基于目标极化分解方法和PALSAR雷达数据的于田绿洲盐渍化监测

以新疆于田绿洲为研究区，利用四极化PALSAR-2数据进行多种目标极化分解处理，获取相应的极化特征参数。通过目视判读选取噪声较少的11种极化参数作为最佳特征信息对支持向量机分类法进行训练。多种极化分解方法与Wishart分类方法及支持向量机分类法相结合，提取研究区不同程度的盐渍化信息。经过目视判读和实地野外考察，结合Landsat-8陆地成像仪影像对分类结果进行定量分析和验证。由混淆矩阵的计算分析可知，相比Wishart分类方法，支持向量机分类法将分类精度从80.48%提高到88.00%，将Kappa系数从0.73提高到0.83。结果表明，单独的相干分解不能充分挖掘PALSAR-2数据包含的丰富信息，将目标极化分解参数用于特征信息分类处理，可以达到较好的分类效果；利用全极化PALSAR-2数据，结合目标极化分解方法和支持向量机分类法提取盐渍化信息有一定的优势。

Abstract

Choosing Yutian Oasis as the study area, the polarimetric characteristic parameters are obtained from quad-polarized PALSAR-2 data in a variety of target polarization decomposition treatments. 11 polarized parameters with lesser noise are selected as the best classification features through visual interpretation to train the support vector machine classification. Wishart classification, support vector machine classification and several polarimetric decomposition methods are combined to extract the different levels of soil salinization information. Classification results are quantitatively analyzed and validated by Landsat-8 operational land imager image combined with visual interpretation and field investigation. The analysis results of confusion matrix show that, comparing with Wishart classification, the support vector machine classification increases the classification accuracy and Kappa coefficient from 80.48% to 88.00% and 0.73 to 0.83 respectively. It is illustrated that the individual coherent decomposition cannot fully exploit the rich information of PALSAR-2 data, and the good classification results can be achieved by using the target polarimetric decomposition parameter for features classification process. Using fully polarimetric PALSAR-2 data, the method combining target polarimetric decomposition with support vector machine classification has advantage to extracting salinization information.

参考文献

[1] 古丽娜尔·哈里别克. 于田绿洲土壤盐分对芦苇生长的影响研究［D］. 乌鲁木齐: 新疆大学, 2012: 3-8.

Gulnar Halik. The soil salinity effects on the growth of phragmitesaustralis in Yutian Oasis［D］. Urumqi: Xinjiang University, 2012: 3-8.

[2] 杨红梅, 徐海量, 樊自立, 等. 塔里木河下游表层土壤盐分空间变异和格局分析［J］. 中国沙漠, 2010, 30(3): 564-570.

Yang Hongmei, Xu Hailiang, Fan Zili, et al. Spatial variability and pattern of surface soil salinity in the lower reaches of the Tarim river［J］. Journal of Desert Research, 2010, 30(3): 564-570.

[3] 王燕, 赵学勇, 赵哈林, 等. 干旱绿洲农田盐渍化对土壤理化特性和农艺特征的影响［J］. 干旱地区农业研究, 2013, 31(3): 184-193.

Wang Yan, Zhao Xueyong, Zhao Halin, et al. Effects of salinization on soil physicochemical characteristics and agronomic traits in arid oasis［J］. Agricultural Research in the Arid Areas, 2013, 31(3): 184-193.

[4] 依力亚斯江·努尔麦麦提, 塔西甫拉提·特依拜, 舒宁, 等. 基于Radarsat和TM图像融合与分类的土壤盐渍化信息遥感监测研究［J］. 测绘科学, 2009, 34(1): 56-59.

Ilyas Nurmemet, Tashpolat Tiyip, Shu Ning, et al. Remote sensing monitoring of soil salinization based on fusion and classification of radarsat and TM image［J］. Science of Surveying and Mappin, 2009, 34(1): 56-59.

[5] 胡小韦. 于田绿洲土壤盐渍化与地下水环境变化的关系研究［D］. 乌鲁木齐: 新疆大学, 2008: 1-8.

Hu Xiaowei. Study of relationship between the soil-salinization and the change of groundwater environment in Yutian Oasis［D］. Urumqi: Xinjiang University, 2008: 1-8.

[6] 吕云海. 于田绿洲典型区域土壤盐分空间分异规律研究［D］. 乌鲁木齐: 新疆大学, 2009: 2-6.

Lu Yunhai. The research for spatial distribution rules of the soil salt of typical area in Yutian Oasis［D］. Urumqi: Xinjiang University, 2009: 2-6.

[7] 王红. 黄河三角洲土壤盐分时空变异研究［D］. 南京: 南京大学, 2005: 5-10.

Wang Hong. Spatio-temporal variability of soil salinity in the Yellow River Delta［D］. Nanjing: Nanjing University, 2005: 5-10.

[8] 丁建丽, 姚远, 王飞. 干旱区土壤盐渍化特征空间建模［J］. 生态学报, 2014, 34(16): 4620-4631.

Ding Jianli, Yao Yuan, Wang Fei. Detecting soil salinization in arid regions using spectral feature space derived from remote sensing data［J］. Acta Ecological Sinica, 2014, 34(16): 4620-4631.

[9] 刘立人. 合成孔径激光成像雷达(Ⅳ): 统一工作模式和二维数据收集方程［J］. 光学学报, 2009, 29(1): 1-6.

Liu Liren. Synthetic aperture imaging radar (Ⅳ): unified operation mode and two-dimensional data collection equation［J］. Acta Optica Sinica, 2009, 29(1): 1-6.

[10] Bindlish R, Barros A P. Parameterization of vegetation backscatter in radar-based, soil moisture estimation［J］. Remote Sensing of Environment, 2001, 76(1): 130-137.

[11] Lonnqvist A, Rauste Y, Molinier M, et al. Polarimetric SAR data in land cover mapping in Boreal zone［J］. IEEE Transactions on Geoscience & Remote Sensing, 2010, 48(10): 3652-3662.

[12] Nurmemet I, Ghulam A, Tiyip T, et al. Monitoring soil salinization in Keriya river basin, northwestern China using passive reflective and active microwave remote sensing data［J］. Remote Sensing, 2015, 7(7): 8803-8829.

[13] Qi Z, Yeh G O, Li X, et al. A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric SAR data［J］. Remote Sensing of Environment, 2012, 118: 21-39.

[14] Deng L, Yan Y, Wang C. Improved POLSAR image classification by the use of multi-feature combination［J］. Remote Sensing, 2015, 7(4): 4157-4177.

[15] Rignot E, Chellappa R. Segmentation of polarimetric synthetic aperture radar data［J］. IEEE Transactions on Image Processing, 1992, 1(3): 281-300.

[16] 宋玉, 塔西甫拉提·特依拜, 吴雪梅, 等. 于田绿洲不同季节表层土壤盐渍化程度的空间变异特征［J］. 干旱地区农业研究, 2014(6): 171-175.

Song Yu, Tashpolat Tiyip, Wu Xuemei, et al. Analysis of seasonal variation of topsoil salinization in Yutian Oasis［J］. Agricultural Research in the Arid Areas, 2014(6): 171-175.

[17] 胡佳楠, 塔西甫拉提·特依拜, 张飞, 等. 新疆于田绿洲地表温度对土地利用/覆被的响应监测［J］. 冰川冻土, 2015, 37(3): 658-667.

Hu Jianan, Tashpolat Tiyip, Zhang Fei, et al. The remote sensing monitoring of land use /cover change and land surface temperature responses over the Yutian Oasis, Xinjiang［J］. Journal of Glaciology and Geocryology, 2015, 37(3): 658-667.

[18] Rosenqvist A, Shimada M, Suzuki S, et al. Operational performance of the ALOS global systematic acquisition strategy and observation plans for ALOS-2 PALSAR-2［J］. Remote Sensing of Environment, 2014, 155(4): 3-12.

[19] Natsuaki R, Nagai H, Motohka T, et al. SAR interferometry using ALOS-2 PALSAR-2 data for the MW7.8 Gorkha, Nepal earthquake［J］. Earth Planets & Space, 2016, 68(1): 1-13.

[20] Huynen J R. Phenomenological theory of Radar targets［J］. Electromagnetic Scattering, 1978: 653-712.

[21] 陈劲松, 邵芸, 李震. 基于目标分解理论的全极化SAR图像神经网络分类方法［J］. 中国图像图形学报, 2004, 9(5): 552-556.

Chen Jingsong, Shao Yun, Li Zhen. Neural networks classification of quad-polarization SAR data based on target decomposition［J］. Journal of Image and Graphics, 2004, 9(5): 552-556.

[22] 张继超, 蔺腊月, 张永红, 等. 基于目标分解的面向对象决策树PolSAR影像分类［J］. 辽宁工程技术大学学报(自然科学版), 2013, 32(5): 642-647.

Zhang Jichao, Lin Layue, Zhang Yonghong, et al. Object-oriented classification of PolSAR imagery based on target decomposition and decision tree algorithms［J］. Journal of Liaoning Technical University (Natural Science), 2013, 32(5): 642-647.

[23] Cloude S R. Group theory and polarization algebra［J］. Optic, 1986, 75(1): 26-36.

[24] Krogager E. New decomposition of the radar target scattering matrix［J］. Electronics Letters, 1990, 26(18): 1525-1527.

[25] Cameron W L, Leung L K. Feature motivated polarization scattering matrix decomposition［C］. IEEE International Radar Conference, 1990: 549-557.

[26] Holm W A, Barnes R M. On radar polarization mixed target state decomposition techniques［C］. IEEE National Radar Conference, 1988: 249-254.

[27] Bombrun L, Vasile G, Gay M, et al. Roll invariant target detection based on PolSAR clutter models［J］. IEEE International Geoscience & Remote Sensing Symposium, 2010, 38(5): 2511-2514.

[28] Yamaguchi Y, Yajima Y, Yamada H. A four-component decomposition of POLSAR images based on the coherency matrix［J］. IEEE Geoscience & Remote Sensing Letters, 2006, 3(3): 292-296.

[29] Freeman A, Durden S L. Three-component scattering model to describe polarimetric SAR data［C］. SPIE, 1993, 1748: 213-224.

[30] Pottier E, Lee J S. Application of the 《H/A/α》 polarimetric decomposition theorem for unsupervised classification of fully polarimetric SAR data based on the Wishart distribution［C］. Proceedings of CEOS SAR workshop, 2000, 450: 335-340.

[31] Van Zyl J, Burnette C F. Bayesian classification of polarimetric SAR images using adaptive a priori probabilities［J］. International Journal of Remote Sensing, 1992, 13(5): 835-840.

[32] Dipanwita H, Anup D, Shiv M, et al. Assessment of L-band SAR data at different polarization combinations for crop and other land use classification［J］. Progress in Electromagnetics Research B, 2012, 36(36): 303-321.

[33] Lee J S, Grunes M R, Kwok R. Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution［J］. International Journal of Remote Sensing, 1994, 15(15): 2299-2311.

[34] 张祥, 邓喀中, 范洪冬, 等. 基于目标分解的极化SAR图像SVM监督分类［J］. 计算机应用研究, 2013, 30(1): 295-298.

Zhang Xiang, Deng Kazhong, Fan Hongdong, et al. PolSAR SVM supervised classification method combining with polarimetric target decomposition［J］. Application Research of Computers, 2013, 30(1): 295-298.

[35] 周晓光. 极化SAR图像分类方法研究［D］. 长沙: 国防科学技术大学, 2008: 2-10.

Zhou Xiaoguang. Polarimetric SAR image classification［D］. Changsha: National University of Defense Technology, 2008: 2-10.

[36] 吴一全, 周杨, 龙云淋. 基于自适应参数支持向量机的高光谱遥感图像小目标检测［J］. 光学学报, 2015, 35(9): 0928001.

Wu Yiquan, Zhou Yang, Long Yunlin. Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM［J］. Acta Optica Sinica, 2015, 35(9): 0928001.

[37] 刘南南, 徐抒岩, 胡君, 等. 基于非下采样Contourlet变换和映射最小二乘支持向量机的高精度星点定位方法［J］. 光学学报, 2013, 33(5): 0512001.

Liu Nannan, Xu Shuyan, Hu Jun, et al. Hyper accuracy star location algorithm based on nonsubsampled contourlet transform and mapped least squares support vector machine［J］. Acta Optica Sinica, 2013, 33(5): 0512001.

[38] 陈芝芬. 基于SVM的遥感数据土地覆盖分类研究［D］. 武汉: 中国地质大学, 2009: 5-18.

Chen Zhifen. Research of land cover classification SVM based remote sensing data［D］. Wuhan: Geosciences University of China, 2009: 5-18.

[39] 赵一博, 秦先祥, 邹焕新. 基于目标分解和SVM的极化SAR图像分类方法［J］. 航天返回与遥感, 2013, 34(2): 50-56.

Zhao Yibo, Qin Xianxiang, Zou Huanxin. Classification of polarimetric SAR image based on target decomposition and SVM［J］. Spacecraft Recovery & Remote Sensing, 2013, 34(2): 50-56.

[40] 依力亚斯江·努尔麦麦提, 塔西甫拉提·特依拜, 丁建丽, 等. 基于多种极化分解方法和全极化合成孔径雷达数据的干旱区盐渍化监测［J］. 农业工程学报, 2015(23): 145-153.

Ilyas Nurmemet, Tashpolat Tiyip, Ding Jianli, et al. Monitoring soil salinization in arid area using PolSAR data and polarimetric decomposition method［J］. Transactions of the Chinese Society of Agricultural Engineering, 2015(23): 145-153.

[41] Touzi R, Goze S, Toan T L, et al. Polarimetric discriminators for SAR images［J］. IEEE Transactions on Geoscience & Remote Sensing, 1992, 30(5): 973-980.

再屯古丽·亚库普, 塔西甫拉提·特依拜, 依力亚斯江·努尔麦麦提, 买买提·沙吾提, 阿不都艾尼·阿不里, 阿卜杜萨拉木·阿布都加帕尔. 基于目标极化分解方法和PALSAR雷达数据的于田绿洲盐渍化监测[J]. 激光与光电子学进展, 2017, 54(6): 062803. Zaytungul Yakup, Tashpolat Tiyip, Ilyas Nurmemet, Mamat Sawut, Abdugheni Abliz, Abdusalam Abdujappar. Monitoring of Soil Salinization in Yutian Oasis Based on Target Polarimetric Decomposition Method and PALSAR Radar Data[J]. Laser & Optoelectronics Progress, 2017, 54(6): 062803.

基于目标极化分解方法和PALSAR雷达数据的于田绿洲盐渍化监测

关于本站 Cookie 的使用提示

全站搜索

基于目标极化分解方法和PALSAR雷达数据的于田绿洲盐渍化监测

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索