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Classification of a diffuse heavy metal polluted mining site using a spectral angle mapper
119-123Views:99Characterization of heavy metal polluted abandoned mining sites is complicated, as the spatial distribution of pollutants often changes dramatically.
In our study, a hyperspectral data analysis of the Gyöngyösoroszi abandoned Pb-Zn mine, located in northern Hungary, where Záray (1991) reported serious heavy metal contamination, was carried out using ENVI 4.3. In this area, galena (PbS), goethite (FeO(OH)), jarosite (KFe3(SO4)2(OH)6), sphalerite ((Zn, Fe)S) and pyrite (FeS2) were the predominant minerals in the alteration zones was chosen as the target mineral.
Spectral angle mapper (SAM) and BandMax classification techniques were applied to obtain rule mineral images. Each pixel in these rule images represents the similarity between the corresponding pixels in the hyperspectral image to a reference spectrum.
As a result of hyperspectral imagery the distribution of pyritic minerals (sphalerite, galena) in the area was defined. Both of the mineral formations occur, especially in mine tailings, the area of the ore preparatory, and the Szárazvölgyi flotation sludge reservoir. According to the results, jarosite and goethite have similar distributions to sphalerite and galena. The results showed that hyperspectral remote sensing is an effective tool for the
characterization of Pb, Zn and Fe containing minerals at the examined polluted sites and for modelling the distribution of heavy metals and minerals in extensive areas.
This classification method is a basis of further detailed investigations, based on field measurements, to map the heavy metal distribution of the studied area and to quantify the environmental risks caused by erosion, which include DEM (digital elevation model) and climatic and hydrological data sources. Furthermore, it can be used primarily to support the potentially applicable phytostabilization technique and to isolate hot spots where only ex-situ remediation techniques can be applied. -
Performance of agricultural factors on yield of sweet corn (Zea mays L. Saccharata ) - A review
143-156Views:56Sweet corn producers and industries require more reliable cultivars which could be accomplished by hybrid breeding. However, progressive phenological growth may be affected by different factors. In this paper, we analyze the key factors that determine the growth and yield of sweet corn. Environmental factors such as temperature and photoperiod were strong determinants of dates of flowering and harvest which are often crucial to yield in diverse climates and agricultural systems, besides the country's pedological conditions, especially soil fertility, affected phenological development. The effectiveness of fertilization in improving sweet corn growth performance was significantly influenced by the soil characteristics, the water supply, the genotype, and the agrotechnological factors. Therefore, genetic improvement of hybrids should be incorporated into the climate and soil elements to stabilize sweet corn yields in various agroecosystems. Decisions made in the sowing period are very significant, as up to 30% of the obtained yield may depend on making the proper choice. Deviation from the optimum date (either early or late sowing) may decrease yield. When deciding about the sowing date of maize, one needs to consider climate, soil quality, geographical location, temperature, weed infestation, sowing seed quality, and the ripening time of the hybrid to be produced.
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The effect of location on the incidence of brown rot blossom and shoot blight infection on apricot
89-91Views:117The aim of our study was to assess the incidence of brown rot blossom and shoot blight and caused by Monilinia laxa. Assessments of incidence were made on cv. Bergeron (susceptible to brown rot) in a flatland and a hilly growing area (at Cegléd and Gönc, respectively). In 2004, when spring and summer weather conditions were wet and cold, incidence reached 95 % for blossom blight and 33 % for shoot blight in the untreated plots. Blossom blight incidence was 1.5-2 times higher in the flatland area compared to the hilly growing area. During the blooming period of apricot, two (at flower bud stage and at full bloom) and three (at flower bud stage, at full bloom and at petal fall) fungicide applications were necessary for the successful control at Gönc and Cegléd, respectively. The difference between the two orchards was due to the fact that blooming started one week later in the hilly region (at Gönc) than in the flatland region (at Cegléd), therefore, the critical weather period coincided with blooming in the orchard in the hilly region only partially.
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Spatially Discrete GIS Analysis of Sampling Points Based on Yield and Quality Analysis of Sugar Beet (Beta vulgaris L.)
32-37Views:89Fulfilment of the increasing quality requirements of sugar beet production can be analysed with sampling of plants and soil at the cultivated area. Analyses of the spatial characteristics of samples require exact geodetic positioning. This is applied in practice using GPS in precision agriculture. The examinations were made in a sample area located in north-western Hungary with sugar beet test plant. According to the traditional sample taking procedure N=60 samples were taken in regular 20 x 20 m grid, where besides the plant micro and macro elements, the sugar industrial quality parameters (Equations 1-2) and the agro-chemical parameters of soils were analysed. Till now, to gain values of mean, weighted mean and standard variance values, geometric analogues used in geography were adapted, which correspond to the mean centre (Equation 3), the spatially weighted mean centre (Equation 4), the standard distance (Equation 5), and the standard distance circle values. Robust spatial statistical values provide abstractions, which can be visually estimated immediately, and applied to analyse several parameters in parallel or in time series (Figure 1). This interpretation technique considers the spatial position of each point to another individually (distance and direction), and the value of the plant and soil parameters. Mapping the sample area in GIS environment, the coordinates of the spatially weighted mean centre values of the measured plant and soil parameters correlated to the mean centre values showed a northwest direction. Exceptions were the total salt and calcium-carbonate contents, and the molybdenum concentration of the soil samples (Table 1). As a new visual analysis, the spatially weighted mean centre values of the parameters as eigenvectors were projected to the mean centre values as origin. To characterize the production yield, the raw and digested sugar contents of the sample area, the absolute rotation angles of the generated vectors were determined, which indicate numerically the inhomogenity of the area (Figure 2). The generated spatial analogues are applicable to characterise visually and quantitatively the spatial positions of sampling points and the measured parameters in a quick way. However, their disadvantage is that they do not provide information on the tightness and direction of the spatial correlation similarly to the original statistical parameters.
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Conceptional Model of Regional Agricultural Water Management System
199-209Views:107Our study focuses on the water management improvement of the Hajdúsági-löszhát (loess ridge). The Hajdúsági-löszhát (loess ridge) is an intensive agricultural area. At the same time, the problem of increasing water demand is still not solved, so towards of safety production irrigation should be improved. To realise this should be known not even agricultural water demands but industrial and urban ones as well, thus a complex water management system is required to be worked out.
In the first part of the research, the water demand in the area is mapped, then a conceptional model of the Hajdúsági-löszhát’s (loess ridge’s) water management system is created. After collecting data the water management scenario is summarized in a real time model splitted into five periods.
During the research, the instruments of spatial informatics (GIS) are used to get acquainted with the variation of the hydrological parameters in space and time. To understand and simulate the different decision making processes and to choose the right decision alternative, a decision support system is created with the use of spatial informatics data.
In addition, considering the potentially right decision alternative, irrigation will be started in practice, an effect and after-effect inquiry will be made, and the results will be analysed, evaluated and summarized. Finally, a suggestion to the most adequate irrigation technology will be made.