Abstract
Abstract. Remote sensing course is a general disciplinary required course of human geography and urban-rural planning major. Its class hour is 48, including theoretical classes and experimental classes. Rapid technological developments is remote sensing area demand quick and steady changes in the education programme and its realization, especially in experimental classes. Experimental classes include: introduction to remote sensing software and basic operations, remote sensing data pre-processing (input, output, 2D and 3D terrain display, image cut, image mosaic, and projection transformation), remote sensing image enhancement, remote sensing image transformation, computer aided classification, image interpretation, and remote sensing image terrain analysis. There are two difficulties in the remote sensing experimental classes. First, it cost a lot of time to prepare the remote sensing software and the remote sensing images. Second, some students just want to use the remote sensing as a tool to investigate environment changing, some other students may want to study more remote sensing image processing technologies. A web-based learning environment of remote sensing is developed to facilitate the application of remote sensing experimental teaching. To make the learning more effective, there are eight modules including four optional modules. The Python programming language is chosen to implement the web-based remote sensing learning environment. The web-based learning environment is implemented in a local network server, including the remote sensing data processing algorithms and many satellite image data. Students can easily exercise the remote sensing experimental courses by connecting to the local network server. It is developed mainly for remote sensing experimental course, and also can be adopted by digital image processing or other courses. The feature of web-based learning may be very useful as the online education adopted because of Corona Virus Disease 2019. The results are encouraging and some recommendations will be extracted for the future.
Highlights
Remote sensing plays an important role in many fields, such as major natural disaster monitoring, global climate dynamics, primary production of terrestrial ecosystems, government decision-making, etc
It cost a lot of time to prepare the remote sensing software and the remote sensing images
Some students just want to use the remote sensing as a tool to investigate environment changing, some other students may want to study more remote sensing image processing technologies
Summary
Remote sensing plays an important role in many fields, such as major natural disaster monitoring, global climate dynamics, primary production of terrestrial ecosystems, government decision-making, etc. The rapid increase in the availability of remote sensing data coupled with the increasing need for accurate and timely earth surface information especially in developing countries has accelerated the demand for and provision of technology transfer of remote sensing by many organizations and governments Much of this increase is related to concerns for global climate change (Haack et al, 2016). The web-based learning environment is implemented in a local network server, including the remote sensing data processing algorithms and many satellite image data. Virtual and remote labs reduce the costs associated with conventional hands-on labs due to their required equipment, space, and maintenance staff They provide additional benefits such as supporting web-based learning (Heradio et al, 2016). E-learning tools and methods will be popular discussed (Anjana et al, 2016), and the feature of web-based learning may be very useful as the online education adopted (Yang et al, 2016.)
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