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Chlorophyll distribution in Haifa Bay was estimated in a period of very high chlorophyll concentrations (up to 70 mg/m3) using remotely sensed data. Radiometric measurements with spectral resolution of 2 nm in the range from 400 to 850 nm, were taken simultaneously with samples for chlorophyll concentration, turbidity and Secchi disk transparency. Prominent features of the reflectance spectra were a wide minimum from 420 to 500 nm, a maximum at 550-570 nm, a minimum at 676 nm and a maximum reflectance showed near 700 nm. High spectral resolution data were used for the selection of the most suitable spectral bands for remote estimating of chlorophyll concentration. The magnitude and position of the peak near 700 nm were highly correlated with chlorophyll concentration. The reflectance height at 690 nm above the baseline from 670 to 850 nm and area above the baseline were used as sensitive indicators of chlorophyll concentration. The best model enabled estimation of chlorophyll concentration with an error of less than 4.3 mg/m3. For the purpose of chlorophyll mapping in Haifa Bay, the use of three relatively narrow spectral bands was sufficient. Radiometric data were also used to simulate radiances in the channels of TM Landsat and to find the algorithm for chlorophyll assessment. The ratios TM3/TM1 and (TM2-TM3)/TM1 were used and enable chlorophyll estimation with an error of less than 8 mg/m3.

This paper proposes and explores an approach in which robotics projects of novice engineering students focus on development of learning robots. We implemented a reinforcement learning scenario in which a humanoid robot learns to lift a weight of unknown mass through autonomous trial-and-error search. To expedite the process, trials of the physical robot are substituted by simulations with its virtual twin. The optimal parameters of the robot posture for executing the weightlifting task, found by analysis of the virtual trials, are transmitted to the robot through internet communication. The approach exposes students to the concepts and technologies of machine learning, parametric design, digital prototyping and simulation, connectivity and internet of things. Pilot implementation of the approach indicates its potential for teaching freshman and HS students, and for teacher education.

Geostatistical tools were used to estimate spatial relations between wheat yield and soil parameters under organic farming field conditions. Thematic maps of each factor were created as raster images in R software using kriging. The Geographic Resources Analysis Support System (GRASS) calculated the principal component analysis raster images for soil parameters and yield. The correlation between the raster arising from the PC1 of soil and yield parameters showed high linear correlation (r = 0.75) and explained 48.50% of the data variance. The data show that durum wheat yield is strongly affected by soil parameter variability, and thus, the average production can be substantially lower than its potential. Soil water content was the limiting factor to grain yield and not nitrate as in other similar studies. The use of precision agriculture tools helped reduce the level of complexity between the measured parameters by the grouping of several parameters and demonstrating that precision agriculture tools can be applied in small organic fields, reducing costs and increasing wheat yield. Consequently, site-specific applications could be expected to improve the yield without increasing excessively the cost for farmers and enhance environmental and economic benefits. Foundation for Science and Technology (Fundacao para a Ciencia e a Tecnologia), Portugal [SFRH/BD/8303/2002]; Research Center of Spatial and Organizational Dynamics (CIEO); Ministery of Science, Culture and Sport, Israel; Bundesmenisterium fuer Bildung and Forschung (BMBF)

Inference and decision making under uncertainty are essential in numerous robotics problems. In recent years, the similarities between inference and control triggered much work, from developing unified computational frameworks to pondering about the duality between the two. In spite of the aforementioned efforts, inference and control, as well as inference and belief space planning (BSP) are still treated as two separate processes. In this paper we propose a novel approach that utilizes the similarities between inference and BSP and make the key observation that inference can be efficiently updated using the precursory planning stage, thus paving the way towards a joint inference and BSP paradigm. We develop four different methods that implement our novel approach under simplifying assumptions and validate them in the context of autonomous navigation in unknown environment. Results indicate that not only our methods improve running time by at least two orders of magnitude, compared to iSAM2 paradigm, they also found to be less sensitive to state dimensionality and loop closures.

Monitoring cloud droplet effective radius (re) is of great significance for studying aerosol-cloud interactions (ACI). Passive satellite retrieval, e.g., MODIS (Moderate Resolution Imaging Spectroradiometer), requires sunlight. This requirement prompted developing re retrieval using active sensors, e.g., CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization). Given the highest sensitivity of vertically homogeneous clouds to aerosols that feed to cloud base, here CALIOP profile measurements were used for the first time to quantify cloud vertical homogeneity and estimate cloud re during both day and night. Comparison using simultaneous Aqua-MODIS measurements demonstrates that CALIOP retrieval has the highest accuracy for vertically homogeneous clouds, with R2 (MAE, RMSE) of 0.72 (1.75 µm, 2.25 µm), while the accuracy is lowest for non-homogeneous clouds, with R2 (MAE, RMSE) of 0.60 (2.90 µm, 3.70 µm). The improved re retrieval in vertically homogeneous clouds provides a basis for possible breakthrough insights in ACI by CALIOP since re in such clouds reflects most directly aerosol effects on cloud properties. Global day-night maps of cloud vertical homogeneity and respective re are presented.

Low temperature energy sources for protected cropping include geothermal waters, waste heat from Industry, and trapped sunshine; application depends on the recovery of heat from circulating warmed water, either via the soil in which the plants are growing or via the air in the greenhouse. Soil warming pipes and ‘water-curtain’ systems of space-heating have shown promise, but heat storage, either for short periods or longer, remains a problem common to all such schemes.

The bio-optical relationships between inherent and apparent optical properties, and between optical properties and phytoplankton pigment concentration (C) averaged in a layer (ΔZ), were derived from analysis of data collected during the period 1996–1998 in the Gulf of Aqaba (Eilat). Parametrization of these relationships was based on radiative transfer theory, Gershun's equation, minimization of model errors by least-square fitting, and on known optical models relating underwater remote sensed reflectance (R rsw) with the ratio of backscattering (b b) to vertical attenuation coefficient (K d) [or to absorption coefficient (a)]. These relationships explain a frequently used form of remote sensing algorithms for C estimation using ratio of water-leaving radiances measured at two or more wavelengths (λ). In this study, the possibility of using for this purpose a single wavelength in the blue range (λ=443 nm) within the framework of in situ and remote sensing algorithms for Case 1 waters was assessed.

In settler colonial settings, agriculture is a means of reclaiming territorial sovereignty and indigenous identity. Turning attention to the Jewish settlers in the West Bank and their multiple uses and abuses of organic farming, this article explores epistemic and political spatial operations on the colonial frontier. Applying a relational conceptualization of three spatial modalities—soil, territory, and land—we explore the ways in which these modalities serve as political apparatuses: Soil designates the romantic perception of cultivable space, territory is concerned with borders and political sovereignty, and land is seen as a space of economic value and as a means of production. While agriculture is a well-known instrument of expansion and dispossession, organic farming contributes to the colonial operation by binding together affective attachment to the place, and new economic singularity in relation to environmental and ethical claims. We argue that organic farming practices converge claims for local authenticity, spatial appropriation, and high economic values that are embedded in what we term the colonial quality turn. Ultimately, organic farming in the West Bank normalizes the inherent violence of the colonial project and strengthens the settlers’ claim for political privilege.