CORRELATION BETWEEN NDVI AND SENTINEL-1 DERIVED FEATURES FOR MAIZE

被引:15
作者
Alvarez-Mozos, I [1 ]
Villanueva, I [1 ]
Arias, M. [1 ]
Gonzalez-Audicana, M. [1 ]
机构
[1] Univ Publ Navarra, Dept Engn, Arrosadia Campus, Pamplona 31006, Spain
来源
2021 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM IGARSS | 2021年
关键词
maize; Sentinel-1; NDVI; backscatter;
D O I
10.1109/IGARSS47720.2021.9554099
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Operational agricultural applications of remote sensing, such as crop monitoring or irrigation scheduling, often rely on the Normalized Difference Vegetation Index (NDVI) obtained from multispectral observations. Yet, cloud cover limits its availability, so the possibility to estimate it from SAR data is appealing, as it would enable a complementary monitoring of crops. The objective of this article is to evaluate the correlation of NDVI with several SAR features obtained from Sentinel-1 data over maize. Eighteen maize fields, located in the province of Navarre (Spain), were analyzed in two agricultural campaigns. Nine SAR features were evaluated, including: the backscattering coefficients in VH and VV polarizations, their ratio, product, sum and difference, as well as the Radar Vegetation Index (RVI), the Vertical Dual De-Polarization Index (VDDPI) and the Normalized Difference Polarization Index (NDPI). The correlations obtained in linear and dB units were compared, as well as the influence of temporal smoothing. The highest correlation was obtained with VH backscatter expressed in dB.
引用
收藏
页码:6773 / 6776
页数:4
相关论文
共 9 条
[1]   Crop Classification Based on Temporal Signatures of Sentinel-1 Observations over Navarre Province, Spain [J].
Arias, Maria ;
Angel Campo-Bescos, Miguel ;
Alvarez-Mozos, Jesus .
REMOTE SENSING, 2020, 12 (02)
[2]   Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics [J].
Bolton, Douglas K. ;
Friedl, Mark A. .
AGRICULTURAL AND FOREST METEOROLOGY, 2013, 173 :74-84
[3]  
Cao Y.G., 2008, Proceedings of the ISPRS Congress Beijing 2008, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V37, P1529
[4]   A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data [J].
Kim, Yunjin ;
van Zyl, Jakob J. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (08) :2519-2527
[5]   Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage [J].
Nasirzadehdizaji, Rouhollah ;
Sanli, Fusun Balik ;
Abdikan, Saygin ;
Cakir, Ziyadin ;
Sekertekin, Aliihsan ;
Ustuner, Mustafa .
APPLIED SCIENCES-BASEL, 2019, 9 (04)
[6]   Significance of dual polarimetric synthetic aperture radar in biomass retrieval: An attempt on Sentinel-1 [J].
Periasamy, Shoba .
REMOTE SENSING OF ENVIRONMENT, 2018, 217 :537-549
[7]   Fusing optical and SAR time series for LAI gap filling with multioutput Gaussian processes [J].
Pipia, Luca ;
Munoz-Mari, Jordi ;
Amin, Eatidal ;
Belda, Santiago ;
Camps-Valls, Gustau ;
Verrelst, Jochem .
REMOTE SENSING OF ENVIRONMENT, 2019, 235
[8]  
Rouse JW, 1973, NASA SP, P309, DOI DOI 10.1021/JF60203A024
[9]  
Villanueva J., 2020, COMP STUDY CORN FIEL