Deepak R Mishra

Department of Geography

Merle C. Prunty, Jr. Professor of Geography and Associate Head

EDUCATION

PhD (2006), University of Nebraska, Lincoln Natural Resources

M. Tech (2002), Indian Institute of Technology, Kanpur Civil Engineering

Research Interests:

Coastal environments have been steadily subjected to natural and anthropogenic events such as hurricanes, coastal development, sea-level rise, and overfishing. These changes have resulted in wetland loss, water quality degradation, loss of barrier islands, reduced storm surge protection, and decline of fisheries. Continuous monitoring and restoration of the fragile ecosystems are fundamental to life along the coast. Geospatial technologies provide the tools to monitor these ecosystems at large spatial scale and in a timely fashion. My research includes combining field-based remote sensing (field spectroscopy) with satellite remote sensing to study inland and coastal water resources.

Current projects focus on: (1) Developing satellite based decision support tools for Coastal salt marsh conservation and restoration; (2) Modeling and mapping the spatio-temporal distribution of cyanobacterial harmful algal blooms in inland and coastal waters; (3) Combining flux tower and satellite datasets to study long-term changes in  gross and net primary productivity, and carbon sequestration in tidal wetlands; (4) Sea Level Rise and coastal resources; (6) Seagrass mapping and coral disease detection using remote sensing; (7) Developing a cyberinfrastructure by combining social, computational, and sensor clouds for monitoring coastal marshes and inland water quality, and (8) Small satellite development for Space AI applications. (Current Project)

EDITED BOOKS

2. Ecology, Conservation, and Restoration of Chilika Lagoon, India (2020). C. Max Finlayson, G. Rastogi, D. R. Mishra and A. Pattnaik. 1st Edition, pp. 438, ISBN: 978-3-030-33423-9, Springer, Switzerland. 

1. Bio-Optical Modeling and Remote Sensing of Inland Waters (2017). D. R. Mishra, I. Ogashawara and A. A. Gitelson. 1st Edition, pp. 332, ISBN: 978-0-128-04644-9, Elsevier, Waltham, MA.

PEER-REVIEWED ARTICLES

111. Diefenderfer, H. L., L. D. McKinney, W. R. Boynton, K. L. Heck, Jr., B. A. Kleiss, D. R. Mishra, H. Greening, A. A. George II, B. A. Carl Kraft, and C. L. Kling (2022). Ten years of Gulf Coast ecosystem restoration projects since the Deepwater Horizon Oil Spill. Proceedings of the National Academy of Sciences, 119 (38): e2213639119, https://doi.org/10.1073/pnas.2213639119 

110. Greening, H., K. L. Heck, Jr., L. D. McKinney, H. L. Diefenderfer, W. R. Boynton, B. A. Kleiss, D. R. Mishra, A. A. George II, B. A. Carl Kraft, C. L. Kling, and L. Windecker (2022). Assessing the effectiveness of large-scale environmental restoration: challenges and opportunities. Estuaries and Coastshttps://doi.org/10.1007/s12237-022-01149-8 

109. Callejas, I., K. Osborn, C. Lee, D. R. Mishra,  N. Gomez, A. Carrias, E. A. Cherrington, R. Griffin, A. Rosado, S. Rosado, and J. Jay (2022). A Google Earth Engine-Based Toolkit for water quality monitoring from 2002-2022 in support of SDG 14 and coral health in Marine Protected Areas in Belize. Frontiers in Remote Sensing, 3:1020184, https://doi.org/10.3389/frsen.2022.1020184 

108. Jaya Prakash, A., M. D. Behera, S. Ghosh, A. K. Das, and D. R. Mishra (2022). Aboveground biomass prediction using L & C SAR data synergy and machine learning- demonstrating an operational framework for mangrove forests. Ecological Informatics, 72:101900, https://doi.org/10.1016/j.ecoinf.2022.101900 

107. Tarafdar, L., M. Mohapatra, P. R. Muduli, A. Kumar, D. R. Mishra, and G. Rastogi (2022). Co-occurrence patterns and environmental factors associated with rapid onset of Microcystis aeruginosa bloom in a tropical coastal lagoon. Journal of Environmental Management, 325, Part B, 116580, https://doi.org/10.1016/j.jenvman.2022.116580

106. Kinane, S. M., C. R. Montes, M. Zapata, B. P. Bullock, R. Cook, and D. R. Mishra (2022). Influence of environmental variables on leaf area index in Loblolly Pine plantations. Forest Ecology and Management, 523: 120445, https://doi.org/10.1016/j.foreco.2022.120445 

105. Narron, C. R., J. L. O’Connell, D. R. Mishra, D. L. Cotten, P. A. Hawman, L. Mao (2022). Flooding in Landsat Across Tidal Systems (FLATS): An index for intermittent tidal filtering and frequency detection in salt marsh environments. Ecological Indicators, 141: 109045, https://doi.org/10.1016/j.ecolind.2022.109045 

104. Sharma, R., D. R. Mishra, M. R. Levi, and L. A. Sutter (2022). Remote sensing of surface and subsurface soil organic carbon in tidal wetlands: A review and ideas for future research. Remote Sensing, 14: 2940, https://doi.org/10.3390/rs14122940 

103. Wright, M., L. R. Pompe, D. R. Mishra, D. S. Baumbach, L. Salinas, and S. G. Dunbar (2022). Hawksbill presence and habitat suitability of a marine reserve in Honduras. Ocean and Coastal Management, 225: 106204, https://doi.org/10.1016/j.ocecoaman.2022.106204 

102. Gaiser, E. E., J. Kominoski, D. McKnight, C. Bahlai, C. Cheng, S. Record, W. Wilfred, K. Christianson, M. Downs, T. Harms, P. Hawman, S. Holbrook, A. Kumar, D. R. Mishra,  N. Molotch, R. Primack, A. Rassweiler, R. Schmitt, and L. Sutter (2022). Long-term ecological research and the COVID-19 anthropause: A window to understanding social-ecological disturbance. Ecosphere, 13(4): e4019, https://doi.org/10.1002/ecs2.4019 

101. Martin-Arias, V., C. Evans, R. Griffin, E. Cherrington, C. Lee, D. R. Mishra, N. Gomez, A. Rosado, I. Callejas, J. Jay, and S. Rosado (2022). Modeled impacts of LULC and climate change predictions on the hydrologic regime of Belize. Frontiers in Environmental Science, 10:848085, https://doi.org/10.3389/fenvs.2022.848085  

100. Veerman, J., A. Kumar, and D. R. Mishra (2021). Exceptional landscape-wide cyanobacteria bloom in Okavango Delta, Botswana in 2020 coincided with a mass elephant die-off event. Harmful Algaehttps://doi.org/10.1016/j.hal.2021.102145

99. Maniyar, C., A. Kumar, and D. R. Mishra (2021). Continuous and synoptic assessment of Indian inland waters for harmful algae blooms, Harmful Algae, 111: 102160, https://doi.org/10.1016/j.hal.2021.102160

98. Acharya, P., P. Muduli, D. R. Mishra, A. Kumar, V. V. Kanuri, M. Das (2021). Imprints of COVID-19 lockdowns on Total Petroleum Hydrocarbon levels in Asia’s largest brackish water lagoon. Marine Pollution Bulletin, 174: 113137, https://doi.org/10.1016/j.marpolbul.2021.113137

97. Dev, P., A. Sukenik, D. R. Mishra, and I. Ostrovsky (2021). Cyanobacterial pigment concentrations in inland waters: Novel semi-analytical algorithms for multi- and hyperspectral remote sensing data. Science of the Total Environment, 805: 150423, https://doi.org/10.1016/j.scitotenv.2021.150423 

96. Rasquinha, D., and D. R. Mishra (2021). Riding the crest of waves: Tropical cyclone events shape mangrove productivity gradients in the Indian subcontinent. Scientific Reports, 11:17355, https://doi.org/10.1038/s41598-021-96752-3

95. O’Connell, J., D. R. Mishra, M. Alber, and K. Byrd (2021). BERM: A Belowground Ecosystem Resiliency Model for estimating Spartina alterniflora belowground biomass. New Phytologisthttps://doi.org/10.1111/nph.17607

94. Hikouei, I. S., S. S. Kim, and D. R. Mishra (2021). Machine-learning classification of soil bulk density in salt marsh environments. Sensors, 21: 4408, https://doi.org/10.3390/s21134408  

93. Ghosh, S., M. D. Behera, B. Jagadish, A. K. Das, and D. R. Mishra (2021). Aboveground biomass estimation of a carbon-rich mangrove site in India using multi-temporal Sentinel series data. Journal of Environmental Management, 292: 112816, https://doi.org/10.1016/j.jenvman.2021.112816 

92. Hawman, P., D. R. Mishra, J. O’Connell, D. Cotten, C. Narron, and L. Mao (2021). Salt marsh light use efficiency is driven by biophysical gradients and species-specific physiology and morphology. Journal of Geophysical Research- Biogeosciences, 126, e2020JG006213,  https://doi.org/10.1029/2020JG006213

91. Callejas, I. A., C. M. Lee, D. R. Mishra, S. L. Felgate, C. Evans, A. Carrias, A. Rosado,  R. Griffin, E. Cherrington, M. Ayad, M. Rudresh, B. Page, and J. A. Jay (2021). Effect of COVID-19 anthropause on water clarity in the Belize coastal lagoon. Frontiers in Marine ScienceDOI: 10.3389/fmars.2021.648522

90. Yin, Y., A. G. Grundstein, D. R. Mishra, L. Ramaswamy, N. Hashemi, and J. Dowd (2021). DTEx: A dynamic urban thermal exposure index based on human mobility patterns. Environment International, 155: 106573, https://doi.org/10.1016/j.envint.2021.106573

89. Tarafdar, L., J. K. Kim, S. Srichandan, M. Mohapatra, P. R. Muduli, A. Kumar, D. R. Mishra, and G. Rastogi (2021). Responses of phytoplankton community structure and association to variability in environmental drivers in a tropical coastal lagoon, Science of the Total Environment, 783: 146873, https://doi.org/10.1016/j.scitotenv.2021.146873

88. Kinane, S. M., C. R. Montes, T. J. Albaugh, and D. R. Mishra (2021). A model to estimate leaf area index in loblolly pine plantations using Landsat 5 and 7 images. Remote Sensing, 13(6): 1140, https://doi.org/10.3390/rs13061140  

87. Das, P., S. Mudi, M. D. Behera, S. K. Barik, P. S. Roy, and D. R. Mishra (2021). Automated mapping for long-term analysis of shifting cultivation in northeast India. Remote Sensing, 13(6): 1066, https://doi.org/10.3390/rs13061066

86. Muduli, P., A. Kumar, V. V. Kanuri, D. R. Mishra, P. Acharya, R. Saha, M. Biswas, A. K. Vidyarthi, and A. Sudhakar (2021). Water quality assessment of the Ganges River during COVID-19 lockdown. International Journal of Environmental Science and Technologyhttps://doi.org/10.1007/s13762-021-03245-x  

85. Mishra, D. R., A. Kumar, P. Muduli, T. Acharyya, P. Acharya, S. Singh, and G. Rastogi (2021). Landfall season is critical to the impact of a cyclone on a monsoon-regulated tropical coastal lagoon, Science of the Total Environment, 770: 145235, https://doi.org/10.1016/j.scitotenv.2021.145235

84. Nanda, D., D. R. Mishra, and D. Swain (2021). COVID-19 lockdowns induced land surface temperature variability in mega urban agglomerations in India. Environmental Science: Processes & Impactshttps://doi.org/10.1039/D0EM00358A 

83. Rasquinha, D., and D. R. Mishra (2020). Impact of wood harvesting on mangrove forest structure, composition and biomass dynamics in India. Estuarine, Coastal and Shelf Science, 106974, https://doi.org/10.1016/j.ecss.2020.106974 

82. Mishra, D. R., A. Kumar, P. R. Muduli, Sk. Md. Equeenuddin, G. Rastogi, T. Acharyya, and D. Swain (2020). Decline in phytoplankton biomass along Indian coastal waters due to COVID-19 lockdown. Remote Sensing, 12(16): 2585, https://doi.org/10.3390/rs12162584 

81. Yin, Y., N. Hashemi, A. Grundstein, D. R. Mishra, L. Ramaswamy, and J. Dowd (2020). Urban ambient air temperature estimation using hyperlocal data from smart vehicle-borne sensors, Computers, Environment and Urban Systems, 84: 101538, https://doi.org/10.1016/j.compenvurbsys.2020.101538  

80. Mishra, D. R., A. Kumar, L. Ramaswamy, V. Boddula, M. Das, B. Page, and S. Weber (2020). CyanoTRACKER: A cloud-based integrated multi-platform architecture for global observation of cyanobacterial harmful algal blooms. Harmful Algae, 96: 101828, https://doi.org/10.1016/j.hal.2020.101828  

79. Wu, W., P. Biber, D. R. Mishra, G. Carter, S. Ghosh, and S. Hagen (2020). Sea-level rise thresholds for the stability of salt marshes in a riverine versus a marine dominated estuary. Science of the Total Environment718: 137181, https://doi.org/10.1016/j.scitotenv.2020.137181 

78. Kumar, A., D. R. Mishra, and N. Ilango (2020). Evaluation of Landsat 8 virtual orange band for mapping cyanobacterial bloom. Remote Sensing, 12(5): 868, https://doi.org/10.3390/rs12050868

77. Kumar, A., D. R. Mishra, and Sk. Md. Equeenuddin (2020). Spatio-temporal dynamics of sediment plume and algal bloom in Chilika Lagoon. In: C. Max Finlayson, G. Rastogi, M. Suar, D. R. Mishra, and A. Pattnaik (eds.) Ecology, Conservation, and Restoration of Chilika Lagoon, India, Springer, Switzerland, https://doi.org/10.1007/978-3-030-33424-6_8

75. Weber, S., D. R. Mishra, E. Kramer, and S. Wilde (2020). Risks for cyanobacterial harmful algal blooms due to land management and climate interactions. Science of the Total Environment, 703: 134608, https://doi.org/10.1016/j.scitotenv.2019.134608

74. Dahal, S., D. H. Franklin, A. Subedi, M. Cabrera, D. Hancock, K. Mahmud, L. Ney, C. Park, and D. R. Mishra (2020). Strategic grazing in beef-pastures for improved soil health and reduced runoff-nitrate-A step towards sustainability. Sustainability, 12(2): 558, https://doi.org/10.3390/su12020558 

73. Astuti, I., K. Sahoo, A. Milewski, and D. R. Mishra (2019). Impact of land use/land cover change on surface runoff in an increasingly urbanized tropical watershed, Indonesia. Water Resources Managementhttps://doi.org/10.1007/s11269-019-02320-w

72. Miller, P., T. L. Mote, A. Kumar, and D. R. Mishra (2019). Systematic precipitation redistribution following a strong hurricane landfall. Theoretical and Applied Climatology, 1- 12, https://doi.org/10.1007/s00704-019-03000-w

71. Page, B., L. Olmanson, and D. R. Mishra (2019). A harmonized image processing workflow using Sentinel-2 and Landsat-8 for mapping water clarity in optically complex lake systems. Remote Sensing of Environment, 231: 111284, https://doi.org/10.1016/j.rse.2019.111284

70. Kumar, A., C. Cooper, C. Remillard, S. Ghosh, A. Haney, F. Braun, Z. Connor, B. Page, K. Boyd, S. Wilde, and D. R. Mishra (2019). Spatio-Temporal Monitoring of Hydrilla to Aid Management Actions. Weed Technology, 1-12, https://doi.org/10.1017/wet.2019.13

69. Miller, P., A. Kumar, T. L. Mote, F. D. S. Moraes, and D. R. Mishra (2019). Persistent hydrological consequences of Hurricane Maria and their coevolution with land surface recovery in Puerto Rico. Geophysical Research Letters, 46, https://doi.org/10.1029/2018GL081591

68. Rotta, L. H. S., D. R. Mishra, E. Alcântara, N. N. Imai, F. S. Y. Watanabe, and T. W. P. Rodrigues (2019). Kd(PAR) and depth based model to estimate the height of submerged aquatic vegetation in a oligotrophic reservoir. Remote Sensing, 11(3): 317, https://doi.org/10.3390/rs11030317

67. Hauer, M. E., R. D. Hardy, D. R. Mishra, and J. S. Pippin (2019). No landward retreat: Examining 80 years of population migration and shoreline change in Louisiana. Population and Environment, 40: 369, https://doi.org/10.1007/s11111-019-00315-8

66. Zhang, C., D. R. Mishra, and S. Pennings (2019). Mapping salt marsh soil properties using imaging spectroscopy. ISPRS Journal of Photogrammetry and Remote Sensing, 148: 221-234, https://doi.org/10.1016/j.isprsjprs.2019.01.006

65. Tao, J., D. R. Mishra, D. L. Cotton, J. O’Connell, M. Leclerc, H. Nahrawi, G. Zhang, and R. Pahari (2018). A comparison between the MODIS product (MOD17A2) and a tide-robust empirical GPP model evaluated in a Georgia wetland. Remote Sensing, 10(11): 1831, https://doi.org/10.3390/rs10111831

64. Cao, F., D. R. Mishra, J. Schalles, and W. Miller (2018). Evaluating ultraviolet (UV) based photochemistry in optically complex coastal waters using the Hyperspectral Imager for the Coastal Ocean (HICO). Estuarine, Coastal and Shelf Science, 215: 199-206, https://doi.org/10.1016/j.ecss.2018.10.013  

63. Rodrigues, T., D. R. Mishra, F. S. Y. Watanabe, E. Alcântara, and N. N. Imai (2018). Performance of existing QAAs in Secchi disk depth retrieval in phytoplankton and dissolved organic matter dominated inland waters. Journal of Applied Remote Sensing, 12(2): 036017, https://doi.org/10.1117/1.JRS.12.036017

62.  Shrestha,  S., I. Miranda, M. L. E. Pardo, A. Kumar, T. Rashid, S. Dahal, C. Remillard, and D. R. Mishra (2018). Identifying and forecasting potential biophysical risk areas within a tropical Mangrove ecosystem using multi-sensor data. International Journal of Applied Earth Observation and Geoinformation, 74: 281-294, https://doi.org/10.1016/j.jag.2018.09.017

61. Astuti, I., D. R. Mishra, S. Mishra, and B. Schaeffer (2018). A hybrid approach for deriving inherent optical properties in oligotrophic estuaries. Continental Shelf Research, 166:92-107, https://doi.org/10.1016/j.csr.2018.06.016 

60. Rotta, L. H. S., D. R. Mishra, F. S. Y. Watanabe, T. W. P. Rodrigues, E. Alcântara, and N. N. Imai (2018). Analyzing the feasibility of a space-borne sensor (SPOT-6) to estimate the height of submerged aquatic vegetation (SAV) in inland waters. ISPRS Journal of Photogrammetry and Remote Sensing, 144: 341-356, https://doi.org/10.1016/j.isprsjprs.2018.07.011

59. Wu, W., M. Bethel, D. R. Mishra, and T. Hardy (2018). Predicting aboveground green biomass in salt marshes based on worldview-2 imagery using mixed-effects modeling in Bayesian framework. GIScience and Remote Sensing, 1(25), https://doi.org/10.1080/15481603.2018.1460934  

58. Zhang, C., S. Denka, and D. R. Mishra (2018). Mapping freshwater marsh species in the wetlands of Lake Okeechobee using very high-resolution aerial photography and LiDAR dataInternational Journal of Remote Sensing, 1-19, https://doi.org/10.1080/01431161.2018.1455242

57. Rodrigues, T., D. R. Mishra, E. Alcântara,  I. Astuti, F. S. Y. Watanabe, and N. N. Imai (2018). Estimating the optical properties of inorganic matter-dominated oligo-to-mesotrophic inland waters. Water10(4): 449, https://doi.org/10.3390/w10040449

56. Zhang, C., S. Denka, H. Cooper, and D. R. Mishra (2018). Quantification of sawgrass marsh aboveground biomass in the coastal Everglades using object-based ensemble analysis and Landsat data. Remote Sensing of Environment, 204: 366-379, https://doi.org/10.1016/j.rse.2017.10.018

55. Page, B., A. Kumar, and D. R. Mishra (2018). A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom. International Journal of Applied Earth Observation and Geoinformation, 66: 69-81, https://doi.org/10.1016/j.jag.2017.11.003

54. Ghosh, S., and D. R. Mishra (2018). Analyzing the long-term phenological trends of salt marsh ecosystem across coastal Louisiana. Remote Sensing, 9(12): 1340; https://doi.org/10.3390/rs9121340

53. Ogashawara, I., D. R. Mishra, and A. A. Gitelson (2017). Remote Sensing of Inland Waters: Background and Current State-of-the-Art. In: D. R. Mishra, I. Ogashawara, and A. A. Gitelson (eds.) Bio-Optical Modeling and Remote Sensing of Inland Waters, 1st Edition, pp. 332, ISBN: 9780128046449, Elsevier, Waltham, MA.

52. Kumar, A., P. Stupp, S. Dahal, C. Remillard, R. Bledsoe, A. Stone, C. Cameron, G. Tastogi, R. Samal, and D. R. Mishra (2017). A multi-sensor approach for assessing mangrove biophysical characteristics in coastal Odisha, India. Special issue of ‘Remote Sensing’ in Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 1-22, https://doi.org/10.1007/s40010-017-0441-y

51. Rodrigues, T., D. R. Mishra, E. Alcântara, F. S. Y. Watanabe, L. Rotta, and N. N. Imai (2017). Retrieving total suspended matter in tropical reservoirs within a cascade system with widely differing optical properties. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 99: 1-18, doi: 10.1109/JSTARS.2017.2745700

50. O’Connell, J., D. R. Mishra, D. Cotten, L. Wang, and M. Alber (2017). The Tidal Marsh Inundation Index (TMII): An inundation filter to flag flooded pixels and improve MODIS tidal marsh vegetation time-series analysis. Remote Sensing of Environment, 201: 34-46, http://dx.doi.org/10.1016/j.rse.2017.08.008

49. Kumar, A., D. R. Mishra, Sk. Md. Equeen, H. J. Cho, and G. Rastogi (2017). Differential impact of anniversary severe cyclones on the water quality of a tropical coastal lagoon, Estuaries and Coasts, 40: 317-342, https://doi.org/10.1007/s12237-016-0172-3

48. Ogashawara, I., D. R. Mishra, R. F. F. Nascimento, E. H. Alcântara, M. Kampel, J. L. Stech (2016). Re-parameterization of a quasi-analytical algorithm for Colored Dissolved Organic Matter dominant inland waters,International Journal of Applied Earth Observation and Geoinformation, 53:128-145, http://dx.doi.org/10.1016/j.jag.2016.09.001

47. Watanabe, F., D. R. Mishra, I. Astuti, T. Rodrigues, E. Alcântara, N. N. Imai, and C. Barbosa (2016). Parameterization and calibration of a quasi-analytical algorithm for tropical eutrophic waters, ISPRS Journal of Photogrammetry and Remote Sensing, 121: 28-47, http://dx.doi.org/10.1016/j.isprsjprs.2016.08.009

46. Wang, G., Z. Lee, D. R. Mishra, and R. Ma (2016). Retrieving absorption coefficients of multiple phytoplankton pigments from hyperspectral remote sensing reflectance measured over cyanobacteria bloom waters, Limnology and Oceanography: Methods, 14(7): 432-447, https://doi.org/10.1002/lom3.10102

45. Mishra, D. R., and R. W. Gould, Jr (2016). Preface: Remote sensing in coastal environments, Remote Sensing, 8(8), 665, https://doi.org/10.3390/rs8080665

44. Rotta, L. H., D. R. Mishra, E. H. Alcântara, and N. N. Imai (2016). Analyzing the status of submerged aquatic vegetation using novel optical parameters, International Journal of Remote Sensing, 37(16), 3786-3810, https://doi.org/10.1080/01431161.2016.1204027

43. Hauer, M. E., J. M. Evans, and D. R. Mishra (2016). Millions projected to be at risk from sea-level rise in the continental United States, Nature Climate Changehttps://doi.org/10.1038/nclimate2961

42. Kumar, A., Sk. Md. Equeen, D. R. Mishra, and B. C. Acharya (2016). Remote monitoring of sediment dynamics in a coastal lagoon: Long-term spatio-temporal variability of suspended sediment in Chilika. Estuarine, Coastal and Shelf Science, 170:155-172; http://dx.doi.org/10.1016/j.ecss.2016.01.018 

41. Mishra, D. R., E. D’Sa, and S. Mishra (2016). Preface: Remote Sensing of Water Resources. Remote Sensing, 8(2): 115, https://doi.org/10.3390/rs8020115

40. Ghosh, S., D. R. Mishra, and A. Gitelson (2016). Long-term monitoring of biophysical characteristics of tidal wetlands in the northern Gulf of Mexico — A methodological approach using MODIS. Remote Sensing of Environment, 173: 39-58; http://dx.doi.org/10.1016/j.rse.2015.11.015

39. Srichandan, S., B. Maharana, J. Y. Kim, A. Kumar, D. R. Mishra, P. Bhadury, P. R. Muduli, A. K. Pattnaik, and G. Rastogi (2015). Interannual and cyclone-driven variability in phytoplankton communities of a tropical coastal lagoon. Marine Pollution Bulletin, 101(1): 39-52; https://doi.org/10.1016/j.marpolbul.2015.11.030

38. Mishra, D. R., S. Ghosh, C. Hladik, J. L. O’Connell, and H. J. Cho (2015). Wetland mapping methods and techniques using multi-sensor, multi-resolution remote sensing: Successes and Challenges. In: Prasad S. Thenkabail (ed.) Remote Sensing Handbook, Vol. III, pp. 191-226, ISBN: 13: 978-1-4822-1972-6, CAT# K22131, CRC Press, Taylor and Francis, Boca Raton, FL

37. Du, X., D. Cao, D. R. Mishra, S. Bernardes, T. R. Jordan, and M. Madden (2015). Self-Adaptive Gradient-Based Thresholding Method for Coal Fire Detection Using ASTER Thermal Infrared Data, Part I: Methodology and Decadal Change Detection. Remote Sensing, 7(6): 6576-6610; https://doi.org/10.3390/rs70606576

36. Mishra, D. R., and S. Ghosh (2015). Using moderate resolution satellite sensors for monitoring the biophysical parameters and phenology of tidal wetlands. In: Ralph Tiner, Victor Klemas, and Megan Lang (eds.) Remote Sensing of Wetlands: Applications and Advances, pp. 283-314, ISBN: 13: 978-1-4822-3738-2, Taylor and Francis, Boca Raton, FL

35. Mishra, S., D. R. Mishra (2014). A novel remote sensing algorithm to quantify phycocyanin in cyanobacterial algal blooms. Environmental Research Letters, 9:114003, https://doi.org/10.1088/1748-9326/9/11/114003

34. Mishra, D. R., (2014). Editorial on Coastal Remote Sensing. GIScience and Remote Sensing, 51(2): 115-119, https://doi.org/10.1080/15481603.2014.895579

33. Cho, H., I. Ogashawara, D. R. Mishra, J. White, A. Kamerosky, L. Morris, C. Clarke, A. Simpson, and D. Banisakher (2014). Evaluating Hyperspectral Imager for the Coastal Ocean (HICO) data for seagrass mapping in Indian River Lagoon, FL. GIScience and Remote Sensing, 51(2): 120-138, https://doi.org/10.1080/15481603.2014.895577

32. Mishra, D. R., B. A. Schaeffer, and D. Keith (2014). Performance evaluation of Normalized Difference Chlorophyll Index in northern Gulf of Mexico estuaries using the Hyperspectral Imager for the Coastal Ocean. GIScience and Remote Sensing, 51(2): 175-198, https://doi.org/10.1080/15481603.2014.895581

31. Mishra S., D. R. Mishra, and Z. Lee (2014). Bio-optical inversion in highly turbid and cyanobacteria dominated waters. IEEE Transactions in Geosciences and Remote Sensing, 52(1): 375-388; doi: 10.1109/TGRS.2013.2240462

30. Ogashawara, I., D. R. Mishra, S. Mishra, M. Pedroso Curtarelli, J. Luiz Stech (2013). A performance review of reflectance based algorithms for predicting phycocyanin concentrations in inland waters. Remote Sensing, 5(10): 4774-4798, https://doi.org/10.3390/rs5104774

29. Mishra, D. R., and S. Ghosh (2013). Moderate resolution satellite data for mapping salt marshes. SPIE Newsroomdoi: 10.1117/2.1201304.004800

28. Cho J., S. Mishra, and D. R. Mishra (2013). Graphical user interface for benthic mapping. ACEEE International Journal on Information Technology, 3(1): 23-27, doi: 01.IJIT.3.1.1138

27. Mishra S., D. R. Mishra, and Z. Lee (2013). Quantifying cyanobacterial phycocyanin concentration in turbid productive waters: A quasi-analytical approach. Remote Sensing of Environment, 133: 141-151, https://doi.org/10.1016/j.rse.2013.02.004  

26. Cho, H. J., D. R. Mishra, P. Kirui, and J. Wood (2012). Remote sensing of submerged aquatic vegetation. In: Boris Escalante-Ramirez (ed.) Remote Sensing – Applications, ISBN: 978-953-51-0651-7, InTech, Available from: http://www.intechopen.com/books/remote-sensing-applications/remote-sensing-of-submerged-aquatic-vegetation.

25. Dash P., N. Walker, D. R. Mishra, E. D’Sa, and S. Ladner (2012). Atmospheric correction and vicarious calibration of Oceansat-1 Ocean Color Monitor (OCM) data in coastal case 2 waters. Remote Sensing, 4(6): 1716-1740, https://doi.org/10.3390/rs4061716

24. Relles, N. J., D. O. B. Jones, and D. Mishra (2012). Creating landscape-scale maps of coral reef cover for marine reserve management from high resolution multispectral remote sensing. GIScience and Remote Sensing, 49(2): 251-274, http://dx.doi.org/10.2747/1548-1603.49.2.251

23. Mishra, D. R., H. J. Cho, S. Ghosh, C. Downs, A. Fox, P. B. T. Merani, P. Kirui, N. Jackson, and S. Mishra (2012). Post-spill state of the marsh: Remote estimation of the ecological impact of the Gulf of Mexico oil spill on Louisiana salt marshes. Remote Sensing of Environment,118: 176-185, https://doi.org/10.1016/j.rse.2011.11.007

22. Mishra, S., D. R. Mishra (2012). Normalized Difference Chlorophyll Index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters. Remote Sensing of Environment,117: 394-406, https://doi.org/10.1016/j.rse.2011.10.016 

21. Dash P., N. Walker, D. R. Mishra, C. Hu, J. L. Pinckney, and E. J. D’Sa (2011). Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data, Remote Sensing of Environment, 115, 3409-3423; http://dx.doi.org/10.1016/j.rse.2011.08.004

20. Swain, S., S. Narumalani, and D. R. Mishra (2011). Monitoring Invasive Species: Detecting Purple Loosestrife and Evaluating Biocontrol along the Niobrara River, Nebraska. GIScience and Remote Sensing, 48, 225-244; https://doi.org/10.2747/1548-1603.48.2.225

19. Mishra, D. R., and S. Mishra (2010). Plume and bloom: effect of the Mississippi River diversion on the water quality of Lake Pontchartrain. Geocrato International, 25(7): 555-568, https://doi.org/10.1080/10106041003763394

18. Mishra, D. R., (2009). High-resolution ocean color remote sensing of coral reefs and associated benthic habitats. In: X. Yang (ed.) Remote Sensing and GIS for Coastal Ecosystem Assessment and Management: Principles and Applications. XIV, 561 p., ISBN: 978-3-540-88182-7, Springer-Verlag GMBH, Germany.

17. Mishra, S., D. R. Mishra, and W. Schluchter (2009). A novel model for predicting phycocyanin concentrations in cyanobacteria: A proximal hyperspectral remote sensing approach. Remote Sensing, 1(4), 758-775; https://doi.org/10.3390/rs1040758 

16. Rundquist, D., A. Gitelson, M. Lawson, G. Keydan, B. Leavitt, R. Perk, J. Keck, D. R. Mishra, and S. Narumalani (2009). Proximal sensing of coral features:  spectral characterization of Siderastrea siderea. GIScience and Remote Sensing, 46(2): 139-160, https://doi.org/10.2747/1548-1603.46.2.139

15. Narumalani, S., D. R. Mishra, R. Wilson, P. Reece, and A. Kohler (2009). Detecting and Mapping Four Invasive Species along the Floodplain of North Platte River, Nebraska. Weed Technology, 23:99-107, doi:10.1614/WT-08-007.1

14. Hoffman, J. D., S. Narumalani, D. R. Mishra, P. Merani, and R. G. Wilson (2008). Predicting Potential Occurrence and Spread of Invasive Plant Species along the North Platte River, Nebraska. Invasive Plant Science and Management, 1:359-367,  https://doi.org/10.1614/IPSM-07-048.1

13. Mishra, D. R., S. Narumalani, D. Rundquist, M. P. Lawson, and R. Perk (2007). Enhancing the detection and classification of coral reef and associated benthic habitats: A hyperspectral remote sensing approach. Journal of Geophysical Research, 112, C08014, https://doi.org/10.1029/2006JC003892

12. Narumalani, S., D. R. Mishra, J. Burkholder, Paul B. T. Merani, and G. Wilson (2006). A comparative evaluation of ISODATA and Spectral Angle Mapping for the detection of Saltcedar using airborne hyperspectral imagery. Geocarto International, 21(2): 59-66; https://doi.org/10.1080/10106040608542384  

11. Mishra, D. R., S. Narumalani, D. Rundquist, and M. P. Lawson (2006). Benthic habitat mapping in tropical marine environments using QuickBird imegery. Photogrammetric Engineering and Remote Sensing, 72(9): 1037-1048, DOI: 10.14358/PERS.72.9.1037 

10. Mishra, D. R., S. Narumalani, R. Bahl, D. Rundquist, and M. P. Lawson (2006). Predicting the percent cover of corals: An in-situ remote sensing approach. Geophysical Research Letters, 33, L06603, https://doi.org/10.1029/2005GL025056 

9. Mishra, D. R., S. Narumalani, D. Rundquist, and M. P. Lawson (2005). Characterizing the vertical diffuse attenuation coefficient for downwelling irradiance in coastal water: Implications for water penetration by high resolution satellite data. ISPRS Photogrammetry and Remote Sensing, 60: 48-64; https://doi.org/10.1016/j.isprsjprs.2005.09.003

8. Narumalani, S., D. R. Mishra, M. Karabulut, and M. A. Palecki, (2005). An assessment of vegetation response to different moisture conditions using SPOT-XS data. International Journal of Geoinformatics, 1(2): 33-46.

7. Singh, R. P., D. R. Mishra, A. K. Sahoo, and S. Dey (2005). Spatial and temporal variability of soil moisture over India using IRS P4 MSMR Data, International Journal of Remote Sensing, 26(10): 2241-2247; https://doi.org/10.1080/01431160500043723

6. Mishra, D. R., S. Narumalani, D. Rundquist, and M. Lawson (2005). High resolution ocean color remote sensing of benthic habitats: A case study at the Roatan Island, Honduras. IEEE Transactions in Geosciences and Remote Sensing, 43 (7): 1592-1604; doi: 10.1109/TGRS.2005.847790

5. Mishra, D. R., S. Narumalani, M. P. Lawson, and D. C. Rundquist (2004). Deriving a bathymetric map using IKONOS multispectral data. Giscience and Remote Sensing, 41(4): 301-321; https://doi.org/10.2747/1548-1603.41.4.301

4. Narumalani, S., D. R. Mishra, and R. Rothwell (2004). Change detection and landscape metrics for inferring anthropogenic processes at EFMO, Iowa. Remote Sensing of Environment, 91(3): 478-489; https://doi.org/10.1016/j.rse.2004.04.008

3. Narumalani, S., D. R. Mishra, and R. Rothwell (2004). Integrating image interpretation and spatial pattern metrics to detect landscape structural change. GIScience and Remote Sensing, 41(1): 25-44, DOI: 10.2747/1548-1603.41.1.25

2. Mishra, D. R., S. Dey, and R. P. Singh (2004). Emissivity of various geological terrains using IRS P4 MSMR data. Journal of Geological Society of India, 63: 453-457.

1. Mishra, D. R., A. K. Sahoo, R. Kanwar, and R. P. Singh (2002). Estimation of monthly rain rate over Indian Ocean region using MSMR data. Current Science, 83 (7): 877-880.

Grants:

53. Continual and robust terrain awareness through advanced fusion and analytics on multi-modal and multi-sensor data streams, (Role: PI, Co-Is: L. Ramaswamy, S. Bhandarkar, and I. Kim,), USACE, $859,762. 09/23/2022-09/22/2023 (current)

52. ESLR 2021 Coastal Resilience: Evaluating risk of tidal marsh inundation and monetizing services to prioritize management actions, (Role: Co-I, PI: L. Sutter, Co-Is: N. Weston and Y. Hashida), NOAA, $1,420,729. 09/01/2022-08/31/2026.

51. Design and assembly of a vibration table for CubeSat testing at UGA, (Role: PI), GA Space Grant Consortium, $20,000. 07/01/2022-06/30/2023 (current)

50. Developing and testing a new hyperspectral backscattering instrument to improve harmful algal bloom detections from space, (Role: Co-I; PI: S. Rivero-Calle), GA Space Grant Consortium, $20,000. 07/01/2022-06/30/2023 (current)

49. Design and assembly of a Helmholtz Cage for orbital magnetic simulations and CubeSat testing at UGA, (Role: PI), GA Space Grant Consortium, $20,000. 08/01/2021-07/31/2022 (current)

48. A CubeSat-based deep learning model for Georgia’s marine environments, (Role: PI and Mentor, Fellowship Proposal), GA Space Grant Consortium, $15,300. 08/01/2021-07/31/2022 (current) 

48. Satellite image and remote sensing analysis for highway asset management, (Role: Co-I, PI: S. Kim, Co-Is: J. Yang, S. Durham, and M. Chorzepa), GDOT, $145,000. 11/1/2021-10/31/2023. 

47. SitS: AweSOMSense: Multi-modal sensing and analytics framework for modeling belowground SOM in salt marsh wetlands, (Role: Co-I, PI: S. Kim, Co-Is: I. Kim and L. Sutter), NSF/USDA, $1,123,905. 01/01/2021-12/31/2023. 

46. Design and assembly of a Helmholtz Cage for orbital magnetic simulations and CubeSat testing at UGA, (Role: PI), GA Space Grant Consortium, $20,000. 08/01/2021-07/31/2022.

45. A CubeSat-based deep learning model for Georgia’s marine environments, (Role: PI and Mentor, Fellowship Proposal), GA Space Grant Consortium, $15,300. 08/01/2021-07/31/2022.
    
44. RAPID: COVID-19 quarantine impacts on urban-source nutrient deposition into UNESCO’s Belize Barrier Reef Reserve World Heritage site, (Role: Co-I, PI: R. Griffin, Co-Is: E. Cherrington and N. Gomez), NASA, $50,000. 08/01/2020-07/31/2022.

43. Testing and operationalizing a fully built ground station at UGA for use by students, (Role: PI, Co-I: D. Cotten), GA Space Grant Consortium, $20,000. 08/01/2020-07/31/2021.

42. Enhancing CubeSat based remote sensing capabilities by utilizing advanced simulations and analytics, (Role: PI and Mentor, Co-I: D. Cotten; Fellowship Proposal), GA Space Grant Consortium, $15,300. 08/01/2020-07/31/2021.

41. Eutrophication of water bodies and land use changes in Uruguay: An evaluation at the basin level using remote sensing, (Role: Co-I, PI: M. Vallejos, Co-Is: V. Ciganda and F. Gallego), National Research Institute for Agriculture (INIA) of Uruguay, $14,000. 01/01/2020-06/30/2021.

40. Enhancing inter satellite communication for swarms, (Role: PI and Mentor, Co-I: D. Cotten; Fellowship Proposal), GA Space Grant Consortium, $18,560. 08/01/2019-07/31/2020.

39. Progressing towards a radiation hardened high performance computer, (Role: PI, Co-I: D. Cotten), GA Space Grant Consortium, $21,440. 08/01/2019-07/31/2020. 

38. Developing an effective and targeted monitoring system for tracking toxic harmful algal blooms across Georgia, (Role: PI, Co-PI: S. Wilde), GWRI, $55,299. 03/01/2019-02/29/2020

37. Climate-influenced Nutrient Flows and Threats to the Biodiversity of the Belize Barrier Reef Reserve System, (Role: Co-I, PI: R. Griffin, Co-Is: E. Cherrington, C. Lee and A. Tewfik), NASA, $724,390. 12/01/2018-11/30/2022

36. LTER: Georgia Coastal Ecosystems IV, (Role: Senior Personnel, PI: M. Alber, Co-Is: numerous), NSF, $6,762,000. 12/01/2018-11/30/2024

35. Advancing space-based GPU computer vision algorithms, (Role: PI, Co-I: C. Cotten), GA Space Grant Consortium, $20,000. 08/01/2018-07/31/2019

34. Board development for space based processors, (Role: Mentor, Fellowship for Mr. Caleb Adams), GA Space Grant Consortium, $20,147. 08/01/2018-07/31/2019

33. Persistent hydrological consequences of hurricane interactions with the Georgia coastline, (Role: Co-I, PI: P. Miller, Co-I: T. Mote), GA Seagrant, $10,000. 01/01/2018-12/31/2018

32. Multi-view Onboard Computational Imager, (Role: Co-PI, PI: D. Cotten, Co-Is: numerous), Air Force Research Laboratory (AFRL) – University Nanosat Program (UNP), Phase-B, $750,650, 04/01/2018-03/31/2023

31. A tidal and species based MODIS GPP product for estimating marsh blue carbon across the southeastern United States, (Co-Is: J. O’Connell and D. Cotten), NASA, $994,963. 03/01/2017-02/28/2023

30. EAGER: A sensor cloud-based community-centric approach for analyzing and mitigating Urban Heat Hazards, (Co-Is: L. Ramaswamy and A. Grundstein), NSF, $238,399. 09/15/2016-09/14/2020

29. A multi-sensor approach to enhance the prediction of mangrove biophysical characteristics in Chilika Lagoon and Bhitarkanika Wildlife Sanctuary, Odisha, India, (Role: faculty advisor), NASA DEVELOP. 09/12/2016-04/01/2017

28. Digital orbital analysis of water resources for Georgia, (Co-Is: numerous) NASA, $467,218. 06/22/2016-06/21/2020

27. GeorgiaSat-1, (Co-Is: numerous), AFRL/Space Dynamics Laboratory, $147,466. 01/01/2016-12/31/2017.

26. Understanding the trajectory of coastal salt marsh structure, function, and processes in the face of sea level rise: a synthesis from historical imagery, biophysical processes, and hierarchical modeling, (Co-Is: P. Biber, W. Wu, and G. Carter), National Academy of Sciences, $506,619. 01/01/2016-12/31/2019.

25. A novel hybrid approach for mapping belowground productivity and carbon sequestration potential within Georgia salt marshes, (Co-Is: J. O’Connell, M. Alber, and K. Byrd), GA SeaGrant, $212,808. 02/01/2016-01/31/2018.

24. Utilizing NASA earth observations and proximal remote sensing for mapping spatio-temporal distribution of Hydrilla, (Role: faculty advisor), NASA DEVELOP. 05/15/2015-07/31/2015.

23. Understanding and managing the risk from cyanobacteria toxicity in farm ponds due to land management and climate interactions, (Co-Is: L. Kramer, and S. Wilde), NIFA/USDA- NNF, $36,000. 08/01/2015-07/31/2017.

22. CyberSEES: Type 1: Meghdoot: A Multi-Cloud Infrastructure for Enhancing Sustainability via Effective Monitoring of Inland Waters and Coastal Wetlands, (Co-Is: L. Ramaswamy, and S. Bhandarkar), NSF, $399,912. 10/01/2014-09/30/2019.

21. A MODIS biophysical parameters centered framework for monitoring carbon sequestration potential of Gulf Coast salt marshes, NASA, $441,413. 09/01/2014 – 08/30/2017.

20. Implications of eutrophication and climate change in promoting toxic cyanobacterial blooms in agricultural ponds across Georgia, (Co-Is: S. Wilde), USGS/Georgia Water Resources Institute, $54,320. 08/01/2014-07/31/2015.

19. Developing a cyanobacteria detection tool for Georgia inland waters using NASA Landsat-8 OLI data for water quality protection and restoration, (Role: faculty advisor), NASA DEVELOP. 06/15/2014-11/30/2014.

18. Parametrization of a bio-optical model for deriving inherent optical properties in tropical reservoirs in Brazil: Nova Avanhandava and Barra Bonita (Sao Paulo State), (Co-Is: E. Alcantara), Science without Borders: CNPq/MCTI, Govt. of Brazil, R$323,287. 08/11/2013-08/10/2016.

17. Preliminary research and data gathering for resubmission of the NSF-CyberSEES proposal- CyberSEES: Type 1: Meghdoot: A multi-cloud infrastructure for effective monitoring of inland waters and coastal wetlands sustainability, (Co-Is: L. Ramaswamy, and S. Bhandarkar), UGA OVPR, $10,000. 01/01/2014-05/15/2014.

16. Transformational approach to monitoring water quality sustainability of coastal ecosystems from satellite remote sensing, (Co-I: B. Schaeffer), NRL. 11/1/2012-12/31/2014.

15. Model to separate water column chlorophyll and benthic vegetation signals from HICO data, (Co-I: H. J. Cho), NRL. 11/1/2012-12/31/2014.

14. RAPID: Quantifying the impact of the Gulf of Mexico oil spill on the health and productivity of Louisiana salt marshes, (Co-I: J. Cho), NSF, $199,703.

13. Strengthening global climate change education through remote sensing application in coastal environment using NASA satellite data and models, (Co-PI: J. Cho), NASA, $320,977.

12. Physics-based ocean-color algorithms for water-quality products of coastal and inland waters, (Co-I: Z. Lee), NASA, $194,550.

11. A MODIS based decision support tool for Gulf Coast salt marsh conservation and restoration, (Co-Is: D. Reed and A. Gitelson), NASA, $395,439.

10. A regional partnership for climate science literacy in the southeastern United States, (Co-Is: K. McNeal, R. Smith, D. Hare, D. Rutherford, U. Nair, J. Cho, V. Anantharaj, J. Paz), NSF, $998,998.

9. Comprehensive study of the impact of the deepwater horizon oil spill on the health and productivity of Gulf Coast salt marshes, (Co-Is: K. McNeal, A. Mercer, and B. Cooke), NGI Phase-2, $193,775.

8. How healthy is this marsh? Employing innovative remote sensing techniques for assessing marsh health in restoration projects involving high school students and teachers, (Co-I: Diane Maygarden), Louisiana Sea Grant, $149,987.

7. Developing a tool for remote detection of cyanobacterial harmful algal bloom in Mississippi waters: A tangible step toward an early warning system, Henry Fund-Mississippi State University, $10,000.

6. Field sampling to study the impact of Deepwater horizon oil spill on the health and productivity of Gulf Coast salt marshes, (Co-Is: K. McNeal, A. Mercer, and B. Cooke), Gulf of Mexico Research Initiative, $80,876.

5. Developing a geospatial tool to quantify the effectiveness of the previous and current marsh restoration efforts, Louisiana Department of Natural Resources, $75,000.

4. Comprehensive study of the impact of the deepwater horizon oil spill on the health and productivity of Gulf Coast salt marshes, NGI Phase-1, $60,000; 05/202010 – 12/2010.

3. Measuring 2005 land loss in the Pontchartrain Basin using high resolution color infrared aerial photography at a scale of 1/12,000: Hurricane impact, NOAA,  $89,128.

2. Mapping, quantifying, and predicting current and future invasive plant species spread along the North Platte River corridor In Nebraska (PI: S. Narumalani), USDA, $45,000.

1. Natural resources mapping of Camp Ashland Training Site, Ashland, NE, using high density LIDAR (PI: S. Narumalani), Nebraska Army National Guard, $69,000.

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