發(fā)布時(shí)間：2018-05-08 18:16

  本文選題：森林物候 + 數(shù)碼相機(jī)　； 參考：《四川農(nóng)業(yè)大學(xué)》2015年碩士論文

【摘要】：物候是氣候與自然環(huán)境變化最直觀、敏感的綜合指示器和“診斷指紋”,植物的物候信息不僅反映當(dāng)?shù)禺?dāng)時(shí)的環(huán)境條件,而且反映過(guò)去一段時(shí)間環(huán)境條件的積累。隨著科學(xué)技術(shù)的發(fā)展,植物物候的研究不再局限于傳統(tǒng)手段,衛(wèi)星遙感技術(shù)及數(shù)碼相機(jī)延時(shí)拍攝技術(shù)等被越來(lái)越多地運(yùn)用到植物物候研究中。利用衛(wèi)星遙感技術(shù),結(jié)合數(shù)碼相機(jī)延時(shí)拍攝技術(shù)記錄植被物候變化過(guò)程,既節(jié)約人力資源和監(jiān)測(cè)成本,又能同時(shí)在大區(qū)域范圍和局部地段內(nèi)研究植被物候變化。本研究基于MODIS衛(wèi)星遙感技術(shù)和數(shù)碼相機(jī)延時(shí)攝影技術(shù),開(kāi)展四川省森林和都江堰市靈巖山森林公園森林植被物候的研究。本研究采用2014年全年的MODIS地表反射率產(chǎn)品,探測(cè)四川省森林植被物候的年度變化。同時(shí),選擇四川農(nóng)業(yè)大學(xué)教學(xué)科研基地——都江堰市靈巖山森林公園為研究樣本,以春秋兩季顏色變化鮮明的落葉樹(shù)種銀杏和水杉為代表,基于自行設(shè)計(jì)的森林(樹(shù)木)物候數(shù)據(jù)采集系統(tǒng),實(shí)現(xiàn)銀杏、水杉冠層數(shù)碼延時(shí)照片的自動(dòng)獲取。采用ENVI/IDL、ArcGIS、TimeSAT等軟件,對(duì)MODIS衛(wèi)星遙感時(shí)間序列影像和近地面數(shù)碼相機(jī)時(shí)間序列數(shù)據(jù)進(jìn)行分析,探討了使用這兩種物候監(jiān)測(cè)手段在大區(qū)域和景觀尺度上提高森林物候監(jiān)測(cè)精細(xì)程度的可能性。主要結(jié)果如下：(1)利用自主開(kāi)發(fā)的數(shù)碼相機(jī)監(jiān)測(cè)自動(dòng)管理軟件,定時(shí)自動(dòng)獲取銀杏、水杉植被冠層可見(jiàn)光及紅外延時(shí)照片。計(jì)算數(shù)碼照片感興趣區(qū)(ROI)、ExG、Gcc、NDVI及EVI等7種植被指數(shù)。從各植被指數(shù)時(shí)間序列曲線看出,只有ExG、Gcc、NDVI能夠正確反映森林植被年內(nèi)生長(zhǎng)變化趨勢(shì)。(2)利用雙Logistic模型對(duì)數(shù)碼相機(jī)3種植被指數(shù)進(jìn)行平滑去噪處理,得出了較為合理的時(shí)間序變化數(shù)據(jù)。采用動(dòng)態(tài)閾值法提取基于數(shù)碼相機(jī)的植被生長(zhǎng)季開(kāi)始期(SOS)、生長(zhǎng)結(jié)束期(EOS)、生長(zhǎng)季長(zhǎng)度(LOS)及生長(zhǎng)最大值日期(MOE)。結(jié)果表明,3種植被指數(shù)中,ExG、Gcc得出的物候關(guān)鍵期較為接近,SOS在130天左右；EOS在天280天左右；LOS在150天左右；MOE在180天左右。表明,基于數(shù)碼相機(jī)監(jiān)測(cè)森林植被冠層物候變化是可行的；基于數(shù)碼相機(jī)的可見(jiàn)光通道植被指數(shù)在表征物候變化信息時(shí)優(yōu)于紅外通道。(3)對(duì)MODIS 8天合成地表反射率產(chǎn)品數(shù)據(jù)進(jìn)行預(yù)處理,計(jì)算NDVI、EVI、ExG及Gcc植被指數(shù),從構(gòu)建的植被指數(shù)時(shí)間序列變化情況看出,4種植被指數(shù)均能夠通過(guò)森林冠層物候正確反映森林植被年內(nèi)生長(zhǎng)變化趨勢(shì)。(4)以EVI植被指數(shù)為例,采用不同平滑方法對(duì)其進(jìn)行平滑去噪處理發(fā)現(xiàn),S-G濾波方法在擬合效果及對(duì)原始數(shù)據(jù)保真度方面優(yōu)于其它方法。采用動(dòng)態(tài)閾值法提取四川森林植被物候關(guān)鍵期,對(duì)比4種植被指數(shù)發(fā)現(xiàn),EVI植被指數(shù)在反映森林植被物候變化方面優(yōu)于其它3種植被指數(shù)。(5)四川森林植被物候關(guān)鍵期空間分布規(guī)律：SOS：盆地內(nèi)部、盆地北部(90-110天)盆地西部、盆地南部、盆地西南部(110-130天)川西亞高山、川西北高原(150-170天)；EOS：盆地西南部(310-330)盆地內(nèi)部、盆地北部(290-310天)盆地西部、盆地南部(270-290天)川西亞高山、川西北高原(250-290天)；LOS：盆地內(nèi)部、盆地北部(190-210天)盆地西部、盆地南部、盆地西南部(150-170天)川西亞高山、川西北高原(110-130天)；MOE：各林區(qū)中除盆地西南緣林區(qū)有超過(guò)30%面積大于220天外,其它林區(qū)大部分森林生長(zhǎng)達(dá)最大值日期在180-200天。(6)分析四川森林物候關(guān)鍵期與海拔高度的關(guān)系發(fā)現(xiàn),在海拔2000m以下,海拔每上升200m, SOS推遲3.1天,EOS推遲5.1天,LOS延長(zhǎng)2天,MOE推遲0.8天；在海拔2000m到4000m之間,海拔每升高200m, SOS提前3.4天,EOS提前8.2天,LOS縮短4.8天,MOE縮短1.5天。海拔4000m以上地區(qū),森林植被物候隨海拔變化的規(guī)律不明顯。(7)比較兩種不同監(jiān)測(cè)手段和不同植被指數(shù)得到的森林植被物候關(guān)鍵期,發(fā)現(xiàn)：衛(wèi)星遙感和數(shù)碼相機(jī)監(jiān)測(cè)及采用不同植被指數(shù)分析得到的結(jié)果存在不同程度偏差。總的來(lái)說(shuō),基于衛(wèi)星遙感的EVI和基于數(shù)碼相機(jī)的ExG及Gcc較其它植被指數(shù)更適合于森林植被物候的研究。(8)利用IDL、C#等初步開(kāi)發(fā)建立了四川森林物候遙感監(jiān)測(cè)系統(tǒng)。該系統(tǒng)包含了數(shù)碼相機(jī)森林物候自動(dòng)監(jiān)測(cè)分析管理、MODIS衛(wèi)星森林物候遙感監(jiān)測(cè)分析和數(shù)據(jù)Web發(fā)布3個(gè)主要模塊,主要實(shí)現(xiàn)了森林(樹(shù)木)物候數(shù)碼照片的自動(dòng)獲取,數(shù)碼照片R、G、B和紅外通道值的批量提取分析,MODIS衛(wèi)星數(shù)據(jù)的預(yù)處理,影像分析,模型擬合分析(S-G濾波),森林植被物候參數(shù)提取,矢量數(shù)據(jù)和影像數(shù)據(jù)疊加顯示,基本的地圖操作工具和監(jiān)測(cè)結(jié)果Wleb發(fā)布等。
[Abstract]:Phenology is the most intuitive, sensitive comprehensive indicator and "diagnostic fingerprint" of climate and natural environment changes. The phenological information of plants not only reflects the environment conditions at the time, but also reflects the accumulation of environmental conditions in the past period. With the development of science and technology, the research of plant phenology is no longer limited to traditional means, satellite remote sensing technology. Technology and digital camera delay shooting technology have been used more and more in the study of plant phenology. Using satellite remote sensing technology and digital camera delay shooting technology to record the process of vegetation phenology change, not only save human resources and monitoring cost, but also study the change of vegetation phenology at the same time in large area and part of the area. Based on MODIS satellite remote sensing technology and digital camera delay photography, the forest vegetation phenology in Sichuan forest and Dujiangyan city of Ling Yan Mountain Forest Park was studied. The annual variation of the forest vegetation phenology in Sichuan province was detected by using the surface albedo of MODIS in 2014. At the same time, the teaching and scientific Research of Sichuan Agricultural Uniersity was selected. Base - the Forest Park of Ling Yan Mountain in Dujiangyan city is the research sample, which is represented by the deciduous tree ginkgo and Metasequoia in the two seasons of spring and Autumn period. Based on the self designed forest (Shu Mu) phenological data collection system, the auto acquisition of the digital delayed photo of Ginkgo and Metasequoia canopy is realized. The software of ENVI/IDL, ArcGIS, TimeSAT and so on is used for MODI The S satellite remote sensing time series image and the time series data of the near ground digital camera are analyzed. The possibility of improving the fine degree of forest phenology monitoring in large area and landscape scale using these two kinds of phenological monitoring means is discussed. The main results are as follows: (1) the automatic management software is monitored by the self developed digital camera. Obtain Ginkgo biloba, the visible light and infrared delay photos of the vegetation canopy of Metasequoia metasequoia. Calculate the 7 planting index of digital photo area (ROI), ExG, Gcc, NDVI and EVI. From the curve of each vegetation index time series, only ExG, Gcc, NDVI can correctly reflect the growth trend of forest vegetation in year. (2) using double Logistic model to digital camera 3 A more reasonable time sequence change data was obtained by the exponential smoothing. The dynamic threshold method was used to extract the vegetative growth season (SOS), the growth end period (EOS), the growth Ji Changdu (LOS) and the maximum growth date (MOE). The results showed that the key phase of phenology obtained by the 3 planting index, ExG, Gcc, was obtained. It is close, SOS is about 130 days, EOS is around 280 days, LOS is about 150 days, and MOE is around 180 days. It shows that monitoring forest vegetation canopy phenology based on digital camera is feasible, and the visible light channel vegetation index based on digital camera is superior to infrared channel in characterizing phenological change information. (3) synthesis of MODIS for 8 days on the surface of MODIS The data of reflectivity products were pretreated and the vegetation index of NDVI, EVI, ExG and Gcc was calculated. From the change of the time series of the vegetation index, the 4 planting index can correctly reflect the growth trend of the forest vegetation through the forest canopy phenology. (4) take the EVI vegetation index as an example and use different smoothing methods to smooth it. The denoising process shows that the S-G filtering method is superior to other methods in the fitting effect and the original data fidelity. The dynamic threshold method is used to extract the key phase of the Sichuan forest vegetation phenology. Compared with the 4 planting index, the EVI vegetation index is better than the other 3 planting indices in reflecting the phenological changes of forest vegetation. (5) the forest vegetation in Sichuan. The spatial distribution law of the key period: SOS: the basin, the north of the basin (90-110 days), the south of the basin, the south of the basin, the southwest of the basin (110-130 days), the Western Sichuan subalpine, the Northwest Sichuan Plateau (150-170 days), the southwest of the basin (310-330), the northern basin (290-310 days), the west of the basin and the southern Sichuan subalpine (270-290 days). The Northwest Plateau (250-290 days); LOS: the basin, the north of the basin (190-210 days), the south of the basin, the south of the basin, the southwest of the basin (150-170 days), the Western Sichuan subalpine, the Northwest Sichuan Plateau (110-130 days); the forest area of the southwest margin of the basin is more than 220 days more than 30% areas, and the most of the most forest growth dates in the other forest areas are at the maximum value. 180-200 days. (6) the analysis of the relationship between the critical period of forest phenology and altitude in Sichuan found that below 2000m, elevation of 200m, SOS delayed 3.1 days, EOS postponed 5.1 days, LOS extension 2 days, MOE postponed 0.8 days; at elevation 2000m to 4000m, each elevation of SOS was 3.4 days ahead of advance, EOS 8.2 days, LOS 4.8 days shortened, 1.5 days shortened. The regularity of forest vegetation phenology changes with altitude is not obvious. (7) compare the key period of forest vegetation phenology of two different monitoring means and different vegetation index. It is found that the results of satellite remote sensing and digital camera monitoring and the use of different vegetation indices have different degrees of deviation. Satellite remote sensing EVI and digital camera based ExG and Gcc are more suitable for the study of forest vegetation phenology than other vegetation indices. (8) using IDL, C# and other preliminary development to establish the Sichuan forest phenology remote sensing monitoring system. The system includes the automatic monitoring and analysis of forest phenology of digital cameras, and the analysis of the forest phenology of MODIS satellite remote sensing monitoring and analysis. And data Web issued 3 main modules, which mainly realized the automatic acquisition of forest (Shu Mu) phenological digital photos, the batch extraction and analysis of digital photos R, G, B and infrared channels, the preprocessing of MODIS satellite data, image analysis, model fitting analysis (S-G filtering), the extraction of phenological parameters of the forest vegetation, the superposition of vector data and image data, Basic map operation tools and monitoring results Wleb release.

【學(xué)位授予單位】：四川農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：S716

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