Information of spatial and temporal variations of soil quality (soil properties) is required for various purposes of sustainable agriculture development and management. Traditionally, soil quality characterization is done by in situ point soil sampling and subsequent laboratory analysis. Such methodology has limitation for assessing the spatial variability of soil quality. Various researchers i...

Remote Sensing and Geographic information System together comprise of Geographic Information Science (GIScience) which is a core research field that tries to emphasis on advanced geographic concepts in Geographic Information System and examines the impact of GIS on individuals and society as a whole and re-examines the themes with incorporation of most recent cognitive and Information Science. ...

In this paper, a new wavelet based image interpolation algorithm is proposed for remote sensing images. Remote sensing images include many mid and high frequency elements such as aerial and satellite photograph images. These frequency elements contain important information. Because conventional interpolation techniques have blurring or blocking effects, the quality of interpolated remote sensin...

The Special Issue (SI) on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, m...

Landslides represent major natural hazards, which cause every year significant loss of lives and damages to buildings, properties and lifelines. In the last decades, a significant increase in landslide frequency took place, in concomitance to climate change and the expansion of urbanized areas. Remote sensing techniques represent a powerful tool for landslide investigation: applications are tra...

In this paper different types of image classification will be studied. Decision level fusion, using a specific criterion or algorithm to integrate the classified results from different classifiers, has shown great benefits to improve classification accuracy of multi-source remote sensing images. Based on a survey to hyperspectral remote sensing classification techniques and decision level fusio...

Several applications have been developed in the field of remote sensing image analysis during the last decades. Besides well-known statistical approaches, many recent methods are based on techniques taken from the field of machine learning. A major aim of machine learning algorithms in remote sensing is supervised classification, which is perhaps the most widely used image classification approa...

As a follow-up to the Best Paper Award of 2014, recognizing the most outstanding papers in the area of remote sensing techniques, design and applications published in Remote Sensing, we are pleased to announce the Remote Sensing Best Paper Award for the year 2015. Nominations were selected by the Editor-in-Chief and selected Associate Editors from among all the papers published in the year 2011...

Conventional query techniques for remote sensing image archives as they are available from various satellite data providers are reviewed. The Swiss National Remote Sensing Image Archive is currently being installed at the Swiss Center for Scientific Computing (CSCS/SCSC) and a status report will be given. In parallel with classical query and retrieval possibilities, content-based image search b...