Melba M. Crawford

Purdue University
Lyles School of Civil Engineering
550 Stadium Mall Drive
West Lafayette, IN 47907-2051

Office: HAMP 4112
Phone: (765) 496-3224
Email: mcrawford@purdue.edu

Education
Ph.D., Ohio State University, 1981
MSCE, University of Illinois, 1973
BSCE, University of Illinois, 1970

Research Summary
Development and application of advanced methods for analysis of remote sensing data, including high dimensional data analysis, data fusion techniques for multisensor problems, multiresolution methods in image analysis, and knowledge transfer in data mining.

Selected Research Projects
NSF, "A Paradigm Shift in Ecosystem and Environmental Modeling: A High Performance Computing and Machine Learning Approach," (with Q. Zhuang (PI), H. Zhang, J. Zhang, Dongbin Xiu), 2010-2014.

NASA, "An Advanced Learning Framework for High Dimensional Multi-sensor Remote Sensing Data," 2012-2015.

DoE ARPA-E, "Automated Sorghum Phenotyping and Trait Development Platform," (with M. Tuinstra), 2015-2018.

Foundation for Food and Agriculture Research, "An Open Source Framework and Community for Sharing Data and Algorithms," (J. Krogmeier, PI), 2018-2021.

CIMMYT International, "Heat Stress Resilient Maize for South Asia Through a Public-Private Partnership," (M. Tuinstra, PI), 2019-2024.

DoE ARPA-E "Automated Sorghum Phenotyping and Trait Development Platform PLUS Up," (with M. Tuinstra), 2019-2021.

Korean Polar Research Institute, "Hyperspectral Sensing of Arctic Vegetation," 2019-2020.

Honors & Awards
UT Engineering Foundation Faculty Excellence Award, 1987, 1990
UT Engineering Foundation Faculty Fellowship #3, 1988 -1991
General Dynamics Departmental Teaching Excellence Award, 1990
Halliburton Education Foundation Award for Excellence in Teaching, 1991
Outstanding Graduate Faculty Award, Graduate School, University of Texas, 1993
Charlotte Maer Patton Centennial Fellow in Engineering, 1991-1998
Engineering Foundation Endowed Professorship #1, 1999 - 2005
NASA Outstanding Service Award, EO-1 Science Team, 2002
Jefferson Senior Science Fellow, U.S. State Department, 2004-2005
Purdue Chair of Excellence in Earth Observation, 2006 - 2019
Fellow, Institute for Electrical and Electronics Engineers, 2007- Present
Woman of Purdue, Mortar Board Honoree, 2009
Mortar Board, Honorary Member, 2009 - 2010
Purdue College of Engineering Team Award for SURF program, 2012
Nancy Uridil and Francis Bossu Professor in Civil Engineering, 2019-present
IEEE GRSS Outstanding Service Award, 2020

Selected Publications

A. Refereed Archival Journals
L. Ma, M.M. Crawford, and J.W. Tian, "Generalized Supervised Local Tangent Space Alignment for Hyperspectral Image Classification," Electronics Letters, 46(7), 498-499, 2010.
L. Ma, M.M. Crawford, and J.W. Tian, "Local Manifold Learning Based K-Nearest Neighbor for Hyperspectral Image Classification," IEEE Trans. on Geoscience and Remote Sensing, 48(11), 4099-4109, 2010.
W. Kim and M.M. Crawford, "Adaptive Classification of Hyperspectral Image Data using Manifold Regularization Kernel Machines," IEEE Trans. on Geoscience and Remote Sensing, 48(11), 4110-4121, 2010.
W. Kim, M.M. Crawford, and S. Lee, "Integrating Spatial Proximity with Manifold Learning for Hyperspectral Data," Korean Journal of Remote Sensing 26(6), 693-703, 2010.
W. Di and M.M. Crawford, "Active Learning via Multi-View and Local Proximity Co-regularization for Hyperspectral Image Classification," IEEE Journal of Selected Topics in Signal Processing, 5(3), 618-628, 2011.
I. Chaubey, K. Cherkauer, M.M. Crawford, and B. Engel, "Multiscale Sensing and Modeling Frameworks: Integrating Field to Continental Scales," NAE Bridge, 41(3), 39-46, 2011.
J. Jung and M.M. Crawford, "Extraction of Features from LIDAR Waveform Data for Characterizing Forest Structure," IEEE Geoscience and Remote Sensing Letters, 9(3), 492-496, 2012.
W. Di and M.M. Crawford, "View Generation for Multi-view Maximum Disagreement Based Active Learning for Hyperspectral Image Classification," IEEE Transactions on Geoscience and Remote Sensing, 50(5), 1942-1954, 2012.
D. Grant, J. Bethel, and M. M. Crawford, "Point-to-Plane Registration of Terrestrial Laser Scans," ISPRS Journal of Photogrammetry and Remote Sensing, 72, 16-26, 2012.
X. Jia, B. Kuo, M.M. Crawford, "Feature Mining for Hyperspectral Image Classification," Proceedings of the IEEE, 101(3), 676-697, 2013.
M.M. Crawford, D. Tuia, and H. Yang, "Active Learning: Any Value for Remote Sensing Applications?" Proceedings of the IEEE, 101(3), 593-608, 2013.
M. Galloza, M.M. Crawford, and G. Heathman, "Crop Residue Modeling and Mapping Using Landsat, ALI, Hyperion, and Airborne Remote Sensing Data," J. Special Topics in Applied Earth Observations and Remote Sensing, 6(2), 446-456, 2013.
J. Chi and M.M. Crawford, "Selection of Landmark Points on Nonlinear Manifolds for Spectral Unmixing Using Local Homogeneity," IEEE Geoscience and Remote Sensing Letters, 10(4), 711-715, 2013.
Lunga, D., S. Prasad, M. M. Crawford, and O. Ersoy, "Manifold Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning," IEEE Signal Processing Magazine, 31(1), 55-66, 2014.
J. Jung, E. Pasolli, S. Prasad, J. Tilton, and M.M. Crawford, "A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation," J. Special Topics in Applied Earth Observations and Remote Sensing, 7(2), 491-502, 2014.
J. Chi and M.M. Crawford, "Spectral Unmixing Based Crop Residue Estimation," J. Special Topics in Applied Earth Observations and Remote Sensing, 7(6), 2531- 2539, 2014.
J. Chi and M.M. Crawford, "Active Landmark Sampling for Manifold Learning Based Spectral Unmixing," IEEE Geoscience and Remote Sensing Letters, 11(11), 1881-1885, 2014.
L. Ma, M. M. Crawford, X. Yang, and Y. Guo, "Local Manifold-Learning-Based Graph Construction for Semi-Supervised Hyperspectral Image Classification," IEEE Transactions on Geoscience and Remote Sensing, 53(5), 2832-2844, 2015.
Y. Zhang, H.H. Yang, S. Prasad, E. Pasolli, J. Jung, and M. Crawford, "Ensemble Multiple Kernel Active Learning for Classification of Multi-Source Remote Sensing Data," J. Special Topics in Applied Earth Observations and Remote Sensing, 8(2), 845-858, 2015.
H. L. Yang and M. M. Crawford, "Spectral and Spatial Proximity Based Manifold Alignment for Multitemporal Hyperspectral Image Classification," IEEE Transactions on Geoscience and Remote Sensing, 54(1), 51-64, 2016.
H. L. Yang and M. M. Crawford, "Domain Adaptation with Preservation of Manifold Geometry for Hyperspectral Image Classification," IEEE J. Special Topics in Applied Earth Observations and Remote Sensing, 9(2), 543-555, 2016.
X. Zhou; S. Prasad, and M.M. Crawford, "Wavelet-Domain Multiview Active Learning for Spatial-spectral Hyperspectral Image Classification," IEEE J. Special Topics in Applied Earth Observations and Remote Sensing, 9(9), 4047-4059, 2016.
Z. Zhang, E. Pasolli, M.M. Crawford, and J. Tilton, "An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation," J. Special Topics in Applied Earth Observations and Remote Sensing, 9(2), 640-654, 2016.
A. Habib, Y. Han, W. Xiong, F. He, Z. Zhang, and M. Crawford, "Automated Ortho-Rectification of UAV-Based Hyperspectral Data over an Agricultural Field Using Frame RGB Imagery," Remote Sensing, 8(10), 796-818, 2016.
Z. Zhang, E. Pasolli, H.H. Yang, and M.M. Crawford "Multi-metric Active Learning for Classification of Multisource Remotely Sensed Data," IEEE Geoscience and Remote Sensing Letters, 13(7), 1007-1011, 2016.
A. Habib, W. Xiong, F. He, H.L. Yang, M. Crawford, "Improving Orthorectification of UAV-Based Push-Broom Scanner Imagery Using Derived Orthophotos From Frame Cameras," J. Special Topics in Applied Earth Observations and Remote Sensing, 10(1), 262-276, 2017.
E. Ibrahim, W. Kim, M. Crawford, and J. Monbaliu, "A Regression Approach to the Mapping of Bio-physical Characteristics of Surface Sediment using In situ and Airborne Hyperspectral Acquisitions," Ocean Dynamics, 67, 299-316, 2017.
Z. Zhang and M. Crawford, "Batch-mode Regularized Multi-metric Active Learning for Classification of Hyperspectral Images," IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6594-6609, 2017.
G. Pignotti, H. Rathjens, R. Cibin, I. Chaubey, and M. Crawford, "Comparative Analysis of Spatial Resolution Effects on HRU and Grid-based SWAT Models." Water, 9(4), 272, 1-20, 2017.
A. Habib, T. Zhou, A. Masjedi, Z. Zhou, J.E. Flatt, M. Crawford, "Boresight Calibration of GNSS/INS-assisted Push-broom Hyperspectral scanners on UAV platforms," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS), 11(5), 1734-1739, 2018.
L. Ma, L. Zhu, M. Crawford, and Y. Liu "Centroid and Covariance Alignment based Domain Adaptation for Unsupervised Classification of Remote Sensing Images," IEEE Transactions on Geoscience and Remote Sensing, 57(4), 2305-2323, 2019.
G. Taskin, M. Crawford, "An Out-of-Sample Extension to Manifold Learning via Meta-Modeling," IEEE Transactions on Image Processing, 28(10), 5227-5238, 2019.
J. Chi and M. Crawford, "A New Global Arctic Sea Ice Concentration Retrieval Algorithm by Incorporating Spectral Mixture Analysis and Deep Learning," Remote Sensing of Environment, 231, Article 111204, 2019.
Z. Zhang, E. Pasolli, and M. Crawford, "An Adaptive Multiview Active Learning Approach for Spectral-Spatial Classification of Hyperspectral Images," IEEE Transactions on Geoscience and Remote Sensing, 58(4), 2557-2570, 2020.
B. Refereed Conference Proceedings
M. Crawford, S. Prasad, X. Zhou, and Z. Zhang, "Classification of multi-source sensor data with limited labeled data," Proc. of the SPIE 9472, April 20, 2015, Baltimore, MD, 2015.
Z. Zhang and M. M. Crawford, "An Ensemble Active Learning Approach for Spectral-Spatial Classification of Hyperspectral Imagery," 2015 IEEE Geoscience and Remote Sensing Symposium, July 27-31, Milan, Italy, 4963-4966, 2015.
E. Ibrahim, W. Kim, M. Crawford, and J. Monbaliu, "The Impact of Bio-physical Thresholds on Sediment Analysis Through Field Reflectance Spectra and Hyperspectral Imagery," INTERCOH2015, September, 2015.
Z. Zhang and M. Crawford, "Semi-supervised Multi-Metric Active Learning for Classification of Hyperspectral Images," 2016 IEEE Geoscience and Remote Sensing Symposium, July 11-15, Beijing, China, 2016.
M. Tuinstra, C. Weil, A. Thompson, C. Boomsma, M. Crawford, K. Cherkauer, E. Delp, A. Habib, Z. Zhang, L. Biehl, N. Abe, M. Kshirsagar, A. Lozano, K. Natesan, P. Olsen, and E. Yang, "Automated Sorghum Phenotyping and Trait Development-Platform in the TERRA Project," Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Workshop on Data Science for Food, Energy, and Water, August 2016, San Francisco, CA. Z. Zhang, A. Masjedi, J. Zhao, and M. Crawford, "Prediction of Sorghum Biomass Based on Image-Based Features from Time Series of UAV Images," Proc. 2017 IEEE Geoscience and Remote Sensing Symposium, July 23-28, 2017, Ft. Worth, TX.
G. Taskin and M. Crawford, "Extending Out-of-Sample Manifold Learning via Meta-Modelling Techniques," Proc. 2017 IEEE Geoscience and Remote Sensing Symposium, July 23-28, Ft. Worth, TX, 562-565, 2017.
R. Ravi, Y.J. Lin, T. Shamseldin, M. Elbahnasawy, M. Crawford, and A. Habib, "Implementation of UAV-based LiDAR for High Throughput Phenotyping," Proc. 2018 IEEE Geoscience and Remote Sensing Symposium, July 23-27, Valencia, Spain, 2018.
M. Elbahnasawy, T. Shamseldin, R. Ravi, J. Zhou, Y. J. Lin, A. Masjedi, E. Flatt, M. Crawford, A. Habib, "Multi-Sensor Integration onboard a UAV-Based Mobile Mapping System for Agricultural Management," Proc. 2018 IEEE Geoscience and Remote Sensing Symposium, July 23-27, 2018, Valencia, Spain.
R. Ravi, Y.J. Lin, T. Shamseldin, M. Elbahnasawy, A. Masjedi, M. Crawford, A. Habib, "Wheel-based LiDAR Data for Plant Height and Canopy Cover Evaluation to aid Biomass Prediction," Proc. 2018 IEEE Geoscience and Remote Sensing Symposium, July 23-27, 3242-3245, Valencia, Spain, 2018.
A. Masjedi, J. Zhao, A. Thompson, J.E. Flatt, M. Crawford, D. Ebert, "Sorghum Biomass Prediction Using UAV-Based Remote Sensing Data and Crop Model Simulations," 2018 IEEE Geoscience and Remote Sensing Symposium, July 23-27, 2018, Valencia, Spain, 2018.
Z. Zhang, G. Taskin, M. Crawford, "Active Manifold Learning for Hyperspectral Image Classification," 2018 IEEE Geoscience and Remote Sensing Symposium, July 23-27, 2587-2590, Valencia, Spain, 2018.
J. Zhao, M. Karimzadeh, A. Masjedi, T. Wang, X. Zhang, M. M. Crawford, and D. S. Ebert, "Feature Explorer: Interactive feature selection and exploration of regression models for hyperspectral images," in 2019 IEEE Visualization Conference (VIS), 161, Oct 2019.
B. Nazeri, and M. Crawford, "Leaf Area Index Prediction of Sorghum using Wheel-based and Airborne Discrete Return LiDAR Data," American Society for Photogrammetry and Remote Sensing (ASPRS) 2019 Annual Conference, Denver, Colorado, January 27-31, 2019. (Abstract only)
A. Masjedi, N. Carpenter, M. Crawford, and M. Tuinstra, "Prediction of Sorghum Biomass Using UAV Time Series Data and Recurrent Neural Networks," CVPR 2019 Computer Vision Problems in Plant Phenotyping (CVPPP 2019), June 17, 2019, San Diego, CA.
E. Cai, S. Baireddy, C. Yang, M. Crawford, and E.J. Delp, "Deep Transfer Learning For Plant Center Localization," CVPR 2020 Agriculture-Vision Workshop, June 14, 2020.
A. Karami, M. Crawford, and E. Delp, "A Weakly Supervised Deep Learning Approach for Plant Center Detection and Counting," 2020 IEEE Geoscience and Remote Sensing Symposium, July 19-24, Waikoloa, HI, 2020 (accepted).
A. Masjedi and M. Crawford, "Prediction of Sorghym Biomass Using Time Series UAV-Based Hyperspectral and LiDAR Data," 2020 IEEE Geoscience and Remote Sensing Symposium, July 19-24, Waikoloa, HI, 2020 (accepted).