区域重力调查成果在江苏地区高精度水准测量改正中的适用性分析

本文分析了空间重力异常精度对水准测量高差重力异常改正的影响.在江苏两处试验区分别采用实测重力和布格异常数据库两种改正方法,计算测段重力异常改正值,对比两者间的差异.结果表明:未顾及地形起伏的实测重力点分布是导致两种改正方法改正值差异大的主要因素;地形起伏较大区域,水准线路出现转折或倾斜过大时,需加测重力,采用实测重力进...     

Local geoid determination combining gravity disturbances and GPS/levelling: a case study in the Lake Nasser area, Aswan, Egypt

 The use of GPS for height control in an area with existing levelling data requires the determination of a local geoid and the bias between the local levelling datum and the one implicitly defined when computing the local geoid. If only scarse gravity data are available, the heights of new data may be collected rapidly by determining the ellipsoidal height by GPS and not using orthometric heights. Hence the geoid determination has to be based on gravity disturbances contingently combined with gravity anomalies. Furthermore, existing GPS/levelling data may also be used in the geoid determination if a suitable general gravity field modelling method (such as least-squares collocation, LSC) is applied. A comparison has been made in the Aswan Dam area between geoids determined using fast Fourier transform (FFT) with gravity disturbances exclusively and LSC using only the gravity disturbances and the disturbances combined with GPS/levelling data. The EGM96 spherical harmonic model was in all cases used in a remove–restore mode. A total of 198 gravity disturbances spaced approximately 3 km apart were used, as well as 35 GPS/levelling points in the vicinity and on the Aswan Dam. No data on the Nasser Lake were available. This gave difficulties when using FFT, which requires the use of gridded data. When using exclusively the gravity disturbances, the agreement between the GPS/levelling data were 0.71 ± 0.17 m for FFT and 0.63 ± 0.15 for LSC. When combining gravity disturbances and GPS/levelling, the LSC error estimate was ±0.10 m. In the latter case two bias parameters had to be introduced to account for a possible levelling datum difference between the levelling on the dam and that on the adjacent roads. Received: 14 August 2000 / Accepted: 28 February 2001     

The determination of potential difference by the joint application of measured and synthetical gravity data: a case study in Hungary

In an elementary approach every geometrical height difference between the staff points of a levelling line should have a corresponding average g value for the determination of potential difference in the Earth’s gravity field. In practice this condition requires as many gravity data as the number of staff points if linear variation of g is assumed between them. Because of the expensive fieldwork, the necessary data should be supplied from different sources. This study proposes an alternative solution, which is proved at a test bed located in the Mecsek Mountains, Southwest Hungary, where a detailed gravity survey, as dense as the staff point density (~1 point/34 m), is available along a 4.3-km-long levelling line. In the first part of the paper the effect of point density of gravity data on the accuracy of potential difference is investigated. The average g value is simply derived from two neighbouring g measurements along the levelling line, which are incrementally decimated in the consecutive turns of processing. The results show that the error of the potential difference between the endpoints of the line exceeds 0.1 mm in terms of length unit if the sampling distance is greater than 2 km. Thereafter, a suitable method for the densification of the decimated g measurements is provided. It is based on forward gravity modelling utilising a high-resolution digital terrain model, the normal gravity and the complete Bouguer anomalies. The test shows that the error is only in the order of 10⁻³mm even if the sampling distance of g measurements is 4 km. As a component of the error sources of levelling, the ambiguity of the levelled height difference which is the Euclidean distance between the inclined equipotential surfaces is also investigated. Although its effect accumulated along the test line is almost zero, it reaches 0.15 mm in a 1-km-long intermediate section of the line.     

Global mean sea surface and marine gravity anomaly from multi-satellite altimetry: applications of deflection-geoid and inverse Vening Meinesz formulae

 Global mean sea surface heights (SSHs) and gravity anomalies on a 2^′×2^′ grid were determined from Seasat, Geosat (Exact Repeat Mission and Geodetic Mission), ERS-1 (1.5-year mean of 35-day, and GM), TOPEX/POSEIDON (T/P) (5.6-year mean) and ERS-2 (2-year mean) altimeter data over the region 0^∘–360^∘ longitude and –80^∘–80^∘ latitude. To reduce ocean variabilities and data noises, SSHs from non-repeat missions were filtered by Gaussian filters of various wavelengths. A Levitus oceanic dynamic topography was subtracted from the altimeter-derived SSHs, and the resulting heights were used to compute along-track deflection of the vertical (DOV). Geoidal heights and gravity anomalies were then computed from DOV using the deflection-geoid and inverse Vening Meinesz formulae. The Levitus oceanic dynamic topography was added back to the geoidal heights to obtain a preliminary sea surface grid. The difference between the T/P mean sea surface and the preliminary sea surface was computed on a grid by a minimum curvature method and then was added to the preliminary grid. The comparison of the NCTU01 mean sea surface height (MSSH) with the T/P and the ERS-1 MSSH result in overall root-mean-square (RMS) differences of 5.0 and 3.1 cm in SSH, respectively, and 7.1 and 3.2 μrad in SSH gradient, respectively. The RMS differences between the predicted and shipborne gravity anomalies range from 3.0 to 13.4 mGal in 12 areas of the world's oceans. Received: 26 September 2001 / Accepted: 3 April 2002 Correspondence to: C. Hwang Acknowledgements. This research is partly supported by the National Science Council of ROC, under grants NSC89-2611-M-009-003-OP2 and NSC89-2211-E-009-095. This is a contribution to the IAG Special Study Group 3.186. The Geosat and ERS1/2 data are from NOAA and CERSAT/France, respectively. The T/P data were provided by AVISO. The CLS and GSFC00 MSS models were kindly provided by NASA/GSFC and CLS, respectively. Drs. Levitus, Monterey, and Boyer are thanked for providing the SST model. Dr. T. Gruber and two anonymous reviewers provided very detailed reviews that improved the quality of this paper.     

Integrating data from remote sensing,geology and gravity for geological investigation in the Tarhunah area,Northwest Libya

Abstract

The present work deals with the integration of remote-sensing, surface-geology and gravity-survey data to improve the structural knowledge of the Tarhunah area, northwest Libya. Geological information and remote-sensing data provided information about the surface structure. A gravity survey was conducted to decipher the subsurface structure. The results revealed that a basin having a width of 39 to 48 km trends NE. A two-dimensional (2-D) schematic model shows that the basin gradually deepens toward the southwest. Faults determined from a horizontal gradient, tilt derivative, and Euler deconvolution show a depth range of 2.5 to 7.5 km. The integration and interpretation of the results indicate that volcanic activity was related to the tectonic activity of an anticlinal structure called the Jabal Uplift.     

Improving a digital elevation model by reducing source data errors and optimising interpolation algorithm parameters: An example in the Loess Plateau,China

A hydrologically correct digital elevation model (DEM) forms a basis for realistic environmental modelling, especially in complex terrain. We have performed a study in the Coarse Sandy Hilly Catchments (CSHC) of the Loess Plateau, China, which demonstrates pragmatic, yet effective methods for improving the quality of the DEM by: (1) identifying and correcting source topographic data errors and (2) optimising ANUDEM algorithm parameters. Improvement in the DEM based on fixing over 1100 errors in the input topographic data, and optimising key ANUDEM parameters was assessed using higher accuracy independent validation of 32 contributing areas and 1474 spot heights, and by semi-quantitative analysis of DEM derivatives produced from ANUDEM and Triangular Irregular Network (TIN) algorithms. Improvement in the ANUDEM DEM over the original TIN DEM was shown where the percentage of the total absolute difference in contributing areas reduced from 10.43 to 3.51%, and the bias between the spot heights and DEM elevations reduced from 45 to 32 m. Large improvement in DEM quality was gained by using ANUDEM instead of TIN, with smaller improvement gained by fixing source data errors, and optimising ANUDEM parameters.     

Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis—A case study in Tengchong,China

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. Based on radiometric calibration, atmospheric correction and emissivity calculation, a simple but efficient single channel algorithm with acceptable precision is applied to retrieve the land surface temperature (LST) of study area. The LST anomalous areas with temperature about 4–10 K higher than background area are discovered. Four geothermal areas are identified with the discussion of geothermal mechanism and the further analysis of regional geologic structure. The research reveals that the distribution of geothermal areas is consistent with the fault development in study area. Magmatism contributes abundant thermal source to study area and the faults provide thermal channels for heat transfer from interior earth to land surface and facilitate the present of geothermal anomalies. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect LST anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.     

Estimation of the zero-height geopotential level W o LVD in a local vertical datum from inversion of co-located GPS, leveling and geoid heights: a case study in the Hellenic islands

The estimation of the zero-height geopotential level of a local vertical datum (LVD) is a key task towards the connection of isolated physical height frames and their unification into a common vertical reference system. Such an estimate resolves, in principle, the ‘ambiguity’ of a traditional crust-fixed LVD by linking it with a particular equipotential surface of Earth’s gravity field under the presence of an external geopotential model. The aim of this paper is to study the estimation scheme that can be followed for solving the aforementioned problem based on the joint inversion of co-located GPS and leveling heights in conjunction with a fixed Earth gravity field model. Several case studies with real data are also presented that provide, for the first time, precise estimates of the LVD offsets for a number of Hellenic islands across the Aegean and Ionian Sea.     

Systematic errors in the Z-geocenter derived using satellite tracking data: a case study from SPOT-4 DORIS data in 1998

Within the scope of the Global Geodetic Observing System, Doppler Orbit Determination and Radiopositioning Integrated by Satellite – as a geodetic technique – can provide precise and continuous monitoring of the geocenter motion related to mass redistribution in the Earth, ocean and atmosphere system. We have reanalyzed 1998 DORIS/SPOT-4 (Satellite pour l’ Observation de la Terre) data that were previously generating inconsistent geocenter positions (?65 cm offset). We show here that this error is due to an incorrect phase center correction provided with the DORIS preprocessed data resulting from a +12 cm offset in the cross-track direction that has been confirmed since. We also conclude that a 1 mm error in the cross-track offset of non-yawing sun-synchronous SPOT satellites will generate a ?6.5 mm error in the derived Z-geocenter. Other non-yawing satellites would also be affected by a similar effect whose amplitude could be easily estimated from the orbit inclination     

Glacier and glacial lake classification for change detection studies using satellite data: a case study from Baspa basin,western Himalaya

Using high-resolution Google Earth^TM images in conjunction with Landsat images, the glaciers and lakes in the Baspa basin are classified to explore the recent changes. A total number of 109 glaciers (187 ± 3.7 km²) are mapped and subsequently classified as compound valley glaciers, simple valley glaciers, cirques, niches, glacieretes and ice aprons. The compound and simple valley glaciers contribute 67.1 ± 1.3% and 19.8 ± 0.3% to the total glacier cover of the basin. Similarly, a total number of 129 glacial lakes (0.360 ± 0.007 km²) are identified. From 1976 to 2011, the compound valley glaciers have lost a small area of 10.3 ± 0.03% at a rate of 0.41 ± 0.002 km² a^-1, whereas the niche glaciers have lost higher area of 40.1 ± 0.001% at a rate of 0.04 ± 0.0001 km² a^-1. Change detection of two benchmark glacial lakes revealed a progressive expansion during recent decades. The Baspa Bamak proglacial lake has expanded from 0.020 ± 0.0004 km² (2000) to 0.069 ± 0.001 km² (2011). Due to the complete loss of source ice, another glacial lake has expanded from 0.09 ± 0.001 km² (1994) to 0.10 ± 0.002 km² (2011). During the study period, the mean annual temperature that is T_avg, T_min and T_max have increased significantly at the 95% confidence level by 1.5 ^oC (0.070 °C a^-1), 1.8 ^oC (0.076 °C a^-1) and 1.6 ^oC (0.0071 °C a^-1) from 1985 to 2008. However, the precipitation has decreased significantly from 1976 and 1985 to 2008.     

Space,time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data

ABSTRACT

Various methods have been developed to investigate the geospatial information, temporal component, and message content in disaster-related social media data to enrich human-centric information for situational awareness. However, few studies have simultaneously analyzed these three dimensions (i.e. space, time, and content). With an attempt to bring a space–time perspective into situational awareness, this study develops a novel approach to integrate space, time, and content dimensions in social media data and enable a space–time analysis of detailed social responses to a natural disaster. Using Markov transition probability matrix and location quotient, we analyzed the Hurricane Sandy tweets in New York City and explored how people’s conversational topics changed across space and over time. Our approach offers potential to facilitate efficient policy/decision-making and rapid response in mitigations of damages caused by natural disasters.     

Application of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak,Kerman, south of Iran

Abstract

The Shahr-e-Babak region located in the Kerman metallogenic belt is one of the high potential segments of Urumieh–Dokhtar magmatic arc for porphyry copper and epithermal gold mineralization in the south of Iran. This high potential zone encompasses several porphyry copper deposits under exploitation, development and exploration stages. The aim of this study is to evaluate Landsat-8 data and comparison with the Advanced Spaceborne Thermal Emission and Reflection Radiometer data-sets for mapping hydrothermal alteration zones related to Cenozoic magmatic intrusions in Shahr-e-Babak region. Previous studies have proven the robust application of ASTER in lithological mapping and mineral exploration; nonetheless, the Landsat-8 data have high capability to map and detect hydrothermal alteration zones associated with porphyry copper and epithermal gold mineralization. In this investigation, several band combinations and multiplications, developed selective principal component analysis and image transformations were developed for discriminating hydrothermal alteration zones associated with porphyry copper mineralization using Landsat-8 data.     

Challenges and lessons from a wetland LiDAR project: a case study of the Okefenokee Swamp,Georgia, USA

Airborne LiDAR (Light Detection and Ranging) provides opportunities to generate high-quality digital elevation models (DEMs) even in wetland environments. Our project, performed over the Okefenokee Swamp in Georgia during the spring of 2010, shows that several, distinctive factors must be considered to ensure successful wetland LiDAR projects. Some of the challenges include selecting optimal flight times in accordance with weather variability and water levels, having effective and quality control protocols, applying and developing filtering and interpolation algorithms, breaklines in swamps and accounting for data striping and noise. While some of these issues are faced in any airborne LiDAR acquisition, many of these require special consideration in a low-slope wetland environment with water saturated soils, widespread shallow water, and sediments and extensive vegetation. An examination of these issues and how they were handled will help in ensuring the success of future LiDAR acquisitions and, in particular, will advance knowledge of producing quality DEMs in wetland environments.     

A method for groundwater prospect zonation in data poor areas using remote sensing and GIS: a case study in Kalikavu Panchayath of Malappuram district,Kerala, India

Abstract

The present study was an attempt to delineate potential groundwater zones in Kalikavu Panchayat of Malappuram district, Kerala, India. The geo-spatial database on geomorphology, landuse, geology, slope and drainage network was generated in a geographic information system (GIS) environment from satellite data, Survey of India topographic sheets and field observations. To understand the movement and occurrence of groundwater, the geology, geomorphology, structural set-up and recharging conditions have to be well understood. In the present study, the potential recharge areas are delineated in terms of geology, geomorphology, land use, slope, drainage pattern, etc. Various thematic data generated were integrated using a heuristic method in the GIS domain to generate maps showing potential groundwater zones. The composite output map scores were reclassified into different zones using a decision rule. The final output map shows different zones of groundwater prospect, viz., very good (15.57% of the area), good (43.74%), moderate (28.38%) and poor (12.31%). Geomorphic units such as valley plains, valley fills and alluvial terraces were identified as good to excellent prospect zones, while the gently sloping lateritic uplands were identified as good to moderate zones. Steeply sloping hilly terrains underlain by hard rocks were identified as poor groundwater prospect zones.     

Regional land-use allocation using a coupled MAS and GA model: from local simulation to global optimization,a case study in Caidian District,Wuhan, China

China is facing the pressures of both rapid economic development and environmental protection, and land-use allocation optimization is an important way to manage the conflicts between these pressures and to achieve sustainable development. Optimization of land-use allocation is a nonlinear multiobjective spatial optimization problem, and a purely local simulation model or global optimization model is insufficient to solve it. It is essential to bridge the gap between the two models through the combination of top-down and bottom-up approaches. This study integrates a multiagent system (MAS) that simulates the behaviors of land-use stakeholders with regard to their choices of specific locations, with a genetic algorithm (GA) that simultaneously evaluates and optimizes land-use configurations to meet various regional development objectives. The model is expected to achieve the optimization of land use in terms of the composition and spatial configuration. Caidian District, Wuhan, China, was chosen as the study area to test the model in this paper. The results show that the performance of the coupled model is superior to a pure GA model or MAS model. The optimal configuration improves on the economic output, spatial compactness, and carbon storage of the current configuration and promotes sustainable regional land-use development from the local scale to the regional scale.     

基于多源数据的城市建设用地扩张时空特征分析——以佛山市顺德区为例

随着我国城市化进程的加快,城市建设用地规模进一步增加,同时带来交通拥堵、环境污染、绿地减少、城市热岛等城市问题。本文综合利用2015年地理国情普查数据、2011和2013年遥感数据,通过建立城市扩张强度指数,运用统计分析、空间聚类等方法,确定了顺德区建设用地在过去4年间年均增长率为1.8%,其中新城区的年均增长率超过14%;此外还发现主城区的扩展模式主要为填充式扩展,其中大良街道和勒流街道主要为工业园区的扩展,伦教街道主要为中央公园的扩展,容桂街道主要为物流园的扩展。     

Groundwater potential in the hard rock terrain of western ghats: A case study from Kottayam district,Kerala using resourcesat (IRS-P6) data and GIS techniques

The present study was aimed to identify and delineate the groundwater potential areas in parts of Western Ghats, Kottayam, covering the upper catchment of Meenachil river. The study area is composed rocks of Archaean age and Charnockite dominated over others. The information on lithology, geomorphology, lineaments, slope and land use/land cover was generated using the Resourcesat (IRS P6 LISS III) data and Survey of India (Sol) toposheets of scale 1:50,000 (surveyed in 1969) and integrated them with raster based Geographical Information System (GIS) to identify the groundwater potential of the study area. Thus, a GIS-based model which takes account of local condition/variations has been developed specifically for mapping groundwater potential. On the basis of hydrogeomorphology, three categories of groundwater potential zones namely good, moderate and poor were identified, and delineated. The high potential zones correspond to the fracture valleys, valley fills, pediments and denudational slope, which coincide with the low slope and high lineaments density areas. The low zone mainly comprise structural hills and escarpments and these act as run-off zones. The derived panchayath-wise groundwater potentiality information could be used for effective identification of suitable locations for extraction of potable water for rural populations.     

Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng,China

Simulations of intra-urban land use changes have gradually attracted more attention as these approaches are extremely helpful in regard to decision making and policy formulation. While prior studies mostly focused on methods of developing intra-urban level simulations, very little research has been conducted explain the factors driving intra-urban land use change. Urban planners are highly concerned with how inner-city structures are formed and how they function. Here, to simulate multiple intra-urban land use changes and to identify the contribution of different driving factors, we developed a random forests (RF) algorithm-based cellular automata (CA) simulation model. In this study, the model applied diverse categories of spatial variables, including traffic location factors, environmental factors, public services, and population density, as the driving factors to enhance our understanding of the dynamics of internal urban land use. The CA model was tested using data from the Huicheng district of Huizhou city in the Guangdong province of China. The Model was validated using actual historical land use data from 2000 to 2010. By applying the validated model, multiple intra-urban land use maps were simulated for 2015. Simultaneously, spatial variable importance measures (VIMs) were calculated by using the out-of-bag (OOB) error estimation approach of the RF algorithm. Based on the calculation results, we assessed and analysed the significance of each intra-urban land use driver for this region. This study provides urban planners and relevant scholars with detailed and targeted information that can aid in the formulation of specific planning strategies for different intra-urban land uses and support the future evolution of this area.     

Monitoring surface changes in discontinuous permafrost terrain using small baseline SAR interferometry,object-based classification,and geological features: a case study from Mayo,Yukon Territory,Canada

Permafrost-induced deformation of ground features is threating infrastructure in northern communities. An understanding of permafrost distribution is therefore critical for sustainable adaptation planning and infrastructure maintenance. Considering the large area underlain by permafrost in the Yukon Territory, there is a need for baseline information to characterize the permafrost in this region. In this study, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique was used to identify areas of ground movement likely caused by changes in permafrost. The DInSAR technique was applied to a series of repeat-pass C-band RADARSAT-2 observations collected in 2015 over the Village of Mayo, in central Yukon Territory, Canada. The conventional DInSAR technique demonstrated that ground deformation could be detected in this area, but the resulting deformation maps contained errors due to a loss of coherence from changes in vegetation and atmospheric phase delay. To address these limitations, the Small BAseline Subset (SBAS) InSAR technique was applied to reduce phase error, thus improving the deformation maps. To understand the relationship between the deformation maps and land cover types, an object-based Random Forest classification was developed to classify the study area into different land cover types. Integration of the InSAR results and the classification map revealed that the built-up class (e.g., airport) was affected by subsidence on the order of ?2 to ?4 cm. The spatial extent of the surface displacement map obtained using the SBAS InSAR technique was then correlated with the surficial geology map. This revealed that much of the main infrastructure in the Village of Mayo is underlain by interbedded glaciofluvial and glaciolacustrine sediments, the latter of which caused the most damage to human made structures. This study provides a method for permafrost monitoring that builds upon the synergistic use of the SBAS InSAR technique, object-based image analysis, and surficial geology data.     

Development of an image based integrated method for determining and mapping aerosol optical thickness (AOT) over urban areas using the darkest pixel atmospheric correction method,RT equation and GIS: A case study of the Limassol area in Cyprus

This paper presents the development of an image-based integrated method for determining and mapping aerosol optical thickness (AOT). Using the radiative transfer (RT) equation, a methodology was developed to create a Geographical Information System (GIS) model that can visually display the AOT distribution over urban areas. In this paper, the model was applied to eleven Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) satellite images of Limassol, Cyprus during 2010 and 2011 to determine the AOT levels in Limassol Cyprus during satellite overpass. The study is innovative and unique in that the RT equation, satellite images, the darkest pixel (DP) method of atmospheric correction and GIS were integrated to derive AOT from satellite images and display the AOT distribution over an urban area without the input of any meteorological or atmospheric parameters. The accuracy of the algorithm was verified through statistical analysis by the strong agreement between the AOT values derived using the algorithm and the in situ AOT values from the ground-based sensors.