Modeling aggregate size distribution of eroded sediment resulting from rain-splash and raindrop impacted flow processes

Soil susceptibility to detachment and transport sub-processes of erosion is generally controled by the aggregate breakdown mechanism. Measuring particle size and aggregation to the estimate erodibility potential of soils is important under erosive rainfall conditions. The Aggregate Size Distribution (ASD) is one of the most important determinants of soil structure along with soil organic matter content for describing the efficiency of applied, sustainable management strategies. This study aimed to compare the performances of three different aggregate size distribution models to predict the characteristic aggregate size parameter (median diameter, D50) for eroded sediment from interrill erosion processes of Rain- Splash Transport (RST) and Raindrop Impacted Flow Transport (RIFT). The ASDs of 1143 collected sediment samples from the RST and RIFT processes were measured and modeled by the Log-normal, Fractal, and Weibull approaches. The D50 value, as a characteristic parameter for aggregate size distributions, derived from the cumulative ASD curve was compared for soils from different land use types and different slope and rainfall intensity conditions. The performance of each model was evaluated using the Mean Square Error (MSE) and Coefficient of Determination (R^2). The Weibull approach was the most accurate model showing the best fit with the lowest MSE values (0.0002 ≤MSE≤ 0.0048) and having the greatest R2 values (0.936≤ R^2≤ 0.998) when compared with the Log-normal and Fractal models. Herewith, for semi-arid land use and soil, specific shape and scale parameters for the Weibull distribution, the respective ASDs were successfully re-generated for modeling the eroded sediment of the simulated RST and RIFT interill processes.     

Exploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area

Remote sensing data utilize valuable information via various satellite sensors that have different specifications. Image fusion allows the user to combine different spatial and spectral resolutions to improve the information for purposes such as forest monitoring and land cover mapping. In this study, I assessed the contribution of dual-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar data to multispectral Landsat imagery. The research investigated the separability of forested areas using different image fusion techniques. Quality analysis of the fused images was conducted using qualitative and quantitative analyses. I applied the support vector machine image classification method for land cover mapping. Among all methods examined, the à trous wavelet transform method best differentiated the forested area with an overall accuracy (OA) of 94.316%, while Landsat had an OA of 92.626%. The findings of this study indicated that optical-SAR-fused images improve land cover classification, which results in higher quality forest inventory data and mapping.     

Evaluation of image fusion methods using PALSAR,RADARSAT-1 and SPOT images for land use/ land cover classification

This research aimed to explore the fusion of multispectral optical SPOT data with microwave L-band ALOS PALSAR and C-band RADARSAT-1 data for a detailed land use/cover mapping to find out the individual contributions of different wavelengths. Many fusion approaches have been implemented and analyzed for various applications using different remote sensing images. However, the fusion methods have conflict in the context of land use/cover (LULC) mapping using optical and synthetic aperture radar (SAR) images together. In this research two SAR images ALOS PALSAR and RADARSAT-1 were fused with SPOT data. Although, both SAR data were gathered in same polarization, and had same ground resolution, they differ in wavelengths. As different data fusion methods, intensity hue saturation (IHS), principal component analysis, discrete wavelet transformation, high pass frequency (HPF), and Ehlers, were performed and compared. For the quality analyses, visual interpretation was applied as a qualitative analysis, and spectral quality metrics of the fused images, such as correlation coefficient (CC) and universal image quality index (UIQI) were applied as a quantitative analysis. Furthermore, multispectral SPOT image and SAR fused images were classified with Maximum Likelihood Classification (MLC) method for the evaluation of their efficiencies. Ehlers gave the best score in the quality analysis and for the accuracy of LULC on LULC mapping of PALSAR and RADARSAT images. The results showed that the HPF method is in the second place with an increased thematic mapping accuracy. IHS had the worse results in all analyses. Overall, it is indicated that Ehlers method is a powerful technique to improve the LULC classification.     

Spatial information of soil hydraulic conductivity and performance of cokriging over kriging in a semi-arid basin scale

Unlike the studies in small parcels by systematic measurements, the spatial variability of soil properties is expected to increase in those over relatively large areas or scales. Spatial variability of soil hydraulic conductivity (K _h) is of significance for the environmental processes, such as soil erosion, plant growth, transport of the plant nutrients in a soil profile and ground water levels. However, its variability is not much and sufficiently known at basin scale. A study of testing the performance of cokriging of K _h compared with that of kriging was conducted in the catchment area of Sarayköy II Irrigation Dam in Cank?r?, Turkey. A total of 300 soil surface samples (0–10 cm) were collected from the catchment with irregular intervals. Of the selected soil properties, because the water-stable aggregates (WSA) indicated the highest relationship with the hydraulic conductivity by the Pearson correlation analysis, it is used as an auxiliary variable to predict K _h by the cokriging procedure. In addition, the sampling density was reduced randomly to n = 175, n = 150, n = 75 and n = 50 for K _h to determine if the superiority of cokriging over kriging would exist. Statistically, the results showed that all reduced K _h was as good as the complete K _h when its auxiliary relations with WSA were used in cokriging. Particularly, the results of the “Relative Reduction in MSE” (RMSE) revealed that the reduced data set of n = 75 produced the most accurate map than the others. In this basin-scaled study, there was a clear superiority of the cokriging procedure by the reduction in data although a very undulating topography and topographically different aspects, two different land uses with non-uniform vegetation density, different parent materials and soil textures were present in the area. Hence, using the statistically significant auxiliary relationship between K _h and WSA might bring about a very useful data set for watershed hydrological researches.     

Structure of the Mt Isa region from seismic ambient noise tomography

We use seismic tomography, exploiting group velocities derived from ambient noise, to delineate the crustal structure beneath Mt Isa and the surrounding blocks and basins. The depth extent of the blocks can be traced into the mid-crust and the spatial extent of the associated velocity anomalies mapped over an area of approximately 500 km by 500 km. The Proterozoic Mt Isa block is imaged as a region of elevated seismic velocities comparable to the Yilgarn craton in Western Australia, while the surrounding basins have relatively low velocities. Seismic velocity anomalies display correlations with the regional Bouguer gravity data and with high crustal temperatures in the region. There are a number of isolated low-velocity anomalies under the Millungera basin that suggest either previously unknown thermal anomalies or zones with high permeability, which can also produce lowered velocities.     

Monitoring of coal mining subsidence in peri-urban area of Zonguldak city (NW Turkey) with persistent scatterer interferometry using ALOS-PALSAR

This paper presents the results of spatiotemporal monitoring of surface subsidence over a mining area in Zonguldak Province of Turkey using Synthetic Aperture Radar (SAR) data, providing maps of subsidence rates in the radar line of sight direction. A total of 18 SAR images, acquired between January 2007 and June 2010 by the Japanese Advanced Land Observing Satellite, have been used to map the surface displacements using the Persistent Scatterer Interferometry technique. The use of Phased Array Type L-band Synthetic Aperture Radar data has proved useful for avoiding signal decorrelation and estimating surface deformation in the heavily vegetated study region. The technique enables the monitoring of continuous small displacements over a large area. Our findings present that many Persistent Scatterers were located on the vegetation cover. The results reveal areas of ground surface subsidence up to 44 mm/year that are well correlated with the underground coal mining galleries particularly in the Gelik region where the Karadon mining galleries are present.