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Gis Modeling for Dust Storm - Essay Example

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This paper 'Gis Modeling for Dust Storm' tells us that in the desert regions, desert storms are very rampant; some regions also call them desert storms especially in context with deserts like the Sahara, they are meteorological phenomenon’s very common in the arid and/or semi-arid regions of the world…
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Running Head: Monitoring the source of trans-national dust storms in north East Asia Name Date Institution In the desert regions, desert storms are very rampant; some regions also call them desert storms especially in context with deserts like the Sahara, they are meteorological phenomenons very common in the arid and/or semi arid regions of the world. They may arise from gust fronts blowing the loose dust and/or sand from the dry surfaces. The particles may be transported through suspension in the air leading to soil erosion from the region of occurrence to deposition on the area where the particles land like the pacific which receives deposits from china's storms. The major leading causes of these storms are forces of wind passing over an area of particles loosely held thus increasing their vibrations and their leaping tendencies. Repeated striking of the ground by the particles leads to loosening of the minor particles of dust, thus they begin to voyage in suspension. When the wind's speed get to speeds causing the smallest of particles to be suspended in air, there is said to be a population mainly of dust grains that are moving in a vast assortment of mechanisms like; creeping, suspension and/or saltation. The other cause of the storms may be due to wind and drought or poor grazing and farming practices that make the soil to be to the wind. Some of the poor farming methods are like dry land farming practice (Zhang et al, 1997). The impacts of a dust storm both physical and environmentally are numerous; a dust storm is capable of moving a whole sand dune while they also cause poor visibility in areas of occurrence. Dust storms as per research have been discovered to lead to an increase to spread of disease globally. Spores of virus on the ground will be blown into the atmosphere plus the minute particles; this then leads to acrid rain and/or smog in the urban areas. To the economy, the storms may lead to soil erosion in the dry lands and preferentially remove the organic matter and nutrient rich particle covering the top soils; this is of major detriment to the agricultural sector as production is greatly reduced while crops planted are greatly damaged. Dust storms are not entirely destructive since they can have good results on the areas of deposition: Southern and Central American rain forests are known to get their main soil mineral nutrients from Sahara desert. While the poor iron oceans get their iron from these storms (Stephenson et al, 1980). Abstract Ksahara et al (2001), vast tracks within the Gobi desert of the Mongolian plateau are susceptible to dust storms, in these isolated regions remote sensing techniques are adequately necessary and the fact that GIS has such equipment, their technology comes in handy to the desert residents who can't visually predict a storm with their naked eyes except when the storm has already formed leaving them at a very disadvantaged position. Remote sensing techniques can thus help in prediction and measurement of dust storms, there is the MODIS satellite data, temperature channel satellite data – AVHRR all used to map sand storms within the desert regions of Northern China and Mongolia. Differences between the thermal bands are used together with the geographic information system to map the storms in studies carried out by (Fung, 1996). Results then clearly show that dust and sand storm maps can be got from massive bands for the monitoring of both sandstorms and/or dust storms. Introduction Geographic information systems/geographic information systems (GIS), can be termed as a system able to capture, store/sort, manage and then present the data in question to a linked location. The term also can be used to refer to information systems able to integrate, store, analyze, store, display and share data that it receives. In a generic sense, GIS applications can be said to be tools allowing users a chance to models of user-created searches, they are able to analyze any spatial information, edit maps, data, and/or present results of the operations. Geographic Information Science may be said to be the science underlying geographic applications, systems and concepts, they are taught as degree courses and/or GIS Certificate programs at several universities. GIS techniques and technology In the modern world today, GIS technologies will use available digital information in which the data creation methods and models are available. In most cases, common methods of creating data is through digitization, in which hard copies of maps or any survey plan can be transferred into digital mediums through use of computer-aided designs (CAD) programs and geo-referencing. Wide availability of ortho rectified imagery from aerial and satellite sources, makes digitizing become a main avenue through that which geographic data may be extracted. Data representation GIS is a representation of the real world i.e., elevation roads, land use etc using digital data. The real world is then sub-divided into two abstractions: discrete objects like a house and continuous fields like elevation. Raster data types are type of digital images that are represented in form of grids. Geographical features can be expressed using vectors when one considers the features as geometrical shapes. Advantages and disadvantages Some of the disadvantages and advantages and of using raster or vector data models may include; Raster dataset models are able to register values for all points covered Raster data enables better and easier interpretations and implementation Vector data has an ability to be displayed as a vector graphic mainly used in the traditional maps The Raster models are able to record values for all the points within any given area meaning that they require more storage while the vector model only stores needed data The Raster models are able to allow easy and fast implementation of the overlay operations that are more difficult compared to the vector data. It is possible to represent the vector's data as vector graphics tat are used in traditional maps. With the vector model, it is easier to scale, register and to re-project thus simplifying the combination of vector layers from the different regions and sources Vector data is known to be more compatible with the relational databases environments, where they are part of a relational table The vector file size is normally minute compared to the raster data, which can be grater than the vector data, i.e. depending on resolution. Vector data will be easier to maintain and update, whereas raster images will have to undergo reproductions. The vector data model will allow more analysis capability, especially for the networks like, rail, roads, power, etc. Data modeling It is usually hard and disappointing to be able to exactly relate the wetlands and their maps to the amount of rainfall that is recorded at varying points like at airports, high schools et. GIS thus comes in handy to help in the depiction of such weather elements. Such maps can be termed as rainfall contour maps. GIS models can be able to recognise and/or spatial relationships existing within the digitally stored date. Networks Let's assume that all factories that are closely located at or near a wetland were to accidentally release chemicals into a nearby river simultaneously, what time would it take for pollutants that are damaging enough to enter the wetland? A GIS comes in handy in such a scenario in that it is able to simulate routing of any materials along any materials in an linear networks. In the deserts, the dust storms and/or sand storms are known to have a major impact on their inhabitants and the physical environments. These impacts will be globally felt and the results will impact on climates, air temperature while the end result is ocean cooling. Dust may have an effect on soil formation, through removal of desert surface cover, making geomorphologic formations in dry lands, and simultaneously; it can transmit pathogens detrimental to human that, impair respiratory function, cause air pollution, and disrupt communications and transport. Environmentally, such storms can hasten soil erosion and encourage desertification. Rosenfeld et al. 2001 identified that the effect of dust on cloud properties can be adequate to hinder precipitation. The reduction in precipitation has potential to cause drier soil, consequently more dust, in a possible positive feedback circle. Such episodes could potentially intensify drought conditions (Middleton, 1991). Both anthropogenic and climatic activities and their variability have led to increased dust storm activities within the Mongolian plateau region. Debate continues over the source and changing frequency of dust storms along the northern China-Mongolian corridor (Arimoto et al. 1998). Moreover dust from this desert region has developed into a global concern as it affects other countries, such as Japan and Korea, and moves out to the Pacific Ocean as well as in a southwesterly direction towards Taiwan. Some known Environmental factors will have an extreme sensitivity to dust activities, thus it is prudent for further research attend to help attend to both human and environmental concerns in the densely populated regions. The identification methods of major sources in this study will facilitate focus on critical regions and characterization of emission rates in response to environmental conditions. With these methods, we will have the capacity to improve global dust models and to assess the consequences of climate change on emissions in the future. This is attainable through remote sensing techniques. Husar et al. (1997) observes that: previously, satellite products have been useful in characterizing dust transport over the oceans, although they cannot be readily used to identify sources because of difficulties associated with the large temporal and spatial variability of the Aledo of land surfaces. Techniques by Stephenson et al 1980, that are based on measurements infrared emissions are very useful, this means that they will suffer from a range of challenges including effects of both water and cloud vapor, making it hard to detect coherent spatial trends over dust source regions. It has recently been displayed that the Total Ozone Mapping Spectrometer /TOMS on the Nimbus 7 satellite, was able to amass data that was suitable in mapping the distribution of engrossing aerosols that mainly comprised of soot emitted chiefly from regions burning biomass and mineral dust that was most commonly emitted from sources in very arid regions but also from occasional volcanic activities. According to Tegen et al, 1996, TOMS data can also illustrate that globally, the prevailing dominant sources of mineral dust are all located within the Northern Hemisphere; in the Middle East, North Africa and Central Asia. Satellite imagery is able to clearly show that the dust aerosols will most often cover large ocean areas. Values of aerosol's optical thickness will be associated with the dust transport will be much greater compared to those that attributed to pollution aerosols that are transported from North America, Asia and Europe. Other dust and sand aerosol models are now being used for daily forecasting of both dust storms and sand. The models similar to CARMA-Dust model in that they also use data from average weather models such as MM5. Both the Universities of University of Malta and Athens use modified versions of ETA weather models to help make the forecasts of dusts over northern Africa possible. The MODIS satellite sensors are able to provide increased quantitative information on the aerosols optical depths and properties; for instance, fine model fraction, aerosol optical thickness etc (Zhi,1997). This paper surveys the synergy of both the MODIS and NOAA satellites for mapping of sand storms and their rates in some parts of Asia. It is evident that every year between March and April yellow sand is seen to originate from Mongolia and China flying to North Pacific archipelago and some going to the west coast of America. Approach   An attempt was made to help monitor both the dust and sand storms using the NOAA data from the NOAA receiving station owned by the National Remote Sensing Center and the MODIS data from the NASA. For this purpose, brightness of temperature difference within the thermal infrared bands from the NOAA and the emissive bands of he TERRA. For the monitoring of true-color display, three bands of MODIS were used to help in the detection of yellow sand when RGB is displayed. Brown color was used to represent dust and/or sand storm. The digital values of the temperature brightness visuals are then converted into degrees centigrade with the selection of a dust storm area based on the brightness of temperatures in the range of 6°C and -9, within the areas where the majority of Gobi spring dust events take place. Wind speeds were also used to predetermine dust storms, less than 5 ms-1 speed equals to no occurrence of a dust storm while 12 to 28 ms-1 wind speed will most likely lead to a dust storm since wind speeds are usually between 6 ms-1 and 15 ms-1 in the event of a dust storm. For the method to be validated use of meteorological station data recorded during the occurrence of sand storms in the study area is vital. For instance, in 2006 March 07, very strong wind was recorded at nine different stations using the AVHRR data analysis technique Results Results from two thermal infrared bands, NOAA/AVHRR and emissive band from the MODIS/TERRA when compared resulted to better GIS data analysis, from this given approach the system is able to produce sandstorm and dust maps for varying periods of say, 6th March to the 9th of March in the year 2006. It is the most effective method for sand and dust storm monitoring and modeling. Further studies that are quantitative in using the MODIS/TERRA emissive bands are vital for a comprehensive study with the other satellites and the ground observation data from Lidar and all the numerical simulation that is based on the meteorological models. Many of the dust sources are in conjunction with areas have well documented human impacts for instance the Aral Seas and the Caspian, Tigris-Euphrates River Basin, southwest North America, and the loess land found in China. While in actual fact the main and largest active sources will be located in the truly remote areas having little or no human activities. Mapping will reveal that the underlying geometry of dust distributions over the specific regions can in most cases be associated with the prevailing geomorphologic features, that is, scrupulous topographical lows within the semiarid or arid regions, like the Mongolian plateau. Synergy levels between high-resolution MODIS and/or NOAA data can very greatly enhance operational accomplishment of the satellite-based dust mapping and monitoring. The study is able to represent effective applications of remote sensing techniques (GIS) to help create dust and sandstorm maps within the Mongolian plateau, while concentrating on Mongolian station's data. It would thus be essential that in the near future intelligence from affected Asian regions can/will be examined for validation. The next step of dust research over Asia will integrate station data from across the region, and hence such trans-national dust storm studies will greatly contribute to the 'Digital Earth' concept. References Ma, C, Kasahara, M,  Holler, R. and Kamiya, T. (2001) Characteristics of single particles sampled in Japan during the Asian dust-storm period. Atmospheric environment 35 , pp. 2707-2714. Tegen, I.,  Lacis, A. A. and Fung, I. (1996) The influence on climate forcing of mineral erosols from disturbed soils. Nature 380 , pp. 419-422. Willis, D. M.,  Easterbrook, M. G. and Stephenson, F. R. (1980) Seasonal variation of oriental sunspot sightings. Nature 287 , pp. 617-619. Zhang, X. Y.,  Arimoto, R.,  An, Z. and Zhi, S. (1997) Dust emission from Chinese desert sources linked to variations in atmospheric circulation. Journal of geophysical research 102:28 , pp. 41-47. http://www.informaworld.com/smpp/section?content=a790358302&fulltext=713240928 Read More
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