Ryan Engstrom

Ryan Engstrom headshot

Ryan Engstrom

Professor, Director of Data Science

Geospatial Science and Applications


Email: Ryan Engstrom
Office Phone: (202) 994-7979
2036 H St NW, Room 210 Washington, DC 20052

Office Hours
Thursdays 2:00pm – 4:00pm and by appointment via Webex

Current Projects

Ryan Engstrom is a Professor of Geography and the Director of the Data Science Program at George Washington University. He is the Director of the Center for Urban and Environmental Research (CUER) and the Spatial Analysis Lab (SAL). He earned his Ph.D. in Geography from the joint program between San Diego State University and University of California, Santa Barbara. His research interests are in using geospatial techniques primarily remote sensing, to understand spatial variations in a wide array of issues including climate change, health, poverty, and population. He has worked in numerous geographic areas including the Arctic, Africa, Asia, and Washington, DC. He has been funded by and collaborated with a wide range of institutions including NASA, NSF, NIH, World Bank, USAID, Children’s National Medical Center, Bill and Melinda Gates Foundation, and the Ford Foundation. He has taught Introduction to Remote Sensing and a follow-on class Digital Image Processing for the last 15 years. In addition to his work at GWU, Dr. Engstrom consulted with the United States Census Bureau, the World Bank, the Inter-American Development Bank, Radiant Earth Foundation, and Fraym.


Remote Sensing
Climate Change
Arctic Environments
Population Estimates

GEOG 1002 - Physical Geography 
GEOG 2107 - Introductory Remote Sensing
GEOG 2136 - Water Resources
GEOG 6307 - Digital Image Processing and Analysis


Iacone, B., Allington, G., and Engstrom, R (2022) A Methodology for Georeferencing and Mosaicking Corona Imagery in Semi-Arid Environments. Remote Sensing. 14(21), 5395; https://doi.org/10.3390/rs14215395

Masaka, T., Newhouse, D., Silwal, A., Bedada, A, and Engstrom, R. (2022) Small Area Estimation of Non-Monetary Poverty with Geospatial Data. The Review of Economics and Statistics (Statistical Journal of the International Association of Official Statistics (IAOS)) DOI: 10.3233/SJI-210902

Chao, S., Engstrom, R., Mann, M.L., and Bedada, A. (2021) Evaluating the Ability to Use Contextual Features Derived from Multi-Scale Satellite Imagery to Map Spatial Patterns of Urban Attributes and Population Distributions, Remote Sensing 13(9). DOI: /10.3390/rs13193962

Engstrom, R., Hersh, J. and Newhouse, D. (2021) Poverty from Space: Using High-Resolution Satellite Imagery for Welfare Estimation, World Bank Economic Review (WBER). Lhab015. DOI: /10.1093/wber/lhab015

Engstrom, R., Newhouse, D., and Soundararajan, V. (2020) Estimating Small Area Population Density Using Satellite Imagery: An Application to Sri Lanka, PlosONE 15 (8) https://journals.plos.org/plosone/article?id=10.1371/journal.pone.02370…

Hersh, J., Engstrom, R. and Mann, M. (2020) Open Data for Development: Mapping Poverty in Belize Using Open Satellite Derived Features and Machine Learning, Information Technology for Development https://doi.org/10.1080/02681102.2020.1811945

Kuffer, M., Thomson, D.R., Boo, G., Mahabir, R.; Grippa, T., Vanhuysse, S., Engstrom, R., Ndugwa, R., Makau, J., Darin, E., de Albuquerque, J.P., and Kabaria, C. (2020) The Role of Earth Observation in an Integrated Deprived Area Mapping “System” for Low-to-Middle Income Countries. Remote Sensing12, 982. Doi: 10.3390/rs12060982

Kugler, T.A., Grace, K., Wrathall, D.J., de Sherbinin, A., Van Riper, D., Aubrecht, C., Comer, D., Adamo, S.B., Cervone, G., Engstrom, R., Hultquit, C., Gaughan, A.E., Linard, C., Moran, E., Stevens, F., Tatem, A.J.,Tellman, B., Van Den Hoek, J. (2019) People & Pixels 20 years later: The current data landscape and research trends blending population and environmental data. Population and Environment. 41, pages 209–234 doi.org/10.1007/s11111-019-00326-5

Nyland, K.E., Gunn, G.E., Shiklomanov, N.I., Engstrom, R. N., and Streletskiy (2018) Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine. Remote Sensing 10, 1226 DOI:10.3390/rs10081226

Olimb, S. K., Dixon, A.P., Dolfi, E., Anderson, K., and Engstrom. R. (2018) Prairie or pasture?: Using time series NDVI to monitor grassland phenology and characteristics in Montana. Geojournal 83 (819-834) https://doi.org/10.1007/s10708-017-9805-8

Qin, Y., Epstein, H., Engstrom, R. and Walker, D. (2017) Circumpolar arctic tundra biomass and productivity dynamics in response to projected climate change and herbivory. Global Change Biology. DOI 10.1111/gcb.13632

Toure, S., Stow, D., Shih, H.S., Coulter, L., Weeks, J. Engstrom, R., and Sandborn, A. (2016) An object-based temporal inversion approach to urban land use change analysis. Remote Sensing Letters. DOI 10.1080/2150704X.2016.1157640

Sandborn, A. and Engstrom, R (2016) Determining the Relationship Between Census Data and Spatial Features Derived From High Resolution Imagery in Accra, Ghana. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS) Special Issue on Urban Remote Sensing. DOI 10.1109/JSTARS.2016.2519843

Yu, Q., Epstein, H., Engstrom, R., Shiklomanov, N. and Streletskiy, D. (2015) Land Cover and Land Use Changes in the Oil/Gas Regions of Northwestern Siberia under Changing Climatic Conditions. Environmental Research Letters. DOI:10.1088/1748-9326/10/12/124020

Gregory EF, Chamberlain JM, Teach S, Engstrom R, and Mathison DJ. (2015) Geographic Variation in the use of low acuity pediatric Emergency Medical Services. Pediatric Emergency Care DOI: 10.1097/PEC.0000000000000581

Mathison, D., Chamberlain, J., Cowan, N., Engstrom, R., Fu, L., Shoo, A., and Teach, S. (2013) Association of Primary Care Spatial Density with Non-Urgent Visits to a Pediatric Emergency Department Academic Pediatrics 13 (3):278-285 DOI: 10.1016/j.acap.2013.02.006

Engstrom, R., Ofiesh, C., Rain, D., Jewell, H., and Weeks, J. (2013) Defining Neighborhood Boundaries for Urban Health Research in Developing Countries: A Case Study of Accra, Ghana Journal of Maps DOI:10.1080/17445647.2013.765366

Azar,D., Engstrom, R., Graesser, J. and Comenetz, J. (2013) Generation of fine-scale population layers using multi-resolution satellite imagery and geospatial data Remote Sensing of Environment 130 219-232. DOI: 10.1016/j.rse.2012.11.022

Weeks, J., Getis, A., Stow, D., Hill, A., Rain, D., Engstrom, R., Stoler, J., Lippitt, C., Jankowska, M., Lopez, A.C., Coulter, L, and Ofiesh, C., Connecting the Dots between Health, Poverty, and Place in Accra, Ghana (2012) Annals of the Association of American Geographers DOI: 10.1080/00045608.2012.671132

Liljedahl, A., Hinzman, L., Harazano, Y., Zona, D., Tweedie, C., Hollister, R., Engstrom, R. and Oechel, W.C., (2011) Nonlinear controls on evapotranspiration in Arctic coastal wetlands. Biogeosciences 8, 3375-3389. doi:10.5194/bgd-8-6307-2011

Jankowska, M., Weeks, J., and Engstrom, R. (2011) Do the Most Vulnerable People Live in the Worst Slums? A Spatial Analysis of Accra Ghana. Annals of GIS 17:4, 221-235. DOI:10.1080/19475683.2011.625976

Engstrom, R. and Hope, A.S. Parameter Sensitivity of the Arctic BIOME BGC Model for Estimating Evapotranspiration in the Arctic Coastal Plain (2011) Arctic, Antarctic, and Alpine Research 43(3):380-388 DOI: 10.1657/1938-4246-43.3.380.

Azar, D., Graesser, J., Engstrom, R., Comenetz, J., Leddy, R., Schechtman, and Andrews, T. (2010) Spatial Refinement of census population distribution using remotely sensed estimates of impervious surface in Haiti. International Journal of Remote Sensing. 31: 21, 5635-5655 DOI: 10.1080/01431161.2010.496799.

Fu, L., Cowan, N., McLaren, R., Engstrom, R, and Teach, S. (2009) Is spatial accessibility to primary care providers associated with vaccination coverage among children with Medicaid insurance? Pediatrics 124(6) pp. 1579-1586; DOI: 10.1542/peds.2009-0233.

Engstrom, R.N., Hope, A.S., Kwon, H. and Stow, D. (2008) The Relationship between Soil Moisture and NDVI near Barrow, Alaska, Physical Geography. 29(1), pp. 38-53; DOI: 10.2747/0272-3646.29.1.38.

Stow, D., Peterson, A., Hope, A., Engstrom. R. and Coulter L. (2007) Greenness Trends of Arctic Tundra Vegetation in the 1990s: Comparison of Two Normalized Difference Vegetation Index Data Sets from NOAA Advanced Very High Resolution Radiometer Systems International Journal of Remote Sensing. Vol. 28 Issue 21, p4807-4822, 16p; DOI: 10.1080/01431160701264284; (AN 27217146).

Sitch, S., McGuire, A. D., Kimball, J., Gedney, N., Gamon, J., Engstrom, R.N., Wolf, A., Zhuang, Q. and Clein, J. (2007) Assessing the circumpolar carbon balance of arctic tundra with remote sensing and process-based modeling approaches. Ecological Applications. 17(1), pp. 213–234 DOI: 10.1890/1051-0761(2007)017[0213:atcboc]2.0.co;2

Engstrom, R., Hope, A.S., Kwon, H., Harazano, Y., Oechel, W.C., and Mano, M (2006)

Modeling evaporation in Arctic coastal plain ecosystems using a modified version of BIOME BGC. Journal of Geophysical Research Biogeosciences- 111, G02021, doi:10.1029/2005JG000102

Engstrom, R. N., Hope, A.S., Kwon, H., Stow, D.A. and Zamolodchikov, D. (2005) Spatial distribution of near surface soil moisture and its relationship to microtopography in the Arctic coastal plain. Hydrology Research, 36 (3): 219-234. https://doi.org/10.2166/nh.2005.0016

Hope, A.S., Engstrom, R., and Stow, D.A. (2005) Relationship between AVHRR surface temperature and NDVI in Arctic Tundra Ecosystems. International Journal of Remote Sensing, 26:8, p. 1771-1776. doi.org/10.1080/01431160500043780

Vourlitis, G.L., Verfaille, J., Oechel, W.C., Hope, A.S., Stow, D.A. and Engstrom, R. (2003) Spatial variation in regional CO2 exchange for the Kuparuk river basin, Alaska over the summer growing season. Global Change Biology 9, p. 930-941. doi: 10.1080/01431160500043780

Engstrom, R. N., Hope, A. S., Stow, D.A., Vourlitis, G. L., and Oechel, W. C. (2002) Co-variability of the Priestley-Taylor alpha coefficient and regional NDVI in Arctic landscapes, Journal of the American Water Resources Association (JAWRA), 38:6, p. 1647-1659. doi: 10.1111/j.1752-1688.2002.tb04371.x



Jennings Anderson, Chad Blevins, Nuala Cowan, Dara Carney-Nedelman, Courtney Clark, Michael Crino, Ryan Engstrom, Richard Hinton, Michael Mann, Brent McCusker, Rory Nealon, Patricia Solís, Marcela Zeballos (2022). Reflecting on the YouthMappers Movement, Open Mapping towards Sustainable Development Goals. In Solís, P., Zeballos, M. Open Mapping towards Sustainable Development Goals, Springer, DOI: 978-3-031-05181-4

Engstrom, R., Ofiesh, C., Rain, D., Jewell, H. and Weeks, J. (2013). Defining Neighborhood Boundaries for Urban Health Research: A Case Study of Accra, Ghana. In Weeks, J., Hill, A., and Stoler, J. (Eds.), Spatial Inequalities: Health, Poverty and Place in Accra, Ghana (pp. 27-38). Netherlands, Springer. DOI: 10.1007/978-94-007-6732-4_2

Rain, D., Engstrom, R., Ludlow C., and Antos, S. (2011). Accra Ghana: A City Vulnerable to Flooding and Drought-Induced Migration, in Global Report on Human Settlements 2011: Human Settlements Background Study for Chapter 4: UN Publications. https://mirror.unhabitat.org/downloads/docs/GRHS2011/GRHS2011CaseStudyC…



Engstrom, R., Thomson, Dana, Ek, Julia, and Kuffer, Monika (2021) Development of a Multi-City Deprived Area Mapping Ecosystem – International Geoscience and Remote Sensing Symposium (IGARSS), Brussels, Belgium. DOI: 10.1109/IGARSS47720.2021.9555016

Kuffer, M., Thomson, D., Boo, G., Mahabir, R., Grippa, T., Vanuysse, S., Porto De Albuquerque, J., Engstrom, R., Ndugwa, R., Makau, J., and Kabaira (2021) An Integrated Deprived Area Mapping “System” EARSeL Joint Workshop – Earth Observation for Sustainable Cities and Communities, Liege, Belgium

Engstrom, R., Pavelesku, D., Tanaka, T., and Wambile, A. (2019) Mapping Poverty and Slums Using Multiple Methodologies in Accra, Ghana, Joint Urban Remote Sensing Event (JURSE 2019) Vannes, France. DOI: 10.1109/JURSE.2019.8809052

Engstrom, R, Harrison, R., Mann, M., and Fletcher, A. (2019) Evaluating the Relationship Between Contextual Features Derived from Very High Spatial Resolution Imagery and Urban Attributes: A Case Study in Sri Lanka, Joint Urban Remote Sensing Event (JURSE 2019) Vannes, France. DOI 10.1109/JURSE.2019.8809041

Engstrom, R., Copenhaver, A., Newhouse, D., Hersh, J., and Haldavanekar, V. (2017) Evaluating the Relationship between Spatial and Spectral Features Derived from High Spatial Resolution Satellite Data and Urban Poverty in Colombo, Sri Lanka.  Joint Urban Remote Sensing Event (JURSE 2017) Dubai, UAE. DOI: 10.1109/JURSE.2017.7924590

Engstrom, R., Copenhaver, A. and Qi, Yang (2016) Evaluating the use of Multiple Imagery Derived Spatial Features to Predict Census Demographic Variables in Accra, Ghana. International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China 10.1109/IGARSS.2016.7730909

Yu, Q., Engstrom, R., and Graesser, J. (2016) Contextural Feature Evaluation of Multi-Resolution Imagery. International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China 10.1109/IGARSS.2016.7730770

Engstrom, R., Sandborn, A., Yu, Q. and Graesser, J. (2015) Assessing the Relationship Between Spatial Features Derived from High Resolution Satellite Imagery and Census Variables in Accra, Ghana. International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, p. 2544-2547, DOI:10.1109/IGARSS.2015.7326330

Engstrom, R., Sandborn, A., Yu, Q. Burgdorfer, J., Stow, D., Weeks, J., and Graesser, J. (2015) Mapping Slums Using Spatial Features in Accra, Ghana.  Joint Urban and Remote Sensing Event Proceedings (JURSE), Lausanne, Switzerland, DOI:  10.1109/JURSE.2015.7120494

Engstrom, R., Ashcroft, E., Jewell, H., and Rain, D. (2011) Using Remotely Sensed Data to Map Variability in Health and Wealth Indicators in Accra, Ghana. Joint Urban and Remote Sensing Event Proceedings, Munich, Germany p. 145-148, DOI: 10.1109/JURSE.2011.5764740



Masaka, T., Newhouse, D., Silwal, A., Bedada, A, and Engstrom, R. (2020) Small Area Estimation of Non-Monetary Poverty with Geospatial Data. Policy Research working paper; https://doi.org/10.1596/1813-9450-9383

Hersh, J., Engstrom, R, Mann, M., Martin, L., Mejía, A. (2020) Mapping Income Poverty in Belize Using Satellite Features and Machine Learning: Inter-American Development Bank Monograph 108, http://dx.doi.org/10.18235/0002345

Engstrom, R, Newhouse, D., and Soundararajan, V. (2019). Estimating Small Area Population Density Using Survey Data and Satellite Imagery : An Application to Sri Lanka (English). Poverty and Equity Global Practice Working Paper; no. 194. Washington, D.C. : World Bank Group. http://documents.worldbank.org/curated/en/256241552483977593/Estimating-Small-Area-Population-Density-Using-Survey-Data-and-Satellite-Imagery-An-Application-to-Sri-Lanka

Engstrom, R., Hersh, J., Newhouse, D. (2017). Poverty from space: using high-resolution satellite imagery for estimating economic well-being (English). Policy Research working paper; no. WPS 8284. Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/610771513691888412/Poverty-from-space-using-high-resolution-satellite-imagery-for-estimating-economic-well-being



Purnamasari, Ririn Salwa, Febriady, Ade, Wirapati, Bagus A., Farid, M. Noor, Milne, Peter, Kawasoe, Yasuhiro, Vun, Jian, Engstrom, Ryan, and Nasiir, Mercoledi. (2021). Welfare Tracking in the Aftermath of Crisis: The Central Sulawesi Disaster Response. World Bank, Jakarta. © World Bank. https://openknowledge.worldbank.org/handle/10986/36649 License: CC BY 3.0 IGO.”

Ph.D. (San Diego State - UC Santa Barbara)