結(jié)合不同分辨率遙感數(shù)據(jù)進(jìn)行大區(qū)域森林面積及其變化的監(jiān)測(cè)和傳統(tǒng)地面調(diào)查的方法相比具有明顯的優(yōu)勢(shì)。剛果民主共和國(guó)（剛果（金））地處非洲中心,不僅有最大的非洲熱帶雨林,還有幾個(gè)生態(tài)區(qū)如Miombo林地等。對(duì)剛果（金）來(lái)說(shuō),掌握森林資源數(shù)據(jù)及其變化情況顯得尤為重要。但目前剛果（金）在這方面還比較薄弱。本研究選取兩個(gè)典型地區(qū)作為研究區(qū)域,分別進(jìn)行兩方面研究:1、提出了基于合計(jì)數(shù)的概率轉(zhuǎn)移矩陣的大規(guī)模遙感抽樣調(diào)查研究。方法步驟為:（1）利用Landsat8數(shù)據(jù)進(jìn)行覆蓋調(diào)查總體的計(jì)算機(jī)有監(jiān)督自動(dòng)分類;（2）利用谷歌高空間分辨率數(shù)據(jù)進(jìn)行總體的系統(tǒng)抽樣,對(duì)樣地進(jìn)行目視解譯,其結(jié)果作為地面真值;（3）利用對(duì)應(yīng)的樣地目視解譯數(shù)據(jù)和TM自動(dòng)分類數(shù)據(jù)建立概率轉(zhuǎn)移矩陣;（4）利用概率轉(zhuǎn)移矩陣和自動(dòng)分類結(jié)果對(duì)總體進(jìn)行概率估計(jì)。作為比較,設(shè)計(jì)了3種概率抽樣估計(jì)方法,（1）稱為方法1,即本文提出的方法,概率轉(zhuǎn)移矩陣基于所有樣地的面積轉(zhuǎn)移矩陣合計(jì)數(shù)計(jì)算;（2）稱為方法2,是已有方法,概率轉(zhuǎn)移矩陣是單個(gè)樣地的概率轉(zhuǎn)移矩陣的平均數(shù);（3）稱為方法3,僅使用目視解譯樣地進(jìn)行簡(jiǎn)單隨機(jī)抽樣估計(jì)。計(jì)算機(jī)自動(dòng)分類和目視解譯均分為7個(gè)地... 

【文章來(lái)源】：浙江農(nóng)林大學(xué)浙江省

【文章頁(yè)數(shù)】：101 頁(yè)

【學(xué)位級(jí)別】：碩士

【文章目錄】：
ABSTRACT
摘要
1 Introduction
    1.1 Subject selection
    1.2 Literature review
        1.2.1 Main forest monitoring systems in the world
        1.2.2 National Forest Monitoring System(NFMS)in the DR Congo
    1.3 Research contents
        1.3.1 ResearchⅠ:Land cover sampling
        1.3.2 ResearchⅡ:Change detection
2 Study area and data
    2.1 Study area
        2.1.1 Study area for ResearchⅠ
        2.1.2 Study area for ResearchⅡ
    2.2 Data
        2.2.1 Data for ResearchⅠ
        2.2.2 Data for ResearchⅡ
3 Research Ⅰ:Sampling design and implementation
    3.1 Land cover type definition
    3.2 Sampling design
    3.3 Advantages of systematic sampling
    3.4 Classification of Landsat data
        3.4.1 Classification method
        3.4.2 Classification result and accuracy assessment
    3.5 Visual interpretation of VHR images
    3.6 Transition matrix from Landsat classified data to visual interpretation data for a single plot
4 Research Ⅰ:Sampling Estimation-Method
    4.1 Probability transition matrix
    4.2 Transition probability– Estimation of variance and covariance
    4.3 Formula proof
    4.4 Sampling estimation
5 Research Ⅰ:Sampling-Estimation Method
    5.1 Probability transfer matrix
    5.2 Variance and covariance estimation
    5.3 Method 3: Simple random sampling
6 Research Ⅰ:Results
    6.1 Result of method 1
    6.2 Result of method 2
    6.3 Result of method 3 -simple random sampling
    6.4 Result comparison
7 Research Ⅰ:Discussion and conclusion
    7.1 Discussion
    7.2 Conclusion
8 Research Ⅱ:Change detection
    8.1 Theoretical basis of robust regression
    8.2 Linear Regression Model
    8.3 Robust Regression
    8.4 M-Estimation formula development
9 Research Ⅱ:Result
    9.1 Analysis of robust regression
    9.2 Change detection under different significant levels
    9.3 Results validation
10 Research Ⅱ:Discussion and conclusion
    10.1 Discussion
    10.2 Conclusion
References
Appendix
About the author
About the supervisor
Acknowledgements


【參考文獻(xiàn)】：
期刊論文
[1]The national forest inventory in China:history-results-international context[J]. Wei Sheng Zeng,Erkki Tomppo,Sean P.Healey,Klaus V.Gadow.  Forest Ecosystems. 2015(04)
[2]漂漂亮亮過(guò)新年[J]. 初雪.  綠色中國(guó). 2008(02)



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