【摘要】：土地荒漠化、土地沙化以及土地退化的原因眾多,其中最主要就是土壤鹽漬化。新疆作為我國最為重要的糧食基地和農(nóng)業(yè)后備資源戰(zhàn)略基地,其綠洲農(nóng)業(yè)的穩(wěn)定和可持續(xù)發(fā)展對于保障國家的糧食安全具有重大的戰(zhàn)略意義。而當前灌溉農(nóng)業(yè)的快速發(fā)展、土地的不合理開發(fā)以及土地利用方式地改變,都破壞了新疆綠洲的水鹽平衡。新疆綠洲的農(nóng)業(yè)生產(chǎn)和生態(tài)環(huán)境在土壤鹽漬化、次生鹽漬化的威脅下變得岌岌可危。目前,世界范圍內(nèi)資源調(diào)查、環(huán)境監(jiān)測常用的方法是遙感技術。它具有很多明顯的優(yōu)勢,如速度快、精度高、花費少又能綜合宏觀的對區(qū)域范圍進行不同時段的多次監(jiān)測�；谏鲜鰞�(yōu)點,它已經(jīng)被用在大面積監(jiān)測土壤鹽漬化上。但相對應的地面實測實驗也在近年快速發(fā)展,取得了豐碩的成果,電磁感技術和實測熱紅外發(fā)射率就是典型代表,其具備明顯的優(yōu)點。電磁感應技術(EM38電磁感應儀)可以直接獲取土壤表觀電導率數(shù)據(jù),具有實時、快速、精度高的特點,但其對于細節(jié)的表達較為粗略,不能夠完整地反映局部小區(qū)域的土壤鹽漬化信息。而熱紅外發(fā)射率光譜能夠獲取地物的連續(xù)光譜信息,具有更為精細的、微米級的光譜分辨率,能夠反映地物細微的光譜特征。本研究將這兩種技術相結合,應用于土壤鹽漬化這一實際問題上,以期為熱紅外遙感技術實現(xiàn)區(qū)域大尺度鹽漬化監(jiān)測提供基礎。本研究在實驗室詳實、細致的野外工作的基礎上,建立基于電磁感應技術與實測數(shù)據(jù)的輕、中、重三種土壤鹽漬化解譯模型。采用ISSTES方法對土壤熱紅外發(fā)射率和溫度進行了分離。以盡量減小外界的各種干擾因素(儀器、環(huán)境、人為)為目的,通過相鄰平均值法(Adjacent-Averaging)、Savitzky-Golay濾波法、分位數(shù)濾波(Percentile Filter)以及FFT Filter四種方法,分別對樣點光譜數(shù)據(jù)進行了平滑去噪,通過最終分析,Savitzky-Golay濾波法的效果是最好的。用一階微分變換、對數(shù)變換、倒數(shù)變換、對數(shù)的倒數(shù)變換、二階微分變換5種數(shù)學變換形式對平滑降噪后的光譜與含鹽量模型結合進行變換處理,分析它們之間的特定關系,提取敏感波段。最后進行了模型的擬合工作,運用了線性(簡單線性模型)、非線性(對數(shù)模型、冪指數(shù)模型、拋物線模型、指數(shù)模型)、逐步多元回歸模型以及偏最小二乘等方法。之后分別對7個模型進行了精度評價,通過不同情況的對比分析,找到最佳模型。
[Abstract]:There are many reasons for land desertification, desertification and land degradation, among which soil salinization is the most important. Xinjiang is the most important food base and agricultural reserve resource strategic base in China. The stability and sustainable development of oasis agriculture is of great strategic significance to ensure the national food security. However, the rapid development of irrigated agriculture, the unreasonable development of land and the change of land use mode have destroyed the balance of water and salt in Xinjiang oasis. Under the threat of soil salinization and secondary salinization, the agricultural production and ecological environment of Xinjiang oasis become precarious. At present, remote sensing technology is commonly used in worldwide resource survey and environmental monitoring. It has many obvious advantages, such as fast speed, high precision, low cost and comprehensive macro monitoring of different periods of time. Based on the above advantages, it has been used to monitor soil salinization in a large area. However, the corresponding experiments on the ground have developed rapidly in recent years and have achieved fruitful results. The electromagnetic induction technology and the measured thermal infrared emissivity are typical examples, which have obvious advantages. Electromagnetic induction technology (EM38 electromagnetic induction instrument) can directly obtain soil apparent conductivity data, which has the characteristics of real time, fast and high precision, but the expression of details is relatively rough. The soil salinization information of local small area can not be completely reflected. The thermal infrared emissivity spectrum can obtain the continuous spectral information of the ground object, and has a more fine, micron spectral resolution, which can reflect the fine spectral characteristics of the ground object. This study combines these two techniques and applies them to the practical problem of soil salinization in order to provide the basis for the realization of regional large-scale salinization monitoring by thermal infrared remote sensing technology. On the basis of detailed and detailed field work in laboratory, three kinds of soil salinization interpretation models based on electromagnetic induction technology and measured data were established. The soil thermal infrared emissivity and temperature were separated by ISSTES method. In order to minimize all kinds of external interference factors (instrument, environment, artificial), the spectral data of sample points are smoothed and de-noised by four methods: adjacent average method (Adjacent-Averaging), Savitzky-Golay filtering method, quantile filtering (Percentile Filter) method and FFT Filter method, respectively. Through the final analysis, the effect of Savitzky-Golay filtering method is the best. The first order differential transform, logarithmic transformation, reciprocal transformation, logarithmic reciprocal transformation and second-order differential transformation are used to transform the smooth denoising spectrum and salt content model, and the special relationship between them is analyzed. The sensitive band is extracted. Finally, the fitting work of the model is carried out. The methods of linear (simple linear model), nonlinear (logarithmic model, power exponential model, parabola model, exponential model), stepwise multivariate regression model and partial least squares are used. After that, the accuracy of the seven models was evaluated, and the best model was found through the comparative analysis of different cases.
【學位授予單位】：新疆大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：S156.41

【參考文獻】

相關期刊論文 前4條

1 夏軍;塔西甫拉提·特依拜;買買提·沙吾提;張飛;韓桂紅;;熱紅外發(fā)射率光譜在鹽漬化土壤含鹽量估算中的應用研究[J];光譜學與光譜分析;2012年11期

2 侯艷軍;塔西甫拉提·特依拜;張飛;買買提·沙吾提;依力亞斯江·努爾麥麥提;;荒漠土壤全磷含量熱紅外發(fā)射率光譜估算研究[J];光譜學與光譜分析;2015年02期

3 劉福漢,王遵親;潛水蒸發(fā)條件下不同質地剖面的土壤水鹽運動[J];土壤學報;1993年02期

4 李洪義;史舟;程街亮;李艷;;基于EM38的土壤剖面電導率預測研究[J];中國農(nóng)業(yè)科學;2008年01期

，

本文編號：2269672