Analysis of InSAR Coherence Loss Caused by Soil Moisture Variation
DOI: 10.12000/JR15075 cstr: 32380.14.JR15075
-
Abstract:
Interferometric Synthetic Aperture Radar (InSAR) coherence is important not only in determining measurement quality but also for extracting thematic information about objects on the ground in combination with backscattering coefficient. The decorrelation of repeat-pass InSAR caused by soil moisture change has received little attention in comparison with other sources of decorrelation. In this paper, we use ENVISAT ASAR data and laboratory experiments to analyze the repeat-pass InSAR coherence loss results due to soil moisture change. C-band ASAR data has high coherence over bare soil and grassland areas, which indicates that these two types of land cover are good choices for the analysis of InSAR coherence loss due to soil moisture change. In addition, spaceborne SAR with short revisit capability, has great potential for this specific application, even for agricultural fields. We conducted further analysis of the soil-sample laboratory data acquired in an anechoic chamber because of its controllable environment and the ability to exclude other sources of decorrelation. We found that the lower frequency range, 2-2.5 GHz, has the highest coherence and is the most insensitive to the initial soil moisture value. This indicates that the S band is more advantageous than the C band when using InSAR coherence to detect soil moisture change. This is true at least with respect to the S band's high coherence level and insensitivity to initial soil moisture values.
-
Key words:
- Repeat pass /
- Radar interferometry /
- Coherence /
- Soil moisture
摘要:干涉SAR的相干性对于数据质量的衡量和与后向散射结合的目标信息提取,都具有重要的意义。然而相比其他的去相干源,土壤湿度变化引起的重轨干涉SAR的去相干尚未得到充分的研究。该文利用EnvisatASAR和暗室数据分析了由土壤湿度变化引起的重轨干涉SAR的相干性损失。C波段ASAR数据仅在裸土或草地区域具有较高的相干性,意味着这两种陆地覆盖类型比较适合作为土壤湿度变化对星载数据干涉相干性影响的研究对象。此外重访周期短的星载SAR即使对于农田区域具有重要的应用潜力。由于微波暗室的可控环境,特别是能够去除其他去相干源的影响,因而设计开展了暗室实验,并详细分析了土壤样本的观测数据。实验发现低频2-2.5 GHz具有较高的相干性,并且对土壤湿度初值的敏感度较低。这表示在利用干涉相干性信息提取土壤湿度变化时,至少是在相干性水平和对土壤湿度初值的敏感度方面,S波段优于C波段。
-
[1] Barrett B, Whelan P, and Dwyer E. Detecting changes in surface soil moisture content using differential SAR interferometry[J]. International Journal of Remote Sensing, 2013, 34(20): 7091-7112. [2] Gabriel A, Goldstein R, and Zebker H. Mapping small elevation changes over large areas: differential radar interferometry[J]. Journal of Geophysical Research, 1989, 94: 9183-9191. [3] Hajnsek I and Prats P. Soil moisture estimation in time with D-InSAR[C]. IEEE International Geoscience and Remote Sensing Symposium, Boston, USA, 2008: 546-549. [4] Hensley S, Michel T, Van Zyl J, et al.. Effect of soil moisture on polarimetric-interferometric repeat pass observations by UAVSAR during 2010 Canadian soil moisture campaign[C]. IEEE International Geoscience and Remote Sensing Symposium, Vancouver, Canada, 2011: 1063-1066. [5] Zhang T, Zeng Q, Li Y, et al.. Study on relation between InSAR coherence and soil moisture[C]. ISPRS Congress, Beijing, China, 2008: 131-134. [6] Nesti G, Tarchi D, and Rudant J. Decorrelation of backscattered signal due to soil moisture changes[C]. IEEE International Geoscience and Remote Sensing Symposium, Firenze, Italy, 1995: 2026-2028. [7] Nolan M, Fatland D, and Hinzman L. DInSAR measurement of soil moisture[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(12): 2802-2813. [8] Morrison K, Bennett J, Nolan M, et al.. Laboratory measurement of the DInSAR response to spatiotemporal variations in soil moisture[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3815-3823. [9] De Zan F, Parizzi A, Prats-Iraola P, et al.. A SAR interferometric model for soil moisture[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(1): 418-425. [10] Yin Q, Hong W, Li Y, et al.. analysis on soil moisture estimation of SAR data based on coherent scattering model[J]. 10th European Conference on Synthetic Aperture Radar, Berlin, Germany, 2014: 739-742. [11] Zwieback S, Hensley S, and Hajnsek I. Assessment of soil moisture effects on L-band radar interferometry[J]. Remote Sensing of the Environment, 2015, 164: 77-89. 期刊类型引用(6)
1. 邢孟道,马鹏辉,楼屹杉,孙光才,林浩. 合成孔径雷达快速后向投影算法综述. 雷达学报. 2024(01): 1-22 . 本站查看
2. 周开心,刘丹阳,朱永锋,张永杰,周剑雄. 强杂波背景下调频步进DBS技术研究. 系统工程与电子技术. 2024(09): 2960-2967 . 百度学术
3. 匡辉,于海锋,高贺利,刘磊,刘杰,张润宁. 超高分辨率星载SAR系统多子带信号处理技术研究. 信号处理. 2022(04): 879-888 . 百度学术
4. 吕明久,陈文峰,徐芳,赵欣,杨军. 基于原子范数最小化的步进频率ISAR一维高分辨距离成像方法. 电子与信息学报. 2021(08): 2267-2275 . 百度学术
5. 张亦凡,黄平平,徐伟,谭维贤,高志奇. 星载斜视滑动聚束SAR子孔径成像处理算法研究. 信号处理. 2021(08): 1525-1532 . 百度学术
6. 吕明久,徐芳,赵丽,陈莉,陈浩. 载频不同分布方式下RSF波形稀疏重构性能分析. 空军预警学院学报. 2020(05): 319-324 . 百度学术
其他类型引用(6)
-
计量
- 文章访问数: 2892
- HTML全文浏览量: 551
- PDF下载量: 1085
- 被引次数: 12