In this paper

I propose a personal view on the general contents of remote sensing science and technology

which includes sensor research and manufacturing

remotely sensed data acquisition

data processing

information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas

there are critical research questions.In particular

I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing

removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration

integrating knowledge and remotely sensed data into effective information extraction

and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion

image classification

regression analysis

three dimensional information extraction

shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation? Finally

4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate

hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return

the quality of remotely sensed parameters can be improved.