Extraction of rice planting area based on Landsat 8 OLI remote sensing image in Shenyang city

doi:10.3969/j.issn.1004-1524.2017.10.22

›› 2017, Vol. 29 ›› Issue (10): 1749-1758.DOI: 10.3969/j.issn.1004-1524.2017.10.22

• Biosystems Engineering • Previous Articles Next Articles

Extraction of rice planting area based on Landsat 8 OLI remote sensing image in Shenyang city

ZHENG Luyue¹, XU Tongyu^{1, 2, *}, ZHOU Yuncheng^{1, 2}, DU Wen¹

1.College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China;
2.Agricultural Informatization Engineering Technology Center in Liaoning Province, Shenyang 110866, China

Received:2017-04-06 Online:2017-10-20 Published:2017-12-05

Abstract

Abstract: In order to study the feasibility of remote sensing data and extraction method to estimate the area of rice planting, this paper used Landsat 8 OLI image as the data source and ENVI5.1 as software platform to monitor rice growth situation in June-September 2015 in Shenyang city, and extracted its acreage eventually. Based on the field survey samples, by analyzing the spectral characteristics, the normalized differential vegetation index and the characteristics of remote sensing images, this paper determined the false color synthesis by band 6, band 5 and band 2. The sampling points of the rice were selected by the mixed pixels, and the number of samples was 100, 150 and 200 respectively. The transformed divergence and Jeffries-Matusita were used to test the separability among the samples. The samples were classified by the support vector machine. The classification results were sorted by Majority/Minority analysis method, and the extraction model of different rice areas were established finally. The results showed that the sample number of 200 was most accurate in June, July and September, and the extraction area was 1 032.044 8, 1 201.125 9 and 1 180.685 5 km². According to the results from Shenyang Agricultural Statistics (2015), the evaluation was 94.73%, 89.75% and 91.62% respectively. The experimental results showed that the Landsat 8 OLI remote sensing data can accurately extract the rice planting area in Shenyang, and lay the foundation for the rice planting monitoring for the multi-source data.

Key words: Shenyang, rice, support vector machine, Landsat 8 OLI data

CLC Number:

TP79

ZHENG Luyue, XU Tongyu, ZHOU Yuncheng, DU Wen. Extraction of rice planting area based on Landsat 8 OLI remote sensing image in Shenyang city[J]. , 2017, 29(10): 1749-1758.

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Extraction of rice planting area based on Landsat 8 OLI remote sensing image in Shenyang city

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