基于SRTM-DEM的阿尔泰山构造地貌特征分析

基于美国SRTM-DEM数据，利用彩色晕染、密度分割与GIS空间统计分析等技术，并结合地质资料，通过地形高程、地表坡度 及地形剖面等分析手段，对阿尔泰山的构造地貌特征进行初步分析。研究表明，阿尔泰山脉平均海拔约1 790 m，平均坡度约21° ，其高海拔与高坡度的现代地貌特征，主要与强烈的断裂构造活动有关； 山脉严格受到以北西向为主的断裂构造活动的影响与控 制，其发育的构造地貌单元基本上呈北西走向特征； 山脉阶梯状地貌特征明显，共发育5级剥夷面，不同级剥夷面所处的海拔不一 样，同级剥夷面具有东北侧高于西南侧，山脉东、中段高于西段的特点。     

台湾地区地貌形态的分析研究

数字高程模型(DEM)是地貌解译有力的辅助工具,同时也是对地形地貌分析研究进行量化表达的一个重要手段。在前人研究的方法上通过对研究区台湾地区的SRTM-DEM数据的处理,运用GIS空间分析和统计方法进行地形分析,并在此基础上完成对地形起伏度、坡度、坡向、高程等地形因子相关的拓展分析。根据分析结果对该地区的地貌形态特征进行总结。     

基于InSAR技术的大别山DEM提取及地貌特征分析

以Envisat ASAR为数据源,运用高密度的InSAR技术反演安徽地区大别山造山带地区的高精度数字高程模型(DEM),并利用GIS的空间分析和统计分析技术,对大别山地区的构造地貌进行剖面分析,生成研究区面状地形起伏特征图,在此基础上对大别山地区的地形地貌进行定量分析,其成果可为我省地震地质研究提供大尺度的参考资料。     

利用DEM平均值滤波法的月表线性构造信息提取

针对国内外仅利用DEM数据对月表典型线性结构的提取还未有成熟方法的问题,该文提出了平均值滤波法。该方法以月表典型线性构造高程的特殊性为重点,根据线性构造与周围地形在高程上的明显差异,在区域坡度的限制下,使用DEM数据的平均高程值对原始数据进行多次滤波,以逐渐逼近月表构造的真实形态。该实验结果表明:平均值滤波法提取得到的线性结构轮廓清晰,形态真实;适用于月表线性构造存在的大部分区域;识别敏感度高,可弥补人眼识别的缺陷;提取效率高,区域内所有线性构造一次性就可以提取出来,可为后续深入研究提供大量的数据基础。     

基于GIS的彭州市崩塌滑坡地质灾害地形因素分析

基于ArcGIS平台,利用DEM数据资料,选择位于四川西北部的彭州市作为研究区域,提取了区内高程、地形起伏等地形因子;统计了5.12震后区内39个滑坡点,58个崩塌点,建立了地形地貌与崩塌滑坡地质灾害之间的关系:这类地区对应的地貌类型主要是海拔高程较高的山坡地带。实验证明,利用GIS技术,结合数字地面模型,进行崩塌、滑坡等地质灾害的地形因子相关性分析,结果可靠,对防灾减灾具有重要的借鉴意义。     

数字高程模型格网间距对提取地形因子的影响研究

数字高程模型(DEM)作为地面高程信息的数字表示形式,在地学研究领域得到了广泛应用.本文通过对DEM基本原理及其现有表示形式进行分析,提出了数字等高线也是DEM表示形式的观点.随后通过选取4种不同地貌类型的规则格网DEM作为实验区,分析研究了DEM格网间距对坡度、坡面曲率、地表切割深度、地表粗糙度和沟谷密度等地形因子提取的影响,为人们根据地貌类型和应用需求合理选择DEM分辨率提供了参考.     

地形平坦地区DEM生成算法的比较研究

数字高程模型(DEM)是GIS的基础数据之一,是许多涉及高程信息的空间分析的重要基础。DEM插值精度的好坏直接影响基于DEM的各种地学分析及应用,因此研究高精度的DEM插值算法具有重要意义。介绍了基于水文强化算法的DEM插值算法——ANUDEM,并与传统的TIN建立DEM的算法进行了比较。认为在地形复杂地区由于等高线密集,高程信息丰富,两种插值算法效果都比较好;而在地形平坦地区ANUDEM算法精度优于TINDEM,并且,ANUDEM得到的DEM很好地避免了平山顶、阶梯状地形,其派生的等高线和水系与原始数据更加吻合。相对于TINDEM算法,ANUDEM算法更适合地形平坦地区的DEM建立。     

用温度植被干旱指数识别河源地区隐伏构造

针对遥感技术在植被覆盖区构造信息提取的难点,使用Landsat 7 ETM+数据提取温度植被干旱指数(TVDI),结合数字高程模型(Digital elevation model,DEM)、GF-1数据和Google earth图像,对河源地区的隐伏断裂构造进行综合解译.综合解译结果对区内大部分的隐伏断裂构造都能很好地反映,可较好地识别规模为1～2 km的次级隐伏断裂构造,以及一些延伸规模10 km以上的断裂.结果表明:TVDI线性异常能够指示隐伏断层的存在,结合DEM及多光谱数据综合解译方法能有效识别植被覆盖区隐伏断层,研究结果对植被覆盖区隐伏断层构造研究具有很好的应用价值.     

顾及地貌特征的矿区地表塌陷DEM的生成方法

地下煤炭资源开采导致矿区地表塌陷和矿区地形的变化,直接由开采沉陷下沉预计数据生成的DEM不能表现矿区地表塌陷后的地形状况。通过在开采沉陷下沉预计程序中增加高程修正计算功能,对矿区原始地貌高程进行下沉修正计算,生成矿区地表塌陷高程数据文件,由该数据文件可以生成顾及地貌特征的矿区地表塌陷DEM。该方法操作和实现简单,生成的DEM精度可靠,能够表现矿区地表塌陷后的地形状况,可以作为矿区地理信息系统的基础数据,对于指导开采沉陷的防治和治理具有重要意义。     

黄土丘陵沟壑第三副区水文地貌关系正确DEM的建立与评价

本文以黄土丘陵沟壑第三副区的藉河流域为研究区,利用ANUDEM软件和1:5万地形图研究了水文地貌关系正确DEM的建立方法,从派生等高线与原始数字化等高线对比等方面对建立的DEM进行了质量评价。并且与传统TIN方法建立的不同水平分辨率的DEM做了比较。结果表明:由等高线、高程点、河流和陡崖线在ANUDEM5.1中生成的DEM质量优于由等高线、高程点和地形特征点用TIN方法生成的DEM。ANUDEM建立的DEM更能精确地反映水文地貌特征。在此基础上,研究了确定集水面积阈值的方法,通过在Arc/Info环境下运行AML程序自动提取了基于水文地貌关系正确DEM的流域特征。     

Analyzing relationship between user‐generated content and local visual information with augmented reality‐based location‐based social networks

Location‐based social networks (LBSNs) have become an important source of spatial data for geographers and GIScientists to acquire knowledge of human–place interactions. A number of studies have used geotagged data from LBSNs to investigate how user‐generated content (UGC) can be affected by or correlated with the external environment. However, local visual information at the micro‐level, such as brightness, colorfulness, or particular objects/events in the surrounding environment, is usually not captured and thus becomes a missing component in LBSN analysis. To provide a solution to this issue, we argue in this study that the integration of augmented reality (AR) and LBSNs proves to be a promising avenue. In this first empirical study on AR‐based LBSNs, we propose a methodological framework to extract and analyze data from AR‐based LBSNs and demonstrate the framework via a case study with WallaMe. Our findings bolster existing psychological findings on the color–mood relationship and display intriguing geographic patterns of the influence of local visual information on UGC in social media.     

多时相ASAR数据的地表覆盖分类研究

本文选择了位于念青唐古拉山脉西段,覆盖范围大约100×100km2的区域,使用四个不同时期内的ASAR图像数据进行地表覆盖分类的研究。研究结果表明,虽然同种类型的地物在同一景雷达图像上的后向散射系数存在一定的差异,但是其后向散射系数随时间的变化规律却是一致的。根据地物后向散射系数的这种时相特征,我们对研究区的地表覆盖进行了分类,结果显示使用该方法能有效地区分草原、草甸、裸岩、水体、终年积雪等。     

Application of satellite — based rainfall products and SRTM DEM in hydrological modelling of Brahmaputra basin

Hydrological modelling of large river catchments is a challenging task for water resources engineers due to its complexity in collecting and handling of both spatial and non-spatial data such as rainfall, gauge discharges, and topographic parameters. In this paper an attempt has been made to use satellite-based rainfall products such as Climatic Prediction Centre (CPC)-National Oceanic and Atmospheric Administration (NOAA) data for hydrological modelling of larger catchment where the limited field rainfall data is available. Digital Elevation Models (DEM) such as Global DEM (1 km resolution) and Shuttle Radar Topography Mission (SRTM) 3-arc second (90 m resolution) DEM have been used to extract topographic parameters of the basin for hydrological modelling of the study area. Various popular distributed models have been used in this study for computing excess rainfall, direct runoff from each sub-basin, and flow routing to the main outlet. The Brahmaputra basin, which is very complex both hydraulically and hydrologically due to its shape, size, and geographical location, has been examined as study area in this study. A landuse map derived from the satellite remote sensing data in conjunction with DEM and soil textural maps have been used to derive various basin and channel characteristics such as each sub-basin and channel slope, roughness coefficients, lag-time. Percentage of residual flows computed between observed flows and simulated flows using Global and SRTM DEMs are discussed. It is found that the topographic parameters computed using SRTM DEM could improve the model accuracy in computing flood hydrograph. Need of using better resolution satellite data products and the use of high-density field discharge observations is discussed.     

The impact of radio source structure on European geodetic VLBI measurements

European geodetic very long baseline interferometry (VLBI) sessions (also known as EUROPE sessions) have been carried out on a regular basis for the past 15 years to study relative crustal motions within Europe. These sessions are based on observations of extragalactic radio sources, which serve as distant fiducial marks to establish an accurate and stable celestial reference frame for long-term geodetic measurements. The radio sources, however, are not always point-like on milliarcsecond scales, as VLBI imaging has revealed. In this work, we quantify the magnitude of the expected effect of intrinsic source structure on geodetic bandwidth synthesis delay VLBI measurements for a subset of 14 sources regularly observed during the EUROPE sessions. These sources have been imaged at both X-band (8.4 GHz) and S-band (2.3 GHz) based on dedicated observations acquired with the European VLBI Network (EVN) in November 1996. The results of this calculation indicate that the reference source 0457+024 causes significant structural effects in measurements obtained on European VLBI baselines (about 10 picoseconds on average), whereas most of the other sources produce effects that are only occasionally larger than a few picoseconds. Applying the derived source structure models to the data of the EUROPE5-96 session carried out at the same epoch as the EVN experiment shows no noticeable changes in the estimated VLBI station locations.     

Snow cover area variability assessment in the upper part of the Satluj river basin in India

In high-altitude areas, snow cover plays a significant role in mountainous hydrology. Satluj, which is a snow-fed river, is a part of the Indus River system in the western Himalayas. Snow cover area (SCA) variability in this river basin affects the spatio-temporal flow availability and avalanche events. Keeping this in mind, the present study focuses on SCA variability and its relationship with various topographical features such as elevation, slope and aspect. The study has been carried out in the upper part of the Satluj River Basin on the basis of MODIS Terra (MOD10A2) data from 2001 to 2014. It has been noticed that the average annual SCA in this part of the Satluj River Basin varies from 44 to 56% with an average of about 48% of the total basin area of 16, 650 km². Further, snow accumulation and depletion curves have been suggested for assessing the SCA in the study area.     

CO-Kriging Approach for Cartosat-1 Height Product with ICESat/GLAS Data for Digital Elevation Surface Generation

Nowadays, Geostatistics and its various interpolation techniques have become a major threshold area in the field of research in GIS. In this research work poorly sampled (less accurate height data relative to ICESat/GLAS height data) Cartosat-1 height data has been used with well sampled (more accurate height data relative to Cartosat-1 height data) ICESat/GLAS LiDAR (Light Detection and Ranging) height point data using Cokriging Interpolation technique, to study the effect of ICESat/GLAS on Cartosat-1 height data. Space borne LiDAR data has led researchers to explore its utilities in many applications. Space borne LiDAR data can be acquired through space borne LiDAR sensors also, like; GLAS (Geoscience Laser Altimeter System) system onboard ICESat (Ice, Cloud and land Elevation Satellite) satellite. In this study, it has been tried to apply Cokriging interpolation on two different sources of data sets, with a common variable (elevation) to generate DES and assessment of this surface has been conducted by DGPS data. After optimizing Cokriging parameters, results of digital elevation surface (DES) generated using Cokriging showed that RMSE has been second least than global polynomial in comparison to Kriging interpolation RMSE after being evaluated by GPS values. So, global polynomial as well as cokriging interpolation technique out performs while comparing with kriging technique for DES generation.     

轨迹数据的时间采样间隔对停留识别和出行网络构建的影响

个体轨迹数据已经广泛用于人群活动的研究中。在静止的局部空间开展的活动是个体日常生活的基本元素,在轨迹数据中对应停留部分。因此学者常从轨迹数据中识别停留来研究个体活动信息。然而,轨迹数据的时间采样间隔会对停留识别带来影响。针对该问题,首先提出了一个框架,量化不同持续时间长度的活动在不同时间采样间隔的轨迹数据中被识别为停留的概率。其次,考虑到个体出行网络依赖于停留识别结果,基于该框架,研究分析了时间采样间隔对出行网络分析结果的影响。最后,利用该框架分别对深圳市居民出行调查数据和手机轨迹数据进行了分析。研究表明,在面向人群活动的研究和应用中,该框架能支持时间采样间隔的选择决策和面向活动类型的研究结果评价。     

Application of GIS-based data-driven models for groundwater potential mapping in Kuhdasht region of Iran

Water shortage and population growth in Iran rapidly diminish groundwater supplies. Thus, finding the techniques such as GIS that can be used as powerful tools in groundwater management, and predicting groundwater potential is required. The main objective of this study is to evaluate the efficiency of the statistical index (SI), frequency ratio (FR) weights of evidence (WoE) and evidential belief function (EBF) models for groundwater potential mapping at Kuhdasht region, Lorestan province, Iran. For this purpose, 12 groundwater influencing factors were considered in this investigation. From 171 available wells in the study area, 114 wells (67%) and 57 wells (33%) were used based on random selection in SI, FR, WoE and EBF models as training and validation data-sets, respectively. The area under the ROC curve (AUC) for SI, FR, WoE and EBF models was calculated as 91.8, 91, 93.6 and 93.3%, respectively. These curve values indicated that all four models have reasonably good accuracy in spatially predicting groundwater potential in this area.     

GeoHyp: an adaptive human interface for geologic maps and their databases

A geologic map is typically a 2D representation of 3D subsurface structures in a given area. It is based on the currently accepted geologists' model explaining the observed phenomena and the processes that shaped them in the geologic past. For historical reasons, this model is recorded in a geologic map with an explanatory booklet that describes the authors' conclusions as well as relevant field observations and other data such as tectonic measurements, drill hole logs or fossil records. Today, however, this variety of information can be better handled by converting it into digital and even hypermedial format. This necessitates the prior conception, development and implementation of a suitable geologic “hypermap model”. The main objective of this study is to design models and tools well-suited for the interaction between users and geologic hypermaps. The unique aspect of this family of applications is that users, in general, are both end-users (e.g., engineers) and designers (e.g., mapmakers). Objectives, concepts and methods for developing a human interface to geologic hypermaps have been tested using a prototype (i.e., GeoHyp) within the GIS environment of ArcView from ESRI. Tools to access the underlying background database via hyperlinks have been implemented, as well as functions especially developed to meet specific geologic requirements. Tests with various types of users have shown that the prototype matches their expectations and serves as a good basis for further development. In this article, we report on our design choices for GeoHyp and the current status of our project.     

Methane emission modelling using MODIS thermal and optical data: A case study on Gujarat

Wetlands are one of the most important sources of atmospheric methane (CH₄) contributing about 22% to the global methane budget. But to improve estimates of CH₄ emission at regional and global scales there is a need to observe the sources such as wetlands frequently and develop process-based models. In this regard, wetland inventory using satellite remote sensing data has conventionally been carried out by analysis of optical data. Due to thermal inertia differences emittive thermal channels data has shown promise to provide highly critical information about wetlands such as water spread, aquatic vegetation and mud flats etc. Thermal channels data of MODIS (Moderate Resolution Imaging Spectroradiometer) sensor with a spatial resolution of 1km and swath of 2330 km is emerging as the key source of remote sensing data for global/ regional wetland estimation and assessment of green house gas emission. In the present study MODIS thermal channels (31 and 32) and optical channels (1,2, and 3) data have been used for evaluating methane emission from wetlands in Gujarat. An empirical model based on temperature and productivity has been used to investigate the response of methane emission from different sources. Model has the potential to estimate country level methane emission based on satellite remote sensing in conjunction with collateral data/information. In this study. MODIS data of two dates pertaining to Gujarat have been analyzed and results compared with respect to methane emission.