Land cover classification of VHR airborne images for citrus grove identification

Managing land resources using remote sensing techniques is becoming a common practice. However, data analysis procedures should satisfy the high accuracy levels demanded by users (public or private companies and governments) in order to be extensively used. This paper presents a multi-stage classification scheme to update the citrus Geographical Information System (GIS) of the Comunidad Valenciana region (Spain). Spain is the first citrus fruit producer in Europe and the fourth in the world. In particular, citrus fruits represent 67% of the agricultural production in this region, with a total production of 4.24 million tons (campaign 2006-2007). The citrus GIS inventory, created in 2001, needs to be regularly updated in order to monitor changes quickly enough, and allow appropriate policy making and citrus production forecasting. Automatic methods are proposed in this work to facilitate this update, whose processing scheme is summarized as follows. First, an object-oriented feature extraction process is carried out for each cadastral parcel from very high spatial resolution aerial images (0.5 m). Next, several automatic classifiers (decision trees, artificial neural networks, and support vector machines) are trained and combined to improve the final classification accuracy. Finally, the citrus GIS is automatically updated if a high enough level of confidence, based on the agreement between classifiers, is achieved. This is the case for 85% of the parcels and accuracy results exceed 94%. The remaining parcels are classified by expert photo-interpreters in order to guarantee the high accuracy demanded by policy makers.     

Prototyping an artificial neural network for burned area mapping on a regional scale in Mediterranean areas using MODIS images

Each year thousands of ha of forest land are affected by forest fires in Southern European countries such as Spain. Burned area maps are a valuable instrument for designing prevention and recovery policies. Remote sensing has increasingly become the most widely used tool for this purpose on regional and global scales, where a large variety of techniques and data has been applied. This paper proposes a semiautomatic method for burned area mapping on a regional scale in Mediterranean areas (the Iberian Peninsula has been used as a study case). A Multi-layer Perceptron Network (MLPN) has been designed and applied to MODIS/Terra Surface Reflectance Daily L2G Global 500m SIN Grid multitemporal composite monthly images. The compositing criterion was based on maximum surface temperature. The research covered a six year period (2001–2006) from June to September, when most of the forest fires occur. The resulting burned area maps have been validated using official fire perimeters and compared with MODIS Collection 5 Burned Area Product (MCD45A1). The MLPN shown as an effective method, with a commission error of 29.1%, in the classification of the burned areas, while the omission error was of 14.9%. The results were compared with the MCD45A1 product, which had a slightly higher commission error (30.2%) and a considerably higher omission error (26.2%), indicating a high underestimation of the burned area.     

陕焦化甲醇生产项目雷击风险评估

为了使人工增雨更有针对性,需要在作业方案制定阶段就对未来影响天气系统有一个明确的判断,需要总结出一套适合山西省进行人工增雨作业的天气概念模型。为此,普查了1991年-2000年欧亚范围高空及地面天气图,筛选出影响山西省并产生降水的天气系统,加以分析归纳,建立了4种有利于山西省人工增雨作业的天气概念模型,即西风槽型、东北冷涡型、切变线型及副高型,并分别给出了未来12h～24h影响山西省的警戒区及最佳人工增雨作业区。     

Toothed whales in the northwestern Mediterranean: insight into their feeding ecology using chemical tracers

Risso’s dolphins, pilot whales and sperm whales rarely strand in the northwestern Mediterranean. Thus, their feeding ecology, through the analysis of stomach contents, is poorly known. The aim of this study was to gain further insight into the segregation/superposition of the diet and habitat of Risso’s dolphins, pilot whales and sperm whales using chemical tracers, namely, stable isotopes (δ¹³C, δ¹⁵N) and organochlorines. Significantly different δ¹⁵N values were obtained in Risso’s dolphins (11.7 ± 0.7‰), sperm whales (10.8 ± 0.3‰) and pilot whales (9.8 ± 0.3‰), revealing different trophic levels. These differences are presumably due to various proportions of Histioteuthidae cephalopods in each toothed whale’s diet. Similar δ¹³C contents between species indicated long-term habitat superposition or corroborated important seasonal migrations. Lower congener 180 concentrations (8.20 vs. 21.73 μg.g⁻¹ lw) and higher tDDT/tPCB ratios (0.93 vs. 0.42) were observed in sperm whales compared with Risso’s dolphins and may indicate wider migrations for the former. Therefore, competition between these species seems to depend on different trophic levels and migration patterns.     

Marine artificial micro‐reserves: a possibility for the conservation of endangered species living on artificial substrata

The installation of urban and commercial infrastructures on the coast has a severe impact on the marine environment. This impact is mostly negative but, simultaneously, some of the species that colonize artificial substrata (sometimes rare or threatened) find refuge in man‐made structures. The protection of endangered species is usually provided by marine protected areas or by laws that punish their damage or collection, but effective enclosure and custody must be achieved in the case of easily accessible intertidal species. We used the ferruginous limpet, Patella ferruginea, as a case study because it is the most endangered invertebrate in the Mediterranean. This species, which lives in the intertidal zone and is very accessible to people, is a free‐spawning, protandric hermaphrodite, highly dependent on population density and individual size for its reproductive success. Previous work by the authors found the species is especially abundant on artificial substrates on both shores of the Strait of Gibraltar, where people collect fewer of them. Spanish laws of coastal management do not allow the enclosure of the natural coastline, but artificial installations like harbour breakwaters may be closed or guarded, and visits for educational purposes may be carried out under control. The possibility of declaring some kind of environmental protection for these artificial areas would be a very helpful tool for conservation and management purposes. Protected individuals would grow larger and eventually produce exponentially more offspring, which could be transported by currents to adjacent habitats. Here we propose a protection concept for artificial sites termed Artificial Marine Micro‐Reserve (AMMR), where some endangered species experience a refuge from human disturbance. This concept is a modification of the land micro‐reserves that have been recently declared in small natural sites that keep rare plant species. A network of AMMRs would be the final objective, allowing the creation of a great metapopulation of P. ferruginea and also giving refuge to other endangered species that have been found to grow in this type of substratum. Critically, the declaration of a micro‐reserve cannot be used as a reason in favour of new construction because of the negative influence of such structures on the marine environment, together with the fact that there is no certainty that valuable species will settle on them.     

Wave height forecasting in Dayyer, the Persian Gulf

Forecasting of wave parameters is necessary for many marine and coastal operations. Different forecasting methodologies have been developed using the wind and wave characteristics. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the wave height for the next 3, 6, 12 and 24 h in the Persian Gulf. To determine the effective parameters, different models with various combinations of input parameters were considered. Parameters such as wind speed, direction and wave height of the previous 3 h, were found to be the best inputs. Furthermore, using the difference between wave and wind directions showed better performance. The results also indicated that if only the wind parameters are used as model inputs the accuracy of the forecasting increases as the time horizon increases up to 6 h. This can be due to the lower influence of previous wave heights on larger lead time forecasting and the existing lag between the wind and wave growth. It was also found that in short lead times, the forecasted wave heights primarily depend on the previous wave heights, while in larger lead times there is a greater dependence on previous wind speeds.     

Trend estimation and univariate forecast of the sunspot numbers: Development and comparison of ARMA, ARIMA and Autoregressive Neural Network models

In the present study, a prominent 11-year cycle, supported by the pattern of the autocorrelation function and measures of Euclidean distances, in the mean annual sunspot number time series has been observed by considering the sunspot series for the duration of 1749 to 2007. The trend in the yearly sunspot series, which is found to be non-normally distributed, is examined through the Mann-Kendall non-parametric test. A statistically significant increasing trend is observed in the sunspot series in annual duration. The results indicate that the performance of the autoregressive neural network-based model is much better than the autoregressive moving average and autoregressive integrated moving average-based models for the univariate forecast of the yearly mean sunspot numbers.     

糙海参(Holothuria scabra)胚胎发育观察

对糙海参的胚胎发育至幼体发生进行显微观察。结果表明:受精45 min开始出现第一次卵裂,随后经过4、8、16等裂细胞,4 h后进入不等裂多细胞期,6 h后出现可游动囊胚期,10 h后进入原肠期,24～26 h成为耳状幼体。经历10～11 d的生长与发育,变态为樽形幼体,幼体经历由小变大再由大变小的过程。樽形幼体2～6 d后再次变态为较大体形的五触手幼体,开始转入底栖,五触手期2～8 d后,幼体最终以稚参形态附着下来。整个发育过程时间为16～25 d。     

Suspended sediment yield modeling in Mahanadi River,India by multi-objective optimization hybridizing artificial intelligence algorithms

River sediment produced through weathering is one of the principal landscape modification processes on earth.Rivers are an integral part of the hydrologic cycle and are the major geologic agents that erode the continents and transport water and sediments to the oceans.Estimation of suspended sediment yield is always a key parameter for planning and management of any river system.It is always challenging to model sediment yield using traditional mathematical models because they are incapable of handling the complex non-linearity and non-stationarity.The suspended sediment modeling of the river depends on the number of factors such as rock type,relief,rainfall,temperature,water discharge and catchment area.In this study,we proposed a hybrid genetic algorithm-based multi-objective optimization with artificial neural network(GA-MOO-ANN)with automated parameter tuning model using these factors to estimate the suspended sediment yield in the entire Mahanadi River basin.The model was validated by comparing statistically with other models,and it appeared that the GA-MOO-ANN model has the lowest root mean squared error(0.009)and highest coefficient of correlation(0.885)values among all comparative models(traditional neural network,multiple linear regression,and sediment rating curve)for all stations.It was also observed that the proposed model is the least biased(0.001)model.Thus,the proposed GA-MOOANN is the most capable model,compared to other studied models,for estimating the suspended sediment yield in the entire Mahanadi river basin,India.The results also suggested that the proposed GA-MOO-ANN model is unable to estimate suspended sediment yield satisfactorily at gauge stations having very small catchment areas whereas performing satisfactorily on locations having moderate to the large catchment area.The models provide the best result at Tikarapara,the gauge station location in the extreme downstream,having the largest catchment area.     

利用VLBI数据确定"探测一号"卫星的轨道

双星计划的“探测一号”是中国首颗真正严格意义上的科学实验卫星,其运行轨道为中国迄今所发射的卫星中距地球最远,远地点地心距达7．8万公里．采用射电天文的VLBI技术可以对“探测一号”以及更远的深空目标,如探月飞行器实现跟踪．为了验证VLBI技术在我国探月计划中的作用,上海天文台组织了国内目前仅有的上海、乌鲁木齐和昆明3个台站对“探测一号”进行试跟踪,利用对“探测一号”约两天的VLBI观测数据,确定“探测一号”卫星的轨道,对VLBI的定轨能力做初步的探讨．按照测控部门提供的初轨 (其精度仅保证跟踪)推算的轨道与VLBI时延的拟合误差平均约2 km,时延率的拟合误差平均约15 cm／s．而利用VLBI数据定轨后的拟合程度相对于初轨有了很大的改善,结果表明,单独利用VLBI时延定轨,时延的拟合精度约5．5 m,作为外部检核的VLBI时延率的拟合精度在2 cm／s左右．单独利用VLBI时延率定轨,时延率的拟合精度约为1．3 cm／s,作为外部检核的VLBI时延的拟合精度约为29 m．而若将时延和时延率数据联合定轨,采用其内符精度加权,VLBI时延和时延率的残差分别为5．5 m和 2 cm／s．为了合理地评估VLBI定轨的真实精度,利用模拟数据进行误差协方差分析,结果表明VLBI定轨精度受动力学模型误差的影响较大,由于"探测一号”卫星的动力学模型难以精确确定,所以利用两天弧段的VLBI数据确定“探测一号”卫星轨道的位置误差为km量级,而速度误差可达cm／s量级．模拟计算还表明, VLBI和USB数据联合定轨可以大大提高定轨精度．