本文選題：遙感影像 + 地形輻射校正�。� 參考：《山東農(nóng)業(yè)大學(xué)》2017年碩士論文

【摘要】：遙感作為一種遠(yuǎn)距離非接觸式獲取地表信息的方法,越來越受到人們的重視。在遙感影像的地物光譜信息分析中,定量遙感一直是人們研究的一個(gè)重要方向,由于衛(wèi)星是在高空獲取地面圖像,不可避免的受到電磁波、大氣、地形等因素的干擾,其中,由于地形起伏造成的地物光譜信息的改變是影響影像質(zhì)量的重要原因之一。地形起伏使太陽(yáng)光易被山體遮擋,導(dǎo)致背向陽(yáng)光的坡面不能反射太陽(yáng)的直射光線,地物紋理特征被削弱,影響了影像的判讀,降低了地物分類精度等諸多遙感分析的過程。因此,基于地形輻射校正的影像光譜信息恢復(fù)是以遙感手段準(zhǔn)確獲取地表真實(shí)光譜信息不可或缺的一步。本文首先介紹地形輻射校正的研究背景和國(guó)內(nèi)外研究現(xiàn)狀,并用ENVI軟件對(duì)影像進(jìn)行大氣校正、幾何校正等預(yù)處理。然后利用MATLAB軟件對(duì)研究所用的地形輻射校正方法(C校正、SCS+C校正、Minnaert-SCS校正、Teillet-回歸校正、VECA校正)進(jìn)行代碼編寫和處理。在Minnaert-SCS校正模型的基礎(chǔ)上通過引入半經(jīng)驗(yàn)參數(shù)C對(duì)其進(jìn)行改進(jìn),避免在太陽(yáng)入射角余弦值cosi過小時(shí)的過度校正現(xiàn)象,并編碼處理比較其校正效果。最后提取出RVI、NDVI、EVI、MSAVI四種植被指數(shù)并作比較分析,利用像元二分法分別計(jì)算這四種植被指數(shù)下的植被覆蓋度,分析地形輻射校正對(duì)植被覆蓋度反演的影響。通過實(shí)驗(yàn)處理和比較發(fā)現(xiàn),改進(jìn)的校正方法可以提高地形效應(yīng)下陰影區(qū)域和低亮度區(qū)域的校正效果,能消除大部分反射率值的差異,通過目視比較和統(tǒng)計(jì)數(shù)據(jù)分析發(fā)現(xiàn),改進(jìn)的模型取得了較好的校正效果;另一方面地形輻射校正對(duì)基于EVI計(jì)算的植被覆蓋度起到了改善作用,對(duì)基于RVI、NDVI和MSAVI計(jì)算的植被覆蓋度提升較小,建議在使用EVI估算多山區(qū)域的植被覆蓋度時(shí)進(jìn)行地形輻射校正。
[Abstract]:As a long distance non-contact method to obtain surface information, remote sensing has attracted more and more attention. Quantitative remote sensing has always been an important research direction in the spectral information analysis of ground objects in remote sensing images. Because the satellite acquires ground images at high altitude, it is inevitably disturbed by electromagnetic waves, atmosphere, topography and other factors, among which, The change of spectral information caused by topographic fluctuation is one of the important factors that affect the image quality. The relief of the terrain makes the sunlight easily obscured by the mountain body, which can not reflect the direct ray of the sun on the slope of the back sun, and the texture feature of the ground object is weakened, which affects the interpretation of the image and reduces the process of remote sensing analysis such as the precision of the classification of the ground objects and so on. Therefore, the restoration of image spectral information based on terrain radiation correction is an indispensable step to accurately obtain the true spectral information of the surface by remote sensing. This paper first introduces the background of topographic radiation correction and the present research situation at home and abroad, and uses ENVI software to preprocess the image such as atmospheric correction, geometric correction and so on. Then, the method of terrain radiation correction (C correction SCS C correction and Minnaert-SCS correction / Teillet-regression correction Veca correction) used in the research is compiled and processed by MATLAB software. Based on the Minnaert-SCS correction model, the semi-empirical parameter C is introduced to improve the correction, to avoid the over-correction of the cosine value cosi at the solar incidence angle, and to compare the correction effect with the coding process. Finally, four vegetation indices were extracted and compared with each other. The vegetation coverage under the four vegetation indices was calculated by pixel dichotomy, and the effect of topographic radiation correction on vegetation coverage inversion was analyzed. Through experimental processing and comparison, it is found that the improved correction method can improve the correction effect of shadow area and low luminance area under terrain effect, and eliminate the difference of most reflectivity values. Through visual comparison and statistical data analysis, it is found that, On the other hand, topographic radiation correction can improve vegetation coverage based on EVI, and improve vegetation coverage based on RVI NDVI and MSAVI. It is suggested to use EVI to estimate vegetation coverage in mountainous areas.
【學(xué)位授予單位】：山東農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P237;Q948

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 文青;;2016年《衛(wèi)星產(chǎn)業(yè)狀況報(bào)告》[J];衛(wèi)星應(yīng)用;2016年06期

2 陳明華;柴鵬;陳文祥;黃坤;陳志彪;;不同植被指數(shù)估算植被覆蓋度的比較研究[J];亞熱帶水土保持;2016年01期

3 王愛蕓;趙志芳;;基于遙感的植被覆蓋度估算方法研究進(jìn)展[J];綠色科技;2015年03期

4 張偉閣;楊遼;曹良中;賈洋;;基于Three Factor+C模型改進(jìn)的地形輻射校正方法[J];國(guó)土資源遙感;2015年02期

5 穆悅;安裕倫;王U，

本文編號(hào)：2084380