Improving gravity anomalies over China marginal sea from retracked Geosat and ERS-1 data

The quality of altimeter data and ocean tide model is critical to the recovery of coastal gravity anomalies. In this contribution, three retracking methods (threshold, improved threshold and Beta-5) are investigated with the aim of improving the altimeter data over a shallow water area. Comparison indicates that the improved threshold is the best retracking method over China Sea. Two ocean tide models, NAO99b and CSR4.0, are analyzed. Results show that different tide models used in the processing of altimeter data may result in differences more than 10 mGal in recovered coastal gravity anomalies. Also, NAO99b is more suitable than CSR4.0 over the shallow water area of China Sea. Finally, gravity anomalies over China Sea are calculated from retracked Geosat/GM and ERS-1/GM data by least squares collocation. Comparison with shipborne gravimetry data demonstrates that gravity anomalies from retracked data are significantly superior to those from non-retracked data. Our results have the same order as the other two altimeter-derived gravity models: Sandwell&Smith(V16) and DNSC08.     

Vulnerability Assessment and Earthquake Risk Mapping in Part of North Iran Using Geospatial Techniques

Earthquakes cause huge loss of lives and infrastructure every year in Iran. Many settlement areas (urban & rural) as well as Tehran, the capital city of Iran are located in the hazardous area. This research deals with the earthquake risk assessment and mapping based on recent remote sensing information on a GIS platform. The study area is part of Central Alborz in southern Caspian Sea and north of capital city of Tehran called Marzanabad area. It is a potentially high-risk zone as several earthquakes have occurred in the past. The study’s main objective is to develop an Earthquake Risk Map at the scale of 1:25,000 to identify high-risk zone and vulnerability areas to the settlements and infrastructure of area. Digital lineaments wear extraction and analysis for identification the faults using several RADAR and optical images with spatial analysis techniques. The probable faults were detected by superimposition of the lithological and geomorphologic features and their variance over the lineaments in a GIS environment. This research work involved fault identification on the remote sensed dataset as well as field studies and the risky areas were classified in the vicinity of the faults by applying different buffer with specifying distance of the source/site of risk to fault location. Statistical analysis of Earthquake Risk Map (ERM) by GIS indicated that 32% of the total area with about 66% of settlements and 52% of population is located in strongly high-risk and high-risk zone. Moderately low risk and low risk zones cover 38.67% of total area, which is free of settlements as well as population. The Earthquake map elaborated in this research work will be a useful tool for disaster management as well as urban and regional planning of future activities in the area.     

An Introduction to MODISI and SCMOD Methods for Correction of the MODIS Snow Assessment Algorithm

Detection, monitoring and precise assessment of the snow covered regions is an important issue. Snow cover area and consequently the amount of runoff generated from snowmelt have a significant effect on water supply management. To precisely detect and monitor the snow covered area we need satellite images with suitable spatial and temporal resolutions where we usually lose one for the other. In this study, products of two sensors MODIS and ASTER both on board of TERRA platform having low and high spatial resolution respectively were used. The objective of the study was to modify the snow products of MODIS by using simultaneous images of ASTER. For this, MODIS snow index image with high temporal resolution were compared with that of ASTER, using regression and correlation analysis. To improve NDSI index two methods were developed. The first method generated from direct comparison of ASTER averaged NDSI with those of MODIS (MODISI). The second method generated by dividing MODIS NDSI index into 10 codes according to their percentage of surface cover and then compared the results with the difference between ASTER averaged and MODIS snow indices (SCMOD). Both methods were tested against some 16 MODIS pixels. It is found that the precision of the MODISI method was more than 96%. This for SCMOD was about 98%. The RMSE of both methods were as good as 0.02.     

Regaining momentum for international climate policy beyond Copenhagen

The 'Copenhagen Accord' fails to deliver the political framework for a fair, ambitious and legally-binding international climate agreement beyond 2012. The current climate policy regime dynamics are insufficient to reflect the realities of topical complexity, actor coalitions, as well as financial, legal and institutional challenges in the light of extreme time constraints to avoid 'dangerous' climate change of more than 2°C. In this paper we analyze these stumbling blocks for international climate policy and discuss alternatives in order to regain momentum for future negotiations.     

Improvement of user’s accuracy through classification of principal component images and stacked temporal images

The classification accuracy of the various categories on the classified remotely sensed images are usually evaluated by two different measures of accuracy, namely, producer’s accuracy (PA) and user’s accuracy (UA). The PA of a category indicates to what extent the reference pixels of the category are correctly classified, whereas the UA of a category represents to what extent the other categories are less misclassified into the category in question. Therefore, the UA of the various categories determines the reliability of their interpretation on the classified image and is more important to the analyst than the PA. The present investigation has been performed in order to determine if there occurs improvement in the UA of the various categories on the classified image of the principal components of the original bands and on the classified image of the stacked image of two different years. We performed the analyses using the IRS LISS III images of two different years, i.e., 1996 and 2009, that represent the different magnitude of urbanization and the stacked image of these two years pertaining to Ranchi area, Jharkhand, India, with a view to assessing the impacts of urbanization on the UA of the different categories. The results of the investigation demonstrated that there occurs significant improvement in the UA of the impervious categories in the classified image of the stacked image, which is attributable to the aggregation of the spectral information from twice the number of bands from two different years. On the other hand, the classified image of the principal components did not show any improvement in the UA as compared to the original images.     

Accuracy improvement of ASTER stereo satellite generated DEM using texture filter

The grid DEM(digital elevation model) generation can be from any of a number of sources:for instance,analogue to digital conversion of contour maps followed by application of the TIN model,or direct elevation point modelling via digital photogrammetry applied to airborne images or satellite images.Currently,apart from the deployment of point-clouds from LiDAR data acquisition,the generally favoured approach refers to applications of digital photogrammetry.One of the most important steps in such deployment i...     

Geo-scape,a granularity depended spatialization tool for visualizing multidimensional data sets

Recently,the expertise accumulated in the field of geovisualization has found application in the visualization of abstract multidimensional data,on the basis of methods called spatialization methods.Spatialization methods aim at visualizing multidimensional data into low-dimensional representational spaces by making use of spatial metaphors and applying dimension reduction techniques.Spatial metaphors are able to provide a metaphoric framework for the visualization of information at different levels of gran...     

山东沂沭河流域2000BC前后古文化兴衰的环境考古

Neolithic culture series in the Yishu River Basin developed in the order of Beixin culture-Dawenkou culture-Longshan culture-Yueshi culture. During the early and middle stage of Longshan culture （4600-4300 cal. yr BP）, the climate in the Yishu River Basin was warm and wet. Paddy-oriented agriculture planted paddy was very developed. The society was flourishing with great amount of archaeological sites. The cooling starting in 4200 cal. yr BP made the paddies shortfall in output or even no seeds were gathered. This situation intensified the discrepancy between population and resource. The scarcity in natural resource led to substantial decrease in population and subsequent drop in archaeological sites. About 4000 cal. yr BP Longshan culture was displaced by Yueshi culture which was relatively un- derdeveloped, simple and unsophisticated.     

Distribution of arsenic and mercury in subtropical coastal beachrock,Gulf of Mannar,India

An assessment of coastal pollution was made on the basis of trace element concentrations (arsenic — As, mercury — Hg) in the Gulf of Mannar. The beachrock samples were collected along the coastal tracts between Rameswaram and Kanyakumari. The samples were dried and digested to determine the As and Hg using atomic absorption spectrophotometer (AAS-air-acetylene and nitrous oxide method). The As and Hg accumulation status of the beachrock was assessed using geo-accumulation index values (I _geo). The accumulation of As and Hg in the beachrock ranges from 2.75 to 20.72 μg g⁻¹ and from 0.06 to 0.31 μg g⁻¹, respectively. The As and Hg concentrations in the beachrocks are compared with crustal average values and average of other region sediments. The possible source of the contamination is from atmospheric deposition and anthropogenic activities.     

Inversion of Vegetation Components Based on the Spectral Mixture Analysis Using Hyperion Data

Hyper spectral remote sensing is widely used to identify ground objects as a result of the advantages of ground radiation intensity characteristics and spectral position characteristics, in which inversion of vegetation components is the difficult point and hotspot. In this study, Huma county of Heilongjiang Province was selected as the study area, the canopy spectra of four types of typical vegetation were measured in situ firstly, including mongolian oak, cotton grass, lespedeza and white birch. Then, on the basis of analyzing the canopy spectral characteristics and their parameterization, the spectral differences of different vegetations were located, and the parameterization method of characteristics identification was determined. Finally, Hyperion data were used to calculate the canopy albedos based on the bidirectional reflectance model of vegetation canopies, and to map the vegetation components in the study area by use of linear spectral mixture model. The results showed that inversion of vegetation components in high vegetation-covered area was accurate using the canopy albedos and liner spectral mixture model, and was identical with the field sampling, which validated the feasibility of canopy albedos and liner spectral mixture model for the inversion of vegetation components.