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בחר הכל

החוג למדעי כדור הארץ

גיאופיזיקה וגיאולוגיה

מדעי האטמוספירה

מדעים פלנטריים

סמינר בחוג לגיאופיזיקה

Dr. Anna Brook, Uuniversity of Haifa

12 ביוני 2017, 11:00 
בניין שנקר, אולם הולצבלט 007 
סמינר בחוג לגיאופיזיקה

Title: 

INLAND NOTCHES MICROTOPOGRAPHY 

Abstract:

Inland notches are well known phenomenon in Israel and can be found mostly along the mountainous backbone, developed in hard limestone or dolomite rocks within the Mediterranean climate zone and up to the desert fringe. LiDAR technology presents an opportunity to study the fine scale rock surface within the notch and its texture patterns. Micro-topography plays an important role for modelling geomorphology dynamics, resulting in improved estimates for micro stream lines network and topographic erosion as well as mineral accumulation or deposition. Clearly, dissolution occurs whenever rock and solvent meet; thus water and moisture’s crucial role in the decay of carbonate rocks results in texture and roughness variability. Study aims is to generate high resolution normalized DEM models using a terrestrial LiDAR, redefining the texture and roughness within the notch while assessing weathering processes caused by water. Plan curvature is the second derivative of slope taken perpendicular to its direction. It influences convergence and divergence of flow and it emphasizes the ridges and valleys across the surface. Concaved classified areas were tested against positive planar curvature areas to distinguish them as unique areas based on their texture co-occurrence measures (GLCM). Overall negative curvature pixels show poor separability, in both TD and JM, while classes of curvature degree describe a positive trend showing medium to high concavity as unique areas. Study aims to link classified areas as the basic micro infrastructure for water flow, potential runoff flow and further accumulation of minerals. On the other hand, positive values of Plan curvature present the convexity of rock surface to imply diverging flow, thus describing the watershed line within the micro-topography. GLCM texture measures also map distinct areas within the notch. Middle section of the notch has uniform texture neighborhood with relatively low mean elevation values (high values for homogeneity and energy). Bottom cavity of notch reveals a more chaotic texture, highlighting the spatial disorder with relatively high mean values. Entropy calculates how random the roughness values are, and as such, high values of this measure, mainly at the cavity’s bottom, suggest a potentially rapid erosion or disposition dynamics.
Point measurements in notch were taken horizontally and vertically using ASD Fieldspec pro (Analytical Spectral Devices, Boulder, CO) with a spectral range of 0.35-2.5 µm, and spectral resolution of 10nm2. Spectral measurements taken in situ were reconstructed as an N dimensional 40x42 matrix. Each pixel within the matrix represent 10 samples mean with N=198 bands. Measurements taken were classified and constructed to spectral endmembers representing the notch's cavity. Classification of endmembers was made with the manipulation of MNF and PPI to extract final cavity’s endmembers. spectral features were compared with various well characterized resampled mineral spectral libraries for identification of the forming minerals

 

 

Title:

Spectroscopy and Hyperspectral Remote Sensing as Practical Tools for Quantitative Mapping of Charcoal Dust near Power Station 

Abstract:

The main task of environmental and geoscience applications are efficient and accurate quantitative classification of earth surfaces and spatial phenomena. In the past decade, there has been a significant interest in employing unmixing approaches in order to retrieve accurate quantitative information latent in hyperspectral imagery data. This study suggests sparse unmixing technique to extract and identify charcoal dust settled over/upon green vegetation canopy using hyperspectral airborne data near power station. It is a known fact that atmospheric dust transports a variety of chemicals, some of which pose a risk to the ecosystem and human health.  
Small amounts of particulate pollution that may carry a signature of a forthcoming environmental hazard are of key interest when considering the effects of pollution. According to the most basic distribution dynamics, dust consists of suspended particulate matter in a fine state of subdivision that are raised and carried by wind. In this context, it is increasingly important to first, understand the distribution dynamics of pollutants, and subsequently develop dedicated tools and measures to control and monitor pollutants in the free environment. The earliest effect of settled polluted dust particles is not always reflected through poor conditions of vegetation or soils, or any visible damages. In most of the cases, it has a quite long accumulation process that graduates from a polluted condition to long-term environmental hazard. 
This study suggests that the sensitivity of sparse unmixing techniques provides an ideal approach to extract and identify dust settled over/upon green vegetation canopy using both in situ spectroscopy and imagery hyperspectral airborne data. The developed approach is applied by the following stages: 1) acquire spectral data and preprocessed it, 2) apply prior trained unmixing using hierarchical NMF (Non-negative Matrix Factorization) approach, first define mixture between vegetation and settled dust, after using only dust endmember define the charcoal fraction within it, 3) apply prior developed PLSR model to quantify the detected settled charcoal dust. 
The study showed that in certain compression tasks content-adapted sparse representation is provided by state-of-the-art solutions. The NMF algorithm estimates endmembers that are used to remove spurious information. If computationally feasible, it should include interaction terms to make the model more flexible. The optimal NMF algorithms, such as Alternating Least-Square (ALS) and Lin’s Projected Gradien (LPG), are assumed to be the simplest methods that achieve the minimum error on the test set. 
The suggested trained and validated PLSR model was developed at laboratory using spectra across MIR (FTIR reflectance spectra) and NIR regions and XRD analysis. The obtained RMSE was satisfying for both spectral regions. Thus, it was concluded that field spectroscopy across NIR region can be used for this purpose, and it can provide fully quantitative measures of settle charcoal dust. 
Nowadays this approach (both spectrometer and algorithm) has been accepted as a practical operational tool for environmental monitoring near power station Orot Rabin in Hadera and will be used by the Sharon-Carmel 

 

 

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