Literature Review On Remote Sensing Environmental Sciences Essay

Literature Review On Remote Sensing environmental Sciences EssayRemote catching is the science or art of acquiring development about the Earths surface without actually being in contact with it. This is through by sensing and recording ricocheted or emitted energy and do working, analyzing, and applying that information. In much of remote sensing, the process involves an interaction between incident radiation and the targets of interest. (Dr. S. M. Rahman, 2001).Remote sensing makes it possible to collect data on dangerous or inaccessible beas. Remote sensing applications include monitoring deforestationin athletic fields such as theAmazon Basin,glacialfeatures in Arctic and Antarctic regions, anddepth soundingof coastal and ocean depths. Military collection during theCold Warmade utilization of stand-off collection of data about dangerous border areas. Remote sensing also replaces costly and slow data collection on the ground, ensuring in the process that areas or objects are not disturbed. Remote sensing exceedingly influences everyday life, ranging fromweather forecaststo reports onclimate changeornatural disasters. As an example, 80% of the German students use the services ofGoogle Earth. (Wikipedia, 2012)In recent time, with mans increasing interventions with the environment, the situation is aggravated. The quality of available data is extremely un blush. Land use planning establish on unreliable data evoke lead to costly and gross errors. crap corroding research is a capital-intensive and time-consuming exercise. Global extrapolation on the nucleotide of few data serene by diverse and non-standardized methods can lead to gross errors and it can also lead to costly mistakes and misjudgements on critical indemnity issues. So, remote sensing provides convenient solution for this problem. Moreover, voluminous data gathered with the help of remote sensing techniques are batter handled and utilized with the help of geographic study System (GIS). (M. H. Mohamed Rinos, 2000)There are two different draw closees that can be adopted for determining the characteristics of basisslide from remote sensing data. The first approach determines more qualitative characteristics such as number, distribution, type and character of debris flow. This can be achieved with either satellite or air borne imagery collected in the visible and infrared regions of the spectrum. The next approach complements the qualitative characterization, estimating dimensions (e.g. length, width, thickness and local pitch, motion, and debris distribution) along and across the mass movement. (V. Singhroy, 2004)Literature Review on Geographical Information System (GIS)Geographical Information System (GIS) is used to arrange the computer hardware, software, and geographic data. It helps the flock interact, analyze, identify relationship and find the solutions to the problems. The body is designed to capture, store, update, manipulate, analyze, and display stud ied data and used to perform analyses (ESRI, 2005). Since 1970s, GIS has been used to analyze various environments. But the extensive application of GIS to hydrologic and hydraulic fabricing and stuff mapping and management begin from early 1990s. (Maidment, 2000).GIS has the ability to represent elevation in terms of topographic surfaces is central to geomorphological analyses and frankincense to the importance of representing topography exploitation digital Elevation Model (DEM). It is through the distribution of skank that the land surface changes over the long term and so the ability to link sedimentation transfer with DEM changes. (Schmidt, 2000)ArcView GIS desktop software provided the tools of map features that will affect a propertys value such as crime rates, environmental pretends, and the condition of surrounding neighborhoods and properties. ESRIs ArcGIS is a GIS which is working with maps and geographic information. ArcGIS software can be used for following functi ons creating and utilize maps, compiling geographic data, analyzing mapped information, sharing and discovering geographic information, using maps and geographic information in a range of applications, and managing geographic information in database. (Wikipedia, ArcGIS, 2012). The ArcGIS provides tools for constructing maps and geographic information.Literature review on colly erodingSoil eroding is genius form of domain degradation along with terra firma compaction, low organic matter, and release of soil structure, poor internal drainage, salinization, and soil acidity problems (Wall, 2003). When the degradation of the soil is getting serious, it will contribute in accelerate the soil erosion. Soil erosion is a natural process it usually does not cause all major problem to the environment. The soil is carried by the agents such as wind, body of water, ice, animals, and the use of tools by man. Soil erosion is a very slow process and even unnoticeable sometime, but it m ay occur at an alarming rate which causing the loss of surface soil.Farmers world encompassing are losing about 24 billion tonnes of topsoil each year. In developing countries, because of the population pres undisputable forces land to be more intensively farmed, the erosion rates per acre are twice as higher(prenominal) as the standard. The soil erosion also will affect the productivity and growth. This is because when the soils are depleted and crops receive poor livelihood from the soil, the food provides poor nourishment to people. The rate of losses soil is faster than the creation of new soil. The difference between creation and loss represents an annual loss of 7.5 to 10 tonnes per acre worldwide. (DeHaan, 1992)The eroded soil that enters watercourse will reduce the water quality, reduces the efficiency of the particulars drainage system and also decreases the storage capacity of lakes. Sediment is the eroded soil that settles in the water systems. Accumulation of the sedim ent will reduce the capacity of a river or reservoirs to hold flood water. Thus, it requires a lot of m superstary to clean the sediment ofttimes and manually. Sediment also can block the sunlight for aquatic plant and inhibit fish spawning. The water becomes not safe for drinking if there is outpouring of chemical and nutrients from surrounding farmers fields.In Malaysia, soil erosion is a common natural occurrence. This is due to particular topography, soils and corresponding botany that predominate and the extensive rainfall that the country experiences. However, accelerated soil erosion is becoming a serious problem in Malaysia because of rapid land use developments. Various forms of erosion concord have been proposed to develop the land in ways that are sensitive to its geography. (Abdullah, 2005)Literature review on Revised Universal Soil Loss equalityThe development of Universal Soil Loss Equation (ULSE) initially was to assist soil preservationists in farm planning. The y used ULSE to estimate the soil loss on circumstantial slopes in specific fields. USLE was a guide for the conservationist and farmer to control the erosion if the estimated soil loss exceeded acceptable limits.Revised Universal Soil Loss Equation (RUSLE) is a science tool that has been modify over the last several years. It is ground on USLE and makes some improvement on the equation. The RULSE has change the effects of soil roughness and the effect of local weather on the prediction of soil loss and sediment delivery. (Revised Universal Soil Loss Equation, 2003). RUSLE can be used for site evaluation and planning purposes and to aid in the decision in selecting erosion control sum. The RUSLE provides number to substantiate the benefits of planned erosion control measures and also an estimate of severity of erosion.A = R.K.LS.C.PA is annual soil loss (tonnes/ha/year).R is rainfall erosivity factor. It is an erosion index for the give storm diaphragm (MJ.mm/ha/h)K is soil e rodibility factor. It is the erosion rate for a specific soil continuous fallow condition on a 9% slope having a length of 22.1m (tonnes/ha/(MJ.mm/ha/h))LS are topographic factor. It represents the slope length and the slope steepness. It represents the ratio of the soil loss from a specific site to that from a unit site (9% slope with slope length 22.1m) while other parameters are held constant.C is the cover management factor. It represents the protecting(prenominal) coverage of canopy and organic material in direct contact with the ground.P is the support practice factor. It includes the soil conservation operations and other measure of control erosion.Literature review on USLE and RUSLETable 2.1 Comparison of USLE and RUSLE (Renard, 1991)FactorUSLERUSLERBased on long term average rainfall conditions for specific geographic areasData from more weather stations and thus the value are more precise for any given location.RUSLE computes a correction to R. This is to reflect the effe ct of raindrop impact for flat slopes striking water ponded on the surface.KBased on soil texture, organic matter content, permeability, and other factors inherent to soil type.Adjusted to account for seasonal changes such as freezing and thawing, soil moisture, and soil consolidation.LSBased on length and steepness of slope, regardless of land use. appoint new equations based on the ratio of rill to interrill erosion, and accommodates complex slopes.CBased on cropping sequence, surface residue, surface roughness, and canopy cover, with are weighted by the percentage. Lumps these factor into a table of soil loss ratios, by crop and tillage scheme.Sub factors (prior land use, canopy cover, surface cover, surface roughness, and soil moisture) are used. Dividing each year into rotation of 15 day intervals, then calculate the soil loss ratio for each period. The value need to recalculate if one of the sub factors change.RUSLE provides improved estimates of soil loss changes as they occu r throughout the year, especially relating to surface and show up surface residue and the effects of climate on residue decomposition.PValues change depending on the slope ranges with some distinction for various ridge heights. It is based on installation of practices that slow overspill and thus reduce soil movement.Values are based on hydrologic soil groups, slope, row grade, ridge height, and the 10 year single storm erosion index value.In RUSLE, it computes the effect of strip-cropping based on the transport capacity of flow in dense strips relative to the amount of sediment reaching the strip.The P factor for conservation planning considers the amount and location of deposition.Literature review on landslideLandslides are a type of soil erosion and major natural geological hazards. Each year, the landslide is responsible for enormous property damage which involves both direct and indirect costs. Malaysia experience frequent landslides. According to the local newspaper report in the years 2006-2009, along east coast highways in Peninsular Malaysia, in Sabah (East Malaysia) and in the island state of Penang, heavy rainfalls triggered landslides and mud flows. (Pradhan, 2009)Landslides draw when there are changes from a stable to an unstable condition in the stability of a slope. There are natural causes and human causes which contributing to a change in the stability of a slope. Natural causes of landslides includeGroundwater (pore water) pressure acting to destabilize the slopeLoss or absence of vertical vegetal structure, soil nutrients and soil structureErosion of the toe of a slope by rivers or ocean wavesWeakening of a slope through vividness by snowmelt, glaciers melting, or heavy rainsEarthquakes adding loads to barely table slopeEarthquake-caused liquefaction destabilizing slopesVolcanic eruptionsLandslides that are due to human causes areDeforestation, cultivation and construction, which destabilize the already fragile slopeVibrations from mach inery or trafficBlastingEarthwork which alters the shape of a slope, or which imposes new loads on existing slopeIn school soils, the removal of deep-rooted vegetation that bind colluvium to bedrock saying, agricultural or forestry activities which change the amount of water which infiltrates the soil. (Wikipedia, 2012)Landslides in Malaysia are mainly triggered by equatorial rainfall and flash floods. The rainfall and floods cause the rock to fail along fracture, joint and cleavage planes. The geology of Malaysia is quite stable but continuous development and urbanisation lead to deforestation and erosion of the covering soil layers thus causing serious threats to the slopes (Pradhan, 2007). Abandoned project at hill sites for a certain period which affecting the maintenance of the slopes could causing the slopes to collapse.List of landslide events happened in Malaysia1 May 1961 A landslide occurred inRinglet,Cameron Highlands,Pahang.21 October 1993 The man-madePantai Remis lan dslidecaused a newcoveto be formed in the coastline.11 December 1993 48 people were killed when a block of theHighland Towers collapsedatTaman Hillview,Ulu Klang,Selangor.30 June 1995 20 people were killed in the landslide atGenting Highlands slip roadnearKarak Highway.6 January 1996 A landslide in theNorth-South Expressway(NSE) nearGua Tempurung,Perak.29 August 1996 A mudflow near Pos DipangOrang Aslisettlement inKampar,Perak, 44 people were killed in this tragedy.15 May 1999 A landslide nearBukit Antarabangsa,Ulu Klang,Selangor. Most of theBukit Antarabangsacivilians were trapped.20 November 2002 Thecottageof theAffin Bankchairman General (RtD) Tan Sri Ismail Omar collapse causing landslide inTaman Hillview,Ulu Klang,Selangor.December 2003 A rockfall in theNew Klang Valley Expressway(NKVE) near theBukit Lanjaninterchange caused the expressway to close for more than six months.31 May 2006 Four persons were killed in thelandslidesat Kampung Pasir, Ulu Klang, Selangor.26 Dece mber 2007 Two villagers were buried alive in a major landslide, which destroyed nine wooden houses in Lorong 1, Kampung Baru Cina,Kapit,Sarawak.12 February 2009 one contract worker was killed in a landslide at the construction site for a 43-storey condominium inBukit Ceylon,Kuala Lumpur.21 May 2011 16 people mostly 15 children and a caretaker of an orphanage were killed in alandslide caused by heavy rainsat the Childrens Hidayah Madrasah Al-Taqwa orphanage in FELCRA Semungkis,Hulu Langat,Selangor. (Wikipedia, 2012)A scientific analyses of landslides need to be carry out to predict landslide-susceptible areas, and thus reduce landslide damages through proper preparation and mitigation. So, understanding landslides and preventing them is a serious challenge across worldwide.Literature review on one-time(prenominal) research and studies title of respectThe application of GIS-based logistic statistical regression for landslide cogency mapping in the Kakuda-Yahiko Mountains, Centra l JapanAUTHOR, YEARLulseged Ayalew, Hiromitsu Yamagishi, 2005STUDY AREAKakuda-Yahiko Mountains and their surroundings. quarry / CONCEPTTo study the landslide risk around the Kakuda-Yahiko Mountains.To study the use of logistic regression.To demonstrate the combination bivariate statistical analyses (BSA) to simplify the interpretation of the mold.methodological analysis / METHODAnalytical approachesIn LR or even in one-dimensional regression, it does little good to combine data with different measuring scales.Make sure that data have been expressionized in a manner LR needs. Failure to do so generally leads to problems during the interpretation of the final results.Statistical resultsOverall model statistics of the regression conducted in this study using IDRISI.Coefficient positive indicating that they are positively related to the probability of landslide formation through the log transformation.Prediction probabilities and the construction of the susceptibility mapIn addition to the model statistics and coefficients, the final result of the regression process in IDRISI is a predicted map of probability defined by numbers that are constrained to fall between 0 and 1.The more these numbers are close to 1, the better they indicate the likelihood of finding the mapped landslides.Depending on the self-sufficing parameters considered, the landslide inventory map and the statistical approach used, the best predictor parameters and the predicted probability map of a logistic regression can vary considerably. widening / outline / RESULTLandslides are portrayed according to the types of movements namely slide, fall, flow, spread and topple.The principle of logistic regression (LR) rests on the analysis of a problem, in which a result measured with dichotomous variables such as 0 and 1 or true and false, is determined from one or more independent factors.TITLEAssessment of soil erosion and sediment delivery ratio using remote sensing and GISAUTHOR, YEARWeifeng ZH OU and Bingfang WU, 2008STUDY AREAUpstream Chaobaihe River catchment, magnetic north China.OBJECTIVE / CONCEPTTo develop monitoring of soil losses in the upstream Chaobaihe River Catchment.To develop a model by using Geographic Information System tools.To compute sediment delivery ratio (SDR) per hydrological unit.methodological analysis / METHODData CollectionRemote sensing data, digital elevation model (DEM), and land use and land cover GIS data were used.Universal Soil Loss Equation (USLE)Simple empirical model, based on regression analyses of soil loss rates on erosion plots in the USA.The model is designed to estimate long-term annual erosion rates for agricultural fields.A = RKLSCA represents mean (annual) soil loss, R is the rainfall erosive factor, K is the soil erosibility factor, L is the slope factor, S is the slope length factor, and C is the cover management factor.OUTPUT / SUMMARY / RESULTThe work indicated there are a number of advantages in using the modify USLE eq uation including the ability to combine it with a raster-based GIS to produce a cell-by-cell basis for mapping spacial patterns of soil erosion rates.The advantage of using a GIS raster based framework is that it allows one to quantify the impact of a single factor on the overall result and it can also easily be updated with improveddatasets.TITLESoil erosion hazard evaluation An integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategiesAUTHOR, YEARMd. Rejaur Rahman, Z.H. Shi, Cai Chongfa, 2009STUDY AREAWithin the Danjiangkou County, with an area of 3115.58 km2 and set(p) in the north-western part of Hubei province of China.OBJECTIVE / CONCEPTTo develope numerical model for soil erosion hazard assessmentTto analyze soil erosion by attempting to estimate the volumes or masses of soil lossMETHODOLOGY / METHODAnalysis of study areaThe selected area is within the Danjiangkou County, with an area of 3115.58 km2 and locate d in the north-western part of Hubei province of China.Sandy clay loam, silt loam and sandy loam on the study area play a dominant role in soil erosion by water.Data acquisition and preparationPrepare and analyze the different types of data in soil erosion prediction and hazard assessment as there are many factors that affect soil erosion status.Soil erosion estimationModels are needed to predict soil erosion rates under different resource and land-use conditions.Empirical erosion prediction models continue to play an important role in soil conservation planning and are widely used to predict soil erosion.OUTPUT / SUMMARY / RESULTThe Z-score analysis with GIS and selected parameters, provided a hazard assessment of soil erosion of the area. The methodology of combining the Z-score with GIS provided an improved method for the synthetic evaluation of soil erosion hazard, which extended the GIS capability of spatial analysis and the Z-score capability of multi-layer analysis.TITLE spac ial Prediction of Landslide bump Using Discriminant AnalysisAUTHOR, YEARPeter V. Gorsevski, Paul Gessler, Randy B. Foltz, 2000STUDY AREARocky Point, a small river basin of the Clearwater River Basin in central Idaho.OBJECTIVE / CONCEPTTo study the concept of Discriminant Analysis and GIS.To analyze the landslide hazard area on Rocky Point.METHODOLOGY / METHODPrincipal Component Analysis (PCA)Help to analyze the multivariate data set.Discriminant AnalysisClassify presence and absence of landslides using principal region scores.Discriminant analysis is a multivariate technique that is used to build rules that can classify landslide hazard into appropriate class.Cross-validationEstimate the probabilities of misclassification.Cross-validation method removes each card vector from the calibration data set at a time, forms the discriminant rule based on all the remaining data to classify the removed watching, and notes whether the observation is correctly classified.GISprovided a detail ed basis for spatial prediction of landslide hazard.OUTPUT / SUMMARY / RESULTHazard map generated.Graph of multivariate normal probability plot for the principal component scores.TITLERemote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia.AUTHOR, YEARBiswajeet Pradhan, 2010STUDY AREAPenang, Cameron and Selangor.OBJECTIVE / CONCEPTTo generate cross-validation of a multivariate logistic regression model using remote sensing and GIS for landslide hazard analysis.METHODOLOGY / METHODData and materialInterpreting celestial photographs and satellite images (SPOT 5 and Landsat TM) of study area.These aerial photographs were taken during 1981-2006 and were acquired from Malaysian Remote Sensing Agency data archives.Data analysis using ARC/INFO GIS software package and a Digital Elevation Model (DEM) was constructed.These data are related to the primary eects (impact of debris or inclusion of a ected site from previously occurred landslides) of a wide variety of landslide typesModel ApproachingTraditional approach using a multivariate logistic regression model implemented in a GIS framework.The landslide hazard analysis is a function of a variety of variables that include slope, aspect, curvature, topography, distance from drainage, land cover, soil texture and types, geology and distance from lineament, rainfall precipitation, and the normalized dierence vegetation index (ndvi)The coefficient applied to the study area, for landslide hazard mapping.Multivariate logistic regression modelEasier to use than discriminant analysis when have a mixture of numerical and categorical regressors , because it includes procedures for generating the necessary dummy variable automatically.Application of multivariate logistic regression model on landslide hazard mapping.Validation of the model.OUTPUT / SUMMARY / RESULTThe validation results showed a satisfying agreement between the hazard maps and the landslide locations verified in the field.TITLEGIS Application in Landslide Hazard AnalysisAUTHOR, YEARChyi-Tyi Lee, 2009STUDY AREAShihmen Reservoir Catchment Area in Northern Taiwan.OBJECTIVE / CONCEPTTo analyze the landslide hazard area using GIS application.METHODOLOGY / METHODImage and data collectionThe basic data utilized included a 5m x 5m grid DEM, SPOT5 images, 1/500 photo-based compliance maps, 1/50000 geologic maps and hourly rainfall data.Establish of event-based landslide inventoryTo develop susceptibility model, only considered new landslides triggered by typhoons.Landslides triggered by Typhoon Aere were interpreted and show by comparing SPOT5 images taken before and after thetyphoon.Determination of causative factors and triggering factorsThese factors are then statistically tested and y effective factors selected for susceptibility analysis.10 factors are selectedLithology, slope gradient, NDVI, slope roughness, profile curvature, total slope height, relative slope height, topographic wetness index, distance to a fault, maximum rainfall intensity.AnalysisConstruction of model via logistic regression.Logistic regression to determine a linear function of factors for interpreting the landslide distribution from a set of training data.The linear function is used to calculate the landslide susceptibility index (LSI) for each cell.The LSI used to establish a probability of failure to LSI curve and determine the spatial probability of landslide occurrence at each cell.Landslide susceptibility mappingThe landslide hazard area could be for the prediction of future landslides providing a scenario rainfall distribution is given.OUTPUT / SUMMARY / RESULTSuccessfully predict landslide location, area and volume in a drainage basin or catchment area using GIS.