刚果（金）大区域森林遥感抽样估计及变化监测研究
发布时间：2021-06-29 11:41
结合不同分辨率遥感数据进行大区域森林面积及其变化的监测和传统地面调查的方法相比具有明显的优势。刚果民主共和国（刚果（金））地处非洲中心,不仅有最大的非洲热带雨林,还有几个生态区如Miombo林地等。对刚果（金）来说,掌握森林资源数据及其变化情况显得尤为重要。但目前刚果（金）在这方面还比较薄弱。本研究选取两个典型地区作为研究区域,分别进行两方面研究:1、提出了基于合计数的概率转移矩阵的大规模遥感抽样调查研究。方法步骤为:（1）利用Landsat8数据进行覆盖调查总体的计算机有监督自动分类;（2）利用谷歌高空间分辨率数据进行总体的系统抽样,对样地进行目视解译,其结果作为地面真值;（3）利用对应的样地目视解译数据和TM自动分类数据建立概率转移矩阵;（4）利用概率转移矩阵和自动分类结果对总体进行概率估计。作为比较,设计了3种概率抽样估计方法,（1）称为方法1,即本文提出的方法,概率转移矩阵基于所有样地的面积转移矩阵合计数计算;（2）称为方法2,是已有方法,概率转移矩阵是单个样地的概率转移矩阵的平均数;（3）称为方法3,仅使用目视解译样地进行简单随机抽样估计。计算机自动分类和目视解译均分为7个地...
【文章来源】：浙江农林大学浙江省
【文章页数】：101 页
【学位级别】：硕士
【文章目录】：
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
【参考文献】：
期刊论文
[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]漂漂亮亮过新年[J]. 初雪. 绿色中国. 2008(02)
本文编号：3256379
【文章来源】：浙江农林大学浙江省
【文章页数】：101 页
【学位级别】：硕士
【文章目录】：
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
【参考文献】：
期刊论文
[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]漂漂亮亮过新年[J]. 初雪. 绿色中国. 2008(02)
本文编号：3256379
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