Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data

Flood Mapping and Flood Dynamics of the Mekong Delta: ENVISAT-ASAR-WSM Based Time Series Analyses

Satellite remote sensing is a valuable tool for monitoring flooding. Microwave sensors are especially appropriate instruments, as they allow the differentiation of inundated from non-inundated areas, regardless of levels of solar illumination or frequency of cloud cover in regions experiencing substantial rainy seasons. In the current study we present the longest synthetic aperture radar-based ...

Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta

Rice Monitoring Using ENVISAT ASAR Data: Preliminary Results of a Case Study in the Mekong River Delta, Vietnam

ABSTRACT: Vietnam is one of the world’s largest rice exporting countries, and the fertile Mekong River Delta at the southern tip of Vietnam accounts for more than half of the country’s rice production. Unfortunately, a large part of rice crop growing time coincides with a rainy season, resulting in a limited number of cloud-free optical remote sensing images for rice monitoring. Synthetic apert...

Varying Scale and Capability of Envisat ASAR-WSM, TerraSAR-X Scansar and TerraSAR-X Stripmap Data to Assess Urban Flood Situations: A Case Study of the Mekong Delta in Can Tho Province

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...

Supervised Wishart Classifier for Rice Mapping Using Multi-temporal Envisat Asar Aps Data

For the operational application of multi-temporal ENVISAT ASAR APS data to rice mapping, a complex Wishart distribution based multi-temporal classifier was evaluated in this paper. The classification accuracy of this classifier was quantitatively compared with commonly used classifiers for optical remote sensing image classification including maximum likelihood classifier and minimum euclidean ...