• Ndekelu, L. M. N, Zhang, H. K.*, Bwangoy, J. R., Henebry, G. M., Maimaitijiang M., Zhang X., Lumbuenamo, R., Liu, P., & Gao, L. (2025). A time series deep learning algorithm for high spatial resolution soil moisture retrieval from Sentinel-1 data. Science of Remote Sensing, in revision.
• Zhang, H. K., Shen, Y., Zhang, X., Li, J., Yang, Z., Xu, Y., Zhang, C., Di, L., & Roy, D. P. (2025). Robust and timely within-season conterminous United States crop type mapping using Landsat Sentinel-2 time series and the transformer architecture. Remote Sensing of Environment, in revision.
• Ju, J., Zhou, Q., Freitag, B., Roy, D. P., Zhang, H. K., Sridhar, M., Mandel, J., Arab, S., Schmidt, G., Crawford, C., Gascon, F., Strobl, P. A., Masek, J., Neigh, C. S. (2025). The Harmonized Landsat and Sentinel-2 Version 2.0 surface reflectance data set. Remote Sensing of Environment, 324, 114723.
• Zhang, H. K., Camps-Valls, G., Liang, S., Tuia, D., Pelletier, C., Zhu, Z. (2025). Preface: Advancing deep learning for remote sensing time series data analysis. Remote sensing of environment, 114711.
• Huang. H., Roy, D.P., De Lemos, H., Qiu, Y., Zhang, H.K. (2025). A global Swin-Unet Sentinel-2 surface reflectance-based cloud and cloud shadow detection algorithm for the NASA Harmonized Landsat Sentinel-2 (HLS) dataset. Science of Remote Sensing, 100213.
• Tran, K. H., Zhang, X.*, Zhang, H. K.*, Shen, Y., Ye, Y., Liu, Y., Gao, S., & An, S. (2025). A transformer-based model for detecting land surface phenology from the irregular Harmonized Landsat and Sentinel-2 time series across the United States. Remote Sensing of Environment, 320, 114656.
• Gao, S., Zhang, X., Zhang, H. K., Shen, Y., Roy, D. P., Wang, W., & Schaaf, C. (2024). A new constant scattering angle solar geometry definition for normalization of GOES-R ABI reflectance times series to support land surface phenology studies. Remote Sensing of Environment, 315, 114407.
• Xiao, Y., Wang, Q., & Zhang, H. K. (2024). Global natural and planted forests mapping at fine spatial resolution of 30 m. Journal of Remote Sensing, 4, 0204.
• Yu, F., Huang, Z., Zhou, L., Zhang, H. K., & Huang, Y. (2024). Multi-temporal InSAR evidence of non-tidal ocean loading effects from Chaoshan coastal plain, China. International Journal of Applied Earth Observation and Geoinformation, 132, 104031.
• Oliveira, P. V., Zhang, H. K., & Zhang, X. (2024). Estimating Brazilian Amazon canopy height using Landsat reflectance products in a random forest model with Lidar as reference data. Remote Sensing, 16(14), 2571.
• Bao, S. G., Wang, W. J., Liu, Z., Zhang, H. K., Wang, L., Ma, J., Sun, H., Ba, S., Wang, Y., & He, H. S. (2024). Revealing post-megafire spectral and compositional recovery in the Siberian boreal forest using Landsat time series and regression-based unmixing approach. Remote Sensing of Environment, 311, 114307.
• Liu, H., Zhang, H. K.*, Huang, B., Yan, L., Tran, K. H., Qiu, Y., Zhang, X., Roy, D. P. (2024). Reconstruction of seamless harmonized Landsat Sentinel-2 (HLS) time series via self-supervised learning. Remote Sensing of Environment, 308, 114191.
• Che, X., Zhang, H. K.*, Li, Z. B., Wang, Y., Sun, Q., Luo, D., Wang, H. (2024). Linearly interpolating missing values in time series helps little for land cover classification using recurrent or attention networks. ISPRS Journal of Photogrammetry and Remote Sensing, 212, 73-95.
• Zhang, H. K., Luo, D., and Roy, D. P. (2024). Improved Landsat Operational Land Imager (OLI) cloud and shadow detection with the learning attention network algorithm (LANA). Remote Sensing, 16(8), 1321.
• Zhang, H. K., Luo, D., Li, Z. (2024). Classifying Raw Irregular Time series (CRIT) for large area land cover mapping by adapting Transformer model. Science of Remote Sensing, 100123.
• Shen, Y., Zhang, X., Gao, S., Zhang, H. K., Schaaf, C., Wang, W., Ye, Y., Liu, Y., Tran, K. H. (2024). Analyzing GOES-R ABI BRDF-adjusted EVI2 time series by comparing with VIIRS observations over the CONUS. Remote Sensing of Environment, 302, 113972.
• Radeloff, V. C., Roy, D. P., Wulder, M. A., Anderson, M., Cook, B., Crawford, C. J., Friedl, M., Gao, F., Gorelick, N., Hansen, M., Healey, S., Hostert, P., Hulley, G., Huntington, J. L., Johnson, D. M., Neigh, C., Lyapustin, A., Lymburner, L., Pahlevan, N., Pekel, J., Scambos, T. A., Schaaf, C., Strobl, P., Vermote, E., Woodcock, C. E., Zhang, H. K., Zhu, Z. (2024). Need and vision for global medium-resolution Landsat and Sentinel-2 data products. Remote Sensing of Environment, 300, 113918.
• Crawford, C. J., Roy, D. P., Arab, S., Barnes, C., Vermote, E., Hulley, G., Gerace, A., Choate, M., Engebretson, C., Micijevic, E., Schmidt, G., Anderson, C., Anderson, M., Bouchard, M., Dittmeier, R., Howard, D., Jenkerson, C., Kim, M., Kleyians, T., Maiersperger, T., Mueller, C., Neigh, C., Owen, L., Page, B., Pahlevan, N., Rengarajan, R., Roger, J., Sayler, K., Scaramuzza, P., Skakun, S., Yan, L., Zhang, H. K., Zhu, Z., Zahn, S. (2023). The 50-year Landsat collection 2 archive. Science of Remote Sensing, 8, 100103.
• Zhang, H. K., Roy, D. P., Luo, D. (2023). Demonstration of large area land cover classification with a one dimensional convolutional neural network applied to single pixel temporal metric percentiles. Remote Sensing of Environment, 295, 113653.
• Luo, D., Zhang, H. K.*, Houborg, R., Ngomba, M., Maimaitijiang, M., Tran, K., McMaine, J. (2023). Utility of daily 3 m Planet Fusion Surface Reflectance data for tillage practice mapping with deep learning. Science of Remote Sensing, 7, 100085.
• Martins, V.S., Roy, D. P., Huang, H., Boschetti, L., Zhang, H. K., Yan, L. (2022). Deep Learning high resolution burned area mapping by transfer learning from Landsat-8 to PlanetScope. Remote Sensing of Environment, 280, 113203.
• Gao, L., Gao, Q., Zhang, H. K., Li, X., Chaubell, M. J., Ebtehaj, A., Shen, L., & Wigneron, J. P. (2022). A deep neural network based SMAP soil moisture product. Remote Sensing of Environment, 277, 113059.
• Zhai, Y., Roy, D. P., Martins, S.V., Zhang, H. K., Yan, L., Li, Z. (2022). Conterminous United States Landsat-8 top of atmosphere and surface reflectance tasseled cap transformation coefficients. Remote Sensing of Environment, 274, 112992.
• Tran, K.H., Zhang, H. K.*, McMaine, J.T., Zhang, X., Luo, D. (2022). 10 m crop type mapping using Sentinel-2 reflectance and 30 m cropland data layer product. International Journal of Applied Earth Observation and Geoinformation, 107, 102692.
• Li, Z., Roy, D. P., Zhang, H. K. (2021). The incidence and magnitude of the hot-spot bidirectional reflectance distribution function (BRDF) signature in GOES-16 Advanced Baseline Imager (ABI) 10 and 15 minute reflectance over north America. Remote Sensing of Environment, 265, 112638.
• Che, X., Zhang, H. K.*, & Liu, J. (2021). Making Landsat 5, 7 and 8 reflectance consistent using MODIS nadir-BRDF adjusted reflectance as reference. Remote Sensing of Environment, 262, 112517.
• Roy, D. P., Li, Z., Zhang, H. K., Huang, H. (2020). A conterminous United States analysis of the impact of Landsat 5 orbit drift on the temporal consistency of Landsat 5 Thematic Mapper data. Remote Sensing of Environment, 240, 111701.
• Roy, D. P., Huang, H., Boschetti, L., Giglio, L., Yan, L., Zhang, H. K., Li, Z. (2019). Landsat-8 and Sentinel-2 burned area mapping - a combined sensor multi-temporal change detection approach. Remote Sensing of Environment, 231, 111254.
• Chai, D., Newsam, S., Zhang, H. K., Qiu, Y., Huang J. (2019). Cloud and cloud shadow detection in Landsat imagery based on deep convolutional neural networks. Remote Sensing of Environment, 225, 307-316.
• Zhang, H. K.*, Roy, D. P., Yan, L., Li, Z., Huang, H., Vermote E. F., Skakun S., Roger J. (2018). Characterization of Sentinel-2A and Landsat-8 top of atmosphere, surface, and nadir BRDF adjusted reflectance and NDVI differences. Remote Sensing of Environment, 215, 482-494.
• Dwyer, J.L., Roy, D. P., Sauer, B., Jenkerson, C.B., Zhang, H. K., Lymburner, L. (2018). Analysis ready data: enabling analysis of the Landsat archive. Remote Sensing, 10(9), 1363.
• Yan, L., Roy, D. P., Li, Z., Zhang, H. K. & Huang, H. (2018). Sentinel-2A multi-temporal misregistration characterization and an orbit-based sub-pixel registration methodology. Remote Sensing of Environment, 215, 495-506.
• Zhang, H. K.* & Roy, D. P. (2017). Using the 500 m MODIS land cover product to derive consistent 30 m continental scale Landsat land cover products. Remote Sensing of Environment, 197, 15-34.
• Roy, D.P, Li, J., Zhang, H. K., Yan, L., Huang, H. & Li Z. (2017). Examination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance. Remote Sensing of Environment, 199, 25-38.
• Xie B., Zhang, H. K.* & Huang, B. (2017). Revealing implicit assumptions of the component substitution pansharpening methods. Remote Sensing, 9(5), 443.
• Zhang, H. K.* & Roy, D. P. (2016). Landsat 5 Thematic Mapper reflectance and NDVI 27-year time series inconsistencies due to satellite orbit change. Remote Sensing of Environment, 186, 217-233.
• Roy, D. P., Zhang, H. K., Ju, J., Gomez-Dans, J. L., Lewis, P.E., Schaaf C.B., Sun, Q., Li, J., Huang, H. & Kovalskyy, V. (2016). A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance. Remote Sensing of Environment, 176, 255-271.
• Roy, D. P., Kovalskyy, V., Zhang, H. K., Vermote, E.F., Yan, L., Kumar, S.S & Egorov, A. (2016). Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sensing of Environment, 185, 57-70.
• Zhang, H. K.*, Roy, D. P. & Kovalskyy, V. (2016). Optimal solar geometry definition for global long-term Landsat time-series bidirectional reflectance normalization. IEEE Transactions on Geoscience and Remote Sensing, 54(3), 1410-1418.
• Roy, D. P., Li, J., Zhang, H. K. & Yan, L. (2016). Best practices for the reprojection and resampling of Sentinel-2 Multi Spectral Instrument Level 1C data. Remote Sensing Letters, 7(11), 1023-1032.
• Zhang, H. K. & Huang, B. (2015). A new look at image fusion methods from a Bayesian perspective. Remote Sensing, 7(6), 6828-6861.
• Zhang, H. K., Huang, B., Zhang, M., Cao, K. & Yu, L. (2015). A generalization of spatial and temporal fusion methods for remotely sensed surface parameters. International Journal of Remote Sensing, 36, 4411-4445.
• Zhang, H. K., Chen J.M., Huang, B., Song H.H. & Li Y.R. (2014). Reconstructing seasonal variation of Landsat vegetation index related to leaf area index by fusing with MODIS data. IEEE Transaction of Selected Topics in Applied Earth Observations and Remote Sensing, 7(3), 950-960.