A new Brown-Peaky (BP) retracker has been developed for peaky waveforms that usually appear within ~10 km to the coastline. The main feature of the BP is that it fits peaky waveforms using the Brown model without introducing a peak function. The retracking strategy first detects the peak location and width of a waveform using an adaptive peak detection method, and then estimates retracking parameters using a weighted least squares (WLS) estimator. The WLS assigns a downsized weight to corrupted waveform gates, but an equal weight to other normal waveform gates. The BP retracker has been applied to 4-year Jason-1 waveform (2002–2006) in two Australian coastal zones. The results retracked by BP, MLE4 and ALES retrackers have been validated against tide-gauge observations located at Burnie, Lorne and Broome. The comparison results show that three retrackers have similar performance over open oceans with the correlation coefficient (~0.7) and RMSE (~13 cm) between altimetric and tide-gauge sea levels for distance >7 km offshore. The main improvement of BP retracker occurs for distance ≤7 km to the coastline, where validation results indicate that data retracked by BP are more accurate (15–21 cm) than those by ALES (16–24 cm) and MLE4 (19–37 cm). 相似文献
The spatial distribution of chemical oxygen demand(COD) and total nitrogen(TN) yield from Qingdao are studied by comparing pollutant yield amount, densities and spatial aggregation(Getis-Ord indexes) among the land-based pollutant source regions(PSRs) entering the three sub-seas(i.e. the Jiaozhou Bay(JZB), other coastal area in the Yellow Sea(OCAYS) and Laizhou Bay(LZB), respectively). Industrial composition of the loads are also studied by comparing pollutant yield among the sources of agriculture, rural domesticity, industry, urban domesticity and service, and calculation of Gini coefficient. Results show that spatial distribution of COD and TN yield from Qingdao are extremely unbalanced. The JZB, with less than 3% of the total coastal sea area of Qingdao, received 62% COD load and 65% TN yield from Qingdao, while the OCAYS, with more than 97% area, only received 23% COD and 20% TN, which consist with the much worsen water quality of JZB than that of OCAYS. On the other hand, the source apportionment of COD and TN loads in the PSRs entering JZB and the OCAYS was similar. The agricultural and domestic sources with high pollution intensity account for more than 80%, while the industrial and service sources with low pollution intensity account for less than 20%. While Gini coefficients, COD 0.81 and TN 0.84 which are much higher than the ‘imbalance' threshold of 0.4, show the uneven industrial structure of Qingdao. These results may be useful in the determination of land-based pollution total amount control at the PSR level. 相似文献
Journal of Oceanology and Limnology - Microcystins (MCs) are cyclic hepatotoxic peptides produced by the bloom-forming cyanobacterium Microcystis and present a public health hazard to humans and... 相似文献
Based on oceanographic survey data in June 2012 in the Lembeh Strait, the zooplankton ecological characteristics such as species composition, individual abundance, dominant species and distribution were analyzed. The results showed that 183 species(including 4 sp.) had been recognized, most of them belonged to copepoda.Cnidaria followed with 43 species(including 1 sp.) were identified. The average abundance of zooplankton was(150.47±58.91) ind./m~3. As to the horizontal distribution, the abundance of the zooplankton was higher in the southern waters than in the northern waters. The dominant species in the study area were Lensia subtiloides,Sagitta enflata, Lucifer intermedius, Oikopleura rufescens, Diphyes chamissoni, Creseis acicula, Subeucalanus subcrassus, Temora discaudata, Aglaura hemistoma, Doliolum denticulatum, Canthocalanus pauper, Oikopleura longicauda and Nanomia bijuga. Zooplankton biodiversity indexes were higher in study area than previous study in the other regions. The findings from this study provide important baseline information for future research and monitoring programs. 相似文献
Atlantic salmon reared in recirculating aquaculture system (RAS) may lead to inappropriately high stocking density, because fish live in a limited space. Finding the suitable stocking density of Atlantic salmon reared in RAS is very important for RAS industry. In this paper, the influence of stocking density on growth and some stress related physiological factors were investigated to evaluate the effects of stocking density. The fish were reared for 220 days at five densities (A: 24 kg/m3; B: 21 kg/m3; C: 15 kg/m3; D: 9 kg/ m3 and E: 6 kg/m3 ). The results show that 30 kg/m3 might be the maximum density which RAS can afford in China. The stocking densities under 30 kg/m3 have no effect on mortality of Atlantic salmon reared in RAS. However, the specific growth rate (SGR), final weight and weight gain in the high density group were significantly lower than the lower density groups and middle density groups. Moreover, feed conversion rate (FCR) had a negative correlation with density. Plasma hormone T3 and GH showed significant decrease with the increase of the stocking density of the experiment. Furthermore, thyroid hormone (T3), GH (growth hormone) activities were decreased with stocking density increase. However, plasma cortisol, GOT (glutamic oxalacetic transaminase) and GPT (glutamic pyruvic transaminase) activities were increase with stocking density increase. And the stocking density has no effects on plasma lysozyme of Atlantic salmon reared in RAS. These investigations would also help devise efficient ways to rear adult Atlantic salmon in China and may, in a way, help spread salmon mariculture in China.
ABSTRACT High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning. 相似文献