Itamar Lensky directs the Remote Sensing and Geographic Information Systems laboratory. His research interests are in land, sea, and air surface temperatures; evaporation and evapotranspiration, the effect of atmospheric circulation in different scales on these surface properties, and applications in agriculture, and epidemiology

Research Projects:

Green smart city

In this project, we are using precision agriculture technologies in green high-rise building walls in order to examine vertical greenery systems (VGS) as a nature-based solution for environmental problems in densely populated cities: the urban heat island, air pollution, noise, and stress. Four colleagues from Bar-Ilan, three from ARO, and one from the Hebrew University of Jerusalem are cooperating on this research. Our aims are to monitor the VGS (using thermal and hyperspectral cameras), and the environment (local climate: temperature, radiation, humidity, wind, and carbon and water fluxes), in order to assess the impact of the VGS on the ambient urban environment (and vice versa); provide health impact assessment of VGS, and explore VGS economic benefits. This project is a cooperation with Nanjing University funded by the China & Israel ministries of science and technology, and the equipment by the Israel Science Foundation (institutional equipment).

Clouds
My interest in clouds includes remote sensing of cloud microphysics using multispectral satellite data (Lensky and Rosenfeld, 1997), retrieval of precipitation formation processes in the daytime (Rosenfeld and Lensky, 1998) and nighttime (Lensky and Rosenfeld, 2003a; Lensky and Rosenfeld, 2003b), cloud aerosols interactions (Lensky and Drori, 2007), and cloud phase (Drori and Lensky, 2010).

I developed a software that uses data from the 11 spectral bands of the European geostationary satellite Meteosat Second Generation (MSG) for qualitative (RGB display) and quantitative analysis of clouds and aerosols and the interaction between them (Lensky and Rosenfeld, 2008). This tool was used to verify one of the assumptions standing at the base of the method for retrieval of precipitation formation processes (Lensky and Rosenfeld, 2006), and is also used by the training department of EUMETSAT.

Epidemiology

I use time series analysis of satellite data for research involving the epidemiology of vector-borne diseases (Morag et al. 2012; Steinman et al. 2012).

The Dead Sea.
The water level of the Dead Sea is declining by more than 1 m/yr, with resulting sinkholes and deteriorated nearby infrastructure. At the same time, the level of the evaporation pond of the Dead Sea Works is rising, endangering nearby hotels. These motivated different national and international projects. My research in the Dead Sea includes the Characterization of the diurnal and seasonal cycles of the Dead Sea surface temperature (Nehorai et al. 2009). The processes occurring in the skin layer of the Dead Sea (~10 mm) (Nehorai et al. 2013).
Suspended matter in the Dead Sea: sources, transport, and dynamics. Suspended mater affects the appearance of the Dead Sea and the quality of brine pumped into evaporation ponds (Nehorai et al. 2013). These studies were conducted together with Nadav Lensky (GSI), and were funded by the World Bank: “Red Sea-Dead Sea Water Conveyance Study Program”; The Dead Sea preservation government company: “Alternative dumping sites in the Dead Sea for harvested salt from pond 5”, and the Dead Sea Works: “The expected quality of the Dead Sea brine expected to be pumped in the planned pumping station P9”.

Agriculture.
Field crops, fruit trees, and arthropods (pests in agriculture and transmitters of diseases), are sensitive to ambient temperature (Lensky and Dayan, 2011). Arthropods are sensitive to several environmental variables such as land surface temperature, vegetation, and soil moisture. I use time series of satellite data and field data to study the dynamics of pests in order to predict damage in crops (with Yafit Cohen, ARO), the transmission of disease in sheep and cattle (with Eyal Klement, HUJI). I use time series analysis of vegetation index to assess the relative contribution of perennial and annual vegetation in arid regions and the effects of grazing and tiling on soil fertility in arid regions (Helman et al, 2014). Moshe Blum in his Ph.D. (co-supervised with David Nestel, ARO), used satellite data to retrieve Olive tree canopy temperature (Blum et al. 2013) and used it as input for assessing the Olive fly population (Blum et al. 2015).

Atmospheric processes at different scales
I am studying with Uri Dayan (HUJI) the factors that affect the land surface temperature in different spatial and temporal scales: Topo-climate (Lensky and Dayan, 2011), Mesoscale: sea breeze (Lensky and Dayan, 2012), and synoptic scale. Insights that emerge from this research have immediate applications in the fields mentioned above. In addition, this study may shed light on the interaction between atmospheric processes in different scales, which is one of the key factors to uncertainty regarding forecasts of climate models in the coming decades.

I also use time series analysis of satellite data to identify clouds and aerosols. So far, spectral and morphological information was used to delineate clouds. Now I develop cloud cover detection using these methods. The Israel Meteorological Service is funding a project that implements these methods for operational use.