Foreword
Special Issue: Cloud-prone And Rainy Area Remote Sensing (CARRS)
It is our great pleasure to introduce the special issue on “Cloudprone And Rainy area Remote Sensing (CARRS).” The theme was originally inspired by the unique environment that inhabit, which is in the sub-tropical monsoon climate region of Southern China with abundant rainfall and frequent cloud cover. In the rest of the world, the cloud-prone and rainy areas occupy the large areas from the equatorial region to Western Europe, Southeastern United States, including many coastal areas.
Many cloudy and rainy areas are also the regions with large human settlements and significant economic development. The need to observe and monitor the natural environment and its changes and the impacts on people is in high demand and a challenging task. Remote sensing theory and technology plays an important role for this task. It often involves utilization of remote sensing in the microwave portion of the electromagnetic spectrum, e.g., radar remote sensing technology.
The scientific significance of CARRS is to further the frontier of our ability to understand, monitor, simulate and predict the current and future states of the Earth system as a whole. The ultimate goal is to be able to capture, on a real-time basis, all physical and biophysical processes that control and govern the atmosphereland- ocean system.
This special issue reflects, from a unique perspective, some current research and application endeavors involved in CARRS. The topic areas covered by the eight articles concern the terrestrial, atmospheric, and oceanic components of the Earth system. One paper by Lu presents an overview of the study of volcanos using SAR and InSAR technology in a cloudy and rainy area over the Aleutian Islands. The successes in monitoring and quantifying the ground deformation and lava flow that occurred in the volcano demonstrate the capability of using radar remote sensing technology in monitoring and modeling such an important natural phenomena.
Monitoring the subsidence due to coal mining has attracted much attention from the remote sensing community. As an interesting approach, use of the SAR interferometry technique has been proven to be effective under certain conditions. The study presented by Ge et al. addresses the application of this technique using multi-source SAR data in quantifying the magnitude of the subsidence caused by coal mining and the spatial distribution and temporal changes of the phenomena in the study area.
Research findings of a study of rain cells by synergistically using data acquired by both optical and radar satellites over the coastal area of the South China Sea is presented in the paper by Alpers et al. It illustrates the great potential of using spaceborne multi-sensors’ remotely-sensed data in concert with other ground-based meteorological observations to understand formation, movement, and control mechanisms of the intense rain cells that is one of the significant weather systems in the coastal areas under a tropical monsoon climate regime.
Polarimetric SAR data has been widely recognized as a promising data source for vegetation classification. The study carried out by Chen et al. quantitatively evaluates the capability of AIRSAR L-band fully polarimetric SAR data in agricultural crop mapping using different classification methods and various input feature combinations. The result shows that the spatial-spectral classifier applied to six intensity and three phase images can achieve the highest classification accuracy among all the evaluated schemes.
SAR remote sensing has long been proved to be a particularly useful tool for monitoring floods over large area. However, such applications may be restrained by the presence of shadow areas caused by high topographic relief. The comparative study carried out by Song et al. shows that the scheme using a radiometric and geometric corrected SAR image and Digital Surface Model is the best choice for delineating flood extent over high relief mountainous areas in terms of both time efficiency and water detection accuracy.
For most applications of vegetation and land surface condition, one of the practical approaches to reduce the effect of the clouds is through data compositing using multi-temporal satellite data. A study on compositing methods made by Fensholt et al. shows that a more efficient and better quality data composite can be produced using geostationary satellite data than using polar orbiting satellite data in terms of shorter compositing period and more cloud-free observations.
Land use/cover change (LUCC) detection has always been a hot topic in the remote sensing community for its wide applications in global change studies. The paper by Zhang et al. presents a new approach combining the canonical correlation analysis and contextual Bayes decision for change detection in bi-temporal multispectral remotely-sensed images. The effectiveness of this approach is demonstrated by an experiment of monitoring land reclamations in Hong Kong using two Landsat TM/ETM+ images.
Understanding of LUCC and its driving forces, as well as its impacts on environmental factors, is of great significance for regional sustainable development. The study presented by Chen et al. makes a quantification of LUCC during the 1990s in the Poyang Lake watershed, and evaluates the correlations between LUCC, rainfall and sediment loads at sub-watershed scale by integrating remote sensing and GIS with statistical analysis. It is concluded that the changing rates of forest cover and climate regimes are primary factors for sediment discharges in the Poyang Lake watershed.
To conclude, we sincerely hope that this special issue will stimulate more interests by the remote sensing community in pursuing basic and applied research on CARRS. The main areas of the research may include theoretical study on the mechanism of interactions between electromagnetic wave and surface targets, development of new algorithms and techniques in image processing and information extraction, and construction of new models and software for various applications.
Dr. Hui Lin, Guest Editor
Professor and Director
Institute of Space and Earth Information Science
The Chinese University of Hong Kong
Shatin, NT, Hong Kong
Dr. Limin Yang, Co-Editor
Institute of Space and Earth Information Science
The Chinese University of Hong Kong
Shatin, NT, Hong Kong
Dr. Yun Shao, Co-Editor
Institute of Remote Sensing Applications
Chinese Academy of Sciences
Beijing, China, 100101