Influence of geological structures on groundwater accumulation and groundwater salinity in Musandam Peninsula,UAE and Oman

The hydrological setting and groundwater quality of Musandam Peninsula was studied to investigate the influence of geological structures on the groundwater accumulation and groundwater salinity. Five sets of modified morphometric maps were used to reduce errors and carry out the geological structures. The modification was modified by applying mean filter to the Digital Elevation Model (DEM) then applying Soble filter with 10% threshold and equalization enhancement. D8 and algorithms were used to reveal the drainage basins and drainage networks of the entire area. The algorithm determines into which neighbouring pixel any water in a central pixel will flow naturally. Flow direction in a DEM is calculated for every central pixel of input blocks of a 3 × 3 window, all the time comparing the value of the central pixel in the window with the value of its eight neighbours. The spatial association between geological structures and drainage networks was studied using 2D graph and rose diagrams. Flood basin model was applied to simulate the Arabian Gulf water intrusion into the coastal aquifer. The concentrations of solutes in groundwater samples collected from Wadi Al Bih well field and well locations were correlated with the geological structure trends and intersections. The results of the study reveal that the drainage basins, drainage network and groundwater quality are structurally controlled by subsurface geological structure displacements.     

Comparing terrain and vegetation-based visibility for explaining sable flight behaviour in a Southern African savanna

In this study, we tested whether terrain-based visibility modelled from a remotely sensed ASTER Digital Elevation Model (DEM) explains sable flight initiation distance (FID) better than vegetation-based visibility measured in the field. We also tested whether the effect of hunting on sable FID varies with spatial scale. We first performed a linear regression analysis relating FID to standardized coefficients of both vegetation- and terrain-based visibility where the variable with the larger coefficient was the better predictor of FID. We latter performed an analysis of covariance (ANCOVA) comparing the slopes relating FID to both measures of visibility, first at the large scale and later at the small scale within the hunting area. Our results suggest that remotely sensed terrain-based visibility predicts the FID of sable better than vegetation-based visibility. We also found that the effect of hunting on sable FID varies with spatial scale.     

Automatic detection of near surface geological and hydrological features and investigating their influence on groundwater accumulation and salinity in southwest Egypt using remote sensing and GIS

This study employs two automated algorithms, the topographic fabric and the deterministic eight-node (D8), to reveal near surface geological fractures and their associated paleodrainages network from a 90?m DEM of the Shuttle Topographic Radar Mission sensor. The topographic fabric algorithm, which calculates the slope and aspect which define a vector normal to the earth’s surface and then compute direction cosines of normal vector at each point, was used to auto-detect fault zones. The deterministic eight-node (D8) algorithm, which determines in which neighbouring pixel any water in a central pixel will flow naturally, was used to delineate paleodrainages concealed beneath sand sheets. Seven sets of geological structures were recognized. Their major trends were found to be in the S46°W, S58°W, S81°W, N107°W, N–S, E–W and N152°W and share similar trends of the revealed paleodrainages. The results suggest a strong spatial relationship between the features extracted from DEM and groundwater potential.     

Cosmo-SkyMed X-band SAR data for classification of ice-free areas and glacier facies on Potter Peninsula,King George Island Antarctica

The climate change phenomena have been influencing terrestrial and glacial ecosystems around the planet. Maritime Antarctica is especially sensitive to these climate variations and over the last 50 years increasing global air temperatures have caused extensive glacial retreat. The objective of this study is to evaluate the potential use of the SAR technology in monitoring the surface dynamics of the Potter Peninsula, King George Island, maritime Antarctica. An image generated by the SAR satellite COSMO-SkyMed, obtained on 2 February 2011, was used to extract the backscattering values of targets on the surface for further processing and classification, using a supervised statistic classifier of maximum likelihood for the determination of the surface classes. The average backscattering of water bodies presented high similarity, which made its separation unattainable. On the other hand, the surface classes’ bare ice and wet snow over the glacier presented distinct average backscattering values, which allowed an efficient and precise classification using only this parameter. The classification process showed satisfactory results for periglacial environments, presenting high fidelity to the field data.     

Groundwater potential modelling using remote sensing and GIS: a case study of the Al Dhaid area,United Arab Emirates

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM and LANDSAT images of spatial resolution 30?m were used to construct groundwater potential zones (GPZ) map by integrating geological fractures, drainage network, slope and relief, and convergence index maps of the study area. Weight and score of each map were developed according to their level of contribution toward groundwater accumulation and spatial distribution of groundwater wells. The area that has very high potential for groundwater is located at the foot of Oman Mountains and Al Dhaid Depression covering an area of about 59.33?km², which is 4.40% of the study area. Further hydrological map and data on hydraulic properties of shallow aquifer, as recorded from observation wells in the regions, have been used to validate the produced GPZ map. The validation result showed sufficient agreement between the produced GPZ map.     

Evaluation of drainage networks developed in hard rock terrain

An attempt was made to study the influence of various factors such as geology, landforms, slope, soil, landuse/cover on the development of the drainage network. To compare and evaluate drainage networks developed in various geologic terrains, differing in rock type and structure, three sub-basins of the Bhadra river basin, located in Chikmagalur district, Karnataka, India were selected for the study. Quantitative morphometric analysis was carried out for both linear aspects and areal aspects for all three sub-basins. The applicability of Horton's laws was also studied. Each of the quantitative parameters was interrelated with thematic details derived from remote sensing data. The results of the study indicate that the drainage characteristics are entirely different for all three sub-basins. The study has also established the applicability of Horton's laws pertaining to quantitative morphometry of the sub-basins.     

地形地质GIS三维可视化及应用

借助GIS强大的三维建模及可视化分析功能,以湖北省崇阳地区1：50 000区域地质成果为例,基于地理矢量数据、地质矢量数据和遥感影像数据,利用地形数据构建数字高程模型（DEM）,将DEM与遥感图像叠合生成三维影像图,建立集地形、地质、遥感等数据为一体的三维可视化模型,解决传统二维地质图件用于表示三维地质不直观等问题,提...     

Coupling of remote sensing data and environmental-related parameters for dengue transmission risk assessment in Subang Jaya,Malaysia

In Malaysia, the endemic level of dengue fever (DF) has already changed morbidity indicators, and the magnitude of these incidences in the last few years has surpassed the incidences of all other diseases of compulsory notification. The reasons for the dramatic emergence of DF are complex and not well understood. There are many factors that contribute to the epidemiological conditions that favour viral transmission by the main mosquito vector. This study, therefore, is filling this gap by analysing the impact of dengue incidence at a local (Subang Jaya) scale using environmental factors. Meteorological data and land-use pattern were consolidated using geographic information system (GIS) and its components as an analytical tool. We have shown that weather variables (relative humidity, temperature and precipitation) have significant correlation with DF incidence with seasonal variation. Besides land-use pattern, DF incidence shows the higher distribution in the residential area, followed by commercial and industrial area. This is due to the higher population density in residential area as well as favourable places for the breeding of dengue-carrying Aedes mosquitos created by humans in the residential area, especially one-storey houses. The analysis on the trends of DF incidence towards various housing types indicate that most of the victims’ houses fall into interconnection houses and mixed houses types compared to the independent houses area. The outcome driven from this analysis suggested that each character of the environmental factors has their own risk towards dengue incidence. In line with that, it is possible to develop a dynamic model of DF transmission using the knowledge produced by this comprehensive time series data and the results provided by the different analyses.     

Delineation of groundwater potential zone in hard rock terrain of India using remote sensing,geographical information system (GIS) and analytic hierarchy process (AHP) techniques

The present study has been undertaken to delineate the groundwater potential zones in the hard rock terrain of Palamu district, Jharkhand using the advanced applications of remote sensing, geographical information systems and analytic hierarchy process techniques. The integration and analyses of various thematic databases viz., geomorphology, lithology, soil, slope, lineament density, weathered zone thickness, drainage density and rainfall proved useful in the delineation of GWP zones. The study indicates that only 136?km² of the study area exhibit excellent groundwater potential, 248?km² has very good groundwater potential, whereas 36.89 and 38.23% are under poor and very poor groundwater potential zones, respectively. Hence, only a total of 11.6% of the area (490?km²) is classified as high to excellent groundwater potential. The final groundwater prospect map obtained was classified as excellent potential, very good potential, good potential, moderate potential, poor potential and very poor potential zone.     

遥感和GIS在冰湖溃决洪水中的应用研究

近年来随着全球气候变暖和冰川退缩,以及人类在高海拔地区活动的增多,冰湖溃决洪水灾害呈增加趋势。由于遥感和GIS技术的众多优势,使其在冰湖溃决洪水研究方面得到广泛应用。首先对冰湖溃决洪水及其研究做简单介绍,然后从冰川、冰湖空间数据获取,冰湖溃决评价指标获取,冰湖溃决洪水模拟和DEM的建立及应用4个方面对遥感和GIS在冰湖溃决洪水研究中的应用进行综述,最后指出,目前遥感和GIS在冰湖溃决洪水应用中的不足,为进一步研究和应用指明了方向。     

Morphometric analysis of Upper Tons basin from Northern Foreland of Peninsular India using CARTOSAT satellite and GIS

The morphometric analysis of river basin helps to explore the interrelationship between hydraulic parameters and geomorphologic characteristics. The study has been conducted in the Upper Tons basin of Northern Foreland of Peninsular India. The river basin has been characterized using the topographical maps, CARTOSAT satellite image integrated using the GIS techniques. The drainage density analysis indicates lower values in the north-eastern regions and thus these regions can be categorized as better ground water potential zone. There are in total 10 sub-watersheds which have been delineated; SW-4 has maximum drainage density (4.75), stream frequency (5.61) and drainage texture (26.64) followed by SW-6–10. The prioritized sub-watershed numbers SW-4 and SW-6–10 need conservation practices because of their high erodibility and run-off. SW-1–3 and SW-5 regions have better permeable bed rocks and hence good for water harvesting. The areal parameter indicates elongated shape of basin and moderate to steeper ground slope. The results are supported by extensive field survey. This study can be applied for soil and water management, as well as disaster prevention from similar type of drainage basins.     

基于ArcGIS平台NetCDF在测绘领域中的应用探讨

本文介绍了时态GIS和NetCDF数据文件,初步探讨了NetCDF数据文件在测绘领域的一些应用,并利用这些原理、步骤、方法,对实例数据进行操作分析.在此基础上,对NetCDF的应用进行进一步讨论.     

Prediction of soil loss differences and sediment accumulation at the Nilufer creek watershed,Turkey, using multiyear satellite data in a GIS

This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km^?2 y^?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area.     

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division, Kenya

<正>Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.     

基于多源国产高分卫星时空信息的米级分辨率耕地提取

及时准确地获取耕地空间分布数据对于农业生产管理、产量估算、种植结构调整等具有重要意义。目前的耕地提取多基于多时相中低分辨率影像或单时相高分辨率影像,难以满足耕地破碎,农作物种植模式复杂的区域精度需求。基于此,本研究通过协同国产高分一号（GF-1）、高分二号（GF-2）和高分六号（GF-6）卫星影像,探索米级分辨率尺度下的耕地高精度提取方法。该方法以深度神经网络UNet为基础,通过协同GF-1/6的多时相优势和GF-2影像的高空间分辨率构建了CEUNet (Cropland Extraction UNet)模型,以充分挖掘耕地的时相特征和空间几何特征。同时,将基于CEUNet模型提取的米级耕地结果分别与基于UNet和多源不同分辨率遥感影像的语义分割（UNet＿m）、基于UNet和单时相高分辨率影像的语义分割（UNet＿s）、基于对象的随机森林分类（OBIA）、基于像元的随机森林分类（RF）提取的耕地结果展开对比,分析所提出的方法在不同区域的适宜性。结果表明,基于CEUNet模型提取的米级耕地总体精度达到92.92%,且基于CEUNet提取的耕地的逐像元验证结果在平均F1-Score值上相...     

Bayesian and Geostatistical Approaches to Combining Categorical Data Derived from Visual and Digital Processing of Remotely Sensed Images

This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification. By experiment with aerial photographs and Landsat TM data, accuracy of spectral, spatial, and combined classification results was evaluated. It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly. Secondly, through test with a 5-class and a 3-class classification schemes, it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy. Lastly, this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging, a non-parametric geostatistical technique.     

Comparison of basin morphometry derived from topographic maps,ASTER and SRTM DEMs: an example from Kerala,India

The drainage network of a sixth-order tropical river basin, viz. Ithikkara river basin, was extracted from different sources such as Survey of India topographic maps (1: 50,000; TOPO) and digital elevation data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (30 m) and Shuttle Radar Topography Mapping Mission (SRTM) (90 m). Basin morphometric attributes were estimated to evaluate the accuracy of the digital elevation model (DEM)-derived drainage networks for hydrologic applications as well as terrain characterization. The stream networks derived from ASTER and SRTM DEMs show significant agreement (with slight overestimation of lower order streams) with that of TOPO. The study suggests that SRTM (despite the coarser spatial resolution) provides better results, in drainage delineation and basin morphometry, compared to ASTER. Further, the variability of basin morphometry among the data sources might be attributed to spatial variation of elevation, raster grid size and vertical accuracy of the DEMs as well as incapability of the surface hydrologic analysis functions in the GIS platform.     

Bayesian and geostatistical approaches to combining categorical data derived from visual and digital processing of remotely sensed images

This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification. By experiment with aerial photographs and Landsat TM data, accuracy of spectral, spatial, and combined classification results was evaluated. It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly. Secondly, through test with a 5-class and a 3-class classification schemes, it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy. Lastly, this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging, a non-parametric geostatistical technique.