Associate Professor in Department of Environmental Science, Policy & Management, Rausser College of Natural Resources, UC Berkeley
Affiliate Professor of Geography, Department of Geography, UC Berkeley
Faculty Affiliate, Global Metropolitan Studies program, UC Berkeley
Research topics: landscape and ecosystem ecology, remote sensing, GIS, spatial analysis, wetland and urban ecology, urbanization, wetland restoration, invasive species
I am interested in diverse aspects of landscape ecology and its potential to inform sustainable, multi-functional landscape-designs, and decision-making in environmental planning. My research combines field ecological methods with remote sensing, geographic information systems (GIS) and spatial analysis to perform analyses of multi-scale structure of ecosystems, to facilitate scaling of ecological processes from local to regional levels and to develop remote sensing-based monitoring approaches for vulnerable areas and sites with limited field access.
1) Dynamics of wetland vegetation and ecosystem services in California's Sacramento-San Joaquin Delta (the Delta). Both in the Delta and globally, emergent wetland plants control important ecosystem processes (e.g., aboveground productivity, greenhouse gas fluxes and subsidence-counteracting belowground peat storage), habitat for birds and other wildlife and recreational, aesthetic and cultural values to humans. Changing climate, increasing demands for water, alien species invasions and other pressures create urgent needs to better understand multi-functionality of wetland canopies and their response to change drivers in order to develop sustainable management and planning strategies for the multi-functional Delta landscape. In our group we are taking advantage of the rich remote sensing and geospatial data libraries and diversity of wetland field sites in the region to interpolate important biophysical characteristics of wetland canopies such as leaf area index and better understand their response to climate, hydrology and recent land use history.
2) Effects of city environment on urban ecosystem services. It is well known that urbanization affects landscape carbon and energy balance by reducing green plant cover while creating more fertilized environments for remaining and new vegetation, and by increasing impervious surface and forming strong thermal gradients within city areas. However, much uncertainty still exists on how the relationships between physical properties of urban environments and ecological function of urban vegetation change over time with the dynamics of urban landscapes, and how they vary across different metropolitan areas of the world. Combining time series of satellite remote sensing with ground-based data on urban ecosystem structure is a promising venue to investigate these complex feedbacks and links between broad-scale urban structure and ecological services of specific sites and their designs.
3) Coupled thermal-vegetation patterns as indicators of development and socioeconomic context in urban regions.Among various benefits of urban vegetation, local cooling and improvement of thermal comfort are especially well-known in light of elevated heat loads in built-up environments. What is not well understood, however, is how these benefits vary with different urban morphologies and socioeconomic contexts of development. Using repeatedly collected optical and thermal satellite imagery, we can characterize spatial patterns of green vegetation cover and surface temperature proxies and develop the indicators of urban environment that may elucidate the character and broader context of development. Such indicators are especially needed in data-scarce regions and locations where the outcomes of development create substantial risks to human well-being and vulnerability to climate change and hazards.
I have a PhD in Environmental Science, Policy and Management from UC Berkeley in 2012, a M.S. degree in Natural Resources/Terrestrial Ecology and Management and a Certificate in Spatial Analysis from the School of Natural Resource and Environment at the University of Michigan, Ann Arbor in 2004 and a B.S. degree in Ecology from the National University of Kyiv-Mohyla Academy, Ukraine in 2001. My previous research included applications of vegetation and landscape ecology, remote sensing and geographic information systems (GIS) to study ecosystem properties and change in grasslands of Ukraine, transitioning forests of northern Michigan, USA, large wetland biodiversity hotspots in PR China and California, USA. My current research focuses predominantly on wetland systems and urbanizing landscapes in California and globally.
LA 110 Ecological Analysis Lecture, Fall 2014, 2015, 2017, 2018, 2020
LA 110L Ecological Analysis Laboratory, Fall 2014, 2015, 2017, 2018, 2020
LA 289 (formerly LA 254 section 003): Applied Remote Sensing, Spring 2015, 2016, 2017, 2018, 2019, 2020
module in LA 201A studio Urban Ecological Design, Fall 2015
LA 255 (Doctoral PhD seminar for LAEP PhD students), Spring 2016, 2018
LA 201 Studio: Ecological Factors in Urban Landscape Design, Fall 2017 (Theme: Mitigating urban heat in Mediterranean-type climates)
Berkeley Collegium “Narrowing the gap between teaching and research” teaching innovation grant for the proposal "Empowering urban design innovation using cutting-edge environmental science tools" (2018) Tsinghua-Berkeley Fund grant, 2014-2015 “Urban vegetation and thermal patterns following city growth: a cross-continental comparison” (with Nicholas Clinton, John Radke & Jun Yang) Hellman Fellows Faculty Fund 2017 award for the project "Urban resilience to intensifying heat under different climatic and socioeconomic contexts" NASA New (Early Career) Investigator Program grant 2018-2021 "The potential of remotely sensed phenology to indicate biodiversity and ecosystem services in wetlands", Principal Investigator Delta Stewardship Council “Tidal wetland restoration in the Bay-Delta Region: Developing tools to measure carbon sequestration, subsidence reversal, and climate resilience”, Co-Investigator (with PI Patricia Oikawa/CSU East Bay and other Co-Investigators)
Taddeo S, Dronova I, Harris K. Greenness, texture, and spatial relationships predict floristic diversity across wetlands of the conterminous United States. 2021. ISPRS Journal of Photogrammetry and Remote Sensing. 175:236-46.
Dronova I, Friedman M, McRae I, Kong F, Yin H. 2018. Spatio-temporal non-uniformity of urban park greenness and thermal characteristics in a semi-arid region. Urban Forestry & Urban Greening 34:44-54. Link
Oikawa, P.Y., Jenerette, G.D., Knox, S.H., Sturtevant, C., Verfaillie, J., Dronova I., Poindexter C., Baldocchi, D.D. 2017. Evaluation of a hierarchy of models reveals importance of substrate limitation for predicting carbon dioxide and methane exchange in restored wetlands. Journal of Geophysical Research - Biogeosciences 122, doi:10.1002/2016JG003438. link
McNicol G., Sturtevant C., Knox SH, Dronova I., Baldocchi DD, Silver W. 2017. Effects of seasonality, transport-pathway, and spatial structure on wetland greenhouse gas fluxes. Global Change Biology doi:10.1111/gcb.13580. link
Yin H, Kong F, Yang X, James P, Dronova I. Exploring zoning scenario impacts upon urban growth simulations using a dynamic spatial model. Cities, doi.org/10.1016/j.cities.2018.04.010 Link
Eitzel M.V., Kelly N.M., Dronova I., Valachovich Y., Quinn-Davidson L., Solera J., de Valpine P. 2016. Challenges and opportunities in synthesizing historical geospatial data using statistical models. Ecological Informatics 31:100-111.
Dronova, I. 2015. Object-based image analysis in wetland research: a review. Remote Sensing 7: 6380-6413. Link: http://www.mdpi.com/2072-4292/7/5/6380
Dronova I, Gong P, Wang L, Zhong L. 2015. Mapping dynamic cover types in a large seasonally flooded wetland using Extended Principal Component Analysis and object-based classification. Remote Sensing of Environment 158:193-206. Link: http://www.sciencedirect.com/science/article/pii/S0034425714004404
Dronova I, Gong P, Clinton N, Wang L, Fu W, Qi S, Liu Y. 2012. Landscape analysis of wetland plant functional types: the effects of image segmentation scale, vegetation classes and classification methods. Remote Sensing of Environment 127:357-369.
Wang L, Dronova I, Gong P, Yang W, Li Y, Liu Q. 2012. A new time-series vegetation-water index of phenological-hydrological trait across species and functional types for Poyang Lake wetland ecosystem. Remote Sensing of Environment 125:49-63.
Dronova I, Taddeo S. 2016. Canopy leaf area index in non-forested marshes of the California Delta. Wetlands 36:705–716. DOI 10.1007/s13157-016-0780-5
Dronova I, Gong P, Wang L. 2011. Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China. Remote Sensing of Environment 115: 3220-3236.
McRae I, Freedman F, Rivera A, Li X, Dou J, Cruz I, Ren C, Dronova I, Fraker H, Bornstein R. Integration of the WUDAPT, WRF, and ENVI-met models to simulate extreme daytime temperature mitigation strategies in San Jose, California. Accepted: Building & Environment, In Press. Link
Dronova I, Bergen KM, Ellsworth DS. 2011. Forest canopy properties and variation in aboveground net primary production over Upper Great Lakes Landscapes. Ecosystems 14: 865–879.
Dronova I, Beissinger SR, Burnham JW, Gong P. 2016. Landscape-level associations of wintering waterbird diversity and abundance from remotely sensed wetland characteristics of Poyang Lake. Remote Sensing, 8(6), 462; doi:10.3390/rs8060462. In: Special issue “What can remote sensing do for the conservation of wetlands?”.
Bergen KM and Dronova I. 2007. A remote sensing-ecosystem approach to observing succession on aspen-dominated landscapes. Landscape Ecology 22: 1395-1410.
Baldocchi DD, Knox SH; Dronova I, Verfaille J, Oikawa P, Sturtevant C, Hatala-Matthes J, Detto M. 2016. The Impact of Expanding Flooded Land Area on the Annual Evaporation of Rice. Agricultural and Forest Meteorology 223:181-193.
Kong F, Sun Ch, Liu F, Yin H, Jiang F, Pu Y, Cavan G, Skelhorn C, Middel A, Dronova I. 2016. Energy saving potential of fragmented green spaces due to their temperature regulating ecosystem services in the summer. Applied Energy 183:1428-1440. link
Knox SH, Dronova I, Sturtevant C, Oikawa P, Matthes J, Verfaille J & Baldocchi DD. 2017. Using digital camera and Landsat imagery with eddy covariance data to model gross primary production in restored wetlands. Agricultural and Forest Meteorology 237:233-245. link
Yin H, Kong F, Middel A, Dronova I, Xu H, James P. 2017. Cooling effect of direct green façades during hot summer days：An observational study in Nanjing, China using TIR and 3DPC data. Building and Environment 116:195-2006. link
Yang J, Dronova I, Q. Ma, X. Zhang. Analysis of urbanization dynamics in mainland China using pixel-based nighttime light trajectories from 1992 to 2013. In Press: International Journal of Remote Sensing. Link
Kong F, Ban Y, Yin H, James P, Dronova I. Modelling stormwater management at the city district level in response to changes in land use and Low Impact Development. Environmental Modelling and Software 95:132-142. Link
Dronova I. 2017. Environmental heterogeneity as a bridge between ecosystem service and visual quality objectives in management, planning and design. Landscape and Urban Planning 13:90-106. Available in open access
2015 and earlier
Taddeo S, Dronova I. Geospatial Tools for the Large-Scale Monitoring of Wetlands in the San Francisco Estuary: Opportunities and Challenges. Accepted in: San Francisco Estuary and Watershed Science. Link
Chapple DE, Dronova I. Vegetation development in a tidal marsh restoration project during a historic drought: a remote sensing approach. Accepted: Frontiers in Marine Science, section Coastal Ocean Processes, July 2017. Link
Dronova I, Spotswood EN, Suding KN. Opportunities and constraints in characterizing landscape distribution of an invasive grass from very high resolution multi-spectral imagery. Accepted in Frontiers in Plant Science, section Technical Advances in Plant Science, special issue on Remote sensing of invasive species. Link
Shapero M, Dronova I, Macaulay L. Implications of changing spatial dynamics of irrigated pasture, California's third largest agricultural water use. Accepted in: Science of Total Environment, June 8 2017. Link
Penny G, Srinivasan V, Dronova I, Lele S, Thompson S. 2018. Spatial characterization of long-term hydrological change in the Arkavathy watershed adjacent to Bangalore, India. Hydrology and Earth System Science 22:595-610. https://doi.org/10.5194/hess-22-595-2018
Dronova I, Liang L. 2018. Phenological inference from time series remote sensing data. Book chapter for “Remote Sensing Time Series Image Processing”, ed. by Dr. Q. Weng. In Press, Taylor & Francis. (Accepted; in press).
Taddeo S, Dronova I. 2018. Indicators of vegetation development in restored wetlands. Ecological Indicators. 94:454-467. (IF=4.391) https://doi.org/10.1016/j.ecolind.2018.07.010
Collins J, Dronova I. Urban Landscape Change Analysis Using Local Climate Zones and Object-Based Classification in the Salt Lake Metro Region, Utah, USA. Accepted in: Remote Sensing, In Press (July 2019). Link
Kislik C, Dronova I, Kelly NM. 2018. UAVs in support of algal bloom research: A review of current applications and future opportunities. Drones 2018; 2(4):35 Link
Gong, P., Liu, H., Zhang, M., Li, C., Wang, J., Huang, H., Clinton, N., Ji, L., Li, Wenyu, Bai, Y., Chen, B., Xu, B., Zhu, Z., Yuan, C., Ping Suen, H., Guo, J., Xu, N., Li, Weijia, Zhao, Y., Yang, J., Yu, C., Wang, X., Fu, H., Yu, L., Dronova, I., Hui, F., Cheng, X., Shi, X., Xiao, F., Liu, Q., Song, L., 2019. Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017. Science Bulletin, In Press. doi.org/10.1016/j.scib.2019.03.002
Yin H, Kong F, Dronova I. 2019. Hydrological performance of extensive green roofs in response to different rain events in a subtropical monsoon climate. Landscape & Ecological Engineering, doi.org/ 10.1007/s11355-019-00380-z
Taddeo S, Dronova I, Harris K. The potential of satellite greenness to predict plant diversity among wetland types, ecoregions, and disturbance levels. Accepted: Ecological Applications, In Press. Link
Yin H, Kong F, Dronova I, Middel A, James P. 2019. Investigation of extensive green roof outdoor spatio-temporal thermal performance during summer in a subtropical monsoon climate. Science of the Total Environment. Vol. 696, doi: 10.1016/j.scitotenv.2019.133976
Taddeo S, Dronova I, Depsky N. 2019. Spectral vegetation indices of wetland greenness: responses to vegetation structure, composition, and spatial distribution. Remote Sensing of Environment 234:111467. https://doi.org/10.1016/j.rse.2019.111467
Roux AVD, Lein AC, Dronova I, Henson RM, Rodríguez DA, Sarmiento OL. Healthy Places to Live, Work and Play. 2020. Chapter 13 in:Planetary Health, Protecting Nature to Protect Ourelves. Edited by S Myers & H Frumkin. Island Press. 456p.
Kasak K, Valach AC, Rey-Sanchez C, Kill K, Shortt R, Liu J, Dronova I, Mander Ü, Szutu D, Verfaillie J, Baldocchi DD. Experimental harvesting of wetland plants to evaluate trade-offs between reducing methane emissions and removing nutrients accumulated to the biomass in constructed wetlands. Accepted in: Science of Total Environment. In Press.
Deng H, Yin H, Kong F, Chen J, Dronova I, Pu Y. 2020. Determination of runoff response to variation in overland flow area by flow routes using UAV imagery. Journal of Environmental Management 256:109868, doi: 10.1016/j.jenvman.2019.109868
Taddeo S, Dronova I. Landscape metrics of post-restoration vegetation dynamics in wetland ecosystems. Accepted in: Landscape Ecology, In Press. Link
Dronova I, Taddeo S, Hemes KS, Knox SH, Valach A, Oikawa PY, Kasak K, Baldocchi DD. 2021. Remotely sensed phenological heterogeneity of restored wetlands: linking vegetation structure and function. Agricultural and Forest Meteorology 296:108215.
Dronova I, Kislik C, Dinh Z, Kelly M. A Review of Unoccupied Aerial Vehicle Use in Wetland Applications: Emerging Opportunities in Approach, Technology, and Data. Drones. 2021; 5(2):45. https://doi.org/10.3390/drones5020045
Huang C, Yang J, Clinton N, Yu L, Huang H, Dronova I, Jin J. 2021. Mapping the maximum extents of urban green spaces in 1039 cities using dense satellite images. Environmental Research Letters. 2021 Jun 10 16(6):064072.
Gouveia N, Kephart JL, Dronova I, McClure L, Granados JT, Betancourt RM, O'Ryan AC, Texcalac-Sangrador JL, Martinez-Folgar K, Rodriguez D, Diez-Roux AV. 2021. Ambient fine particulate matter in Latin American cities: Levels, population exposure, and associated urban factors. The Science of the total environment.772:145035.
Kong F, Wang D, Yin H, Dronova I, Fei F, Chen J, Pu Y, Li M. 2021. Coupling urban 3-D information and circuit theory to advance the development of urban ecological networks. Conservation Biology: the Journal of the Society for Conservation Biology. 2021 Jan 21. https://doi.org/10.1111/cobi.13682
Valach AC, Kasak K, Hemes KS, Anthony TL, Dronova I, Taddeo S, Silver WL, Szutu D, Verfaillie J, Baldocchi DD. 2021. Productive wetlands restored for carbon sequestration quickly become net CO2 sinks with site-level factors driving uptake variability. PLOS ONE. 2021 16(3):1-22
Ju Y, Moran M, Wang X, Avila-Palencia I, Cortinez-O'Ryan A, Moore K, Slovic AD, Sarmiento OL, Gouveia N, Caiaffa WT, Aguilar G, Marques Sales D, de Pina M de F R P, COelho DM, Dronova I. "Latin American cities with higher socioeconomic status are greening from a lower baseline: evidence from the SALURBAL project" Accepted. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ac2a63
Cunha MD, Ju Y, Morais MH, Dronova I, Ribeiro SP, Bruhn FR, Lima LL, Sales DM, Schultes OL, Rodriguez DA, Caiaffa WT. 2021. Disentangling associations between vegetation greenness and dengue in a Latin American city: Findings and challenges. Landscape and Urban Planning. 2021 Dec 1;216:104255.
Miller GJ, Dronova I, Oikawa PY, Knox SH, Windham-Myers L, Shahan J, Stuart-Haëntjens E. The Potential of Satellite Remote Sensing Time Series to Uncover Wetland Phenology under Unique Challenges of Tidal Setting. Remote Sensing. 2021; 13(18):3589. https://doi.org/10.3390/rs13183589