An unmixing algorithm for remotely sensed soil moisture

نویسندگان

  • Amor V. M. Ines
  • Binayak P. Mohanty
  • Yongchul Shin
چکیده

[1] We present an unmixing method, based on genetic algorithm-soil-vegetationatmosphere-transfer modeling to extract subgrid information of soil and vegetation from remotely sensed soil moisture (downscaled; e.g., soil hydraulic properties, area fractions of soil-vegetation combinations, and unmixed soil moisture time series) that most land surface models use. The unmixing method was evaluated using numerical experiments comprising mixed pixels with simple and complex soil-vegetation combinations, in idealized case studies (with or without uncertainty) and under actual field conditions (Walnut Creek (WC11) field, Soil Moisture Experiment 2005, Iowa). Additional validation experiments were conducted at an airborne-remote sensing footprint (Little Washita (LW21) site, Southern Great Plains 1997 hydrology campaign, Oklahoma) using Electronically Scanning Thin Array Radiometer (ESTAR). Results of the idealized experiments suggest that the unmixing method can extract optimal or near-optimal solutions to the inverse problem under different hydrologic and climatic conditions. Errors in soil moisture data and initial and boundary conditions can compound uncertainty in the solution. The solutions generated under actual field conditions (WC11 field) were able to match soil moisture observations. Analysis showed that typical soil moisture retention curves of cataloged dominant soils in WC11 field did not match well with the measurements, but those derived from actual fieldscale soil moisture inversion matched better. The unmixing method performed well in replicating soil hydraulic behavior at the ESTAR footprint. Unlike in WC11 field, the typical soil moisture retention curves of cataloged soils in LW21 field matched better with the measurements. We envisaged that the unmixing method can provide quick and easy way of extracting subgrid soil moisture variability and soil-vegetation information in a pixel.

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

Spatial Interpolation as a Tool for Spectral Unmixing of Remotely Sensed Images

Super resolution-based spectral unmixing (SRSU) is a recently developed method for spectral unmixing of remotely sensed imagery, but it is too complex to implement for common users who are interested in land cover mapping. This study makes use of spatial interpolation as an alternative approach to achieve super resolution reconstruction in SRSU. An ASTER image with three spectral bands was used...

متن کامل

Soil Moisture Estimation by Microwave Remote Sensing for Assimilation into WATClass

I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. Abstract This thesis examines the feasibility of assimilating space borne remotely-sensed microwave data into WATClass using the ensemble Kalman filter. W...

متن کامل

A Novel Method for Quantifying Value in Spaceborne Soil Moisture Retrievals

A novel methodology is introduced for quantifying the added value of remotely sensed soil moisture products for global land surface modeling applications. The approach is based on the assimilation of soil moisture retrievals into a simple surface water balance model driven by satellite-based precipitation products. Filter increments (i.e., discrete additions or subtractions of water suggested b...

متن کامل

Irrigation Scheduling Using Remote Sensing Data Assimilation Approach

Remote sensing and crop growth models have enhanced our ability to understand soil water balance in irrigated agriculture. However, limited efforts have been made to adopt data assimilation methodologies in these linked models that use stochastic parameter estimation with genetic algorithm (GA) to improve irrigation scheduling. In this study, an innovative irrigation scheduling technique, based...

متن کامل

The Role of Remotely Sensed Soil Moisture to Predict Surface Water Elevation at the Watershed Scale in Korea

Soil moisture is one of the most important key physical parameters in hydrological and environmental processes. During the past decade, remote sensing measurements have been widely used to provide mean surface soil moisture on a large spatial scale because conventional ground based measurements are not always available and require more time and cost. However, very few studies have been conducte...

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 2013