Soil Moisture Estimation under Vegetation applying Polarimetric Decomposition Techniques

نویسندگان

  • Thomas Jagdhuber
  • Helmut Schön
  • Irena Hajnsek
  • Konstantinos P. Papathanassiou
چکیده

Polarimetric decomposition techniques and inversion algorithms are developed and applied on the OPAQUE data set acquired in spring 2007 to investigate their potential and limitations for soil moisture estimation. A three component model-based decomposition is used together with an eigenvalue decomposition in a combined approach to invert for soil moisture over bare and vegetated soils at L-band. The applied approach indicates a feasible capability to invert soil moisture after decomposing volume and ground scattering components over agricultural land surfaces. But there are still deficiencies in modeling the volume disturbance. The results show a root mean square error below 8.5vol.-% for the winter crop fields (winter wheat, winter triticale and winter barley) and below 11.5Vol-% for the summer crop field (summer barley) whereas all fields have a distinct volume layer of 55-85cm height.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Soil Moisture Retrieval from Polarimetric Sar Data: a Short Review of Existing Methods and a New One

Soil moisture retrieval from SAR data is not an easy task, especially in presence of vegetation cover. Accordingly, in recent years several methods for soil-moisture retrieval under vegetation cover have been developed, relying on model-based or hybrid polarimetric targetdecomposition techniques. However, most of these decomposition techniques suffer from the so-called negative-power problem, w...

متن کامل

Inversion of Surface Parameters from NASA/JPL AIRSAR Polarimetric SAR Data

The improvements of polarimetric SAR data inversion algorithms are discussed and presented. The confounding influence of roughness and vegetation cover on the estimation of the soil moisture contents are considered in the inversion algorithm that estimates moisture content and roughness parameters simultaneously from the pertinent combination of polarization measurements. The estimation of soil...

متن کامل

Polarimetric Decompositions for Soil Moisture Retrieval from Vegetated Soils in TERENO Observatories

A refined hybrid polarimetric decomposition and inversion method for soil moisture estimation under vegetation is investigated for its potential to retrieve soil moisture from vegetated soils in TERENO observatories. The refined algorithm is applied on Lband fully polarimetric data acquired by DLR’s novel F-SAR sensor. Two flight and field measurement campaigns were conducted in 2011 and 2012 f...

متن کامل

Exploring the Validity Range of the Polarimetric Two-scale Two- Component Model for Soil Moisture Retrieval by Using Agrisar Data

The recently proposed polarimetric two-scale twocomponent model (PTSTCM) in principle allows us obtaining a reasonable estimation of the soil moisture even in moderately vegetated areas, where the volumetric scattering contribution is non-negligible, provided that the surface component is dominant and the double-bounce component is negligible. Here we test the PTSTCM validity range by applying ...

متن کامل

Evaluation of Simplified Polarimetric Decomposition for Soil Moisture Retrieval over Vegetated Agricultural Fields

This paper investigates a simplified polarimetric decomposition for soil moisture retrieval over agricultural fields. In order to overcome the coherent superposition of the backscattering contributions from vegetation and underlying soils, a simplification of an existing polarimetric decomposition is proposed in this study. It aims to retrieve the soil moisture by using only the surface scatter...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009