Terrace erosion and sediment transport model: a new tool for soil conservation planning in bench-terraced steeplands. - Albert I. J. M. van Dijk; L. Adrian Bruijnzeel (Environ. Model. Softw., 2003)

Improving Curve Number Based Storm Runoff Estimates Using Soil Moisture Proxies. - Hylke E. Beck; Richard A. M. de Jeu; Jaap Schellekens; Albert I. J. M. van Dijk; L. Adrian Bruijnzeel (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2009)

Analysis of uncertainties in the inference of groundwater dynamics from gravity recovery and climate experiment observations over Australia. - Albert I. J. M. van Dijk; Russell S. Crosbie; Jorge L. Peña-Arancibia; Paul Tregoning; Simon McClusky (IGARSS, 2012)

Conceptual evaluation of continental land-surface model behaviour. - Luk Peeters; Russell S. Crosbie; Rebecca C. Doble; Albert I. J. M. van Dijk (Environ. Model. Softw., 2013)

How do Spatial Scale, Noise, and Reference Data affect Empirical Estimates of Error in ASAR-Derived 1 km Resolution Soil Moisture? - Marcela Doubková; Alena Dostálová; Albert I. J. M. van Dijk; Günter Blöschl; Wolfgang Wagner 001; Diego Fernández-Prieto (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Streamflow rating uncertainty: Characterisation and impacts on model calibration and performance. - Jorge L. Peña-Arancibia; Yongqiang Zhang 004; Daniel Edward Pagendam; Neil R. Viney; Julien Lerat; Albert I. J. M. van Dijk; Jai Vaze; Andrew J. Frost (Environ. Model. Softw., 2015)

Spatio-temporal evaluation of resolution enhancement for passive microwave soil moisture and vegetation optical depth. - A. I. Gevaert; Robert M. Parinussa; Luigi J. Renzullo; Albert I. J. M. van Dijk; Richard A. M. de Jeu (Int. J. Appl. Earth Obs. Geoinformation, 2016)

Deriving comprehensive forest structure information from mobile laser scanning observations using automated point cloud classification. - Suzanne M. Marselis; Marta Yebra; Tom Jovanovic; Albert I. J. M. van Dijk (Environ. Model. Softw., 2016)

Mapping Live Fuel Moisture Content and Flammability for Continental Australia Using Optical Remote Sensing. - Marta Yebra; Xingwen Quan; David Riaño 002; Pablo Rozas Larraondo; Albert I. J. M. van Dijk; Geoffrey J. Cary (IGARSS, 2018)

Influence of emissivity angular variation on land surface temperature retrieved using the generalized split-window algorithm. - Tian Hu; Hua Li 005; Biao Cao; Albert I. J. M. van Dijk; Luigi J. Renzullo; Zhihong Xu; Jun Zhou 001; Yongming Du; Qinhuo Liu (Int. J. Appl. Earth Obs. Geoinformation, 2019)

On agricultural drought monitoring in Australia using Himawari-8 geostationary thermal infrared observations. - Tian Hu; Albert I. J. M. van Dijk; Luigi J. Renzullo; Zhihong Xu; Jie He; Siyuan Tian; Jun Zhou 001; Hua Li 005 (Int. J. Appl. Earth Obs. Geoinformation, 2020)

Woody vegetation cover, height and biomass at 25-m resolution across Australia derived from multiple site, airborne and satellite observations. - Zhanmang Liao; Albert I. J. M. van Dijk; Binbin He; Pablo Rozas Larraondo; Peter F. Scarth (Int. J. Appl. Earth Obs. Geoinformation, 2020)

Improved Forest Biomass Estimation by Adding Time-Series Characteristics of Landsat Reflectance. - Xia Liu; Zhanmang Liao; Albert I. J. M. van Dijk; Binbin He; Yue Shi (IGARSS, 2021)

Global trends in vegetation seasonality in the GIMMS NDVI3g and their robustness. - Wentao Ye; Albert I. J. M. van Dijk; Alfredo Huete; Marta Yebra (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Continuous woody vegetation biomass estimation based on temporal modeling of Landsat data. - Zhanmang Liao; Xia Liu; Albert I. J. M. van Dijk; Chao Yue; Binbin He (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Comparing CNNs and Random Forests for Landsat Image Segmentation Trained on a Large Proxy Land Cover Dataset. - Tony Boston; Albert I. J. M. van Dijk; Pablo Rozas Larraondo; Richard Thackway (Remote. Sens., 2022)

Convolutional Neural Network Shows Greater Spatial and Temporal Stability in Multi-Annual Land Cover Mapping Than Pixel-Based Methods. - Tony Boston; Albert I. J. M. van Dijk; Richard Thackway (Remote. Sens., 2023)

U-Net Convolutional Neural Network for Mapping Natural Vegetation and Forest Types from Landsat Imagery in Southeastern Australia. - Tony Boston; Albert I. J. M. van Dijk; Richard Thackway (J. Imaging, 2024)