Dissertation > Excellent graduate degree dissertation topics show

Evaluation and Scale Effect Analysis of Soil Salinity in Dry and Wet Seasons of the Oasia Using Remote Sensing and Electromagnetic Induction Instruments

Author: YaoYuan
Tutor: DingJianLi
School: Xinjiang University
Course: Geography
Keywords: remote sensing EM38 scale effect dry and wet seasons soil salinization Regression-Universal Kriging
CLC: S157.1
Type: Master's thesis
Year: 2013
Downloads: 70
Quote: 0
Read: Download Dissertation

Abstract


Soil salinization is a worldwide ecological and environmental problems, it is oneof the main induced factors of the global soil desertification and soil degradation. Soilsalinization with soil pollution, soil degradation, soil erosion and soil desertificationconstitute the five soil problems, which can affect the global ecological environmentalstability and regional ecological security. The salinized soil is mainly concentrated inthe arid and semi-arid regions in the continents of the world, this is mainly due to soilevaporation in arid and semi-arid areas is larger than other regions, ground water levelis higher and more soluble salts contained in water, which can easily lead to theoccurrence of soil salinization. The oasis as a unique landscape type and ecologicalunit in the arid and semi-arid areas is not only a basic place to sustain human survivaland development in the arid areas, but also is a space for biosphere reproduction andhabitat. It is a best part in the arid region. The stability of the ecological environment inoasis can affect the human survival, social stability and sustainable economicdevelopment in arid area. The problems of soil salinization and secondary salinizationthat brought by the rapid development of irrigated agriculture in the oasis is not onlyrestricted the sustainable development of oasis agriculture, but also affect the overallstability of the oasis ecological environment. So, to slove soil salinization problem is astrategy related to the quality of ecological environment improvement and sustainabledevelopment problems in the arid area.Seasonal precipitation can influence the degree of soil salinization of oasis in aridarea. The degree and status of soil salinization are difference obviously in dry seasonthat lack of precipitation and wet season that plenty of the precipitation. It issignificance that to carry out the research on the spatial change of soil salinization indry and wet seasons and the spatio-temporal variability, which can expand evaluationscale from the spot to region, it can help people to master the soil salinity variation of oasis in arid area, to prevent soil desertification and soil degradation, to promote thesustainable development of oasis agriculture and to maintain the stability of theecological environment.Using the electromagnetic induction (EM38) can directly obtain the data ofapparent soil electrical conductivity, it has many advantages such as real-time, fast andhigh precision. It is the effective means to measured soil salinization in a large area,combined it with remote sensing technology which can effectively reflect the soilsalinization, and the data of salt dynamic change is an advanced methods of evaluating,monitoring and forecasting the soil salinization in the oasis area currently. An area ofsoil salinization seriously of the Weigan-Kuqa River Delta Oasis in the north of theTarim River Basin of Xinjiang, China was selected. In this contribution,electromagnetic induction EM38and its soil electrical conductivity data in horizontalmode (EMH) and vertical mode (EMV), field observation data and remote sensing areused to evaluate top soil salinity. The model of top soil salinity and composite in studyarea in dry and wet seasons was build in two modes with EM38. Investigate the spacedistribution change of soil salinization in two crucial seasons by interpreted the imagesin dry and wet seasons, in order to carry out the research on the spatio-temporal changeof different degree of soil salinization of oasis on regional scale. Spatial distribution oftop soil salinity in dry and wet seasons was conducted by using EM38surveying, soilsampling and Landsat-TM images. Scale extension of soil salinization was studiedfrom a spot to region, in order to reveal the spatio-temporal variability of top soilsalinity in arid area, it provide the theoretical reference and scientific basis to evaluateand improve soil salinization as well as to prevent and control secondary soilsalinization. The following were the main contents and conclusions:1. Based on ground sampling techniques in study area in dry and wet seasons,the inte rpreted model of soil salinity and composite was build by using the data offield measurement and apparent electrical conductivity (EM38), and analyzed the spatio-temporal variation of the top soil salinity and composite in study area. Thefollowing were the main conclusions:(1) After inspection, EMHis significantly correlated with EMVin study area, thecorrelation coefficient R2=0.8952between EMVand EMHin dry season and R2=0.8831in wet season, it is prove that the measured data has a high accuracy and credibility.(2) The model of EMHand EMVwas better than EMHor EMVas variable for topsoil layer in dry and wet seasons in study area, the model provides a reference for thechoice of the soil salinization interpreted model based on EM38of the oasis. The resultshows that the data interpreted by model are consistent with a P-P normal probabilityplot. The spherical model was fitted to the experimental variogram and top soil salinityin dry and wet seasons. It showed that the spatial construction characteristic and theserious spatial auto correlation.(3) The variability of the top soil salinity interpreted based on EM38existcomplex effect scale, it has certain scales dependency. Considering the scaledependency of spatial variation, the nested spherical models are fitted forsemi-variance of top soil.(4) The predominant cation or ion was Na+, Mg2+, K+, Ca2+and Cl-, CO32-, HCO3-,SO42-in the soil respectively. However, salinized soil restricted mainly by Na+and Cl-in the0-10cm top soil. The ions of Na+and Cl-interpreted model was build based onEM38, the model of EMHand EMVwas better than EMHor EMVas variable for topsoil layer in dry and wet seasons in study area.(5) The spatio-temporal distribution of top soil salinity and its main ions, includeNa+ion and Cl-ion in dry and wet seasons was analyzed by using Universal Kriging,and the trend is consistent. So we can use electromagnetic induction instruments tomonitoring spatial distribution of soil salinity and its composition in dry and wetseasons.2. The Landsat-TM images dates and soil sampling data we re used to extract the characte ristic variables, the decision tree method based on the characteristicvariables were used to build the soil salinization extraction models in dry and wetseasons, and drawing the classification map of the soil saliniza tion. Thespatio-temporal evolution of soil salinization was mainly regularities anddiscussed, the change were concluded of oasis on the regional scale.(1) Two temporal phase of Landsat-TM images in dry and wet seasons were usedto investigate the dynamic changes of soil salinization based on decision tree method,which use characteristic variables of normalized difference vegetation index(NDVI),modified normalized difference water index (MNDWI), the third principal component(K-L-3), TM7and TM1. The spatio-temporal evolution of soil salinization was mainlyregularities and discussed, the change was concluded of the oasis on the regional scale.The result showed that using this classification method can effectively to extract theinformation of soil salinization. This method has a higher accuracy of recognition fordifferent classes, especially on the different degree of soil salinization can bedistinguished effectively.(2) The classification results indicate that severe salinization soil is mainlydistributed in the downstream region of river basin and the desert-oasis ectone. Thelight and moderate salinization soil was distributed inside and outside of the oasis.Among them, the server salinization occupies a large area in dry season and occupies asmall area in wet season, which the degree of soil salinization significantly reducedcompared with the dry season.3. Scale extension from spot to region was studied based on the techniques ofremote sensing and EM38surveying.Scale extension of soil salinity was conducted from a spot to region by using soilsampling, EM38and remote sensing. The regression model of EM38(field data) andremote sensing (regional data) was used to scale extension, which had a high precision.The spatio-temporal variability of soil salinity of oasis had more detailed description owing to remote sensing images involved, for different scale assessment of soilsalinization provided a good theoretical basis.4. The techniques of remote sensing and EM38surveying we re used toanalyze the spatial variability of soil salinity in dry and wet seasons by SpectralIndex Regression, Universal Kriging and Regression-Universal Kriging.(1) This research using the method of Spectral Index Regression to reflect theinformation of soil salinization, which include NDSI (Normalized Difference SalinityIndex), SI (Salinity Index), BI (Brightness Index), DVI (Different Vegetation Index)and NDVI (Normalized Difference Vegetation Index). Integrated spectral index andapparent soil electrical conductivity by EM38surveying to build the regression modelof spectral index in dry and wet seasons in study area, and drawing the classificationmap of soil salinization. The regression model of spectral index of SI and NDVI wasbetter than other spectral index as variable for top soil layer in dry season, and DVIwas better in wet season. The correlation coefficient is significance at P<0.01.(2) Results indicated spatial distribution of top soil salinity in dry and wet seasonsby Regression-Universal Kriging was more specific and through than by SpectralIndex Regression and Universal Kriging. The Regression-Universal Kriging wasoverly residuals map and soil salinity by regression methods. The residuals werecalculated by real value and predicted was interpolated by Universal Kriging. Thespatio-temporal of top soil salinity was mapping by overlay spectral index regressionmap and residuals map. Combination this method with classical statistical andgeostatistical method can improve the accuracy of prediction of the spatial variabilityof top soil salinity of oasis.(3) The result shown that soil salinization, mainly located in the southeast, south,southwest and east of the study area, concentrated in downstream areas ofWeigan-Kuqa River Basin and the desert-oasis ectone, exhibited obvious trend effectof the soil salinity in dry season is greater than wet season, around of oasis and the desert-oasis ectone is greater than inter of oasis. We can conclude that this study mayprovide a theoretical reference for rapid and accurate assess and predict the change ofthe spatial distribution of soil salinity in dry and wet seasons.

Related Dissertations

  1. Research on Spaceborne Hyperspectral Sensor Simulation,TP391.9
  2. Research on Remote Sensing Image Processing Combining High Fidelity Compression and Resolution Enhancement,TP751
  3. Road extraction algorithm based on region segmentation of remote sensing image,TP751
  4. Modelling Phycocyanin and CDOM Concentration from Hyperspectral Reflectance Data in Lake Taihu,X87
  5. A Study on Building Remote Sensing Retrieval System for Countryside Water-Body Quality Based on ArcGIS Server,S127
  6. Scale Effect on Spatial Expressions of Paddy Soil Organic Carbon in Tai Lake Region,S158
  7. Spectral Characteristics of Rice Damaged by Nilaparvata Lugens (St(?)l) and Cnaphalocrocis Medinalis(Guen(?)e),S435.112
  8. Study on Growth Monitoring Technique Based on Pixel Un-Mixing Method and HJ Remote Sensing Images in Paddy Rice,S511
  9. Study on Growth Predicting Technique Based on Integration of Remotely Sensed Information and Crop Model in Rice,S511
  10. Study on Growth Monitoring and Predicting Technique Based on Integration of Remote Sensed Information and Model in Wheat,S512.1
  11. The Estimation on the Total Nitrogen of the Rice Field by Remote Sensing in Lishui County, Nanjing City,S153
  12. Optical Properties of Chlorphyll-a in Reservoir Water and Its Concentration Inversion Models by Remote Sensing,S127
  13. Land Desertification in Qinghai Lake Landscape Pattern Change,X171
  14. Remote sensing data processing grid platform design and initial implementation,TP79
  15. Web-based scientific computing legacy application sharing technology research,TP393.09
  16. Vegetation Stress Level Monitoring in Mine Area Based on HJ-1 Hyperspectral Data,TP751
  17. Study of the Active Faults Using Remote Sensing and Activity Analysis,P542.3
  18. Designing and Realization Integreated Management System of Multi-Source Remote Sensing Image in Mining Area,P208
  19. Researches on Change Detection of Multitemporal Remote Sensing Image,TP391.41
  20. Research and Implementation of Multi-Scale Remote Sensing Image Segmentation,TP391.41
  21. Object-Based Automatic Extraction of Change Information Based on High-Resolution Remote Sensing Image Research,P237

CLC: > Agricultural Sciences > Agriculture as the foundation of science > Soil > Soil and Water Conservation > The causes and prevention of soil erosion
© 2012 www.DissertationTopic.Net  Mobile