Total Water Storage in Small Islands Using Multi-satellite Products: The case of Cyprus

The world’s longest international undersea water pipeline has recently been laid from southern Turkey to Northern Cyprus to address the water scarcity problems in the Cyprus Island. When completed, the project will add 19.8 million gallons of water annually for drinking and irrigation. Moreover, it will spur further development in the Turkish area divided from Greek community for four decades. Under such circumstances, satellite remote sensing provides a unique tool to evaluate the water policy for the entire island. The objective of this study is, therefore, to examine the potential of satellite-based remote sensing hydrologic models covering a small-scale Mediterranean island, which is under drought conditions. Satellite-based measurements such as GRACE (total water storage), TRMM (precipitation) and MODIS (evapotranspiration) data over a 1°–1° grid together with related information from global hydrological model, specifically WGHM and GLDAS, were collected for this purpose.     

Sea-Level Change Over the China Sea and Its Vicinity Derived from 25-Year T/P Series Altimeter Data

The characteristics of sea-level change in the China Sea and its vicinity are studied by combining TOPEX/Poseidon (T/P), Jason-1, Jason-2, and Jason-3 altimeter data. First, the sea-surface height is computed by using monthly data via collinear adjustment, regional selection, and crossover adjustment. The sea-level anomaly (SLA) from October 1992 to July 2017 is calculated based on the difference that is obtained by the value derived from the inverse distance weighting method to interpolate the CNES_CLS15 model value at a normal point. By analyzing the satellite data at the same time in orbit, three mean bias groups over the China Sea and its vicinity are obtained: the difference between T/P and Jason-1 is ??11.76 cm, the difference between Jason-1 and Jason-2 is 9.6 cm, and the difference between Jason-2 and Jason-3 is 2.42 cm. To establish an SLA series for 25 years in the study area, the SLAs are corrected. Mean rate of sea-level rise of the Bohai Sea, Yellow Sea, East China Sea, and South China Sea of 4.87 mm/a, 2.68 mm/a, 2.88 mm/a, and 4.67 mm/a, respectively, is found by analyzing the series of SLAs.     

Gondwana-Derived Terranes Structural Mapping Using PALSAR Remote Sensing Data

Gondwana-derived terranes are now separated by major faults or suture zone, which are rarely simple and easily recognizable lineaments. Different association of ore mineral systems such as deposits of sediment-hosted/orogenic gold and granite-related minerals is discovered in collision and subduction zones of the Gondwana-derived terranes. They are associated with large-scale, terrane-bounding fault systems and broad areas of deformation. Mineralization mostly associated with structurally-controlled complex lodes, veins, sheeted veins and veinlets in diverse orientations. Recognizing the structural significance of lineaments and curvilinear is very difficult in tropical, arid and Antarctic regions due to environmental obstacles. Remote sensing data could be used to detect geological structures associated with suture zones between Gondwana-derived terranes especially for large inaccessible regions where fieldwork is limited or nonexistent. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to map major geological structures in the Bentong-Raub Suture Zone of Peninsular Malaysia. It is one of the major structural zones in Sundaland, Southeast Asia, which forms the boundary between the Gondwana-derived the Sibumasu terrane and Sukhothai-Indochina arc. Structural features associated with sediment-hosted/orogenic gold deposits in the Central Gold Belt and tin mineralization in S-type granites in the Main Range were investigated using PALSAR data and comprehensive fieldwork. Results indicate that main faults strike along 340° to 350° that are intersected by many shear or lateral fault zones are high potential zone for gold mineralization in the Central Gold Belt. Hydrothermally alteration mineral zones and cataclastic rocks are also the other indicators of gold mineralized veins in the gold belt. High potential zones for tin mineralization are N–S strike-slip faults, fault zones and shear zones trending E–W, NE–SW and WNW–ESE in dissected crystalline granitic rocks that are associated with hydrothermal alteration zones in the Western Tin Belt. Lineament analysis using PALSAR satellite remote sensing data is a useful tool for mapping major geological structural features and detection of the boundary between the Gondwana-derived terranes and detailed structural analysis of fault systems and deformation with high potential for a variety of mineral resources, especially in tropical, arid and Antarctic regions.     

A Directed-Line-Segment-Based Photogrammetry Method to Survey the Tunneling Working Surface of Mine Roadway

Absolute orientation is a basic technical work in digital image geologic logging of underground coal mine. Traditional control-point-based absolute orientation method requires setting object space control points of the known three-dimensional coordinates, which may lead to low efficiency. Therefore, this paper proposed a point-free close-range photogrammetry absolute orientation algorithm, which utilized direction line segments including plumb line segments and line segments with known directions and lengths to identify the dimensional orientation of a stereoscopic model. Experiment results show that the precision of the orientation results is favorable. σ _X and σ _Y are as high as 0.5 mm, and σ _Z is 0.3 mm. Finally, this paper introduced the application of the proposed algorithm in rapid geological logging of coal mine roadway, which was fast and reliable, convenient and feasible.     

Surface Reflectance Climate Data Records (CDRs) is a Reliable Landsat ETM+ Source to Study Chlorophyll Content in Pecan Orchards

We evaluated the relationships among three Landsat Enhanced Thematic Mapper (ETM+) datasets, top-of-atmosphere (TOA) reflectance, surface reflectance climate data records (surface reflectance-_CDR) and atmospherically corrected images using Fast Line-of-Sight atmospheric analysis of Spectral Hypercubes model (surface reflectance-_FLAASH) and their linkto pecan foliar chlorophyll content(chl-cont). Foliar chlorophyll content as determined with a SPAD meter, and remotely-sensed data were collected from two mature pecan orchards (one grown in a sandy loam and the other in clay loam soil) during the experimental period. Enhanced vegetation index derived from remotely sensed data was correlated to chl-cont. At both orchards, TOA reflectance was significantly lower than surface reflectance within the 550–2400 nm wavelength range. Reflectance from atmospherically corrected images (surface reflectance-_CDR and surface reflectance-_FLAASH) was similar in the shortwave infrared (SWIR: 1550–1750 and 2080–2350 nm) and statistically different in the visible (350–700 nm). Enhanced vegetation index derived from surface reflectance-_CDR and surface reflectance-_FLAASH had higher correlation with chl-cont than TOA. Accordingly, surface reflectance is an essential prerequisite for using Landsat ETM+  data and TOA reflectance could lead to miss-/or underestimate chl-cont in pecan orchards. Interestingly, the correlation comparisons (Williams t test) between surface reflectance-_CDR and chl-cont was statistically similar to the correlation between chl-cont and commercial atmospheric correction model. Overall, surface reflectance-_CDR, which is freely available from the earth explorer portal, is a reliable atmospherically corrected Landsat ETM+ image source to study foliar chlorophyll content in pecan orchards.     

Distributed Source Coding of Hyperspectral Images Based on Three-Dimensional Wavelet

To reduce the possibility of poor efficiency and weak anti-error capability while encoding and transmitting hyperspectral images, we present a distributed source coding scheme for hyperspectral images based on three-dimensional (3D) set partitioning in hierarchical trees (SPIHT). First, the 3D wavelet transform is performed on the hyperspectral image. Thereafter, the low frequency section is regarded as the Key frame and the high frequency section as the Wyner–Ziv frame to enable independent SPIHT coding through different transmission channels. The Wyner–Ziv encoder uses Turbo channel coding to create high frequency information that reflects the details of the image with better anti-error capacity, while the low frequency information shows the main energy of the image. In this study, we used SPIHT coding to acquire a bit stream with quality scalability. Results show that the proposed scheme is more efficient during coding, while at the same time providing improved anti-error capability and quality scalability of the bit stream.     

Comparative Analyses of the Point Cloud Produced by Using Close-Range Photogrammetry and Terrestrial Laser Scanning for Rock Surface

Point cloud produced by using theoretically and practically different techniques is one of the most preferred data types in various engineering applications and projects. The advanced methods to obtain point cloud data in terrestrial studies are close range photogrammetry (CRP) and terrestrial laser scanning (TLS). In the TLS technique, separated from the CRP in terms of system structure, denser point cloud at certain intervals can be produced. However, point clouds can be produced with the help of photographs taken at appropriate conditions depending on the hardware and software technologies. Adequate quality photographs can be obtained by consumer grade digital cameras, and photogrammetric software widely used nowadays provides the generation of point cloud support. The tendency and the desire for the TLS are higher since it constitutes a new area of research. Moreover, it is believed that TLS takes the place of CRP, reviewed as antiquated. In this study that is conducted on rock surfaces located at Istanbul Technical University Ayazaga Campus, whether point cloud produced by means photographs can be used instead of point cloud obtained by laser scanner device is investigated. Study is worked on covers approximately area of 30 m?×?10 m. In order to compare the methods, 2D and 3D analyses as well as accuracy assessment were conducted. 2D analysis is areal-based whereas 3D analysis is volume-based. Analyses results showed that point clouds in both cases are similar to each other and can be used for similar other studies. Also, because the factors affecting the accuracy of the basic data and derived product for both methods are quite variable, it was concluded that it is not appropriate to make a choice regardless of the object of interest and the working conditions.     

Dimensionality Reduction and Classification of Hyperspectral Images Using Object-Based Image Analysis

Object-based image analysis (OBIA) has attained great importance for the delineation of landscape features, particularly with the accessibility to satellite images with high spatial resolution acquired by recent sensors. Statistical parametric classifiers have become ineffective mainly due to their assumption of normal distribution, vast increase in the dimensions of the data and availability of limited ground sample data. Despite pixel-based approaches, OBIA takes semantic information of extracted image objects into consideration, and thus provides more comprehensive image analysis. In this study, Indian Pines hyperspectral data set, which was recorded by the AVIRIS hyperspectral sensor, was used to analyse the effects of high dimensional data with limited ground reference data. To avoid the dimensionality curse, principal component analysis (PCA) and feature selection based on Jeffries–Matusita (JM) distance were utilized. First 19 principal components representing 98.5% of the image were selected using the PCA technique whilst 30 spectral bands of the image were determined using JM distance. Nearest neighbour (NN) and random forest (RF) classifiers were employed to test the performances of pixel- and object-based classification using conventional accuracy metrics. It was found that object-based approach outperformed the traditional pixel-based approach for all cases (up to 18% improvement). Also, the RF classifier produced significantly more accurate results (up to 10%) than the NN classifier.