ASAR image target detection and recognition has been always a hot research. In this paper, on the foundation of the previous studies, a target recognition method based on combined wavelet transformation and cloud model is proposed. According to the good local characteristic, multi-resolution, effectiveness and the sensitivity to both direction and texture of the combined wavelet transformation,...

In order to quantify real time pasture biomass from SAR image, regression model between ground measurements of biomass and ENVISAT ASAR backscattering coefficient should be built up. An important prerequisite of valid and accurate regression model is accurate grass backscattering coefficient which, however, cannot be obtained when there is speckle. Speckle noise is the best known problem of SAR...

During 1996–2006, the Ministry of Agriculture and Forestry in Finland (MAFF), MTT Agrifood Research and the Finnish Geodetic Institute performed a joint remote sensing satellite research project. It evaluated the applicability of optical satellite (Landsat, SPOT) data for cereal yield estimations in the annual crop inventory program. Four Optical Vegetation Indices models (I: Infrared polynomia...

Earth Observation is a powerful tool for the detection of floods. Microwave sensors are typically favored as they deliver data enabling water detection independent of solar illumination or cloud cover conditions. However, scale issues play an important role in radar based flood mapping. Depending on the flood related phenomenon under investigation, some sensors might be more suitable than other...

A wavelet based methodology has been developed to retrieve the wind field over the sea surface from SAR images without any a-priori information of the wind direction. The method relies on the ability of the twodimensional continuous wavelet technique to detect the spatial structure of the Marine Atmospheric Boundary Layer (MABL). The analysis of the geometric and radiometric characteristics of ...

The availability of reliable land surface information is crucial for a wide range of applications such as environmental monitoring including essential climate change variables, or agroeconomical aspects for a sustainable land management. Compared to optical remote sensing data, radar sensors can provide datasets with regular coverage of a specific area without suffering from missing images beca...

In this paper, a technique that is able to retrieve soil moisture maps in areas at risk of flood from ENVISAT/ASAR images, based on a Neural Network approach, was tested. Some experimental trials were carried out in 2003 and 2004 in the agricultural area of the Scrivia watershed in northern Italy, simultaneously to the ASAR passes. This area is susceptible to flooding and has a dense hydrometri...

Spectra derived from ENVISAT Advanced Synthetic Aperture Radar (ASAR) and QuikSCAT near-surface ocean winds are investigated over the North Sea. The two sensors offer a wide range of spatial resolutions, from 600 m to 25 km, with different spatial coverage over the area of interest. This provides a unique opportunity to study the impact of the spatial resolution on the spectral properties of th...

Poyang Lake is the largest freshwater lake in China with an area of about 3,000 km2. Its wetland ecosystem has a significant impact on China’ s environment change. Traditional way to monitor biomass change on this area is to use linear or nonlinear model from TM/ETM data. In this paper we discuss the neural network algorithms(NNA) to retrieve wetland biomass from multipolarization(HH and VV) ba...

The objective of this study is to present a new application of optical and radar remote sensing with high spatial ( 10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one...