Cereal Crops Soil Parameters Retrieval Using L-Band ALOS-2 and C-Band Sentinel-1 Sensors

نویسندگان

چکیده

This paper discusses the potential of L-band Advanced Land Observing Satellite-2 (ALOS-2) and C-band Sentinel-1 radar data for retrieving soil parameters over cereal fields. For this purpose, multi-incidence, multi-polarization dual-frequency satellite were acquired simultaneously with in situ measurements collected a semiarid area, Merguellil Plain (central Tunisia). The L- signal sensitivity to roughness, moisture vegetation was investigated. High correlation coefficients observed between signals roughness values all processed multi-configurations ALOS-2 data. SAR (Synthetic Aperture Radar) investigated three classes normalized difference index (NDVI) (low cover, medium cover dense cover), illustrating decreasing increasing NDVI values. highest under class is various properties (leaf area (LAI), height (H) water content (VWC)), strong (in HH(Horizontal-Horizontal) HV(Horizontal-Vertical) polarizations). Different empirical models that link C-bands) parameters, as well semi-empirical Dubois modified model (Dubois-B) integral equation (IEM-B), bare soils are proposed polarizations. results reveal IEM-B performed better accuracy comparing Dubois-B. analysis also covered surfaces using different options provided by cloud (WCM) (with without soil–vegetation interaction scattering term) coupled best backscattering models: co-polarization entire dataset. Based on validated models, tested inversion. integration component WCM illustrates considerable contribution precision HV polarization mode frequency neglected effect

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Retrieval Bare-soil Moisture Using L-band Sar

This paper reports a study of algorithm development and testing for soil moisture retrieval for bare fields using L-band SAR imagery. First-order surface scattering models predict that the co-polarization ratio is sensitive to soil moisture but not to surface roughness. Our previous study indicated that the measurement of (Jvv / (Jhh at L-band is proportional to soil moisture. In this study, th...

متن کامل

Preliminary Study on Developing an L-band Wind Retrieval Model Function Using Alos/palsar

The relationship between ocean wind vectors and Lband normalized radar cross sections (NRCS) is examined using the Phased-Array L-band Synthetic Aperture Radar (PALSAR). We used PALSAR ScanSAR images with a wide range of incidence angles from 17o to 43o. More than 6,000 match-ups, each consisting of the NRCS, incidence angles, wind speeds and wind directions, were collected. The NRCS exhibits a...

متن کامل

Narrow band based and broadband derived vegetation indices using Sentinel-2 Imagery to estimate vegetation biomass

Forest’s ecosystem is one of the most important carbon sink of the terrestrial ecosystem. Remote sensing technology provides robust techniques to estimate biomass and solve challenges in forest resource assessment. The present study explored the potential of Sentinel-2 bands to estimate biomass and comparatively analyzed of red-edge band based and broadband derived vegetation indices. Broadband...

متن کامل

Polarimetric Parameters for Growing Stock Volume Estimation Using ALOS PALSAR L-Band Data over Siberian Forests

In order to assess the potentiality of ALOS L-band fully polarimetric radar data for forestry applications, we investigated a four-component decomposition method to characterize the polarization response of Siberian forest. The decomposition powers of surface scattering, double-bounce and volume scattering, derived with and without rotation of coherency matrix, were compared with Growing Stock ...

متن کامل

Soil moisture retrieval using the passive/active L- and S-band radar/radiometer

In the present study, remote sensing of soil moisture is carried out using the Passive and Active Land S-band airborne sensor (PALS). The data in this paper were taken from 5 days of overflights near Chickasha, Oklahoma during the 1999 Southern Great Plains (SGP) experiment. Presently, we analyze the collected data to understand the relationships between the observed signals (radiometer brightn...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Remote Sensing

سال: 2021

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs13071393