Predicting Diel,Diurnal and Nocturnal Dynamics of Dissolved Oxygen and Chlorophyll‐a Using Regression Models and Neural Networks

Human‐induced and natural interruptions with continuous streams of observational data necessitate the development of gap‐filling and prediction strategies towards better understanding, monitoring and management of aquatic systems. This study quantified the efficacy of multiple non‐linear regression (MNLR) versus artificial neural network (ANN) models as well as the temporal partitioning of diurnal versus nocturnal data for the predictions of chlorophyll‐a (chl‐a) and dissolved oxygen (DO) dynamics. The temporal partitioning increased the predictive performances of the best MNLR models of diurnal DO by 45% and nocturnal DO by 4%, relative to the best diel MNLR model of diel DO ($r_{{\rm adj}}^{2} = 68.8\%$ ). The ANN‐based predictions had a higher predictive power than the MNLR‐based predictions for both chl‐a and DO except for diurnal DO dynamics. The best ANNs based on independent validations were multilayer perceptron (MLP) for diel chl‐a, generalized feedforward (GFF) for diurnal and nocturnal chl‐a, MLP for diel DO, GFF for diurnal DO, and MLP for nocturnal DO.     

Geochemical characteristics and age of metamorphic sole rocks within a Neotethyan ophiolitic mélange from Konya region (central southern Turkey)

Palaeo- and Neo-Tethyan-related magmatic and metamorphic units crop out in Konya region in the south central Anatolia. The Neotethyan assemblage is characterized by mélange and ophiolitic units of Late Cretaceous age. They tectonically overlie the Middle Triassic–Upper Cretaceous neritic to pelagic carbonates of the Tauride platform. The metamorphic sole rocks within the Konya mélange crop out as thin slices beneath the sheared serpentinites and harzburgites. The rock types in the metamorphic sole are amphibolite, epidote-amphibolite, garnet-amphibole schist, plagioclase-amphibole schist, plagioclase-epidote-amphibole schist and quartz-amphibole schist. The geochemistry of the metamorphic sole rocks suggests that they were derived from the alkaline (seamount) and tholeiitic (E-MORB, IAT and boninitic type) magmatic rocks from the upper part of the Neotethyan oceanic crust. Four samples from the amphibolitic rocks yielded ⁴⁰Ar/³⁹Ar isotopic ages, ranging from 87.04 ± .36 Ma to 84.66 ± .30 Ma. Comparison of geochemistry and geochronology for the amphibolitic rocks suggests that the alkaline amphibolite (seamount-type) cooled below 510 ± 25 °C at 87 Ma whereas the tholeiitic amphibolites at 85 Ma during intraoceanic thrusting/subduction. When all the evidence combined together, the intraoceanic subduction initiated in the vicinity of an off-axis plume or a plume-centered spreading ridge in the Inner Tauride Ocean at 87 Ma. During the later stage of the steady-state subduction, the E-MORB volcanics on the top of the down-going slab and the arc-type basalts (IAT/boninitic) detached from the leading edge of the overriding plate, entered the subduction zone after ~2 my and metamorphosed to amphibolite facies in the Inner Tauride Ocean. Duration of the intraoceanic detachment (~87 Ma) and ophiolite emplacement onto the Tauride-Anatolide Platform (Tav?anl? Zone), followed by subsequent HP/LT metamorphism (~82 Ma) spanned ~5 my in the western part of the Inner Tauride Ocean.     

Modeling and Validating Long‐Term Dynamics of Diel Dissolved Oxygen with Particular Reference to pH in a Temperate Shallow Lake (Turkey)

Long‐term monitoring of changes in dissolved oxygen (DO) and pH is of great importance to quantifying aquatic ecosystem metabolism, particularly for lakes under the changing global environment. During 173 days, diel DO cycles were measured in situ along with the main driving variables of pH, wind speed (WS), and net solar radiation (Rn) in a temperate shallow lake. Best‐fit multiple non‐linear regression (MNLR) models of diel DO time series were built and validated on a monthly basis, with R² values ranging from 42.4% in September to 95.4% in November for validation. The strong relationship between diel DO and pH (r = 0.6) appeared to be related to the patterns of ecosystem productivity and respiration, and sensitivity of decomposing bacteria to changes in pH. pH‐driven lake metabolism appears to have significant implications for diel and seasonal lake metabolism in a changing global environment.     

Automated Detection of 3D Roof Planes from Lidar Data

The purpose of this study is to derive vectoral 3D roof planes from the LIDAR point cloud of the detected buildings. For segmentation of the LIDAR point cloud, the RANSAC algorithm has been used. Because the RANSAC algorithm is sensitive to the used parameters, and results in over- or under-segmentation of the clusters, a refinement method has been proposed. The detection of roof planes has been improved with use of the refinement method. Therefore, similar plane surfaces have been combined, followed by the region-growing algorithm, to split the under-segmented plane surfaces. The digitization of the roof boundaries is performed using the alpha-shapes algorithm, followed by line fitting to generalize the roof edges. The quality assessment has been done using the reference vector dataset with comparison using four different criteria.     

Automatic extraction of sparse trees from high-resolution ortho-images

Obtaining information about tree species distribution in agricultural lands is a topic of interest for various applications, such as tree inventory, forest management, agricultural land management, crop estimation, etc. This information can be derived from images obtained from modern remote sensing technology, which is the most economical way as compare to field surveys covering large geographic areas. Therefore, in this study, a new method is proposed for extraction and counting of sparse and regular distributed individual pistachio trees from agricultural areas on large scale from high-resolution digital ortho-photo maps, which were obtained using an airborne sensor (Ultracam-X). The input images were first smoothed by applying Gaussian filter to reduce the impact of noise. Normalized difference vegetation indices (NDVI) were then derived to obtain vegetation areas followed by Otsu’s global thresholding algorithm to obtain candidate tree areas. Further, connected component (CC) analysis was applied to segregate each object. Morphological processing was performed to fill holes within tree objects and get smooth contours, which were obtained by using the Moore-neighbor tracing method (MNTM) for each CC, while geometrical constraints were applied to undermine possible non-tree elements from output image. To further improve the segmentation results for sparse trees, a new method was applied, called quadratic local analysis (QLA). QLA helped to segment the trees, which were missed by the Otsu method due to low contrast and resulted in improved accuracy (3–6%). The obtained results were compared with well-known support vector machine (SVM) classifier. Proposed method produced slightly better results (1–5%) than SVM for extraction of pistachio trees and obtained accuracy for QLA and SVM were 96 and 91% for region 1, while 91 and 90% for region 2 respectively.     

Geochemistry and zircon U–Pb geochronology constrains late cretaceous plagiogranite intrusions in Mersin ophiolite complex (southern Turkey).

In this study, LA-ICP-MS U–Pb zircon dating were used to determine the age of the newly discovered plagiogranite suite intruding gabbro and volcanic units of Mersin ophiolites from the Inner Tauride Belt. Obtained U–Pb zircon ages from the plagiogranite yielded crystallization ages of 93.0?±?1.5 to 94.2?±?2.4 Ma (Turonian–Cenomanian) supporting the idea of Late Cretaceous active subduction factory in the Tauride Suture Zone. The plagiogranites are mainly granodioritic, and tonalitic in composition, and contain mafic microgranular enclaves (MME) ranging from 10 to 45 cm in size. The plagiogranites are geochemically defined by low K₂O (0.02–1.03 wt%) and TiO₂ (0.17–1.88 wt%) and comparatively high Na₂O (2.3–10.2 wt%) and SiO₂ (70–78 wt%) compositions together with depletion in Ti, Ta, and Nb. The tectonomagmatic discrimination diagrams, trace, and REE-normalized multi-element patterns indicate that the plagiogranites are distinctive calc-alkaline, I-type volcanic arc granites. Plagiogranites are furthermore characterized by the diffuse presence of isotropic pseudomorphic growth of secondary calcic-amphibole (edenite and actinolite) over a pristine not preserved Ca-inosilicate. Inverse geothermobarometry models indicate a secondary amphibole genesis at ca. 600 °C and 1.5–1.7 kbar, suggesting HT-metasomatism affecting the already intruded plagiogranites. While it is already accepted that Mersin ophiolite complex is generated in a supra-subduction zone, this study represents a new contribution on the evolution of the Mersin ophiolite during the Late Cretaceous Neotethys subduction and could shed light on the genesis of plagiogranites in arc-environments.     

Advanced Lake Shoreline Extraction Approach by Integration of SAR Image and LIDAR Data

Noise and an abnormal distributed-image histogram is the main challenge of using SAR data. From this point of view, this study’s authors motivated the non-use of user-defined input parameters. To achieve this purpose, a fuzzy approach was proposed to extract shoreline from SENTINEL-1A data. The parameters in the processing of the SENTINEL-1A image were generated automatically with LIDAR-intensity-derived object-based segmentation results. The LIDAR-intensity image was segmented with the Mean-shift method. The corresponding result was used to estimate the input parameters for fuzzy clustering of the SENTINEL-1A image. Fuzzy segmentation was proposed, due to the expected large number of values regarding water and land classes except for the pixels along the shoreline. The memberships for land and water classes were separately computed. In the proposed approach, the results from LIDAR and SENTINEL-1A dataset are promising, with differences below 1 pixel (10?m) by evaluation with the used reference vector data.     

Geodynamic significance and genesis of chromitites from the Islahiye ophiolite (Gaziantep,SE Anatolia) as constrained by platinum group element (PGE) compositions and mineral chemistry characteristics

Acta Geochimica - Chromitites associated with intensely altered dunites and harzburgites from fourteen different localities in the Islahiye ophiolites (SE Anatolia) is reported here for the first...     

An Extended Approach of Particle Swarm Optimization for Shoreline Extraction from RASAT Imagery

This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment.