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Tran T.T.,Vietnam Academy of Science and Technology | Nguyen T.Y.,Vietnam Academy of Science and Technology | Duong C.C.,Institute of Geodesy and Cartography | Vy Q.H.,Vietnam Academy of Science and Technology | And 3 more authors.
Journal of Geodynamics | Year: 2013

The Red River Fault system has a special position in northern Vietnam, forming the boundary between Sunda and South China blocks. The other fault systems include the Dien Bien Phu, Da River and Son La faults. GPS technology has been used to measure recent tectonic activity along these fault zones during the recent years. It is for the first time when all measurement data have been analyzed by GAMIT/GLOBK to get the ITRF2000 solutions for point absolute motion rates of the study area. GPS data collected at 27 stations in northern Vietnam from 1994 to 2007 have shown that the southwestern and northeastern sides of the Red River Fault are moving eastward at the same rate of 34.5. ±. 1. mm/yr and southward, at slightly different velocities of 12. ±. 1. mm/yr and 13. ±. 1. mm/yr, respectively. © 2012 Elsevier Ltd. Source

Musial J.P.,University of Bern | Musial J.P.,Institute of Geodesy and Cartography | Husler F.,University of Bern | Sutterlin M.,University of Bern | And 2 more authors.
Atmospheric Measurement Techniques | Year: 2014

Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability.Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clearsky/ snow conditions. As opposed to th majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm. Source

Boschetti M.,CNR Institute for Electromagnetic Sensing of the Environment | Nutini F.,CNR Institute for Electromagnetic Sensing of the Environment | Nutini F.,University of Milan | Brivio P.A.,CNR Institute for Electromagnetic Sensing of the Environment | And 3 more authors.
ISPRS Journal of Photogrammetry and Remote Sensing | Year: 2013

Studies of the impact of human activity on vegetation dynamics of the Sahelian belt of Africa have been recently re-invigorated by new scientific findings that highlighted the primary role of climate in the drought crises of the 1970s-1980s. Time series of satellite observations revealed a re-greening of the Sahelian belt that indicates no noteworthy human effect on vegetation dynamics at sub continental scale from the 1980s to late 1990s. However, several regional/local crises related to natural resources occurred in the last decades despite the re-greening thus underlying that more detailed studies are needed. In this study we used time-series (1998-2010) of SPOT-VGT NDVI and FEWS-RFE rainfall estimates to analyse vegetation - rainfall correlation and to map areas of local environmental anomalies where significant vegetation variations (increase/decrease) are not fully explained by seasonal changes of rainfall. Some of these anomalous zones (hot spots) were further analysed with higher resolution images Landsat TM/ETM+ to evaluate the reliability of the identified anomalous behaviour and to provide an interpretation of some example hot spots. The frequency distribution of the hot spots among the land cover classes of the GlobCover map shows that increase in vegetation greenness is mainly located in the more humid southern part and close to inland water bodies where it is likely to be related to the expansion/intensification of irrigated agricultural activities. On the contrary, a decrease in vegetation greenness occurs mainly in the northern part (12°-15°N) in correspondence with herbaceous vegetation covers where pastoral and cropping practices are often critical due to low and very unpredictable rainfall. The results of this study show that even if a general positive re-greening due to increased rainfall is evident for the entire Sahel, some local anomalous hot spots exist and can be explained by human factors such as population growth whose level reaches the ecosystem carrying capacity as well as population displacement leading to vegetation recovery. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. Source

Ewiak I.,Institute of Geodesy and Cartography | Kaczynski R.,Military University of Technology
Geodesy and Cartography | Year: 2010

The results of the research project funded by the Polish Ministry of Science and Higher Education are presented. The main aim of the project was an assessment of new Russian satellite data for orthophoto generation. The methodology of the geometrical correction and orthorectification of raw Resurs DK-1 panchromatic images on the basis of metadata analysis with accuracy acceptable for mapping in the scale of 1:10,000 was elaborated and presented. The algorithm of the geometrical correction of Resurs DK-1 image data was elaborated based on the adopted modules valid for IKONOS data which is implemented in the Ortho Engine PCI Geomatica software. Two geometric correction methods have been tested. In each method, the measurements of the image coordinates of Ground Control Points (GCP's) and Independent Check Points (ICP's) along with the use of semi-automatic methods implemented in the Ortho Engine software were performed. A Digital Elevation Model (DEM) with accuracy better than 4m is required. Source

Kowalik W.,Institute of Geodesy and Cartography | Dabrowska-Zielinska K.,Institute of Geodesy and Cartography | Meroni M.,European Commission - Joint Research Center Ispra | Raczka T.U.,Institute of Geodesy and Cartography | de Wit A.,Wageningen University
International Journal of Applied Earth Observation and Geoinformation | Year: 2014

In the period 1999-2009 ten-day SPOT-VEGETATION products of the Normalized Difference Vegetation Index (NDVI) and Fraction of Absorbed Photo synthetically Active Radiation (FAPAR) at 1 km spatial resolution were used in order to estimate and forecast the wheat yield over Europe. The products were used together with official wheat yield statistics to fine-tune a statistical model for each NUTS2 region, based on the Partial Least Squares Regression (PLSR) method. This method has been chosen to construct the model in the presence of many correlated predictor variables (10-day values of remote sensing indicators) and a limited number of wheat yield observations. The model was run in two different modalities:the "monitoring mode", which allows for an overall yield assessment at the end of the growing season,and the "forecasting mode", which provides early and timely yield estimates when the growing seasonis on-going. Performances of yield estimation at the regional and national level were evaluated using across-validation technique against yield statistics and the estimations were compared with those of a reference crop growth model. Models based on either NDVI or FAPAR normalized indicators achieved similar results with a minimal advantage of the model based on the FAPAR product. Best modelling results were obtained for the countries in Central Europe (Poland, North-Eastern Germany) and also Great Britain. By contrast, poor model performances characterize countries as follows: Sweden, Finland, Ireland, Portugal,Romania and Hungary. Country level yield estimates using the PLSR model in the monitoring mode, andthose of a reference crop growth model that do not make use of remote sensing information showed comparable accuracies. The largest estimation errors were observed in Portugal, Spain and Finland for both approaches. This convergence may indicate poor reliability of the official yield statistics in these countries. © 2014 Elsevier B.V. Source

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