Remote sensing monitoring of maize planting area at town level

被引：0

作者：

Guo W. ^{[1
,2
,3
]}

Zhao C. ^{[2
]}

Gu X. ^{[2
]}

Huang W. ^{[2
]}

Ma Z. ^{[2
]}

Wang H. ^{[2
]}

Wang D. ^{[2
]}

机构：

[1] College of Forestry, Beijing Forestry University

[2] Beijing Research Center for Information Technology in Agriculture

[3] College of Information and Management Science, Henan Agriculture University

来源：

Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2011年 / 27卷 / 09期

关键词：

Maize; Model; Monitoring; Multi-layers decision tree; Object spectral characteristics; Planting area; Remote sensing; Town level;

D O I：

10.3969/j.issn.1002-6819.2011.09.014

中图分类号：

学科分类号：

摘要：

In order to extract maize planting acreage rapidly and accurately, taking Changchun city in Jilin province as study area, a multi-layer decision tree classification model was constructed based on multi-temporal HJ-1A/1B CCD images and digital elevation model (DEM), which introduced with multi-information including planting structure, phenological characteristics, terrain feature of the study area, spectral characteristics and vegetation index. The precision of classification results was evaluated by spatial agricultural census data at town level. The results indicated that the method could improve maize identification accuracy, which reached up to 92.57%. The method can meet the demand for large-scale and multi-temporal agricultural monitoring system and resolve the spatiotemporal contradiction effectively in the large-scale crop acreage monitoring system.

引用

页码：69 / 74

页数：5

共 17 条

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