Fuzzy Logic System for Road Identification Using Ikonos Images

Research into both extraction of man-made objects and automatic change detection from aerial and satellite images has made significant progress in recent years. This paper presents an approach, based on a fuzzy logic system, for the identification of suburban roads in Ikonos images. The linguistic variables are the mean and standard deviation (SD) of different objects with Gaussian membership function. After the roads have been identified provisionally and their skeleton extracted, the skeleton can be vectorised and then used as direct input to a GIS for further analysis. The method was tested on an Ikonos "Geo" image covering Bilesavar in north-western Iran. For the suburban area of Bilesavar, the results showed that grey scale values ranged from 20 to 190 for non-roads and 226 to 228 for roads, the optimum width of the Gaussian kernel function was 3 and the SD was 0.4. It was also found that about 91% of main roads with a width of 6 to 12 pixels could be extracted from high resolution satellite imagery by the algorithm. The computer program for this study has been developed in visual C++ based on Windows 98     

Evaluation of gene expression programming approaches for estimating daily evaporation through spatial and temporal data scanning

Evaporation of water from free water surfaces or from land surfaces is one of the main components of the hydrological cycle, and its occurrence is governed by various meteorological and physical factors. There is a multitude of models developed for estimating daily evaporation values by using weather data. This paper evaluates a Gene Expression Programming (GEP) model for estimating evaporation through spatial and temporal data scanning techniques. It is by using ‘leave‐one‐out’ procedures, a complete scan of the possible train and test set configurations is carried out according to temporal and spatial criteria. Comparison of the GEP model with empirical‐physical models shows that daily evaporation values computed by the GEP model are more accurate. Further, local calibration of the GEP model may not be needed, if enough climatic data are available at other stations. The performance of the GEP model fluctuates throughout the period of study and between stations. A suitable assessment of the model should consider a complete temporal and/or spatial scan of the data set used. Copyright © 2012 John Wiley & Sons, Ltd.     

Incorporation of a Non-linear Image Filtering Technique for Noise Reduction in Seismic Data

Seismic noise is a fundamental part of seismic data which cannot be avoided when conducting any seismic survey. It consists of coherent and random noise. Noise removal or filtering is one of the major concerns in the field of seismic processing. In this paper, we introduce an image filtering technique based on a detection-estimation algorithm for Gaussian and random noise removal in seismic data, namely the trilateral filter, based on a statistic called rank-ordered absolute differences. The non-linear and adaptive behaviour of this filter makes it very robust in the presence of random and coherent noise, in addition to its computational simplicity and its ability to automatically identify noise in data. We have modified the strategy of trilateral filtering by adapting the rank-ordered absolute differences formula in order to extract the signal component. We have successfully used this filter for the removal of surface waves and random spiky noise from synthetic and field data. Results are very encouraging and show the superiority of this filter compared with other filters, particularly when used recursively.     

Groundwater nitrate pollution in the Essaouira Basin (Morocco)

The Essaouira Basin (Morocco) contains a multi-layered aquifer situated in fractured and karstic materials from the Middle and Upper Cretaceous (the Cenomanian, Turonian and Senonian). Water percolates through the limestone and dolomite formations of the Turonian stage either through the marls and calcareous marls of the Cenomanian or through the calcareous marly materials of the Senonian. The aquifer system may be interconnected since the marl layer separating the Turonian, Cenomanian and Senonian aquifers is thin or intensively fractured. In that case, the water is transported through a network of fractures and stratification joints. This paper describes the extent of the nitrate pollution in the area and its origin. Most of the wells and drillholes located in the Kourimat perimeter are contaminated by nitrates with some concentrations over $\text{400 }\text{mg}\text{l}{}^{\mathrm{?1}}$. Nitrate contamination is also observed in the surface water of the Qsob River, which constitutes the natural outlet of the multi-layered complex aquifer system. In this area, agriculture is more developed than in the rest of the Essaouira Basin. Diffuse pollution of the karstic groundwater body by agricultural fertiliser residues may therefore partially explain the observed nitrate pollution. However, point pollution around the wells, springs and drillholes from human wastewater, livestock faeces and the mineralisation of organic debris close to the Muslim cemeteries cannot be excluded.     

Étude du fonctionnement du système aquifére karstique Cénomano-Turonien de l'oued Igrounzar, bassin d'Essaouira, Maroc

In the Meskala-Kourimat area, the Bouabout Syncline aquifer system, intersected by the Igrounzar Wadi, feeds most of the karstic sources of the region. This aquifer is contained within Cenomanian and Turonian limestones and dolomitic limestones. The base of the system corresponds to the lower Cenomanian grey clays, and the top to the Senonian white marls. Hydrodynamic studies of various springs shows that each water source is different from the other, indicating a heterogeneous underground reservoir belonging to a complex karst system. The springs waters show a large chemical variability in space and time. These waters are a mixture of chloride, sulphate, Na and Mg. High Mg contents of some springs result from dissolution of evaporite, confirmed by low Ca/Mg ratios. The total dissolved solids (TDS) in spring water increases from upstream to downstream, probably as a response to residency time, but also due to interaction with Cenomanian evaporites. However, the springs are good for drinking water, as well as for irrigation. The monthly survey of selected springs indicated a large chemical variability but with little or no correlation between discharge and TDS.Stable isotope data (¹⁸O) suggests that the altitude of the recharge area, for this aquifer system, is 1200 m. The ¹⁸O gradient versus altitude, established on springs whose recharge areas are well known is, −0.25% versus SMOW/100 m. When compared with the ‘Meteoric Water Line’ established on worldwide spring water whose recharge areas are well known, the Essaouira Basin shows rain recharge without any significant evaporation.     

New alternatives for reference evapotranspiration estimation in West Africa using limited weather data and ancillary data supply strategies.

Accurate estimation of reference evapotranspiration (ET ₀ ) is essential for the computation of crop water requirements, irrigation scheduling, and water resources management. In this context, having a battery of alternative local calibrated ET ₀ estimation methods is of great interest for any irrigation advisory service. The development of irrigation advisory services will be a major breakthrough for West African agriculture. In the case of many West African countries, the high number of meteorological inputs required by the Penman-Monteith equation has been indicated as constraining. The present paper investigates for the first time in Ghana, the estimation ability of artificial intelligence-based models (Artificial Neural Networks (ANNs) and Gene Expression Programing (GEPs)), and ancillary/external approaches for modeling reference evapotranspiration (ET ₀ ) using limited weather data. According to the results of this study, GEPs have emerged as a very interesting alternative for ET ₀ estimation at all the locations of Ghana which have been evaluated in this study under different scenarios of meteorological data availability. The adoption of ancillary/external approaches has been also successful, moreover in the southern locations. The interesting results obtained in this study using GEPs and some ancillary approaches could be a reference for future studies about ET ₀ estimation in West Africa.     

Estimation of dew point temperature using neuro-fuzzy and neural network techniques

This study investigates the ability of two different artificial neural network (ANN) models, generalized regression neural networks model (GRNNM) and Kohonen self-organizing feature maps neural networks model (KSOFM), and two different adaptive neural fuzzy inference system (ANFIS) models, ANFIS model with sub-clustering identification (ANFIS-SC) and ANFIS model with grid partitioning identification (ANFIS-GP), for estimating daily dew point temperature. The climatic data that consisted of 8 years of daily records of air temperature, sunshine hours, wind speed, saturation vapor pressure, relative humidity, and dew point temperature from three weather stations, Daego, Pohang, and Ulsan, in South Korea were used in the study. The estimates of ANN and ANFIS models were compared according to the three different statistics, root mean square errors, mean absolute errors, and determination coefficient. Comparison results revealed that the ANFIS-SC, ANFIS-GP, and GRNNM models showed almost the same accuracy and they performed better than the KSOFM model. Results also indicated that the sunshine hours, wind speed, and saturation vapor pressure have little effect on dew point temperature. It was found that the dew point temperature could be successfully estimated by using T _mean and R _H variables.