Surface Reflectance Climate Data Records (CDRs) is a Reliable Landsat ETM+ Source to Study Chlorophyll Content in Pecan Orchards

We evaluated the relationships among three Landsat Enhanced Thematic Mapper (ETM+) datasets, top-of-atmosphere (TOA) reflectance, surface reflectance climate data records (surface reflectance-_CDR) and atmospherically corrected images using Fast Line-of-Sight atmospheric analysis of Spectral Hypercubes model (surface reflectance-_FLAASH) and their linkto pecan foliar chlorophyll content(chl-cont). Foliar chlorophyll content as determined with a SPAD meter, and remotely-sensed data were collected from two mature pecan orchards (one grown in a sandy loam and the other in clay loam soil) during the experimental period. Enhanced vegetation index derived from remotely sensed data was correlated to chl-cont. At both orchards, TOA reflectance was significantly lower than surface reflectance within the 550–2400 nm wavelength range. Reflectance from atmospherically corrected images (surface reflectance-_CDR and surface reflectance-_FLAASH) was similar in the shortwave infrared (SWIR: 1550–1750 and 2080–2350 nm) and statistically different in the visible (350–700 nm). Enhanced vegetation index derived from surface reflectance-_CDR and surface reflectance-_FLAASH had higher correlation with chl-cont than TOA. Accordingly, surface reflectance is an essential prerequisite for using Landsat ETM+  data and TOA reflectance could lead to miss-/or underestimate chl-cont in pecan orchards. Interestingly, the correlation comparisons (Williams t test) between surface reflectance-_CDR and chl-cont was statistically similar to the correlation between chl-cont and commercial atmospheric correction model. Overall, surface reflectance-_CDR, which is freely available from the earth explorer portal, is a reliable atmospherically corrected Landsat ETM+ image source to study foliar chlorophyll content in pecan orchards.     

Fòlaga: A low-cost autonomous underwater vehicle combining glider and AUV capabilities

The paper describes the current developments of a class of low-cost, light-weight autonomous underwater vehicles for coastal oceanographic applications; the vehicle class is named Fòlaga, the Italian name of an aquatic bird that swims on the water surface and dives to catch fish. The main design characteristics of the most recent vehicle of the class, the Fòlaga III, are reviewed. Navigation and control system design are discussed, with particular attention to the diving phase, which is accomplished as in oceanographic gliders by varying the vehicle buoyancy and attitude. Experimental results show that the PID robust controllers implemented are effective in the diving control phase. Finally, a distributed cooperation algorithm to be applied by a team of Fòlaga-like vehicles in adaptive oceanographic sampling applications is described. The algorithm optimizes area coverage while taking into account the accuracy in the reconstruction of the oceanographic field and inter-vehicle communication through a range constraint. The resulting dynamic programming algorithm can be implemented in a distributed fashion among the team components.     

南海地区热通量的时空变化特征

本文利用美国 NCEP1958-1998 年高斯网格月平均再分析资料,分析了南海及周边地区(0～20°N,100～125°E)热通量(包括潜热通量和感热通量)的时空变化,结果表明该潜热通量、感热通量具有明显的季节转换特征.南海中部海区是潜热通量、感热通量季节变化最剧烈的关键区,南海季风对潜热、感热输送均有影响,并且蒸发潜热输送大于感热输送.EOF 分析表明,风速对潜热、感热输送贡献较大,另外气温和相对湿度对潜热输送有贡献,而水温与气温差对感热输送有贡献.整个南海地区潜热通量、感热通量具有明显的年际变化特征,潜热通量存在5～8 a 以及 2 a 左右的周期振动,而感热通量只有 5～8 a 的周期振动.     

Localization of autonomous underwater vehicles by floating acoustic buoys: a set-membership approach

This paper addresses localization of autonomous underwater vehicles (AUVs) from acoustic time-of-flight measurements received by a field of surface floating buoys. It is assumed that measurements are corrupted by unknown-but-bounded errors, with known bounds. The localization problem is tackled in a set-membership framework and an algorithm is presented, which produces as output the set of admissible AUV positions in a three-dimensional (3-D) space. The algorithm is tailored for a shallow water situation (water depth less than 500 m), and accounts for realistic variations of the sound speed profile in sea water. The approach is validated by simulations in which uncertainty models have been obtained from field data at sea. Localization performance of the algorithm are shown comparable with those previously reported in the literature by other approaches who assume knowledge of the statistics of measurement uncertainties. Moreover, guaranteed uncertainty regions associated to nominal position estimates are provided. The proposed algorithms can be used as a viable alternative to more traditional approaches in realistic at-sea conditions.     

Mapping ocean sediments by RBF networks

Estimation of ocean-sediment properties by sparse noisy measurements using generalized Radial Basis Function networks is proposed. Given a set of scattered data points, an RBF network is able to generate a continuous smooth approximation for sediment properties as a function of the x-y-z position, where z is the sediment depth. Advantages and disadvantages of the method are discussed, from both a physical and a computational viewpoint. An example using sediment density data obtained by sparse core measurements and different configurations of RBF networks is presented     

提升小波变换在气象格点数据无损压缩中的应用

提升小波变换实现了整数到整数的变换,同时保证了小波变换的正交特性。在二维预测编码基础上引入提升小波变换,并结合"洗牌"技术和熵编码,设计了气象格点数据的无损压缩方案。以位势高度、经向风、纬向风、温度4个要素为例,对数据处理前后的熵值进行了对比分析,并设计了4种方案进行验证。结果表明:提升小波变换能有效去除数据间的相关性,消除冗余信息,降低数据集的熵值,与二维预测编码相结合能实现优势互补,提高压缩效率,并能保证在有效精度内数据完全无损,从而有效提高气象海量数据的存储和传输效率,为快速气象数据响应和预报服务提供数据支持。     

Beamforming on seismic interface waves with an array of geophoneson the shallow sea floor

The problem of locating very low frequency sound sources in shallow water is made difficult by the interaction of propagating acoustic waves with the sea floor. Slow wave speeds and the attendant short wavelengths suggest that low frequency beamforming and source localization with sea floor geophones can be accomplished with relatively small arrays when compared with hydrophone arrays in the water column. To test the feasibility of this approach, experiments were carried out in the shallow water of the Malta Channel of the Straits of Sicily where the Scholte wave speed was some 10 to 20 times slower that the speed of sound in water. A linear array of ten vertically gimballed geophones was deployed and measurements were made on propagating seismic wave fields generated by explosive shots. The resulting directivities, beam patterns, and sidelobe characteristics are in excellent agreement with array theory, which suggests that coherent processing is a viable technique on which to base new applications for seismic arrays on the sea floor. Supporting materials on the geophysics of Scholte waves and calculations of the wave field at the site are presented     

Evolutionary path planning for autonomous underwater vehicles in a variable ocean

This paper proposes a genetic algorithm (GA) for path planning of an autonomous underwater vehicle in an ocean environment characterized by strong currents and enhanced space-time variability. The goal is to find a safe path that takes the vehicle from its starting location to a mission-specified destination, minimizing the energy cost. The GA includes novel genetic operators that ensure the convergence to the global minimum even in cases where the structure (in space and time) of the current field implies the existence of different local minima. The performance of these operators is discussed. The proposed algorithm is suitable for situations in which the vehicle has to operate energy-exhaustive missions.     

Autonomous underwater vehicle teams for adaptive ocean sampling: a data-driven approach

The current technological developments in autonomous underwater vehicles (AUVs) and underwater communication have nowadays allowed to push the original idea of autonomous ocean sampling network even further, with the possibility of using each agent of the network not only as an operative component driven by external commands (model-driven) but as a reactive element able to act in response to changing conditions as measured during the exploration (data-driven). With this paper, we propose a novel data-driven algorithm for AUVs team for adaptive sampling of oceanic regions, where each agent shares its knowledge of the environment with its teammates and autonomously takes decision in order to reconstruct the desired oceanic field. In particular, sampling point selection is made in order to minimize the uncertainty in the estimated field while keeping communication contact with the rest of the team and avoiding to repeatedly sampling sub-regions already explored. The proposed approach is based on the use of the emergent behaviour technique and on the use of artificial potential functions (interest functions) to achieve the desired goal at the end of the mission. In this way, there is no explicit minimization of a cost functional at each decision step. The oceanic field is reconstructed by the application of radial basis functions interpolation of irregularly spaced data. A simulative example for the estimation of a salinity field with sea data obtained using the Mediterranean Sea Forecasting System is shown in the paper, in order to investigate the effect of the different uncertainty sources, including sea currents, on the behaviour of the exploration team and ultimately on the reconstruction of the salinity field.