新疆2001-2010年农业气候干旱脆弱性分析

选取新疆维吾尔自治区14个地（州）为研究对象,从农业气候干旱的敏感性和恢复力2个角度选取10个指标,对该区2001-2010年的农业气候干旱脆弱性进行评价。通过计算新疆各地（州）农业气候干旱脆弱度并绘制新疆农业气候干旱脆弱性区划图,分析该区农业气候干旱脆弱性的年际变化和地域分布特点及规律,初步探讨了其成因,提出缓解新疆农业气候干旱脆弱性的科学对策。结果表明：新疆各地区农业气候干旱脆弱度在时间尺度存在差异性变化,并存在显著地域性差异,总体呈现出 “东高西低,南高北低”的分布状况,主要原因不仅有地形、水文和气候等自然环境因素的差异,还包括经济产业结构、科学技术研究、灌溉设施、全民意识和政策管理等社会经济因素,可以通过采用先进技术和高效管理措施、根据气候采取种植结构格局和方式、合理开采高效利用水资源、增强全民生态保护意识等措施,缓解干旱影响、降低区域干旱脆弱性。     

Advanced analysis of differences between C and X bands using SRTM data for mountainous topography

By Interferometric Synthectic Aperture Radar (InSAR), during the Shuttle Radar Topography Mission (SRTM) height models have been generated, covering the earth surface from 56° south to 60.25° north. With the exception of small gaps in steep parts, dry sand deserts and water surfaces, the free available US C-band data cover the earth surface from 56° south to 60.25° north completely while the X-band data, distributed by the DLR (German Aerospace Center), cover it only partially. The C-band and X-band radar cannot penetrate the vegetation because of the short wavelength. Therefore, the height models are not Digital Elevation Models (DEM) representing bare Earth surface without any details, they are Digital Surface Models (DSM) representing the visible surface including vegetation and buildings. In the area of Zonguldak, Turkey, C-band and X-band DSMs are available and have been analysed in cooperation between Zonguldak Karaelmas University (ZKU) and Leibniz University of Hannover. The digitized contour lines from the 1:25,000 scale topographic maps and also a more precise height model derived directly from large scale photogrammetric mapping are used as reference height models. The terrain inclination influences the accuracy strongly, but also the directions of the inclination in relation to the radar view direction, the aspects, are important. Independent from the aspects, the analysed results do have root mean square differences against the reference data fitting very well to the Koppe formula SZ=a+b*tan α. The analyses are made separately for open and forest areas, with clear accuracy differences between both. Also, the analysis of X-band separately for three sub-areas is done and the positive effect of double observation to the accuracy has been clearly determined. The C-band data are only available with a spacing of 3 arcsec, corresponding to 92m × 70m, while the X-band data do have a spacing of 1 arcsec. This is important for the interpolation in the mountainous test area. The accuracy of the height points is approximately the same for the C- and the X-band data. But the C-band data which have three times larger spacing than Xband data, do not include the same morphological information. While C-band data contain very generalised contour lines X-band data have quite more details depending on 1 arcsec point spacing. The differential DEMs have been generated, separately, for displaying the differences between SRTM height models and reference DEMs of the test field.     

Prediction of unconfined compressive strength of carbonate rocks using artificial neural networks

The unconfined compressive strength (UCS) of intact rocks is an important geotechnical parameter for engineering applications. Determining UCS using standard laboratory tests is a difficult, expensive and time consuming task. This is particularly true for thinly bedded, highly fractured, foliated, highly porous and weak rocks. Consequently, prediction models become an attractive alternative for engineering geologists. The objective of study is to select the explanatory variables (predictors) from a subset of mineralogical and index properties of the samples, based on all possible regression technique, and to prepare a prediction model of UCS using artificial neural networks (ANN). As a result of all possible regression, the total porosity and P-wave velocity in the solid part of the sample were determined as the inputs for the Levenberg–Marquardt algorithm based ANN (LM-ANN). The performance of the LM-ANN model was compared with the multiple linear regression (REG) model. When training and testing results of the outputs of the LM-ANN and REG models were examined in terms of the favorite statistical criteria, which are the determination coefficient, adjusted determination coefficient, root mean square error and variance account factor, the results of LM-ANN model were more accurate. In addition to these statistical criteria, the non-parametric Mann–Whitney U test, as an alternative to the Student’s t test, was used for comparing the homogeneities of predicted values. When all the statistics had been investigated, it was seen that the LM-ANN that has been developed, was a successful tool which was capable of UCS prediction.     

Quantitative assessment of remotely sensed global surface models using various land classes produced from Landsat data in Istanbul

Digital elevation model(DEM) is the most popular product for three-dimensional(3D) digital representation of bare Earth surface and can be produced by many techniques with different characteristics and ground sampling distances(GSD). Space-borne optical and synthetic aperture radar(SAR) imaging are two of the most preferred and modern techniques for DEM generation. Using them, global DEMs that cover almost entire Earth are produced with low cost and time saving processing. In this study, we aimed to assess the Satellite pour l'observation de la Terre-5(SPOT-5), High Resolution Stereoscopic(HRS), the Advanced Space-borne Thermal Emission and Reflection Radiometer(ASTER), and the Shuttle Radar Topography Mission(SRTM) C-band global DEMs, produced with space-borne optical and SAR imaging. For the assessment, a reference DEM derived from 1∶1000 scaled digital photogrammetric maps was used. The study is performed in 100 km2 study area in Istanbul including various land classes such as open land, forest, built-up land, scrub and rough terrain obtained from Landsat data. The analyses were realized considering three vertical accuracy types as fundamental, supplemental, and consolidated, defined by national digital elevation program(NDEP) of USA. The results showed that, vertical accuracy of SRTM C-band DEM is better than optical models in all three accuracy types despite having the largest grid spacing. The result of SPOT-5 HRS DEM is very close by SRTM and superior in comparison with ASTER models.