本文關(guān)鍵詞：多源數(shù)據(jù)協(xié)同下的林地提取研究　出處：《四川師范大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 林地 多源數(shù)據(jù) GIS 知識(shí)發(fā)現(xiàn) 生物量 動(dòng)態(tài)變化

【摘要】：本文通過(guò)開(kāi)展多源數(shù)據(jù)協(xié)同下的林地提取研究,達(dá)到監(jiān)測(cè)森林動(dòng)態(tài)變化的目的。本研究對(duì)維護(hù)和提升區(qū)域生態(tài)系統(tǒng)服務(wù)功能具有重要意義,是提高林地監(jiān)管能力、開(kāi)展生態(tài)空間規(guī)劃、兌現(xiàn)生態(tài)效益補(bǔ)償、加強(qiáng)林地保護(hù)利用管理和科學(xué)預(yù)測(cè)植被長(zhǎng)勢(shì)的重要基礎(chǔ)和科學(xué)支撐,并為區(qū)域經(jīng)濟(jì)社會(huì)發(fā)展、城鄉(xiāng)建設(shè)、土地利用及生態(tài)環(huán)境保護(hù)等奠定基礎(chǔ)。本文主要探討了以下內(nèi)容:1、利用GF1、GF2、ZY3三種高分?jǐn)?shù)據(jù)源開(kāi)展基于知識(shí)發(fā)現(xiàn)的2015年林地提取研究。首先,探索高分影像的光譜、遙感派生、紋理和形狀特征。第二,依據(jù)特征知識(shí),建立知識(shí)庫(kù)進(jìn)行林地資源提取與目視解譯修正。最后,采用google earth影像和實(shí)地調(diào)查數(shù)據(jù)進(jìn)行精度驗(yàn)證。結(jié)果表明GF1、GF2、ZY3和總體提取結(jié)果的精度分別達(dá)到95.1%、94.5%、91.4%、92%,Kappa系數(shù)分別為0.9、0.89、0.83、0.84。說(shuō)明本次提取結(jié)果較好,并可以用于接下來(lái)的研究。2、開(kāi)展生物量估算研究。首先,在提取結(jié)果的基礎(chǔ)之上,結(jié)合2015年林地變更數(shù)據(jù)中的公頃蓄積量和主要樹(shù)種信息,建立生物量與蓄積量之間的線性回歸模型,開(kāi)展研究區(qū)內(nèi)的生物量估算工作。第二,通過(guò)DEM、坡度、坡向數(shù)據(jù)對(duì)生物量開(kāi)展空間分析研究。結(jié)果表明在中起伏山地即海拔500-1000m、緩的即坡度15-25o、東南即坡向112.5-157.5o范圍內(nèi)分布的林地資源生物量較多。3、開(kāi)展2011—2015年林地動(dòng)態(tài)變化分析。首先,將2011年林保數(shù)據(jù)、2013年國(guó)土數(shù)據(jù)和本次2015年提取結(jié)果分為三個(gè)時(shí)段(2011—2013、2013—2015、2011—2015)進(jìn)行三種數(shù)據(jù)源的銜接分析工作。分析發(fā)現(xiàn)2011—2013年林地面積減少115.53hm2,2013—2015年增加8701.17hm2,2011—2015年增加7546.02hm2。變化原因主要分成人為和自然因素,變化的面積基本符合實(shí)際。第二,通過(guò)DEM、坡度、坡向數(shù)據(jù)開(kāi)展地形因子對(duì)植被分布影響分析。結(jié)果表明,區(qū)內(nèi)林地在海拔200-1000m、坡度8-25o、坡向112.5-202.5o的范圍內(nèi)分布面積較多。
[Abstract]:In this paper, the purpose of monitoring forest dynamic change is achieved through the study of forest land extraction under the cooperation of multi-source data. This study is of great significance to maintain and enhance the regional ecosystem service function. It is an important foundation and scientific support for improving the ability of forestland supervision, carrying out ecological space planning, realizing ecological benefit compensation, strengthening forestland conservation and utilization management and scientifically forecasting vegetation growth, and also for the development of regional economy and society. Urban and rural construction, land use and ecological environment protection laid the foundation. This paper mainly discusses the following content: 1, using GF1 and GF2. ZY3 three kinds of high score data sources based on knowledge discovery in 2015 woodland extraction research. First, explore the high score image spectrum, remote sensing derivation, texture and shape features. Second, based on feature knowledge. Finally, google earth images and field survey data were used to verify the accuracy. The results showed that GF1 and GF2. The accuracy of ZY3 and total extraction was 95.1 and 91.4, respectively, and the coefficient of Kappa was 0.90.89 and 0.83, respectively. 0.84.The result of this extraction is good, and can be used in the following research. 2, to carry out biomass estimation research. First, on the basis of the extraction results. Based on the data of forest land change in 2015, the linear regression model between biomass and biomass was established to estimate the biomass in the study area. Based on the data of DEM, slope and direction, the spatial analysis of biomass was carried out. The results showed that the gradient was 15-25o in the middle undulating mountain area, that is, 500-1000m above sea level. The biomass of forestland resources distributed in the range of 112.5-157.5o in southeastern China was more than .3. the dynamic change analysis of forest land was carried out from 2011 to 2015. Firstly, the data of forest protection in 2011 were analyzed. The data of 2013 and 2015 are divided into three periods: 2011-2013 / 2013-2015. The analysis shows that the forest land area decreased 115.53 hm ~ 2 in 2011-2013. An increase of 8701.17hm2hm2in 2013-2015 and an increase of 7546.02hm2between 2011-2015. The main causes of change are adult and natural factors. The change of the area is basically in line with the reality. Second, through DEM, slope, slope data to analyze the impact of terrain factors on the vegetation distribution. The results show that the woodland in the area is 200-1000m above sea level. The slope is 8 to 25 o. and the distribution area is more in the range of 112.5-202.5 o.
【學(xué)位授予單位】：四川師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：S771

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