论文总字数：18703字

摘 要

　随着时代的不断发展，遥感技术已经逐渐运用到各个方面。尤其是在农业方面，遥感技术不仅可以使人们更简易的获取各个地区农产品的种植类型，也可使人们了解到具体的种植面积等。不同部分地区基于当地的气候环境、地理因素等各种条件，冬小麦的种植面积也不相同。因此，运用新时代的遥感技术对各地区冬小麦种植面积的进行监测和提取不仅是农业发展的重要环节也是体现遥感技术运用的现实例子。如何提高其提取精度也是国内外研究的热点问题。本实验在了解冬小麦生长期特点的基础上，运用最大似然法对丰县地区的农作物进行分类，从而提取出冬小麦的种植区域从而进行冬小麦的面积计算。通过了解遥感影像自动分类的理论与方法，运用一种影像处理软件，进行影像分类模块的使用，通过基于GF-1卫星的遥感数据，进行图像的预处理，通过arcgis图像分类法对其进行提取，提取完成后建立混淆矩阵，从而对精度进行验证。

关键词：农业遥感 冬小麦种植面积 最大似然法 面积提取 精度检验

Extraction of winter wheat planting area based on GF-1 satellite data

Abstract

With the continuous development of The Times, remote sensing technology has been gradually applied in all aspects. Especially in agriculture, remote sensing technology can not only make it easier for people to obtain the types of agricultural products planted in various regions, but also enable people to know specific planting areas. The planting area of winter wheat is also different in different regions due to the local climate environment, geographical factors and other conditions. Therefore, using remote sensing technology in the new era to monitor and extract winter wheat planting area in various regions is not only an important link in agricultural development, but also a practical example to reflect the application of remote sensing technology. How to improve its extraction precision is also a hot research issue at home and abroad. The experiment on the basis of understanding the characteristics of winter wheat growing period, using the maximum likelihood classifying venture area of crops, so as to extract the winter wheat planting area and thus for the winter wheat area calculation. By understanding the theory and method of the automatic categorization for the remote sensing image, using a kind of image processing software, the use of image classification module, based on GF - 1 satellite remote sensing data, image preprocessing, through arcgis image classification on the extraction, extraction, the confusion matrix was established after the completion of precision can be validated.

Key words: agricultural remote sensing、winter wheat planting area、maximum likelihood method、area extraction、precision test

目录

摘要 I

ABSTRACT II

第一章 绪论 1

1.1 研究背景 1

1.2 国内外研究进展 2

1.3 课题研究内容 2

1.4 论文组织结构 2

第二章 研究区域概况与数据处理 4

2.1 研究区域概况 4

2.2 GF-1卫星介绍 5

2.3 数据源 6

2.4图像预处理 7

2.4.1 辐射校正..............................................................................................7

2.4.2 几何校正..............................................................................................8

2.4.3 图像配准............................................................................................10

2.4.4 处理结果............................................................................................11

2.5 本章小结.......................................................................................................11

第三章 冬小麦种植面积提取方法 12

3.1 冬小麦生长期分析 12

3.2 分类方法 12

3.2.1 软件选择 12

3.2.2 最大似然法........................................................................................13

3.3 面积提取.......................................................................................................18

3.3.1栅格计算器.........................................................................................18

3.3.2 操作过程............................................................................................18

3.3.3 提取过程............................................................................................20

3.3.4 提取结果............................................................................................23

3.3.5 本章小结............................................................................................23

第四章 精度分析 24

4.1 需求分析 24

4.2 建立点图层 25

4.3 验证过程 25

4.3.1 添加字段............................................................................................25

4.3.2 精度评定点判别................................................................................26

4.3.3 混淆矩阵............................................................................................27

4.4 精度运算 28

第五章 结论与展望 30

参考文献 31

致谢.............................................................................................................................32

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