight Center, Hydrological Sciences Laboratory,
Greenbelt, MD Develop new techniques for rainfall-triggered landslide hazard assessment and forecasting using statistical and deterministic landslide models and remote sensing data.
Specific objectives:
• Develop a regional landslide hazard and forecasting system focused on a prototype in Central America with the goal of expanding the model to other regional nodes
• Implement a web-based visual interface to view landslide hazard and remote sensing products for improved situational awareness for landslide hazards
• Advance a global satellite-based rainfall-triggered landslide hazard algorithm through improved susceptibility, rainfall threshold and soil moisture calculations.
• Compile a Global Landslide Catalog (data available from 2007-present) to be viewed in the online landslide hazard visualization tool and use the GLC for validation of landslide hazard algorithms to characterize model performance accuracy.
• Perform sensitivity analysis of a physically-based slope-stability model (TRIGRS) within the Land Information System (LIS) framework developed within the Hydrological Sciences Laboratory and test input parameters for several case studies using uncertainty testing of model variables and error characterization of slope stability outputs.
9/2014
-
Present
Global Precipitation Measurement Mission Deputy Project Scientist for Applications
NASA Goddard Space Flight Center,
Greenbelt, Maryland Lead scientific support for applications research and activities for the Global Precipitation Measurement (GPM) mission. Specific objectives and activities:
- Coordinate and facilitate data access issues in terms of TRMM and GPM data format, accessibility and availability for expert to non-expert users
- Coordinate GPM Applications Workshop (Fall 2013, planned for Spring 2015) to bring together the applications community to discuss both the applications of TRMM and GPM data as well as identify existing issues relating to data quality control, data access, and provenance.
- Communicate with end users on data and product access, availability and needs
- Work with the Office of Communications and Visualization groups to release GPM data imagery, including first light and subsequent data releases
- Represent GPM Science and Applications at both domestic and international conferences and meetings
- Serve as a GPM science liaison for many media activities, including Live Shots, Hyperwall Presentations, interviews, and other presentations
- Supervised, planned and implemented GPM’s Education and Public Outreach projects by leading a team of scientists, educators, and technical specialists to communicate the science and societal activities of the GPM mission to the general public.
1/2016
-
2/2017
Acting Associate Director for Applied Sciences at GSFC
NASA Goddard Space Flight Center,
Greenbelt, Maryland Serves as the principal operating official in the Division for planning, coordinating, and implementing strategies for applied science research at NASA GSFC. Responsible for the strategic initiatives and organizational processes leading to applied science research that strategically supports the mission of the Division.
Specific objectives and activities:
- Promote and facilitate coordination amongst scientists, missions and current/future partnerships within GSFC in the area of applied research and applications.
- Works with the ESD senior management team to guide the development of specific new business plans, including the development of the Division's investment plans, to foster strategic applied science research with the required institutional support.
- Manages and reports on Earth science applied research and mission applications activities to GSFC senior management and HQ representatives.
- Serves as the principal liaison and main point of contact between the Division and the NASA HQ Earth Sciences applied science research program and GSFC Mission applications activities and communicates activities throughout the organization
7/2010
-
1/2011
Research Associate
Earth System Science Interdisciplinary Center (ESSIC), University of Maryland,
Greenbelt, MD Collaborated with scientists in the Hydrological Sciences Branch at NASA Goddard to develop and test statistical and deterministic landslide models within the Land Information System (LIS) framework developed within the Hydrological Sciences Branch. Evaluation strategies consider how model inputs and spatial scaling impact performance accuracy.
Specific objectives:
• Improve a global satellite-based rainfall-triggered landslide hazard algorithm using LIS-based optimization strategies for threshold detection and characterize system uncertainty using sensitivity testing of input parameters.
• Integrate a physically-based slope-stability model into LIS and test input parameters using uncertainty testing of model variables and error characterization of slope stability outputs.
7/2009
-
6/2010
NASA Postdoctoral Program Fellow, NASA Goddard Space Flight Center
NASA Post Doctoral Program,
Greenbelt, MD Collaborated with scientists in the Hydrological Sciences Branch at NASA Goddard to develop and evaluate satellite-based landslide hazard assessment tools within the Land Information System (LIS) framework in order to improve global and regional landslide modeling capabilities.
Specific objectives:
• Integrate a newly developed landslide forecasting algorithm into Land Information System (LIS), an Earth system modeling and data assimilation platform
• Consider how the different spatial scales and accuracy of satellite and in situ data affect hazard evaluation and model outputs
• Characterize data and model sensitivity and within an uncertainty framework
• Advance modeling capabilities to improve satellite-based landslide hazard assessment and real-time hazard forecasting
8/2008
-
6/2009
Visiting Graduate Student, Massachusetts Institute of Technology (MIT)
Columbia University,
Cambridge, MA Collaborated with the Hydrology Research group in the Civil and Environmental Engineering Department to develop landslide susceptibility methodologies and compare results within Central America and the Caribbean region
Specific objectives:
• Focus on how the spatial and temporal resolution of surface and atmospheric satellite data effect landslide susceptibility assessment
• Work with colleagues in the Hydrology Group to developed two static landslide susceptibility methodologies
• Develop and evaluate two landslide susceptibility methodologies and compared model results for Central America and Puerto Rico
• Participated in bi-monthly Hydrology Research group meetings
• Continuing collaboration with several colleagues in the research group to improve landslide susceptibility and hazard modeling results and compare evaluation methodologies
6/2015
-
Present
GSFC Disaster Coordinator
NASA,
GSFC Leads disaster response activities for NASA to enable the use of satellite data and products during natural disasters to improve situational awareness and inform decision making. Also periodically represents at the OSTP Subcommittee for Disaster Reduction on behalf of NASA, which meets monthly.
Deputy Project Science for Applications for the Global Precipitation Measurement (GPM) mission
Lead scientific support for applications research and activities for the Global Precipitation Measurement (GPM) mission.
Specific objectives and activities:
• Coordinate and facilitate data access issues in terms of TRMM and GPM data format, accessibility and availability for expert to non-expert users
• Coordinate GPM Applications Workshop (Fall 2013, planned for Spring 2015) to bring together the applications community to discuss both the applications of TRMM and GPM data as well as identify existing issues relating to data quality control, data access, and provenance.
• Communicate with end users on data and product access, availability and needs
• Work with the Office of Communications and Visualization groups to release GPM data imagery, including first light and subsequent data releases
• Represent GPM Science and Applications at both domestic and international conferences and meetings
• Serve as a GPM science liaison for many media activities, including Live Shots, Hyperwall Presentations, interviews, and other presentations
• Coordinate GPM’s Education and Public Outreach projects by leading a team of scientists, educators, and technical specialists to communicate the science and societal activities of the GPM mission to the general public.
Disaster Response Coordinator for NASA Goddard Space Flight Center
Dr. Kirschbaum serves as the disaster coordinator for GSFC. In this role, she routinely interfaces with NASA HQ and the Disasters Program Manager to represent GSFC in disasters activities at the agency level. She has been coordinating disaster activities at GSFC since 2013.. She is also working to bring disaster-related experts and data system leaders together to discuss current activities and find synergistic projects across disciplines that could lead to futur opportunities.
High Mountain Asia Science Team
This project considers landslide hazard and impacts can vary on the order of hours to decades through the integration of landslide modeling, landslide inventories, satellite products and model projections. This work focuses on characterizing the spatial and temporal frequency of extreme rainfall across this region both in the past and into the future to establish relationships for how trends in extreme rainfall may modulate patterns in landslide activity and their impacts.
Landslide indicators for the National Climate Assessment
This project develops landslide and related indicators for the National Climate Assessment to support the characterization of potential landslide variability across the U.S. both in past and looking towards the future. This work brings together a database of landslide inventories from across the U.S., with a focus on the Pacific Northwest United States.
Precipitation Measurement Mission Science Team
This work considers how extreme rainfall characteristics vary in complex terrain and evaluate the limits of extreme rainfall estimates from satellites within the context of natural hazards. A main focus of this project is linking both empirical and deterministic landslide models with rainfall distributions to better understand the role that precipitation uncertainty plays in affecting landslide hazard assessment.
Co-lead of CEOS Disaster Working Group Landslide Pilot
Through this effort, Dr. Kirschbaum is co-leading a new Committee on Earth Observing Satellites (CEOS) Landslide Pilot, working closely with colleagues at the USGS and in Italy. She is working to formulate the pilot objectives and deliverables with representatives from the landslide and remote sensing communities from over 12 countries.
Disasters Applied Sciences Team
Through a project entitled "Enabling Landslide Disaster Risk Reduction and Response throughout the disaster life cycle with a multi-scale toolbox" this work focuses on assessing the impacts of landslides and cascading hazards triggered by heavy rainfall or earthquakes and how can these impacts (hazard, exposure and risk) be estimated dynamically for iterative decision making throughout the disaster lifecycle.This work leverages remotely sensed observations to develop rapid response data sets informed by pre-event characterization and post-event impacts, exposure and risk for landslides.
SERVIR Applied Science Team
Through a funded project entitled "Landslide Hazard and Risk Modeling in the SERVIR Mekong Region" this work seeks to expand landslide hazard and risk modeling activities within the Lower Mekong Region using newly available satellite sources and landslide models. This work will engage the SERVIR-Mekong hub to work with regional decision makers to characterize landslide hazard impacts at time and space scales relevant for their applications.
Co-lead of Applications Implementation Team for the ACCP Designated Observable Study
Serve as a co-lead for the Applications Implementation Team for the 3-year Aerosols, Clouds, Convection and Precipitation (ACCP) Designated Observable Study team. In this role I serve on the Science and Applications Leadership Team (SALT) for this study and work with a team to communicate and assess the applications value of different architectures being proposed for this DO study.
10/03/2016 -
09/30/2019
High Mountain Asia Science Team,
NASA
Multi-sensor impact analysis of cascading hazards and transportation corridors in Nepal
;
Science Team PI
05/01/2016 -
04/30/2019
Climate Indicators and Data Products for Future National Climate Assessments,
NASA
Landslide hazard and exposure indicators for the National Climate Assessment
;
Principal Investigator
01/01/2016 -
12/31/2018
Precipitation Measurement Missions Science Team,
NASA
A Regional Analysis Framework for Evaluating Satellite Rainfall Extremes in Complex Terrain for Landslide Hazards Applications
;
Principal Investigator
08/01/2012 -
07/31/2016
NASA SERVIR Applied Sciences Team,
NASA ROSES
Landslide Hazard Assessment and Forecasting System using near real-time remote sensing information over SERVIR-Mesoamerica
;
PI on project
10/01/2012 -
09/30/2015
NASA New Investigator Program (NIP) in Earth Science,
NASA ROSES
Application of remotely sensed information to a multi-scale landslide modeling and forecasting framework
;
PI for project
07/11/2012 -
06/30/2015
NASA Earth Surface and Interior,
NASA ROSES
Advancing Multi-scale Landslide Hazard Prediction by Integrating High Resolution Remote Sensing Data and Subsurface In-situ Monitoring
;
Co-I for project
02/01/2012 -
01/31/2015
NASA AIST: Advanced Information Systems Technology,
NASA ROSES
A mission simulation and evaluation platform for terrestrial hydrology using the NASA Land Information System (LIS)
;
Co-I on project
02/04/2019 -
02/03/2022
Precipitation Measurement Missions (PMM) Science Team,
NASA, NASA NRA #: NNH18ZDA001N
Characterizing and Communicating Global IMERG Error Estimates for End User Applications
04/15/2019 -
04/14/2022
Earth Science Applications: Disaster Risk Reduction and Response,
NASA ROSES, NASA NRA #: NNH18ZDA001N
Enabling Landslide Disaster Risk Reduction and Response throughout the disaster life cycle with a multi-scale toolbox
;
As Project Investigator of the project I am coordinating and overseeing the work and conducting landslide hazard and risk analyses in coordination with the team.
10/01/2019 -
09/30/2022
SERVIR Applied Science Team,
NASA, NASA NRA #: NNH18ZDA001N-SERVIR
A Landslide Hazard and Risk Assessment System for SERVIR-Mekong
;
I am leading a team in coordination with the Asia Disaster Preparedness Center (ADPC) to develop landslide hazard and risk tools to improve situational awareness and planning in the SERVIR Mekong Region.
2019: Robert H. Goddard Science Honor Award for Scientific Achievement
2018: Scientific Achievement Award NASA’s Hydrospheric and Biospheric Lab
2017: Presidential Early Career Award for Scientists and Engineers (PECASE) - Awarded by Obama, January 2017
2017: Arthur S. Flemming Award
2016: Scientific Achievement Award NASA’s Hydrospheric and Biospheric Labs
2015: Robbert H Goddard Exceptional Achievement Outreach Team - GPM Outreach Team Award
2014: NASA Agency Award - Early Career Achievement Medal
2014: Achievement in Outreach Award from NASA's Hydrospheric and Biospheric Labs
2013 Best Publication from NASA’s Hydrospheric and Biospheric Labs
2005 Sara F. Langer Book Prize, Lamont-Doherty Earth Observatory
2004 William Bonini Prize for Excellence in Teaching, Geosciences, Princeton University
Guest Scientist on NASA Science Live Episode 4 - Storms Across the Solar System
5
/
2019
-
5
/
2019
https://www.nasa.gov/nasasciencelive
NASA Science Live is a 30 minute show put on by the NASA Communications team that takes viewers behind-the-scenes alongside expert to explore the secrets of the universe. Episode 4 featured storms across the universe, including our home planet Earth.
Media Liveshots for GPM IMERG 20-year Release
4
/
2020
-
4
/
2020
https://svs.gsfc.nasa.gov/Gallery/GPM.html
Conducted 15 Media interviews with outlets across the U.S. to talk about the recent roll-out of the near 20-year GPM IMERG product, that now spans 2000-2020.
Live Launch Coverage of the Global Precipitation Measurement (GPM) mission Core Observatory
2
/
2014
-
2
/
2014
http://svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=11496#18869
I was the science host for 3 hours of Live launch coverage on NASATV for the launch of the GPM Core Observatory satellite from Tanegashima Space Center, Japan. I was the co-host to provide information to the public about what was happening prior to the launch, give people a background on the the mission and its relevance, and interview other scientists about the mission. A link to this coverage can be found at http://svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=11496#18869
Communicating GPM Science to the community
7
/
2010
-
Present
Presented GPM overview talks on applications and E/PO activities to thousands of people and tens of talks, including (but not limited to): Museum Alliance, Earth to Sky Workshop, NOAA User Workshop on GPM, PMM Science Team Meetings, IGARSS Annual Meeting, AGU Hyperwall, GSA Hyperwall, classroom visits (K-12, college)
GPM Education and Outreach Coordinator
7
/
2009
-
Present
As the Education and Outreach coordinator for GPM, I have given a large number of presentations to groups ranging from elementary and middle school students, to high schoolers, community and 4-year college audiences, Capitol Hill staff members, congressmen, and delegations from other countries. I have given many tours of the GPM satellite when it was being built and tested at GSFC and was the science host of the program covering GPM's launch on February 27th, 2014. I have also participated in Live Shots and given a large number of hyperwall presentations relating to GPM and the water cycle.
Editor/reviewer of Journal articles
2014
-
Present
• Served as guest editor for the Journal of Earth and Environmental Sciences, Special Issue: Remote Sensing and Modeling of Landslides: Detection, Monitoring and Risk Evaluation.
• Reviewed at least 1 research paper per month for various journals (Natural Hazards, Natural Hazards and Earth Systems Sciences, International Journal of Remote Sensing, Earth and Environmental Sciences, etc.)
Refereed
Emberson, R., D. Kirschbaum, and T. Stanley. 2021. "Global connections between El Nino and landslide impacts."
Nature Communications,
12
(1):
2262
[10.1038/s41467-021-22398-4]
Amatya, P., D. Kirschbaum, T. Stanley, and H. Tanyas. 2021. "Landslide mapping using object-based image analysis and open source tools."
Engineering Geology,
282:
106000
[10.1016/j.enggeo.2021.106000]
Emberson, R. A., D. B. Kirschbaum, and T. Stanley. 2021. "Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh."
Earth's Future,
9
(2):
[10.1029/2020ef001666]
Getirana, A., D. Kirschbaum, F. Mandarino, et al. 2020. "Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil."
Remote Sensing,
12
(24):
4095
[10.3390/rs12244095]
Emberson, R., D. Kirschbaum, and T. Stanley. 2020. "New global characterisation of landslide exposure."
Natural Hazards and Earth System Sciences,
20
(12):
3413-3424
[10.5194/nhess-20-3413-2020]
Hartke, S. H., D. B. Wright, D. B. Kirschbaum, T. A. Stanley, and Z. Li. 2020. "Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System."
Journal of Hydrometeorology,
21
(8):
1741-1759
[10.1175/jhm-d-19-0295.1]
Mirus, B. B., E. S. Jones, R. L. Baum, et al. 2020. "Landslides across the USA: occurrence, susceptibility, and data limitations."
Landslides,
17:
2271–2285
[10.1007/s10346-020-01424-4]
Ward, P. J., V. Blauhut, N. Bloemendaal, et al. 2020. "Review article: Natural hazard risk assessments at the global scale."
Natural Hazards and Earth System Sciences,
20
(4):
1069-1096
[10.5194/nhess-20-1069-2020]
Stanley, T. A., D. B. Kirschbaum, S. Pascale, and S. Kapnick. 2020. "Extreme Precipitation in the Himalayan Landslide Hotspot."
Satellite Precipitation,
69:
1087-1111
[10.1007/978-3-030-35798-6]
Stanley, T., D. Kirschbaum, S. Sobieszczyk, et al. 2020. "Building a landslide hazard indicator with machine learning and land surface models."
Environmental Modelling & Software,
129:
104692
[10.1016/j.envsoft.2020.104692]
Kirschbaum, D., S. Kapnick, T. Stanley, and S. Pascale. 2020. "Changes in Extreme Precipitation and Landslides Over High Mountain Asia."
Geophysical Research Letters,
47
(4):
[10.1029/2019gl085347]
Amatya, P., D. Kirschbaum, and T. Stanley. 2019. "Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal."
Remote Sensing,
11
(19):
2284
[10.3390/rs11192284]
Kirschbaum, D., C. S. Watson, D. R. Rounce, et al. 2019. "The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia."
Frontiers in Earth Science,
7:
[10.3389/feart.2019.00197]
Juang, C. S., T. A. Stanley, and D. B. Kirschbaum. 2019. "Using citizen science to expand the global map of landslides: Introducing the Cooperative Open Online Landslide Repository (COOLR)."
PLOS ONE,
14
(7):
e0218657
[10.1371/journal.pone.0218657]
Yoon, Y., S. V. Kumar, B. A. Forman, et al. 2019. "Evaluating the uncertainty of terrestrial water budget components over High Mountain Asia."
Frontiers in Earth Science,
7:
[10.3389/feart.2019.00120]
Fayne, J. V., A. Ahamed, J. Roberts-Pierel, A. C. Rumsey, and D. Kirschbaum. 2019. "Automated Satellite-Based Landslide Identification Product for Nepal."
Earth Interactions,
23
(3):
1-21
[10.1175/ei-d-17-0022.1]
Yatheendradas, S., D. Kirschbaum, G. Nearing, et al. 2019. "Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations."
Computational Geosciences,
[10.1007/s10596-018-9804-y]
Monsieurs, E., D. B. Kirschbaum, J. Tan, et al. 2018. "Evaluating TMPA Rainfall over the Sparsely Gauged East African Rift."
Journal of Hydrometeorology,
19
(9):
1507-1528
[10.1175/jhm-d-18-0103.1]
Skofronick-Jackson, G., W. Berg, C. Kidd, et al. 2018. "Global Precipitation Measurement (GPM): Unified Precipitation Estimation from Space."
Springer Remote Sensing/Photogrammetry,
175-193
[10.1007/978-3-319-72583-3_7]
Skofronick-Jackson, G., D. Kirschbaum, W. Petersen, et al. 2018. "The Global Precipitation Measurement (GPM) mission's scientific achievements and societal contributions: reviewing four years of advanced rain and snow observations."
Quarterly Journal of the Royal Meteorological Society,
144:
27-48
[10.1002/qj.3313]
Kirschbaum, D., and T. Stanley. 2018. "Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness."
Earth's Future,
6
(3):
505-523
[Full Text (Link)]
[10.1002/2017ef000715]
Skofronick-Jackson, G., W. A. Petersen, W. Berg, et al. 2017. "The Global Precipitation Measurement (GPM) Mission for Science and Society."
Bulletin of the American Meteorological Society,
98
(8):
1679-1695
[10.1175/bams-d-15-00306.1]
Wright, D. B., D. B. Kirschbaum, and S. Yatheendradas. 2017. "Satellite Precipitation Characterization, Error Modeling, and Error Correction Using Censored Shifted Gamma Distributions."
Journal of Hydrometeorology,
18
(10):
JHM-D-17-0060.1
[10.1175/jhm-d-17-0060.1]
Stanley, T. A., and D. B. Kirschbaum. 2017. "Effects of inventory bias on landslide susceptibility calculations."
Landslides: Putting Experience, Knowledge And Emerging Technologies Into Practice, AEG Special Publication No. 27,
794-806,
ISBN: 978-0-9897253-7-8.
Kirschbaum, D. B., G. J. Huffman, R. Adler, et al. 2017. "NASA’s Remotely-sensed Precipitation: A Reservoir for Applications Users."
Bulletin of the American Meteorological Society,
98
(6):
1169-1184
[10.1175/BAMS-D-15-00296.1]
Stanley, T., D. B. Kirschbaum, G. J. Huffman, and R. F. Adler. 2017. "Approximating Long-Term Statistics Early in the Global Precipitation Measurement Era."
Earth Interactions,
21
(3):
1-10
[10.1175/ei-d-16-0025.1]
Rossi, M., S. Luciani, D. Valigi, et al. 2017. "Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data."
Geomorphology,
285:
16-27
[10.1016/j.geomorph.2017.02.001]
Stanley, T., and D. B. Kirschbaum. 2017. "A heuristic approach to global landslide susceptibility mapping."
Natural Hazards,
1-20
[10.1007/s11069-017-2757-y]
Kidd, C., A. Becker, G. J. Huffman, et al. 2017. "So, how much of the Earth’s surface is covered by rain gauges?"
Bulletin of the American Meteorological Society,
98
(1):
69-78
[10.1175/bams-d-14-00283.1]
Biasutti, M., R. Seager, and D. B. Kirschbaum. 2016. "Landslides in West Coast metropolitan areas: The role of extreme weather events."
Weather and Climate Extremes,
14:
67-79
[10.1016/j.wace.2016.11.004]
Wu, H., M. Huang, Q. Tang, D. B. Kirschbaum, and P. Ward. 2016. "Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses."
Advances in Meteorology,
2016:
1-3
[10.1155/2016/2367939]
Schumann, G., D. Kirschbaum, E. Anderson, and K. Rashid. 2016. "Role of Earth Observation data in disaster response and recovery: from science to capacity building."
Earth Science Satellite Applications: Current and Future Prospects,
119-146,
ISBN: 978-3-319-33436-3.
[10.1007/978-3-319-33438-7_5]
Schumann, G. J., S. Frye, G. Wells, et al. 2016. "Unlocking the full potential of Earth observation during the 2015 Texas flood disaster."
Water Resources Research,
52
(5):
3288-3293
[10.1002/2015wr018428]
Kirschbaum, D. B., and K. G. Patel. 2016. "Precipitation data key to food security and public health."
Eos,
97:
[Full Text (Link)]
[10.1029/2016EO045583]
Kirschbaum, D. B., T. Stanley, and S. '. Yatheendradas. 2016. "Modeling Landslide Susceptibility over Large Regions with Fuzzy Overlay."
Landslides,
13:
485-496
[Full Text (Link)]
[10.1007/s10346-015-0577-2]
Kargel, J. S., G. J. Leonard, D. H. Shugar, et al. 2015. "Geomorphic and geologic controls of geohazards induced by Nepals 2015 Gorkha earthquake."
Science,
351
(6269):
aac8353-aac8353
[10.1126/science.aac8353]
Kirschbaum, D. B., T. Stanley, and Y. Zhou. 2015. "Spatial and temporal analysis of a global landslide catalog."
Geomorphology,
249
(Geohazard Databases):
4-15
[Full Text (Link)]
[10.1016/j.geomorph.2015.03.016]
Kirschbaum, D. B., T. Stanley, and J. M. Simmons. 2015. "A Dynamic Landslide Hazard Assessment System for Central America and Hispaniola."
Natural Hazards and Earth System Sciences,
15
(10):
2257-2272
[Full Text (Link)]
[10.5194/nhess-15-2257-2015]
Wan, Z., Y. Hong, S. Khan, et al. 2014. "A cloud-based global flood disaster community cyber-infrastructure: Development and demonstration."
Environmental Modelling & Software,
58:
86–94
[10.1016/j.envsoft.2014.04.007]
Kumar, S. V., K. W. Harrison, C. D. Peters-Lidard, J. A. Santanello, and D. B. Kirschbaum. 2014. "Assessing the Impact of L-Band Observations on Drought and Flood Risk Estimation: A Decision-Theoretic Approach in an OSSE Environment."
J. Hydrometeor,
15
(6):
2140-2156
[Full Text (Link)]
[10.1175/JHM-D-13-0204.1]
Taramelli, A., M. Pasqui, J. Barbour, et al. 2013. "Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis."
Earth Surface Processes and Landforms,
38
(8):
793–809
[10.1002/esp.3321]
Kucera, P. A., E. E. Ebert, J. F. Turk, et al. 2013. "Precipitation from Space: Advancing Earth System Science."
Bulletin of the American Meteorological Society,
94
(3):
365-375
[10.1175/BAMS-D-11-00171.1]
Kirschbaum, D. B., R. F. Adler, D. Adler, C. D. Peters-Lidard, and G. J. Huffman. 2012. "Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years."
J. Hydrometeor.,
13
(5):
1536-1551
[10.1175/JHM-D-12-02.1]
Liao, Z., Y. Hong, D. Kirschbaum, and C. Liu. 2012. "Assessment of shallow landslides from Hurricane Mitch in central America using a physically based model."
Environmental Earth Sciences,
66
(6):
1697-1705
[10.1007/s12665-011-0997-9]
Kirschbaum, D. B., and H. Fukuoka. 2012. "Remote sensing and modeling of landslides: detection, monitoring and risk evaluation."
Environmental Earth Sciences,
66
(6):
1583
[10.1007/s12665-012-1543-0]
Kirschbaum, D. B., R. F. Adler, Y. Hong, S. V. Kumar, and C. D. Peters-Lidard. 2011. "Advances in landslide nowcasting: evaluation of a global and regional modeling approach."
Environmental Earth Sciences,
66
(6):
1683-1696
[10.1007/s12665-011-0990-3]
Hong, Y., R. F. Adler, D. B. Kirschbaum, and G. J. Huffman. 2010. "Capacity Building for Disaster Prevention in Vulnerable Regions of the World: Development of a Prototype Global Flood/Landslide Prediction System."
Disaster Advances,
3
(3):
14-19.
Kirschbaum, D. B., R. F. Adler, Y. Hong, S. Hill, and A. Lerner-Lam. 2010. "A global landslide catalog for hazard applications: method, results, and limitations."
Natural Hazards,
52
(3):
561-575
[10.1007/s11069-009-9401-4]
Kirschbaum, D., R. Adler, Y. Hong, and A. Lerner-Lam. 2009. "Evaluation of a Satellite-based Landslide Algorithm using Global Landslide Inventories."
Natural Hazards and Earth System Sciences,
9:
673-686.
Kirschbaum, D., R. F. Adler, Y. Hong, and A. Lerner-Lam. 2009. "Evaluation of a preliminary satellite-based landslide hazard algorithm using global landslide inventories."
Natural Hazards and Earth System Science,
9
(3):
673-686
[10.5194/nhess-9-673-2009]
Non-Refereed
Kirschbaum, D. B. 2017. "A view from above: Earth Observation."
Crisis Response Journal
12
(4):
64-67.
Ward, A., D. Kirschbaum, and M. Hobish. 2015. "Measuring Rain and Snow for Science and Society: The Second GPM Applications Workshop."
The Earth Observer
27
(5):
4--11.
American Geophysical Union,
2003
-
Present
2013-present: Natural Hazards Focus Group Fall Meeting Program Committee
American Meteorological Society,
2010
-
2012
Geological Society of America,
2009
-
2011
2019-present: President-Elect for AGU Natural Hazards Section
2019-present: Editor for Remote Sensing in Earth System Sciences Journal
2013-present: Executive Committee for the Remote Sensing and Hydrology Focus Group for AGU
2014-present: Executive Committee for Natural Hazards Focus Group
2015-present CEOS Disaster Working Group Landslide Pilot Lead
2013-2015: Program Committee for AGU Natural Hazards Focus Group
2009-present Convened landslide sessions in the Natural Hazards Focus Group at the Fall AGU Conference in San Francisco
November 2013: 1st GPM/TRMM Applications Workshop: November, 2013 - Coordinated and ran meeting. https://pmm.nasa.gov/meetings/2015-gpm-applications-workshop
June 2015: 2nd GPM/TRMM Applications Workshop - Coordinated and ran meeting.https://pmm.nasa.gov/meetings/2015-gpm-applications-workshop
Invited
Global Landslide Hazard Assessment with Satellite Data
9
/
28
/
2017
Remote presentation to group of landslide experts from Indonesia regarding the use of satellite capabilities for landslide hazard assessment and monitoring.
Presenter at Library of Congress NASA Series
8
/
11
/
2015
Panelist on National Research Council Agenda for NRC Special Workshop on Landslides
2
/
24
/
2015
Finding the Slippery Slope: “Detecting” Landslides from Space
3
/
2014
NASA Goddard Science Colloquim
Finding the Slippery Slope: Detecting Landslides from Space
1
/
2014
Gerald Soffen Public Lecture at NASA GSFC VIsitor's Center
Evaluation of a Satellite-based Landslide Algorithm using Global Landslide Inventories
9
/
2011
Colorado School of Mines/USGS Hazards Seminar Series
Other
Uncertainty evaluation of a regional real-time system for rain-induced landslides
4
/
15
/
2015
A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three variables: a static susceptibility map; a 24 rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. Dynamic thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables and generates a landslide nowcast in real-time based on the previous 24 hours over this region.
This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics are presented here based on evaluation of landslides reported within the catalog as well as comparisons with other regional models. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.
Uncertainty and Sensitivity analysis of a physically-based landslide model
4
/
17
/
2015
Rainfall-induced landslides are hazardous to life and property. Rain data sources like satellite remote sensors combined with physically-based models of landslide initiation are a potentially economical solution for anticipating and early warning of possible landslide activity. In this work, we explore the output uncertainty of the physically-based USGS model, TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability) under both an a priori model parameter specification scenario and a model calibration scenario using a powerful stochastic optimization algorithm. We study a set of 50+ historic landslides over the Macon County in North Carolina as an example regional robust analysis. We then conduct a robust multivariate sensitivity analysis of the modeled output to various factors including rainfall forcing, initial and boundary conditions, and model parameters including topographic slope. Satellite rainfall uncertainty distributions are prescribed based on stochastic regressions to benchmark rain values at each location. Information about the most influential factors from sensitivity analysis will help to preferentially direct field work efforts towards associated observations. This will contribute to reducing output uncertainty in future modeling efforts. We also show how we can conveniently reduce model complexity considering negligibly influential factors to maintain example required levels of predictive accuracy and uncertainty.
Teaching Assistant and lecturer for a Graduate Seminar for SIPA Policy students at Columbia University (2005)
Teaching Assistant for an undergraduate Hazards course at Barnard College.
Teaching Assistant for Upper Level Natural Hazards Seminar and Laboratory Assistant for entry level geology course on Volcanoes and Earthquakes at Princeton University.
Developed Landslide Catalog and Model Framework: Website https://pmm.nasa.gov/precip-apps
Refereed
Emberson, R., D. Kirschbaum, and T. Stanley. 2021. "Global connections between El Nino and landslide impacts."
Nature Communications
12
(1):
2262
[10.1038/s41467-021-22398-4]
Amatya, P., D. Kirschbaum, T. Stanley, and H. Tanyas. 2021. "Landslide mapping using object-based image analysis and open source tools."
Engineering Geology
282
106000
[10.1016/j.enggeo.2021.106000]
Emberson, R. A., D. B. Kirschbaum, and T. Stanley. 2021. "Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh."
Earth's Future
9
(2):
[10.1029/2020ef001666]
Getirana, A., D. Kirschbaum, F. Mandarino, et al. 2020. "Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil."
Remote Sensing
12
(24):
4095
[10.3390/rs12244095]
Emberson, R., D. Kirschbaum, and T. Stanley. 2020. "New global characterisation of landslide exposure."
Natural Hazards and Earth System Sciences
20
(12):
3413-3424
[10.5194/nhess-20-3413-2020]
Hartke, S. H., D. B. Wright, D. B. Kirschbaum, T. A. Stanley, and Z. Li. 2020. "Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System."
Journal of Hydrometeorology
21
(8):
1741-1759
[10.1175/jhm-d-19-0295.1]
Mirus, B. B., E. S. Jones, R. L. Baum, et al. 2020. "Landslides across the USA: occurrence, susceptibility, and data limitations."
Landslides
17
2271–2285
[10.1007/s10346-020-01424-4]
Ward, P. J., V. Blauhut, N. Bloemendaal, et al. 2020. "Review article: Natural hazard risk assessments at the global scale."
Natural Hazards and Earth System Sciences
20
(4):
1069-1096
[10.5194/nhess-20-1069-2020]
Stanley, T. A., D. B. Kirschbaum, S. Pascale, and S. Kapnick. 2020. "Extreme Precipitation in the Himalayan Landslide Hotspot."
Satellite Precipitation
69
1087-1111
[10.1007/978-3-030-35798-6]
Stanley, T., D. Kirschbaum, S. Sobieszczyk, et al. 2020. "Building a landslide hazard indicator with machine learning and land surface models."
Environmental Modelling & Software
129
104692
[10.1016/j.envsoft.2020.104692]
Kirschbaum, D., S. Kapnick, T. Stanley, and S. Pascale. 2020. "Changes in Extreme Precipitation and Landslides Over High Mountain Asia."
Geophysical Research Letters
47
(4):
[10.1029/2019gl085347]
Amatya, P., D. Kirschbaum, and T. Stanley. 2019. "Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal."
Remote Sensing
11
(19):
2284
[10.3390/rs11192284]
Kirschbaum, D., C. S. Watson, D. R. Rounce, et al. 2019. "The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia."
Frontiers in Earth Science
7
[10.3389/feart.2019.00197]
Juang, C. S., T. A. Stanley, and D. B. Kirschbaum. 2019. "Using citizen science to expand the global map of landslides: Introducing the Cooperative Open Online Landslide Repository (COOLR)."
PLOS ONE
14
(7):
e0218657
[10.1371/journal.pone.0218657]
Yoon, Y., S. V. Kumar, B. A. Forman, et al. 2019. "Evaluating the uncertainty of terrestrial water budget components over High Mountain Asia."
Frontiers in Earth Science
7
[10.3389/feart.2019.00120]
Fayne, J. V., A. Ahamed, J. Roberts-Pierel, A. C. Rumsey, and D. Kirschbaum. 2019. "Automated Satellite-Based Landslide Identification Product for Nepal."
Earth Interactions
23
(3):
1-21
[10.1175/ei-d-17-0022.1]
Yatheendradas, S., D. Kirschbaum, G. Nearing, et al. 2019. "Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations."
Computational Geosciences
[10.1007/s10596-018-9804-y]
Monsieurs, E., D. B. Kirschbaum, J. Tan, et al. 2018. "Evaluating TMPA Rainfall over the Sparsely Gauged East African Rift."
Journal of Hydrometeorology
19
(9):
1507-1528
[10.1175/jhm-d-18-0103.1]
Skofronick-Jackson, G., W. Berg, C. Kidd, et al. 2018. "Global Precipitation Measurement (GPM): Unified Precipitation Estimation from Space."
Springer Remote Sensing/Photogrammetry
175-193
[10.1007/978-3-319-72583-3_7]
Skofronick-Jackson, G., D. Kirschbaum, W. Petersen, et al. 2018. "The Global Precipitation Measurement (GPM) mission's scientific achievements and societal contributions: reviewing four years of advanced rain and snow observations."
Quarterly Journal of the Royal Meteorological Society
144
27-48
[10.1002/qj.3313]
Kirschbaum, D., and T. Stanley. 2018. "Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness."
Earth's Future
6
(3):
505-523
[Full Text (Link)]
[10.1002/2017ef000715]
Skofronick-Jackson, G., W. A. Petersen, W. Berg, et al. 2017. "The Global Precipitation Measurement (GPM) Mission for Science and Society."
Bulletin of the American Meteorological Society
98
(8):
1679-1695
[10.1175/bams-d-15-00306.1]
Wright, D. B., D. B. Kirschbaum, and S. Yatheendradas. 2017. "Satellite Precipitation Characterization, Error Modeling, and Error Correction Using Censored Shifted Gamma Distributions."
Journal of Hydrometeorology
18
(10):
JHM-D-17-0060.1
[10.1175/jhm-d-17-0060.1]
Stanley, T. A., and D. B. Kirschbaum. 2017. "Effects of inventory bias on landslide susceptibility calculations."
Landslides: Putting Experience, Knowledge And Emerging Technologies Into Practice, AEG Special Publication No. 27
794-806
Kirschbaum, D. B., G. J. Huffman, R. Adler, et al. 2017. "NASA’s Remotely-sensed Precipitation: A Reservoir for Applications Users."
Bulletin of the American Meteorological Society
98
(6):
1169-1184
[10.1175/BAMS-D-15-00296.1]
Stanley, T., D. B. Kirschbaum, G. J. Huffman, and R. F. Adler. 2017. "Approximating Long-Term Statistics Early in the Global Precipitation Measurement Era."
Earth Interactions
21
(3):
1-10
[10.1175/ei-d-16-0025.1]
Rossi, M., S. Luciani, D. Valigi, et al. 2017. "Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data."
Geomorphology
285
16-27
[10.1016/j.geomorph.2017.02.001]
Stanley, T., and D. B. Kirschbaum. 2017. "A heuristic approach to global landslide susceptibility mapping."
Natural Hazards
1-20
[10.1007/s11069-017-2757-y]
Kidd, C., A. Becker, G. J. Huffman, et al. 2017. "So, how much of the Earth’s surface is covered by rain gauges?"
Bulletin of the American Meteorological Society
98
(1):
69-78
[10.1175/bams-d-14-00283.1]
Biasutti, M., R. Seager, and D. B. Kirschbaum. 2016. "Landslides in West Coast metropolitan areas: The role of extreme weather events."
Weather and Climate Extremes
14
67-79
[10.1016/j.wace.2016.11.004]
Wu, H., M. Huang, Q. Tang, D. B. Kirschbaum, and P. Ward. 2016. "Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses."
Advances in Meteorology
2016
1-3
[10.1155/2016/2367939]
Schumann, G., D. Kirschbaum, E. Anderson, and K. Rashid. 2016. "Role of Earth Observation data in disaster response and recovery: from science to capacity building."
Earth Science Satellite Applications: Current and Future Prospects
119-146
[10.1007/978-3-319-33438-7_5]
Schumann, G. J., S. Frye, G. Wells, et al. 2016. "Unlocking the full potential of Earth observation during the 2015 Texas flood disaster."
Water Resources Research
52
(5):
3288-3293
[10.1002/2015wr018428]
Kirschbaum, D. B., and K. G. Patel. 2016. "Precipitation data key to food security and public health."
Eos
97
[Full Text (Link)]
[10.1029/2016EO045583]
Kirschbaum, D. B., T. Stanley, and S. '. Yatheendradas. 2016. "Modeling Landslide Susceptibility over Large Regions with Fuzzy Overlay."
Landslides
13
485-496
[Full Text (Link)]
[10.1007/s10346-015-0577-2]
Kargel, J. S., G. J. Leonard, D. H. Shugar, et al. 2015. "Geomorphic and geologic controls of geohazards induced by Nepals 2015 Gorkha earthquake."
Science
351
(6269):
aac8353-aac8353
[10.1126/science.aac8353]
Kirschbaum, D. B., T. Stanley, and Y. Zhou. 2015. "Spatial and temporal analysis of a global landslide catalog."
Geomorphology
249
(Geohazard Databases):
4-15
[Full Text (Link)]
[10.1016/j.geomorph.2015.03.016]
Kirschbaum, D. B., T. Stanley, and J. M. Simmons. 2015. "A Dynamic Landslide Hazard Assessment System for Central America and Hispaniola."
Natural Hazards and Earth System Sciences
15
(10):
2257-2272
[Full Text (Link)]
[10.5194/nhess-15-2257-2015]
Wan, Z., Y. Hong, S. Khan, et al. 2014. "A cloud-based global flood disaster community cyber-infrastructure: Development and demonstration."
Environmental Modelling & Software
58
86–94
[10.1016/j.envsoft.2014.04.007]
Kumar, S. V., K. W. Harrison, C. D. Peters-Lidard, J. A. Santanello, and D. B. Kirschbaum. 2014. "Assessing the Impact of L-Band Observations on Drought and Flood Risk Estimation: A Decision-Theoretic Approach in an OSSE Environment."
J. Hydrometeor
15
(6):
2140-2156
[Full Text (Link)]
[10.1175/JHM-D-13-0204.1]
Taramelli, A., M. Pasqui, J. Barbour, et al. 2013. "Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis."
Earth Surface Processes and Landforms
38
(8):
793–809
[10.1002/esp.3321]
Kucera, P. A., E. E. Ebert, J. F. Turk, et al. 2013. "Precipitation from Space: Advancing Earth System Science."
Bulletin of the American Meteorological Society
94
(3):
365-375
[10.1175/BAMS-D-11-00171.1]
Kirschbaum, D. B., R. F. Adler, D. Adler, C. D. Peters-Lidard, and G. J. Huffman. 2012. "Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years."
J. Hydrometeor.
13
(5):
1536-1551
[10.1175/JHM-D-12-02.1]
Liao, Z., Y. Hong, D. Kirschbaum, and C. Liu. 2012. "Assessment of shallow landslides from Hurricane Mitch in central America using a physically based model."
Environmental Earth Sciences
66
(6):
1697-1705
[10.1007/s12665-011-0997-9]
Kirschbaum, D. B., and H. Fukuoka. 2012. "Remote sensing and modeling of landslides: detection, monitoring and risk evaluation."
Environmental Earth Sciences
66
(6):
1583
[10.1007/s12665-012-1543-0]
Kirschbaum, D. B., R. F. Adler, Y. Hong, S. V. Kumar, and C. D. Peters-Lidard. 2011. "Advances in landslide nowcasting: evaluation of a global and regional modeling approach."
Environmental Earth Sciences
66
(6):
1683-1696
[10.1007/s12665-011-0990-3]
Hong, Y., R. F. Adler, D. B. Kirschbaum, and G. J. Huffman. 2010. "Capacity Building for Disaster Prevention in Vulnerable Regions of the World: Development of a Prototype Global Flood/Landslide Prediction System."
Disaster Advances
3
(3):
14-19
Kirschbaum, D. B., R. F. Adler, Y. Hong, S. Hill, and A. Lerner-Lam. 2010. "A global landslide catalog for hazard applications: method, results, and limitations."
Natural Hazards
52
(3):
561-575
[10.1007/s11069-009-9401-4]
Kirschbaum, D., R. Adler, Y. Hong, and A. Lerner-Lam. 2009. "Evaluation of a Satellite-based Landslide Algorithm using Global Landslide Inventories."
Natural Hazards and Earth System Sciences
9
673-686
Kirschbaum, D., R. F. Adler, Y. Hong, and A. Lerner-Lam. 2009. "Evaluation of a preliminary satellite-based landslide hazard algorithm using global landslide inventories."
Natural Hazards and Earth System Science
9
(3):
673-686
[10.5194/nhess-9-673-2009]
Non-Refereed
Kirschbaum, D. B. 2017. "A view from above: Earth Observation."
Crisis Response Journal
12
(4):
64-67
Ward, A., D. Kirschbaum, and M. Hobish. 2015. "Measuring Rain and Snow for Science and Society: The Second GPM Applications Workshop."
The Earth Observer
27
(5):
4--11
