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GEOAI · REMOTE SENSING · MACHINE LEARNING

Publications

147 peer-reviewed journal articles and conference papers since 2007, spanning hyperspectral remote sensing, InSAR, precision agriculture, and GeoAI — plus everything currently in review.

ORCID: 0000-0003-4375-2096 Google Scholar

147 Peer-Reviewed Publications

13 Papers In Review

2007 Publishing Since

Permafrost chemistry

Forest monitoring

SAR / InSAR change detection

Land use change

Drought monitoring

Land subsidence in Springfield, IL measured from C-band SAR

Land subsidence (SAR)

Urban heat islands

Soil carbon

Permafrost chemistry

Forest monitoring

SAR / InSAR change detection

Land use change

Drought monitoring

Land subsidence (SAR)

Urban heat islands

Soil carbon

FORTHCOMING

Papers Under Peer Review

Shrestha, N., Sagan, V., Tesser, D., Pawar, A., Farbo, A., Gul, C., Patel, A. K., Raju, D., Ye, H., Nguyen, H. T. Beyond Canopy Closure: Voxel-Based UAV LiDAR Phenotyping of Genetically Informative Soybean Canopy Architecture

Patel, A. K., Sagan, V., Baser, T., Ozdemir, S. K., Johnson, J. T., Lanagan, M. T., Iwahana, G., Shrestha, N., Islam, J., Roy, B. Recent Advances in Remote Sensing of Permafrost: A Review

Sagan, V., Rhodes, K., Bhadra, S., Alifu, H., Giri, A., Pawar, A., Roy, B., Sarkar, S., Fritschi, F. Genotype-aware estimation of soybean seed composition from multimodal UAV imagery of the standing crop

Wells, K., Sagan, V., Lopes, F., Roy, B. Multimodal Fusion of SAR Imagery and Radio Frequency Kinematics: A Bayesian Framework for Robust Vessel–Iceberg Discrimination

Muhetaer, N., Sagan, V., Tesser, D., Lopes, F. A., Rahaman, M., Farbo, A. Tracking Boreal Forest Recovery: Mapping Regrowth Stages Using Multi-Sensor Remote Sensing and Machine Learning

Roy, B., Sagan, V., Saxton, J., Gul, C., Coqurel, M., Shakoor, N. Subsurface Soil Organic Carbon Prediction from Optical and Geospatial Foundation Model Embeddings with Physics-Informed Profile Regularization: A Single-Site Agroecosystem Experiment

Sagan, V., Rhodes, K., Bhadra, S., Haireti, A., Giri, A., Fritschi, F. Unravelling seed composition from standing crops: An end-to-end CNN approach with multimodal and multitemporal imagery data (undergoing review)

Al Akkad, O., Sagan, V., Haireti, A. Beyond Pixels: A Knowledge-infused multispectral transferable model for soybean yield prediction

Haireti, A., Sagan, V., Maiwulanjiang, A., Sarkar, S., Al Akkad, O., Roy, B., Ye, H., Raju, D., Nguyen, H. Adversarial domain alignment improves root biomass prediction from SkySat imagery. IEEE Geoscience and Remote Sensing Letters. DOI

Rhodes, K. and Sagan, V. MONARCHS: Scalable Digital Twin for Migration Outcomes through Nectaring and Roosting with Comparative Habitat Suitability Under review

AliAkbarpour, H., Collins, J., Blasch, E., Seetharaman, G., Sagan, V., Palaniappan, K. Flexible Multi-Camera Focal Plane: A Light-Field Dynamic Homography Approach for Remote Sensing. In: Scanning Technologies for Autonomous Systems. Publisher: Springer Nature

Patel, A. K., Berteloni, E., Sagan, V., et al. Genomic prediction of maize tassel traits through LiDAR point cloud segmentation and machine learning phenotyping. Submitted DOI

Pawar, A., Sagan, V., et al. The Bovine Slurry Index (BSI): A spectrally informed framework for global-scale manure pond detection Under review

2007 – 2026

Peer-Reviewed Publications

2026 8 publications

[147] Vilbig, M.J., Sagan, V., Jilek, A. J., Gul, C. (2026). Finding the Features with LiDAR and SAR: Automated Detection of Archaeological Earthworks at Cahokia. Remote Sensing, 18(13), 2229. DOI

[146] Shrestha, N., Sagan, V., Tesser, D., Pawar, A., Akbarpour, H. A. (2026). Scalable Digital Twins for Complex Architecture: Preserving Neural Geometry via Deterministic Alignment. CaGIS 2026 Conference, St. Louis, Missouri. Accepted

[145] Roy, B., Sagan, V., Gul, C., Shakoor, N. (2026). Foundation Model Embeddings for Subsurface Soil Carbon Estimation: Beyond Optical Imagery. IGARSS 2026, Washington, D.C. Accepted

[144] Pawar, A., Sagan, V., Tesser, D., Boyda, E., Davitt, A. (2026). Linking Manure Management to Emissions: A Satellite–GeoAI Traceability Pipeline for U.S. Cattle Operations. CaGIS 2026 Conference, St. Louis, Missouri. Accepted

[143] Pawar, A., Sagan, V., Gul, C., Lopes, F. A., Koirala, P., Valliyodan, B. (2026). Data-Centric Phenotyping Under Scale Mismatch: A Spectral-Spatial Search Model. IGARSS 2026, Washington, D.C. Accepted

[142] Pawar, A., Sagan, V., Alifu, A., Tamang, K.R., Bagnall, G.C., Gul, C., Shrestha, N., Lopes, F., Topp, C., Valliyodan, B. (2026). A novel approach to estimate total carbon accounting for below and above-ground carbon content of industrial hemp with UAV LiDAR and hyperspectral data fusion. Smart Agriculture Technology, 13: 101897. DOI

[141] Vilbig, M.J., Sagan, V., Bodine, C. (2026). Constructing Greater Cahokia: Site concentrations and visibility surrounding America's first city. Journal of Computer Applications in Archaeology, 9(1): 43-65. DOI

[140] Roy, B., Sagan, V., Alifu, H., Saxton, J., Gul, C., Shakoor, N. (2026). Physics-aware neural framework for multidepth soil carbon mapping. IEEE Geosci. Remote Sens. Letters, 23, 3000105: 1-5. DOI

2025 8 publications

[139] Lopes, F. A., Sagan, V., Esposito, F., Stylianou, A. (2025). Geospatial Time Machine: A generative model to enhance spectral-temporal data resolution. IEEE Trans. Geosci. Remote Sens., 63, 4407613. DOI

[138] Roy, B., Sagan, V., Alifu, H., Saxton, J., Ghoreishi, D., Shakoor, N. (2025). Soil carbon estimation from hyperspectral imagery with wavelet decomposition and frame theory. IEEE Trans. Geosci. Remote Sens., 62, 4511312: 1-12. DOI

[137] Roy, B., Sagan, V. (2025). Geolocating Images Using Solar and Scanning Geometry. IGARSS 2025, Brisbane, Australia: 8896-8899. DOI

[136] Rahaman, M., Sagan, V., Lopes, F. A., Alifu, H., Gul, C., Aliakbarpour, H., Palaniappan, K. (2025). Self-Supervised Learning for Soybean Disease Detection Using UAV Hyperspectral Imagery. Remote Sensing, 17(23), 3928. DOI

[135] Malik, S.S., Moshrefizadeh, M., Tahri, O., Bai, X., Sagan, V., AliAkbarpour, H. (2025). EvSat3D: Satellite Pose Estimation and 3D Reconstruction with Event Camera. IEEE Access, 13: 130340-130352. DOI

[134] Tesser, D. S., McDonald, K. C., Podest, E., Lamb, B. T., Blüthgen, N., Tremlett, C. J., Newell, F. L., Villa-Galaviz, E., Schaefer, H. M., Nieto, R. (2025). Monitoring Tropical Forest Disturbance and Recovery: A Multi-Temporal L-Band SAR Methodology from Annual to Decadal Scales. Remote Sensing, 17(13), 2188. DOI

[133] Said, I., Sagan, V., Peterson, K.T., Haireti, A., Maiwulanjiang, A., Stylianou, A., Al Akkad, O., Sarkar, S., Al Shakarji, N. (2025). Seed protein content estimation with bench-top hyperspectral imaging and attentive convolutional neural network models. Sensors, 25(2), 303. DOI

[132] Nieto, K., Medhat, N. I., Yusupujiang, A., Sagan, V., Baser, T. (2025). Stability Assessment of the Tepehan Landslide: Before and After the 2023 Kahramanmaras Earthquakes. Geosciences, 15(5), 181. DOI

2007 – 2024

Browse Earlier Years

2024 15 publications

[131] Sagan, V., Coral, R., Bhadra, S., Alifu, H., Al Akkad, O., Giri, A., Esposito, F. (2024). Hyperfidelis: A Software Toolkit to Empower Precision Agriculture with GeoAI. Remote Sens., 16(9), 1584. DOI

[130] Skobalski, J., Sagan, V., Haireti, A., Akkad, O.A., Lopes, F., Grignola, F. (2024). Bridging the gap between crop breeding and GeoAI: Soybean yield prediction from multispectral UAV images with transfer learning. ISPRS J. Photogramm. Remote Sens., 210: 260-281. DOI

[129] Sarkar, S., Sagan, V., Bhadra, S., Fritschi, F. (2024). Spectral enhancement and expansion of PlanetScope images with Sentinel-2 data for improved soybean yield and seed composition estimation. Sci Rep 14, 15063. DOI

[128] Bhadra, S., Sagan, V., Sarkar, S., Braud, M., Mockler, T.C., Eveland, A. (2024). ROSAIL-Net: A transfer learning-based dual stream neural network to estimate leaf chlorophyll and leaf angle of crops from UAV hyperspectral images. ISPRS J. Photogramm. Remote Sens., 210: 1-24. DOI

[127] Lopes, F. A., Sagan, V., Esposito, F. (2024). PlantPlotGAN: A physics-informed generative adversarial network for plant disease prediction. IEEE/CVF WACV. PDF

[126] Roy, B., Sagan, V., Haireti, A., Newcomb, M., Tuberosa, R., LeBauer, D., Shakoor, N. (2024). Early detection of drought stress in durum wheat using hyperspectral imaging and photosystem sensing. Remote Sensing, 16(1): 155. DOI

[125] Giri, A., Sagan, V., Alifu, H., Maiwulanjiang, A., Sarkar, S., Roy, B., Fritschi, F. B. (2024). A wavelet decomposition method for estimating soybean seed composition with hyperspectral data. Remote Sensing, 16(23): 4594. DOI

[124] Giri, A., Sagan, V., Podgursky, M. (2024). The ballpark effect: spatial-data-driven insights into Baseball's local economic impact. Applied Sciences, 14(18): 8134. DOI

[123] Jaroenchai, N., Wang, S., Stanislawski, L., Shavers, S., Jiang, Z., Sagan, V., Usery, L. (2024). Transfer learning with convolutional neural networks for hydrological streamline delineation. Environmental Modelling & Software, 181: 106165. DOI

[122] Vipparla, C., Krock, T., Nouduri, K., Fraser, J., AliAkbarpour, H., Sagan, V., Cheng, J.-R. C., Kannappan, P. (2024). Fusion of visible and infrared aerial images from uncalibrated sensors using wavelet decomposition and deep learning. Sensors, 24(24), 8217. DOI

[121] Gano, B., Bhadra, S., Vilbig, J. M., Ahmed, N., Sagan, V., Shakoor, N. (2024). Drone-based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive review. The Plant Phenome Journal, 7, e20100. DOI

[120] Cox, A.L., Meyer, D., Botero-Acosta, A., Sagan, V., Demir, I., Muste, M., Boyd, P., Pathak, C. (2024). Estimating reservoir sedimentation using machine learning. Journal of Hydrologic Engineering, 29(4), 04024016.

[119] Botero-Acosta, A., Cox, A.L., Sagan, V., Demir, I., Muste, M., Boyd, P., Pathak, C. (2024). Multivariate Analysis and Anomaly Detection of U.S. Reservoir Sedimentation Dataset. Journal of Hydrologic Engineering, 29, 5. DOI

[118] Aimaiti, Y., Sagan, V., Gul, C., Maurer, J., Cothren, J.D., Klelm, C., Koenig, E., Scott, N. (2024). Improving InSAR accuracy for slow deformation and change detection with LiDAR and GPS. IEEE CISA 2024, Boulder, CO: 01-05. DOI

[117] Roy, B., Sagan, V., Alifu, H., Saxton, J., Shakoor, N. (2024). Comparative analysis of wavelet transformation techniques in enhancing soil organic carbon detection through hyperspectral imaging. IGARSS 2024, Athens, Greece: 8010-8014.

2023 12 publications

[116] Bhadra, S., Sagan, V., Skobalski, J., Grignola, F., Sarkar, S., Vilbig, J. (2023). End-to-end 3D CNN for plot-scale soybean yield prediction using multitemporal UAV-based RGB Images. Precision Agriculture, 25: 834–864. DOI

[115] Sarkar, S., Sagan, V., Bhadra, S., Rhodes, K., Pokharel, M., Fritschi, F. (2023). Soybean seed composition prediction from standing crops using PlanetScope satellite imagery and machine learning. ISPRS J. Photogramm. Remote Sens., 204: 257-274. DOI

[114] Nguyen, C., Sagan, V., Skobalski, J., Severo, J.I. (2023). Early detection of wheat yellow rust disease and its impact on terminal yield with multi-spectral UAV imagery. Remote Sensing, 15(13): 3301. DOI

[113] Nguyen, C., Sagan, V., Bhadra, S., Moose, S. (2023). UAV multisensory data fusion and multi-task deep learning for high-throughput maize phenotyping. Sensors, 23(4): 1827. DOI

[112] Wells, K., Sagan, V., Aimaiti, Y. (2023). Differentiating vessel and iceberg with CNN using SAR imagery for arctic navigation. IGARSS 2023, Pasadena, CA: 2430-2433. DOI

[111] Wells, K., Lopez, F., Sagan, V., Esposito, F. (2023). A multifaceted benchmarking of GAN architectures on generating synthetic satellite imagery. IEEE AIPR 2023, St. Louis, MO. DOI

[110] Wells, K., Sagan, V., Yusupujiang, A. (2023). Assessing climate change impact on arctic navigability using SAR imagery. IGARSS 2023.

[109] Chapell, D.C., Shang, E.R., Kucukpinar, T., Fraser, J., Collins, J., Sagan, V., Calyam, P., Palaniappan, K. (2023). NeRF-based 3D reconstruction and orthographic novel view synthesis experiments using city-scale aerial images. IEEE AIPR 2023, St. Louis, MO: 1-7. DOI

[108] Lawrence, T.J., Takenaka, B.P., Garg, A., Tao, D., Deem, S.L., Fèvre, E.M., Gluecks, I., Sagan, V., Shacham, E. (2023). A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review. Front. Public Health 11:1244084. DOI

[107] Lawrence, T.J., Vilbig, J.M., Kangogo, G., Fevre, E.M., Deem, S.L., Sagan, V., Shacham, E. (2023). Shifting climate zones and expanding tropical and arid climate regions across Kenya (1980-2020). Reg Environ Change, 23, 59. DOI

[106] Lawrence, T.J., Vilbig, J.M., Kangogo, G., Fèvre, E.M., Deem, S.L., Gluecks, I., Sagan, V., Shacham, E. (2023). Spatial changes to climatic suitability and availability of agropastoral farming systems across Kenya (1980-2020). Outlook on Agriculture. DOI

[105] Kadhim, I., Abed, M.F., Vilbig, J., Sagan, V., Desilvey, C. (2023). Combining remote sensing approaches for detecting marks of archaeological and demolished constructions in Cahokia's Grand Plaza, Southwestern Illinois. Remote Sens., 15(4), 1057. DOI

2022 7 publications

[104] Sagan, V., Maimaitijiang, M., Sidike, P., Bhadra, S., Gosselin, N., Burnette, M., Demieville, J., Hartling, S., LeBauer, D., Newcomb, M., Pauli, D., Peterson, K.T., Shakoor, N., Sylianou, A., Zender, C., Mockler, T. (2022). Data-driven artificial intelligence for calibration of hyperspectral big data. IEEE Trans. Geosci. Remote Sens., 60: 1-20. DOI

[103] Rhodes, K., Sagan, V. (2022). Integrating remote sensing and machine learning for regional scale habitat mapping: advances and future challenges for desert locust monitoring. IEEE Geoscience and Remote Sensing Magazine, 10(1): 289-319. DOI

[102] Buffa, C., Sagan, V., Brunner, G., Phillips, Z. (2022). Predicting terrorism in Europe with remote sensing, spatial statistics, and machine learning. ISPRS Int. J. Geo-Inf., 11(4), 211. DOI

[101] Dilmurat, K., Sagan, V., Maimaitijiang, M., Moose, S., Fritschi, F.B. (2022). Estimating crop seed composition using machine learning from multisensory UAV data. Remote Sensing, 14(19): 4786. DOI

[100] Dilmurat, K., Sagan, V., Moose, S. (2022). AI-driven maize yield forecasting using UAV-based hyperspectral and LiDAR data fusion. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 193–199.

[99] Bhadra, S., Sagan, V., Nguyen, C., Braud, M., Eveland, A., Mockler, T.C. (2022). Automatic extraction of solar and sensor imaging geometry from UAV-borne push-broom hyperspectral camera. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 131-137.

[98] Wardle, J.A., Sagan, V., Mohammed, F. (2022). Using Open Data Cube on the cloud to investigate food security by means of cropland changes in Djibouti. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1039–1044.

2021 9 publications

[97] Sagan, V., Maimaitijiang, M., Bhadra, S., Maimaitiyiming, M., Brown, D.R., Sidike, P., Fritschi, F. (2021). Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite images and deep learning. ISPRS J. Photogramm. Remote Sens., 174: 265-281. DOI

[96] Adrian, J., Sagan, V., Maimaitijiang, M. (2021). Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine. ISPRS J. Photogramm. Remote Sens., 175: 215-235. DOI

[95] Hartling, S., Sagan, V., Maimaitijiang, M. (2021). Urban tree species classification using a UAV-based multi-sensor data fusion approach. GIScience & Remote Sensing, 58(8): 1250-1275. DOI

[94] Hartling, S., Sagan, V., Maimaitijiang, M., Dannevik, W., Pasken, R. (2021). Estimating tree-related power outages for regional utility network using airborne LiDAR data and spatial statistics. Int. Journal of Applied Earth Observation and Geoinformation, 100:102330. DOI

[93] Nguyen, C., Sagan, V., Maimaitiyiming, M., Maimaitijiang, M., Bhadra, S., Kwasniewski, M.T. (2021). Early detection of plant viral disease using hyperspectral imaging and deep learning. Sensors, 21(3), 742. DOI

[92] Cota, G., Sagan, V., Maimaitijiang, M., Freeman, K. (2021). Forest conservation with deep learning: A deeper understanding of human geography around the Betampona Nature Reserve, Madagascar. Remote Sens., 13(17), 3495. DOI

[91] Maimaitijiang, M., Sagan, V., Bhadra, S., Nguyen, C., Mockler, T., Shakoor, N. (2021). A fully automated and fast approach for canopy cover estimation using high-resolution remote sensing imagery. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 219–226.

[90] Qin, Q., Wu, Z., Zhang, T., Sagan, V., Zhang, Z., et al. (2021). Optical and Thermal Remote Sensing for Monitoring Agricultural Drought. Remote Sensing, 13(24), 5092. DOI

[89] Maimaitijiang, M., Sagan, V., Fritschi, F.B. (2021). Crop yield prediction using satellite/UAV synergy and machine learning. IGARSS 2021: 6276-6279.

2020 9 publications

[88] Sagan, V., Peterson, K.T., Maimaitijiang, M., Sidike, P., Sloan, J., Greeling, B.A., Maalouf, S., Adams, C. (2020). Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing. Earth-Science Reviews, 205: 103187. DOI

[87] Peterson, K.T., Sagan, V., Sloan, J. (2020). Deep learning-based water quality estimation and anomaly detection using Landsat-8/Sentinel-2 virtual constellation and cloud computing. GIScience & Remote Sensing, 57(4): 510-525. DOI

[86] Maimaitijiang, M., Sagan, V., Sidike, P., Hartling, S., Esposito, F., Fritschi, F. (2020). Unmanned Aerial System (UAS)-based crop yield prediction using multi-sensor data fusion and deep learning. Remote Sensing of Environment, 237:111537. DOI

[85] Maimaitijiang, M., Sagan, V., Erkbol, H., Adrian, J., Newcomb, M., LeBauer, D., Pauli, D., Shakoor, N., Mockler, T. (2020). UAV-based sorghum growth monitoring: a comparative analysis of LiDAR and photogrammetry. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 489-496.

[84] Maimaitiyiming, M., Sagan, V., Sidike, P., Maimaitijiang, M., Miller, A.J., Kwasniewski, M. (2020). Leveraging very high spatial resolution hyperspectral and thermal UAV imageries for characterizing diurnal grapevine physiology. Remote Sens., 12(19), 3216. DOI

[83] Bhadra, S., Sagan, V., Maimaitijiang, M., Maimaitiyiming, M., Newcomb, M., Shakoor, N., Mockler, T. (2020). Quantifying leaf chlorophyll concentration of sorghum from hyperspectral data using derivative calculus and machine learning. Remote Sensing, 12(13), 2082. DOI

[82] Maimaitijiang, M., Sagan, V., Sidike, P., Daloye, A., Erkbol, H., Fritschi, F. (2020). Crop monitoring using Satellite/UAV data fusion and machine learning. Remote Sensing, 12(9), 1357. DOI

[81] Vilbig, J.M., Sagan, V., Bodine, C. (2020). Archaeological surveying with LiDAR and photogrammetry: A comparative analysis at Cahokia Mounds. Journal of Archaeological Sciences: Reports, 33: 102509. DOI

[80] Muhammad, W., Esposito, F., Maimaitijiang, M., Sagan, V., Bonaiuti, E. (2020). Polly: a tool for rapid data integration and analysis in support of agricultural research and education. Internet of Things, 9: 100141. DOI

2019 12 publications

[79] Sagan, V., Maimaitijiang, M., Sidike, P., Eblimit, K., Peterson, K.T., Hartling, S., Esposito, F., Khanal, K., Newcomb, M., Pauli, D., Ward, R., Fritschi, F., Shakoor, N., Mockler, T. (2019). UAV-Based high resolution thermal imaging for vegetation monitoring, and plant phenotyping using ICI 8640 P, FLIR Vue Pro R 640 and thermoMap Cameras. Remote Sensing, 11(3), 330. DOI — 2021 Best Paper Award

[78] Sagan, V., Maimaitijiang, M., Sidike, P., Maimaitiyiming, M., Erkbol, H., Hartling, S., Peterson, K.T., Peterson, J., Burken, J., Fritschi, F. (2019). UAV/Satellite multiscale data fusion for crop monitoring and early stress detection. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W13 — Best Paper Award. PDF

[77] Sidike, P., Sagan, V., Maimaitijiang, M., Maimaitiyiming, M., Shakoor, N., Burken, J., Mockler, T., Fritschi, F. (2019). dPEN: deep Progressively Expanded Network for mapping of heterogeneous agricultural landscape using WorldView-3 imagery. Remote Sensing of Environment, 221: 756-772.

[76] Maimaitijiang, M., Sagan, V., Sidike, P., Maimaitiyiming, M., Hartling, S., Peterson, K.T., Maw, M., Shakoor, N., Mockler, T., Fritschi, F. (2019). Vegetation Index Weighted Canopy Volume Model (CVMVI) for soybean biomass estimation from Unmanned Aerial System-based RGB Imagery. ISPRS J. Photogramm. Remote Sens., 151:27-41.

[75] Gosselin, N., Sagan, V., Maimaitiyiming, M., Fishman, J., Belina, K., Podleski, A., Maimaitijiang, M., Bashir, A., Balakrishna, J., Dixon, A. (2019). Using visual ozone damage scores and spectroscopy to quantify soybean responses to background ozone. Remote Sensing, 12(1), 93. DOI

[74] Manley, P., Sagan, V., Fritschi, F.B., Burken, J.G. (2019). Remote sensing of explosives-induced stress in plants: Hyperspectral imaging analysis for remote detection of threats. Remote Sensing, 11(15), 1827. DOI

[73] Peterson, K.T., Sagan, V., Sidike, P., Hasenmueller, E., Sloan, J., Knouft, J. (2019). Machine learning based ensemble prediction of water quality variables with proximal remote sensing using feature-level and decision-level fusion. Photogrammetric Engineering and Remote Sensing, 85(4): 269-280.

[72] Hartling, H., Sagan, V., Sidike, P., Maimaitijiang, M., Carron, J. (2019). Urban tree species classification using a WorldView-2/3 and LiDAR data fusion approach and deep learning. Sensors, 19(6), 1284. DOI

[71] Maimaitiyiming, M., Sagan, V., Sidike, P., Kwasniewski, M. (2019). Dual activation function based Extreme Learning Machine (ELM) for estimating grapevine berry yield and quality. Remote Sensing, 11(7), 740. DOI

[70] Babaeian, E., Sidike, P., Newcomb, M.S., Maimaitijiang, M., White, S.A., Demieville, J., Ward, R.W., Sadeghi, M., LeBauer, D.S., Jones, S.B., Sagan, V., Tuller, M. (2019). A new optical remote sensing technique for high-resolution mapping of soil moisture. Frontiers in Big Data, 2. DOI

[69] Flavio, E., Gururajan, S., Luna, R., Sagan, V. (2019). Improving Disaster Preparedness via (Cutting) Edge Computing and Analytics. Geospatial Informatics IX, SPIE Defense + Commercial Sensing.

[68] Wang, D., Sagan, V., Guillevic, P.C. (2019). Quantitative Remote Sensing of Land Surface Variables: Progress and Perspective. Remote Sens., 11(18), 2150. DOI

2018 18 publications

[67] Sagan, V., Maimaitiyiming, M., Fishman, J. (2018). Effects of ambient ozone on soybean biophysical variables and mineral nutrient accumulation. Remote Sens., 10(4), 562. DOI

[66] Sagan, V., Pasken, R., Zarauz, J., Krotkov, N. (2018). Monitoring SO2 trajectories in a complex terrain environment using CALIPUFF, OMI and MODIS data. Int. Journal of Applied Earth Observation and Geoinformation, 69: 99-109.

[65] Peterson, K.T., Sagan, V., Sidike, P., Cox, A.L., Martinez, M. (2018). Suspended sediment concentration estimation from Landsat imagery along the lower Missouri and middle Mississippi Rivers using extreme learning machine. Remote Sens., 10(10), 1503. DOI

[64] Sidike, P., Asari, V., Sagan, V. (2018). Progressively Expanded Neural Network (PEN Net) for hyperspectral image classification: a new neural network paradigm for remote sensing image analysis. ISPRS J. Photogramm. Remote Sens., 146: 161-181.

[63] Albalooshi, F., Sidike, P., Sagan, V., Albastaki, Y., Asari, V. (2018). Deep Belief Active Contours (DBAC) with Its Application to Oil Spill Segmentation from Remotely Sensed Aerial Imagery. Photogrammetric Engineering and Remote Sensing, 84(7): 451-458.

[62] Sidike, P., Sagan, V., Qumsiyeh, M., Maimaitijiang, M., Essa, A., Asari, V. (2018). Adaptive Trigonometric Transformation Function with Image Contrast and Color Enhancement: Application to Unmanned Aerial System Imagery. IEEE Geoscience and Remote Sensing Letters, 15(3): 404-408.

[61] Loesch, E., Sagan, V. (2018). SBAS Analysis of Induced Ground Surface Deformation from Wastewater Injection in East Central Oklahoma, USA. Remote Sens., 10(2), 283. DOI

[60] Nurmemet, I., Sagan, V., Ding, J-L., Halik, Ü., Abliz, A., Yakup, Z. (2018). A WFS-SVM model for Soil Salinity Mapping in Keriya Oasis, NW China using polarimetric decomposition and fully PolSAR data. Remote Sens., 10(4), 598. DOI

[59] Ding, J., Yang, A., Wang, J., Sagan, V., Yu, D. (2018). Machine learning based quantitative estimation of soil organic carbon content by VIS/NIR spectroscopy. PeerJ 6: e5714. DOI

[58] Dawson, T., Sandoval, J.O., Sagan, V., Crawford, T. (2018). A Spatial Analysis of the Relationship between Vegetation and Poverty. ISPRS Int. J. Geo-Information, 7(3), 83. DOI

[57] Sidike, P., Mohammad, A., Sagan, V. (2018). Robust pattern recognition via joint transform correlation. In Advances in Pattern Recognition, pp. 81-99. Nova Science Publishers.

[56] Shavers, E., Ghulam, A., Encarnacion, J. (2018). Surface alteration of a melilitite-clan carbonatite and the potential for remote detection among sedimentary carbonates, Southeast Missouri, USA. Ore Geology Reviews, 92: 19-28.

[55] Pereira, L., Andes, L., Cox, A., Ghulam, A. (2018). Measuring suspended-sediment concentration and turbidity in the Middle Mississippi and Lower Missouri Rivers using Landsat data. JAWRA, 54(2): 440-450.

[54] Sidike, P., Sagan, V., Asari, V.K. (2018). A multi-component based volumetric directional pattern for texture feature extraction from hyperspectral imagery. SPIE Defense + Security: Pattern Recognition and Tracking XXIX, Orlando, FL.

[53] Burnette, M., Willis, C., Kooper, R., Maloney, J.D., Ward, R., Shakoor, N., Newcomb, M., Rohde, G.S., Fahlgren, N., Sagan, V., Sidike, P., Terstriep, J.A., LeBauer, D. (2018). TERRA-REF Data Processing Infrastructure. PEARC 2018.

[52] Flavio, E., Gururajan, S., Luna, R., Sagan, V. (2018). Improving disaster preparedness via (cutting) edge computing and analytics. Geospatial Informatics IX, SPIE Defense + Commercial Sensing.

[51] Sidike, P., Sagan, V., Asari, V.K. (2018). A multi-component based volumetric directional pattern for texture feature extraction from hyperspectral imagery. SPIE Defense + Security: Pattern Recognition and Tracking XXIX, Orlando, FL.

[50] Burnette, M., Willis, C., Kooper, R., Maloney, J.D., Ward, R., Shakoor, N., Newcomb, M., Rohde, G.S., Fahlgren, N., Sagan, V., Sidike, P., Terstriep, J.A., LeBauer, D. (2018). TERRA-REF Data Processing Infrastructure. PEARC 2018.

2017 6 publications

[49] Maimaitijiang, M., Ghulam, A., Sidike, P., Hartling, S., Maimaitiyiming, M., Peterson, K., Shavers, E., Peterson, J., Kadam, S., Burken, J., Fritschi, F. (2017). Unmanned aerial system-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine. ISPRS J. Photogramm. Remote Sens., 134:43-58.

[48] Sidike, P., Ghulam, A., Asari, V.K., Alam, M.S. (2017). Efficient hyperspectral target detection using class-associative spectral fringe-adjusted JTC with dimensionality reduction techniques. Asian Journal of Physics, 26(3&4): 171-180.

[47] Maimaitiyiming, M., Ghulam, A., Bozzolo, A., Wilkins, J., Kwasniewski, M. (2017). Early detection of plant physiological responses to different levels of water stress using reflectance spectroscopy. Remote Sens., 9(7), 745. DOI

[46] Shavers, E., Ghulam, A., Encarnacion, J., Hartling, S. (2017). Emplacement of Ultramafic-carbonatite Intrusions Along Reactivated North American Mid-continent Rift Structures. Tectonophysics, 712-713: 716-722.

[45] Rao, M., Silber-Coats, Z., Fox, L., Ghulam, A. (2017). Mapping Drought-Impacted Vegetation Stress in California Using Remote Sensing. GIScience and Remote Sensing, 54(2): 185-201.

[44] Wang, X., Zhang, F., Kung, H., Ghulam, A., Trumbo, A., Yang, J., Ren, Y., Jing, Y. (2017). Evaluation and estimation of surface water quality in an arid region based on EEM-PARAFAC and 3D fluorescence spectral index: A case study of the Ebinur Lake Watershed, China. Catena, 155: 62-74.

2016 6 publications

[43] Ghulam, A., Grzovic, M., Maimaitijiang, M., Sawut, M. (2016). InSAR monitoring of land subsidence for sustainable urban planning. In Weng, Q. (Eds.), Remote Sensing for Sustainability. CRC Press.

[42] Huang, J., Khan, S., Ghulam, A., Crupa, W., Abir, I., Khan, A., Kakar, D., Kasi, A., Kakar, N. (2016). Surface Deformation in Quetta Valley, Balochistan, Pakistan. Remote Sensing, 8(11), 956. DOI

[41] Zoogman, P., Liu, X., Suleiman, R.M., Pennington, W.F., Flittner, D.E., Al-Saadi, J.A., et al., Ghulam, A., et al. (2016). Tropospheric Emissions: Monitoring of Pollution (TEMPO). Journal of Quantitative Spectroscopy & Radiative Transfer, 186: 17-39.

[40] Shavers, E., Ghulam, A., Encarnacion, J., Bridges, D.L., Luetkemeyer, P.B. (2016). Carbonatite associated with ultramafic diatremes in the Avon Volcanic District, Missouri, USA: Field, petrographic, and geochemical constraints. Lithos, 248-251: 506-516.

[39] Maimatiyiming, M., Miller, A., Ghulam, A. (2016). Discriminating spectral signatures among and within two closely related grapevine species. Photogrammetric Engineering and Remote Sensing, 82(2): 15-26.

[38] Abliz, A., Tiyip, T., Ghulam, A., Ding, J-L, Halik, Ü., Sawut, M., Fei, Z., Nurmemet, I., Abliz, A. (2016). Effects of shallow groundwater table and salinity on soil salt dynamics in the Keriya Oasis, Northwestern China. Environmental Earth Sciences, 75(3): 260.

2015 8 publications

[37] Ghulam, A., Ghulam, O., Maimaitijiang, M., Freeman, K., Porton, I., Maimaitiyiming, M. (2015). Remote sensing based spatial statistics to document tropical rainforest transition pathways. Remote Sensing, 7(5): 6257-6279.

[36] Ghulam, A., Fishman, J., Maimaitiyiming, M., Wilkins, J-L., Maimaitijiang, M., Welsh, J., Bira, B., Grzovic, M. (2015). Characterizing crop responses to background ozone in open air agricultural field by using reflectance spectroscopy. IEEE Geoscience and Remote Sensing Letters, 12(6): 1307-1311.

[35] Grzovic, M., Ghulam, A. (2015). Monitoring residual land subsidence due to underground coal mining using TimeSAR (SBAS and PSI) in Springfield, Illinois, USA. Natural Hazards, 79(3): 1739-1751.

[34] Maimaitijiang, M., Ghulam, A., Sandoval, J.S.O., Maimaitiyiming, M. (2015). Drivers of land cover and land use changes in St. Louis Metropolitan area over the past 40 years characterized by remote sensing and census population data. Int. Journal of Applied Earth Observation and Geoinformation, 35: 161-174.

[33] Zeng, T., Ghulam, A., Yang, W-N, Grzovic, M., Maimaitiyiming, M. (2015). Estimating the volume and spatial extent of loose deposits, and its contribution to potential geological hazards over Wenchuan Earthquake zone, China. IEEE JSTARS, 8(2): 750-762.

[32] Nurmemet, I., Ghulam, A., Tiyip, T., et al. (2015). Monitoring Soil Salinization in Keriya River Basin, Northwestern China Using Passive reflective and Active Microwave Remote Sensing Data. Remote Sensing, 7(7): 8803-8829.

[31] Abir, I., Khan, S., Ghulam, A., Tariq, S., Shah, M. (2015). Active tectonics of western Potwar Plateau-Salt Range, Northern Pakistan from InSAR observations and seismic imaging. Remote Sensing of Environment, 168: 265-275.

[30] Chen, C., Qin, Q., Chen, L., Zheng, H., Fa, W., Ghulam, A., Zhang, C. (2015). Photometric correction and reflectance calculation for lunar images from the Chang'E-1 CCD stereo camera. Journal of the Optical Society of America A, 32(12): 2409-2422.

2014 7 publications

[29] Ghulam, A. (2014). Monitoring tropical forest degradation in Betampona Nature Reserve, Madagascar using multi-source remote sensing data fusion. IEEE JSTARS, 7(12): 4960-4971.

[28] Ghulam, A., Porton, I., Freeman, K. (2014). Detecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm. ISPRS J. Photogramm. Remote Sens., 88: 174-192.

[27] Sawut, M., Ghulam, A., Teyip, T., Zhang, Y-J., Ding, J-L., Zhang, F. (2014). Estimating soil sand content using thermal infrared spectra in arid lands. Int. Journal of Applied Earth Observation and Geoinformation, 33: 203-210.

[26] Maimatiyiming, M., Ghulam, A., Tiyip, T., Pla, F., Latorre-Carmona, P., Sawut, M., Halik, Ü., Caetano, M. (2014). Effects of spatial pattern of green space on land surface temperature: implications for sustainable urban planning and climate change adaptation. ISPRS J. Photogramm. Remote Sens., 89: 59-66.

[25] Jordan, Y.C., Ghulam, A., Chu, M.L. (2014). Assessing the impacts of future urban developing patterns and climate changes on surface water quality using geoinformatics. Journal of Environmental Informatics, 24(2): 65-79.

[24] Jordan, Y.C., Ghulam, A., Hartling, S. (2014). Traits of surface water pollution under climate and land use changes: A remote sensing and hydrological modeling approach. Earth-Science Reviews, 128: 181-195.

[23] Shahabfar, A., Ghulam, A., Conrad, C. (2014). Understanding hydrological repartitioning and shifts in drought regimes in Central and South-West Asia using MODIS derived perpendicular drought index and TRMM data. IEEE JSTARS, 7(3): 983-993.

2013 4 publications

[22] Chu, M.L., Ghulam, A., Knouft, J., Pan, Z. (2013). A hydrologic data screening procedure for exploring the trends and shifts in rainfall and runoff patterns. JAWRA, 50(4): 928-942.

[21] Chu, M.L., Knouft, J., Ghulam, A., Pan, Z. (2013). Impacts of urbanization on river flow variables: A controlled experimental modeling-based evaluation approach. Journal of Hydrology, 495: 1-12.

[20] Rajendran, S., Nasir, S., Kusky, T.M., Ghulam, A., Gabr, S., Gali, M.E. (2013). Detection of hydrothermal mineralized zones associated with Listwaenites rocks in the Central Oman using ASTER data. Ore Geology Reviews, 53: 470-488.

[19] Amer, R., Sultan, M., Ripperdan, R., Ghulam, A., Kusky, T. (2013). An integrated approach for groundwater potential zoning in shallow fracture zone aquifers. International Journal of Remote Sensing, 34(19): 6539-6561.

2012 3 publications

[18] Jordan, Y.C., Ghulam, A., Herrmann, R. (2012). Floodplain ecosystem response to climate variability and land-cover and land-use change in Lower Missouri River Basin. Landscape Ecology, 27: 843-857.

[17] Shahabfar, A., Ghulam, A., Eitzinger, J. (2012). Drought monitoring in Iran using the Perpendicular Drought Indices. Int. Journal of Applied Earth Observation and Geoinformation, 18: 119-127.

[16] Rajendran, S., al-Khirbash, S., Pracejus, B., Nasir, S., Al-Abri, A.H., Kusky, T.M., Ghulam, A. (2012). ASTER detection of chromite bearing mineralized zones in Semail Ophiolite Massifs of the northern Oman Mountains: Exploration strategy. Ore Geology Reviews, 44: 121-135.

2011 3 publications

[15] Ghulam, A., Kusky, T., Teyip, T., Qin, Q. (2011). Subcanopy soil moisture modeling in n-dimensional spectral feature space. Photogrammetric Engineering and Remote Sensing, 77(2): 149-156.

[14] Yao, Y., Qin, Q., Ghulam, A., Zhao, S., Liu, S. (2011). A simple method to determine the Priestley-Taylor parameter for evapotranspiration estimation using Albedo-VI triangular space from MODIS data. Journal of Applied Remote Sensing, 5, 053505.

[13] Ghulam, A., Freeman, K., Bollen, A., Ripperdan, R., Porton, I. (2011). Mapping invasive plant species in tropical rainforest using fully polarimetric RADARSAT-2 and PALSAR data. IGARSS 2011, Vancouver, Canada.

2010 5 publications

[12] Gabr, S., Ghulam, A., Kusky, T. (2010). Detecting areas of high-potential gold mineralization using ASTER data. Ore Geology Reviews, 38(1-2): 59-69.

[11] Kusky, T., Ghulam, A., Wang, L., et al. (2010). Focusing Seismic Energy Along faults through time-variable rapture modes: Wenchuan Earthquake, China. Journal of Earth Science, 21(6): 910-922.

[10] Amer, R., Kusky, T., Ghulam, A. (2010). Lithological mapping in the Central Eastern Desert of Egypt using ASTER data. Journal of African Earth Sciences, 56(2-3): 75-82.

[09] Zarauz, J., Ghulam, A., Pasken, R. (2010). Sulfur dioxide estimations in the planetary boundary layer using ozone monitoring instrument. ASPRS/CaGIS 2010, Orlando, FL.

[08] Ghulam, A., Amer, R., Ripperdan, R. (2010). A filtering approach to improve deformation accuracy using large baseline, low coherence DInSAR phase images. IEEE IGARSS 2010, Honolulu, Hawaii: 3494-3497.

2008 4 publications

[07] Ghulam, A., Li, Z-L, Qin, Q., Yimit, H., Wang, J. (2008). Estimating crop water stress with ETM+ NIR and SWIR data. Agricultural and Forest Meteorology, 148: 1679-1695.

[06] Ghulam, A., Qin, Q., Kusky, T., Li, Z-L. (2008). Re-examination of perpendicular drought indices. International Journal of Remote Sensing, 29(20): 6037-6044.

[05] Qin, Q., Ghulam, A., Zhu, L., Wang, L., Li, J., Nan, P. (2008). Evaluation of MODIS derived perpendicular drought index for estimation of surface dryness over northwestern China. International Journal of Remote Sensing, 29(7): 1983-1995.

[04] Qin, Q., Zhu, L., Ghulam, A., Li, Z., Nan, P. (2008). Satellite monitoring of spatio-temporal dynamics of China's coastal zone eco-environments: preliminary analysis on the relationship between the environment, climate change and human behavior. Environmental Geology, 55: 1687-1698.

2007 3 publications

[03] Ghulam, A., Qin, Q., Teyip, T., Li, Z-L. (2007). Modified perpendicular drought index (MPDI): a real-time drought monitoring method. ISPRS J. Photogramm. Remote Sens., 62: 150-164.

[02] Ghulam, A., Qin, Q., Zhan, Z. (2007). Designing of the perpendicular drought index. Environmental Geology, 52(6): 1045-1052.

[01] Ghulam, A., Li, Z-L, Qin, Q., Tong, Q. (2007). Exploration of the spectral space based on vegetation index and albedo for surface drought estimation. Journal of Applied Remote Sensing, Vol 1, 013529.

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