Publications
2024
41. Chakhvashvili, E., Machwitz, M., Antala, M., Rozenstein, O., Prikaziuk, E., Schlerf, M., ... & Rascher, U. (2024). Crop stress detection from UAVs: best practices and lessons learned for exploiting sensor synergies. Precision Agriculture, 1-29.
40. Kooistra, L., Berger, K., Brede, B., Graf, L. V., Aasen, H., Roujean, J. L., ... & Verrelst, J. (2023). Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity. Biogeosciences Discussions, 2023, 1-67.
2023
39. Rozenstein, O. (2023). Discussion on Friedman SP 2023 ‘Is the crop evapotranspiration rate a good surrogate for the recommended irrigation rate?’. Irrigation and Drainage, 72(4), 943-944.
38. Rozenstein, O., Cohen, Y., Alchanatis, V. et al. (2023) Data-driven agriculture and sustainable farming: friends or foes?. Precision Agriculture.
37. Rozenstein, O., Fine, L., Malachy, N., Richard, A., Pradalier, C., & Tanny, J. (2023). Data-driven estimation of actual evapotranspiration to support irrigation management: Testing two novel methods based on an unoccupied aerial vehicle and an artificial neural network. Agricultural Water Management, 283, 108317.
36. Gregoriy Kaplan, Lior Fine, Victor Lukyanov, Nitzan Malachy, Josef Tanny, Offer Rozenstein. (2022). Using Sentinel-1 and Sentinel-2 imagery for estimating cotton crop coefficient, height, and Leaf Area Index. Agricultural Water Management, 273, 108056.
2022
35. Berger, K., Machwitz, M., Kycko, M., Kefauver, S. C., Van Wittenberghe, S., Gerhards, M., ... & Schlerf, M. (2022). Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review. Remote Sensing of Environment, 280, 113198.
34. Bar-On, P., Yaakobi, A., Moran, U., Rozenstein, O., Kopler, I., & Klein, T. (2022). A montane species treeline is defined by both temperature and drought effects on growth season length. Tree Physiology, tpac070.
33. Itkin D, Bar-tal A, Crouvi O, Dor M, Erel R, Gross A, Levy GJ, Minz D, Rozenstein O, Yalin D., & Eshel G (2022). Soil priorities in Israel. Geoderma Regional, e00505.
32. Fine, L., Richard, A., Tanny, J., Pradalier, C., Rosa, R., & Rozenstein, O. (2022). Introducing State-of-the-Art Deep Learning Technique for Gap-Filling of Eddy Covariance Crop Evapotranspiration Data. Water, 14(5), 763.
31. Malachy, N., Zadak, I., & Rozenstein, O. (2022). Comparing Methods to Extract Crop Height and Estimate Crop Coefficient from UAV Imagery Using Structure from Motion. Remote Sensing, 14(4), 810.
2021
30. Weksler, S., Rozenstein, O., & Ben-Dor, E. (2021). Continuous seasonal monitoring of nitrogen and water content in lettuce (Lactuca sativa) using a dual phenomics system. Journal of experimental botany.
29. Gao, Y., Gao, M., Wang, L., & Rozenstein, O. (2021). Soil Moisture Retrieval over a Vegetation-Covered Area Using ALOS-2 L-Band Synthetic Aperture Radar Data. Remote Sensing, 13(19), 3894.
28. Kaplan, G., & Rozenstein, O. (2021). Spaceborne Estimation of Leaf Area Index in Cotton, Tomato, and Wheat Using Sentinel-2. Land, 10(5), 505.
27. Goldberg, K., Herrmann, I., Hochberg, U., & Rozenstein, O. (2021). Generating Up-to-Date Crop Maps Optimized for Sentinel-2 Imagery in Israel. Remote Sensing, 13(17), 3488.
26. Kaplan, G., Fine, L., Lukyanov, V., Manivasagam, V. S., Tanny, J., & Rozenstein, O. (2021). Normalizing the Local Incidence Angle in Sentinel-1 Imagery to Improve Leaf Area Index, Vegetation Height, and Crop Coefficient Estimations. Land, 10(7), 680.
25. Weksler, S., Rozenstein, O., Haish, N., Moshelion, M., Wallach, R., & Ben-Dor, E. (2021). Pepper Plants Leaf Spectral Reflectance Changes as a Result of Root Rot Damage. Remote Sensing, 13(5), 980.
24 .Yuval Sadeh, Xuan Zhu, David Dunkerley, Jeffrey P. Walker, Yuxi Zhang, Offer Rozenstein, V.S. Manivasagam, Karine Chenu. (2020). Fusion of Sentinel-2 and PlanetScope time-series data into daily 3 m surface reflectance and wheat LAI monitoring. International Journal of Applied Earth Observation and Geoinformation, 96, 102260.
23. Manivasagam, V. S., Sadeh, Y., Kaplan, G., Bonfil, D. J., & Rozenstein, O. (2021). Studying the Feasibility of Assimilating Sentinel-2 and PlanetScope Imagery into the SAFY Crop Model to Predict Within-Field Wheat Yield. Remote Sensing, 13(12), 2395.
22. Kaplan, G., Fine, L., Lukyanov, V., Manivasagam, V. S., Malachy, N., Tanny, J., & Rozenstein, O. (2021). Estimating Processing Tomato Water Consumption, Leaf Area Index, and Height Using Sentinel-2 and VENµS Imagery. Remote Sensing, 13(6), 1046.
21. Weksler, S., Rozenstein, O., Haish, N., Moshelion, M., Wallach, R., & Ben-Dor, E. (2021). Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting. Sensors, 21(3), 958.
2020
20 .Manivasagam, V. S & Rozenstein, O. (2020). Practices for upscaling crop simulation models from field scale to large regions. Computers and Electronics in Agriculture, 175, 105554.
19. Weksler, S., Rozenstein, O., Haish, N., Moshelion, M., Walach, R., & Ben-Dor, E. (2020). A hyperspectral-physiological phenomics system: Measuring diurnal transpiration rates and diurnal reflectance. Remote Sensing, 12(9), 1493.
2019
18. Lausch, A., Baade, J., Bannehr, L., Borg, E., Bumberger, J., Chabrilliat, S., ... & Schaepman, M. E. (2019). Linking remote sensing and geodiversity and their traits relevant to biodiversity—part I: soil characteristics. Remote sensing, 11(20), 2356
17. Rozenstein, O., Haymann, N., Kaplan, G., & Tanny, J. (2019). Validation of the cotton crop coefficient estimation model based on Sentinel-2 imagery and eddy covariance measurements. Agricultural Water Management, 223, 105715.
16. Manivasagam, V. S., Kaplan, G., & Rozenstein, O. (2019). Developing Transformation Functions for VENμS and Sentinel-2 Surface Reflectance over Israel. Remote Sensing, 11(14), 1710.
15. Panigada, C., Tagliabue, G., Zaady, E., Rozenstein, O., Garzonio, R., Di Mauro, B., ... & Rossini, M. (2019). A new approach for biocrust and vegetation monitoring in drylands using multi-temporal Sentinel-2 images. Progress in Physical Geography: Earth and Environment, 43(4), 496-520.
2018
14. Rozenstein, O., Haymann, N., Kaplan, G., & Tanny, J. (2018). Estimating cotton water consumption using a time series of Sentinel-2 imagery. Agricultural Water Management, 207, 44-52.
13. Weksler, S., Rozenstein, O., & Ben-Dor, E. (2018). Mapping Surface Quartz Content in Sand Dunes Covered by Biological Soil Crusts Using Airborne Hyperspectral Images in the Longwave Infrared Region. Minerals, 8(8), 318.
2017
12. Rozenstein, O., Puckrin, E., & Adamowski, J. (2017). Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry. Waste Management, 68, 38-44.
11. Rozenstein, O., & Adamowski, J. (2017). A review of progress in identifying and characterizing biocrusts using proximal and remote sensing. International journal of applied earth observation and geoinformation, 57, 245-255.
10. Rozenstein, O., & Adamowski, J. (2017). Linking Spaceborne and Ground Observations of Autumn Foliage Senescence in Southern Québec, Canada. Remote Sensing, 9(6), 630.
2016
9. Rozenstein, O., Siegal, Z., Blumberg, D. G., & Adamowski, J. (2016). Investigating the backscatter contrast anomaly in synthetic aperture radar (SAR) imagery of the dunes along the Israel–Egypt border. International journal of applied earth observation and geoinformation, 46, 13-21.
2015
8. Rozenstein, O., Agam, N., Serio, C., Masiello, G., Venafra, S., Achal, S., ... & Karnieli, A. (2015). Diurnal emissivity dynamics in bare versus biocrusted sand dunes. Science of the Total Environment, 506, 422-429.
7. Rozenstein, O., Paz-Kagan, T., Salbach, C., & Karnieli, A. (2015). Comparing the Effect of Preprocessing Transformations on Methods of Land-Use Classification Derived From Spectral Soil Measurements. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(8), 2393-2404.
6. Rozenstein, O., & Karnieli, A. (2015). Identification and characterization of Biological Soil Crusts in a sand dune desert environment across Israel–Egypt border using LWIR emittance spectroscopy. Journal of Arid Environments, 112, 75-86.
2014
5. Rozenstein, O., Zaady, E., Katra, I., Karnieli, A., Adamowski, J., & Yizhaq, H. (2014). The effect of sand grain size on the development of cyanobacterial biocrusts. Aeolian Research, 15, 217-226.
4. Rozenstein, O., Devir, A., & Karnieli, A. (2014). In-field absolute calibration of ground and airborne VIS-NIR-SWIR hyperspectral point spectrometers. Remote Sensing, 6(2), 1158-1170.
3. Rozenstein, O., Qin, Z., Derimian, Y., & Karnieli, A. (2014). Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm. Sensors, 14(4), 5768-5780.
2012
2. Roskin, J., Blumberg, D. G., Porat, N., Tsoar, H., & Rozenstein, O. (2012). Do dune sands redden with age? The case of the northwestern Negev dunefield, Israel. Aeolian Research, 5, 63-75.
2011
1. Rozenstein, O., & Karnieli, A. (2011). Comparison of methods for land-use classification incorporating remote sensing and GIS inputs. Applied Geography, 31(2), 533-544.