Remote Sensing Lab

Image acquired by the VENµS satellite, 2018, over the Zin Valley, Negev Desert, Israel


Adar, S., Sternberg, M., Paz-Kagan, T., Henkin, Z., Dovrat, G., Zaady, E., & Argaman, E. (2022). Estimation of aboveground biomass production using an unmanned aerial vehicle (UAV) and VENμS satellite imagery in Mediterranean and semiarid rangelands. Remote Sensing Applications: Society and Environment26, [100753].

Bessin Z, Dedieu J-P, Arnaud Y, Wagnon P, Brun F, Esteves M, Perry B, Matthews T. Processing of VENµS Images of High Mountains: A Case Study for Cryospheric and Hydro-Climatic Applications in the Everest Region (Nepal). Remote Sensing. 2022; 14(5):1098.

Salvoldi, M., Tubul, Y., Karnieli, A. and Herrmann, I. VENµS-derived NDVI and REIP at different view azimuth angles. Remote Sensing.  14, 184.


Bonfil DJ, Michael Y, Shiff S, Lensky IM. Optimizing Top Dressing Nitrogen Fertilization Using VENμS and Sentinel-2 L1 Data. Remote Sensing. 2021; 13(19):3934.

Kaplan G, Fine L, Lukyanov V, Manivasagam VS, Malachy N, Tanny J, Rozenstein O. Estimating Processing Tomato Water Consumption, Leaf Area Index, and Height Using Sentinel-2 and VENµS Imagery. Remote Sensing. 2021; 13(6):1046.

Li, Longwei ; Li, Nan ; Zang, Zhuo ; Lu, Dengsheng ; Wang, Guangxing ; Wang, Ni. 2021; Examining phenological variation of on-year and off-year bamboo forests based on the vegetation and environment monitoring on a New Micro- Satellite (VENμS) time-series data.
International journal of remote sensing,  Vol.42 (6), p.2203-2219

Lacerda LN, Cohen Y, Snider J, Huryna H, Liakos V, Vellidis G. Field Scale Assessment of the TsHARP Technique for Thermal Sharpening of MODIS Satellite Images Using VENµS and Sentinel-2-Derived NDVI. Remote Sensing. 2021; 13(6):1155.

Elbaz S, Sheffer E, Lensky IM, Levin N. The Impacts of Spatial Resolution, Viewing Angle, and Spectral Vegetation Indices on the Quantification of Woody Mediterranean Species Seasonality Using Remote Sensing. Remote Sensing. 2021; 13(10):1958.

Granero-Belinchon, Carlos & Adeline, Karine & Briottet, Xavier. (2021). Impact of the number of dates and their sampling on a NDVI time series reconstruction methodology to monitor urban trees with Ven μ s satellite. International Journal of Applied Earth Observation and Geoinformation. 95. 102257. 10.1016/j.jag.2020.102257.

Baba MW, Gascoin S, Hagolle O, Bourgeois E, Desjardins C, Dedieu G. Evaluation of Methods for Mapping the Snow Cover Area at High Spatio-Temporal Resolution with VENμS. Remote Sensing. 2020; 12(18):3058.

הרמן, א., שדה, ר., אבנרי, א., לאטי, ר., עבו, ש., בונפיל, ד., פלג, צ., 2020. שימוש במידע ספקטרלי להערכת פוטנציאל מים ויבול של חמצה. כנס דיווחי מחקרים בגידולי פלחה בקיץ

Erwin W.J. Bergsma, E. W.J. Bergsma, Rafael Almar, R. Almar, Amandine Rolland, A. Rolland, Renaud Binet, R. Binet, Katherine L. Brodie, K. L. Brodie, & A. Spicer Bak, A. Spicer Bak. (2021). Coastal morphology from space: A showcase of monitoring the topography-bathymetry continuum. Remote sensing of environment, 261, 112469. doi: 10.1016/j.rse.2021.112469

Altena, B. and Kääb, A.: Satellite remote sensing of ice cliff migration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5057,, 2020

Vladislav, D., Svoray, T., Stavi, T., and Yizhaq, H (2020) Using LANDSAT 8 and VENμS Data to Study the Effect of Geodiversity on Soil Moisture Dynamics in a Semiarid Shrubland. Remote Sensing, 12, 3377. DOI: doi:10.3390/rs12203377

Gao, F., Anderson, M.C. and Hively, D. (2020) Detecting Cover Crop End-Of-Season Using VENµS and Sentinel-2 Satellite Imagery. Remote Sensing, 12, 3390. doi:10.3390/rs12213524

French, N.A., Hunsaker, J.D., Sanchez, C.A,., Saber, M., Gonzalez, J.R. and Anderson, R. 2020. Satellite-based NDVI crop coefficients and evapotranspiration with eddy covariance validation for multiple durum wheat fields in the US Southwest. Agricultural Water Management.239, 106266.

Upreti, D., Pignatti, S., Pascucci, S., Tolomio, M., Huang, W. and Casa, R. 2020. Bayesian Calibration of the Aquacrop‐OS Model for Durum Wheat by Assimilation of Canopy Cover Retrieved from VENμS Satellite Data. Remote Sensing.12, 2666. doi:10.3390/rs12162666

Bar-Massada, A. and Sviri, A. 2020. Utilizing Vegetation and Environmental New Micro Spacecraft (VENµS) Data to Estimate Live Fuel Moisture Content in Israel’s Mediterranean Ecosystems. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING.13, 3204.

Liao, C., Wang, J., Xie, Q., Al Baz, A., Huang, X., Shang, J. and He, Y. 2020. Synergistic Use of Multi-Temporal RADARSAT-2 and VENS Data for Crop Classification Based on 1D Convolutional Neural Network. Remote Sensing.12, 832. doi:10.3390/rs12050832

Gao, F., Anderson, M., Daughtry, C., Karnieli, A., Hively, D. and Kustas, W. 2020. A within-season approach for detecting early growth stages in corn and soybean using high temporal and spatial resolution imagery. Remote Sensing of Environment.242, 111752.

Gao, F., Anderson, M., Daughtry, C., Karnieli, A., Hively, D. and Kustas, W. 2020. A within-season approach for detecting early growth stages in corn and soybean using high temporal and spatial resolution imagery. Remote Sensing of Environment.242, 111752.

Chen, J., Ouyang, Z., John, R., Henebry, G. M., Groisman, P., Karnieli, A., Kussainova, M., Amartuvshin, A., Tulobaev, A., Isabaevich, E. T., Crank, C., Kadhim, A., Qi, J. and Gutman. G. 2020. Social-Ecological Systems across the Asian Drylands Belt (ADB). In Gutman et al. (Eds.) Land-Cover and Land-Use Change in Drylands of EurasiaPeople, Societies and Ecosystems. 191-225. Springer Nature, Switzerland AG 2000,

Manivasagam, V.S., Kaplan, G. and Rozenstein, O. 2019. Developing transformation functions for VENµS and Sentinel-2 surface reflectance over IsraelRemote Sening, 11, 1710; doi:10.3390/rs11141710

 Claverie, M., V. Demarez, B. Duchemin, O. Hagolle, D. Ducrot, C. Marais-Sicre, J. F. Dejoux, M. Huc, P. Keravec, P. Beziat, R. Fieuzal, E. Ceschia and G. Dedieu (2012). Maize and sunflower biomass estimation in southwest France using high spatial and temporal resolution remote sensing data. Remote Sensing of Environment, 124, 844-857

Herrmann, I., Pimstein, A., Karnieli, A., Cohen, Y., Alchanatis, V. and Bonfil, D.J. 2011. LAI assessment of wheat and potato crops by VENµS and Sentinel-2 bands. Remote Sensing of the Environment115, 2141-2151.

Hagolle, O., M. Huc, D. V. Pascual and G. Dedieu (2010). “A multi-temporal method for cloud detection, applied to FORMOSAT-2, Venµs, LANDSAT and SENTINEL-2 images.” Remote Sensing of Environment 114, 1747-1755.

Hagolle, O., Dedieu, G., Mougenot, B., Debaecker, V., Duchemin, B., and A. Meygret (2008). “Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: application to Formosat-2 images”. Remote Sensing of Environment, 112, pp.1689-1701.

Herscovitz, J. and Karnieli, A. VENµS program: broad and new horizons for super-spectral imaging and electric propulsion missions for a small satellite. In: 22nd Annual AIAA/USU Conference on Small Satellites: Small Satellites – Big Business, held in Logan, Colorado, 10-13 August 2008.

Herscovitz, J., & Karnieli, A. (2008). VENμS Program: Broad and New Horizons for Super-Spectral Imaging and Electric Propulsion Missions for a Small Satellite.

Dedier, G., Karnieli, A., Hagolle, O., Jeanjean, H., Cabot, F., Ferrier, P. and Yaniv, Y. VENμS: A joint French Israeli earth observation scientific mission with high spatial and temporal resolution capabilities. In: J.A. Sobrino (Ed.) Proceedings of the 2nd International Symposium on Recent Advances in Qualitative Remote Sensing, held in Torrent (Valencia), Spain, 25-29 September, 2006. pp. 517-521.

Updated 20 December 2014

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