Evaluating a thermal image sharpening model over a mixed agricultural landscape in India

Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and to forecast agriculture drought and famine. However, current optical sensors do not provide frequent thermal data at a fine spatial resolution. The TsHARP model provides a possibility to generate fine spatial resolution thermal data from coarse spatial resolution (≥1 km) data on the basis of an anticipated inverse linear relationship between the normalised difference vegetation index (NDVI) at fine spatial resolution and land surface temperature at coarse spatial resolution. The current study utilised the TsHARP model over a mixed agricultural landscape in the northern part of India. Five variants of the model were analysed, including the original model, for their efficiency. Those five variants were the global model (original); the resolution-adjusted global model; the piecewise regression model; the stratified model; and the local model. The models were first evaluated using Advanced Space-borne Thermal Emission Reflection Radiometer (ASTER) thermal data (90 m) aggregated to the following spatial resolutions: 180 m, 270 m, 450 m, 630 m, 810 m and 990 m. Although sharpening was undertaken for spatial resolutions from 990 m to 90 m, root mean square error (RMSE) of <2 K could, on average, be achieved only for 990–270 m in the ASTER data. The RMSE of the sharpened images at 270 m, using ASTER data, from the global, resolution-adjusted global, piecewise regression, stratification and local models were 1.91, 1.89, 1.96, 1.91, 1.70 K, respectively. The global model, resolution-adjusted global model and local model yielded higher accuracy, and were applied to sharpen MODIS thermal data (1 km) to the target spatial resolutions. Aggregated ASTER thermal data were considered as a reference at the respective target spatial resolutions to assess the prediction results from MODIS data. The RMSE of the predicted sharpened image from MODIS using the global, resolution-adjusted global and local models at 250 m were 3.08, 2.92 and 1.98 K, respectively. The local model consistently led to more accurate sharpened predictions by comparison to other variants.     

多尺度空间对象拓扑相似关系的表达与计算

研究了空间数据多尺度表达中,在进行模型综合时空间对象拓扑关系的表达、变化和相似性。基于空间对象之间拓扑关系的概念邻域,给出了空间对象拓扑关系相似性的定义以及在数字景观模型中拓扑关系相似性的度量方法,为空间数据的多尺度表达提供了拓扑关系分析和评价手段。     

建筑物的渐进式图形简化方法

以建筑物轮廓图形的直线段为基本图形单元,研究了建筑物图形渐进式综合的算法以及综合过程中的控制策略和数据预处理方法,并实现了该算法.     

道路网示意性地图的渐进式综合研究

研究并总结了示意性道路网地图的制图规则,量化了约束条件,提出了一种道路网渐进式图形简化方法和移位方法,并研究了拓扑关系检查方法。在具体实验中,通过对道路网上点的分类,依据约束条件,快速生成有效的道路网示意性地图,同时保证了原始道路图与示意性道路图之间的拓扑关系一致性。     

A new technique to determine geoid and orthometric heights from satellite positioning and geopotential numbers

This paper takes advantage of space-technique-derived positions on the Earth’s surface and the known normal gravity field to determine the height anomaly from geopotential numbers. A new method is also presented to downward-continue the height anomaly to the geoid height. The orthometric height is determined as the difference between the geodetic (ellipsoidal) height derived by space-geodetic techniques and the geoid height. It is shown that, due to the very high correlation between the geodetic height and the computed geoid height, the error of the orthometric height determined by this method is usually much smaller than that provided by standard GPS/levelling. Also included is a practical formula to correct the Helmert orthometric height by adding two correction terms: a topographic roughness term and a correction term for lateral topographic mass–density variations.     

SIMD correlator library for GNSS software receivers

Software receivers have had a discernable impact on the GNSS research community. Often such receivers are implemented in a compiled programming language, such as C or C++. A software receiver must emulate the digital signal processing (DSP) algorithms executed on dedicated hardware in a traditional receiver. The DSP algorithms, most notably correlation, have a high computational cost; this burden precludes many software receivers from running in real time. However, the computational cost can be lessened by utilizing single instruction multiple data (SIMD) operations found on modern ×86 processors. The following demonstrates how C/C++ compatible code can be written to directly utilize the SIMD instructions. First, an analysis is carried out to demonstrate why real time operation is not possible when using traditional C/C++ code is carried out. Secondly a tutorial outlines how to write and insert ×86 assembly, with SIMD operations, into C/C++ code. Performance gains achieved via SIMD operations are then demonstrated, and pseudo code outlines how SIMD operations can be employed to perform correlation. Finally, a C/C++ compatible SIMD enabled arithmetic library is added to the GPS Toolbox for use in software receivers.     

Efficient satellite orbit modelling using pseudo-stochastic parameters

If the force field acting on an artificial Earth satellite is not known a priori with sufficient accuracy to represent its observations on their accuracy level, one may introduce so-called pseudo-stochastic parameters into an orbit determination process, e.g. instantaneous velocity changes at user-defined epochs or piecewise constant accelerations in user-defined adjacent time subintervals or piecewise linear and continuous accelerations in adjacent time subintervals. The procedures, based on standard least-squares, associated with such parameterizations are well established, but they become inefficient (slow) if the number of pseudo-stochastic parameters becomes large. We develop two efficient methods to solve the orbit determination problem in the presence of pseudo-stochastic parameters. The results of the methods are identical to those obtained with conventional least-squares algorithms. The first efficient algorithm also provides the full variance–covariance matrix; the second, even more efficient algorithm, only parts of it.     

Simulation of the Ku-band Radar altimeter sea ice effective scattering surface

A radiative transfer model is used to simulate the sea ice radar altimeter effective scattering surface variability as a function of snow depth and density. Under dry snow conditions without layering these are the primary snow parameters affecting the scattering surface variability. The model is initialized with in situ data collected during the May 2004 GreenIce ice camp in the Lincoln Sea (73/spl deg/W; 85/spl deg/N). Our results show that the snow cover is important for the effective scattering surface depth in sea ice and thus for the range measurement, ice freeboard, and ice thickness estimation.     

The Global Impact of Clouds on the Production of MODIS Bidirectional Reflectance Model-Based Composites for Terrestrial Monitoring

A global data set of cloud occurrence probability derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua gridded daily data is analyzed to investigate the probability of obtaining at least a minimum number of cloud-free observations within various compositing periods. The probabilities derived from Terra and Aqua, with morning and afternoon overpass times, respectively, are similar and increase with compositing period. Compositing both Terra and Aqua observations results in considerably higher probabilities of obtaining a sufficient number of observations for bidirectional reflectance model-based compositing. Given that the only alternative to obtaining sufficient samples is to extend the observation period, which can cause significant problems when the surface state changes, it is concluded that using data from the two MODIS sensors provides the most effective way of generating composited products. Findings with respect to the availability of cloud-free composites when n-day composites are generated on a temporally overlapping daily rolling basis, i.e., every day, rather than every n-days, are also discussed for regional and global applications     

Evolutionary stages of the karst-anthropogenic system of the Yucatán Peninsula

An analysis is made of the karst geomorphosystems of the Yucatán Peninsula. It is found that the main factors influencing its formation were climate and ocean level oscillations, tectonic movements, and impact effects. It is established that as a result of an active influence of the Maya civilization on the karst landscape of the peninsula, the geomorphosystems was transformed to the karst-anthropogenic system. The karstic landforms, and also the underground caverns experienced the anthropogenic impact, and the subsurface waters were particularly heavily influenced, which, on the one hand, determined the places of concentration of settlements and were actively consumed by the population, and, on the other, their reserves were replenished at regular intervals as a result of the creation of artificial subsurface water storages. In a further transformation of the karst-anthropogenic system, two stages were additionally identified: dominated by natural karstic processes (after the decline of the Maya civilization), and with a renewed intensification of anthropogenic pressure (1980s–current period). The last transformation stage is distinguished by an extension of the impact to the surface karst as well as to the underground caverns: they are subjected to mechanical destruction with an enhancement in the chemical impact as a result of inputs of polluted runoffs to encompass ever deeper horizons of subsurface waters. It is established that the rates of transformation processes of anthropogenic objects created of limestone are, in general, comparable with the mean rates of natural karstic processes on the neighboring territories: the formation of karrens on Maya steles is generally proceeding at the rate of 0.04 mm/year, while the growth rates of flowstones within urban structures of limestone vary from 0.03 to 0.6 mm/year.