| 摘要: |
| 利用温室、大棚等设施进行蔬菜种植，一直是我国北方蔬菜种植的主要方式之一，因此，及时、 准确地获取大棚菜地的面积及分布状况，是确保政府“菜篮子”工程顺利实施的需要，也是关系民生的一 项重要工作。为探索及时准确提取大棚菜地信息的技术方法。该研究以山东省寿光市为例，采用HJ-1卫 星图像，在分析各主要地物光谱特征的基础上，结合研究区的背景资料以及专家知识，对遥感影像进行分 类，准确提取了大棚菜地的信息。通过在影像上随机抽取样本点，结合RGB假彩色合成影像及部分实地调 查资料进行精度分析，得出样本点总体精度为92.01%。该研究表明，在HJ-1影像中大棚菜地光谱特征 明显，易于同其他地类区别，利用遥感影像提取大棚菜地信息的方法，适合北方地区大棚菜地信息提取。 |
| 关键词: HJ-1影像 监测 大棚菜地 遥感 山东寿光 |
| DOI：10.7621/cjarrp.1005-9121.20130516 |
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| 基金项目: |
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| MONITORING OF GREENHOUSE VEGETABLES LAND USING HJ-1 REMOTELY-SENSED IMAGERY |
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Huang Zhenguo1, Chen Zhongxin2, Liu Fangqing3, Liu Jun3
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1.Institute of Agricultural Economics and Agricultural Zoning， Hunan Academy of Agricultural Sciences，Changsha 410125/Key Laboratory of Agricultural Information Technology，Ministry of Agriculture Beijing 100081;2.Key Laboratory of Agricultural Information Technology，Ministry of Agriculture Beijing 100081/Institute of Agricultural Resources and Regional Planning， Chinese Academy of Agricultural Sciences，Beijing 100081;3.Institute of Agricultural Economics and Agricultural Zoning， Hunan Academy of Agricultural Sciences，Changsha 410125
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| Abstract: |
| Greenhouse Vegetables production played important role in guaranteeing vegetables supply for the citi- zens. In this paper， the authors tested the greenhouse vegetables land monitoring technique in Shouguang of Shan- dong using remotely-sensed HJ-1 imagery. Based on the analysis of the spectral characteristics of land cover types in HJ-1 image， the authors made remote sensing classification to retrieve the information of greenhouse vegetables. The overall classification accuracy is 92.01% through randomly sampled points conbined with the analysis of RGB false color composite images and field investigation. This study showed the greenhouse vegetables land had obvious spectral features in HJ-1 imagery and could be distinguished easily from other land cover types in the study region. This paper suggested that the method may be applicable in other region in northern China. |
| Key words: HJ-1 image monitoring greenhouse vegetable land remote sensing |
