Mapping paddy fields by using spatial and temporal remote sensing data fusion technology

被引：0

作者：

Wu M. ^{[1
]}

Niu Z. ^{[1
]}

Wang C. ^{[1
]}

机构：

[1] The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences

来源：

Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2010年 / 26卷 / SUPPL. 2期

关键词：

Crops; Data fusion; Landsat; MODIS; Remote sensing; Rice extraction;

D O I：

10.3969/j.issn.1002-6819.2010.z2.010

中图分类号：

学科分类号：

摘要：

In order to solve the problem of data loss in mapping paddy fields, a novel rice extraction method was proposed in this paper by using spatial and temporal remote sensing data fusion technology (STDFT). Using the temporal change information extracted from time series MODIS data, combining with the texture information of Landsat-ETM+ data at former, fusion data was produced which had the same temporal resolution with MODIS data and the same spatial resolution with Landsat-ETM+ image. Then using fusion data in critical period, rice fields was mapped through SVM. The algorithm had been tested over a study area in Jiangning Country, Nanjing City, Jiangsu Province, China. Results showed that this method could map rice effectively. High mapping precision of 93% was acquired with Kappa coefficient of 0.96.

引用

页码：48 / 52

页数：4

共 17 条

[1]

Oguro Y., Suga Y., Takeuchi S., Et al., Monitoring of a rice field using landsat-5 TM and landsat-7 ETM+ data, Advances in Space Research, 32, pp. 2223-2228, (2003)

[2]

Leckie D., Advances in remote sensing technologies for forest survey and management, Canadian Journal of Forest Research, 21, pp. 464-483, (1990)

[3]

Cheng Q., Wang R., Estimation of the rice planting area using digital elevation model and multitemporal moderate resolution imaging spectroradiometer, Transactions ofthe CSAE, 23, 5, pp. 89-92, (2005)

[4]

Sun H., Huang J., Peng D., Detecting major growth stages of paddy rice using MODIS data, Journal of Remote Sensing, 13, 6, pp. 1007-1137, (2009)

[5]

Xiao X., Stephen B., Et al., Mapping paddy rice agriculture in southern China using multi-temporal MODIS images, Remote Sensing of Environment, 95, pp. 480-492, (2005)

[6]

Xiao X., Stephen B., Et al., Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images, Remote Sensing of Environment, 100, pp. 95-113, (2006)

[7]

Lunetta R.S., Lyon J.G., Guindon B., Et al., North Americal landscape characterization dataset development and fusion issues, Photogrammetric Engineering & Remote Sensing, 64, pp. 821-829, (1998)

[8]

Zhukov B., Oertel D., Lanzl F., Et al., Unmixing-based multisensor multiresolution image fusion, IEEE Transactions on Geoscience and Remote Sensing, 37, pp. 1212-1226, (1999)

[9]

Maselli F., Definition of spatially variable spectral endmembers by locally calibrated multivariate regression analyses, Remote Sensing of Environment, 75, pp. 29-38, (2001)

[10]

Lorenzo B., Michele M., Roberto C., Combining medium and coarse spatial resolution satellite data to improve the estimation of sub-pixel NDVI time series, Remote Sensing of Environment, 112, pp. 118-131, (2008)

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