Satellite time series with high spatial resolution is critical for monitoring land surface dynamics in heterogeneous landscapes. Although remote sensing technologies have experienced rapid development in recent years, data acquired from a single satellite sensor are often unable to satisfy our demand. As a result, integrated use of data from different sensors has become increasingly popular in the past decade. Many spatiotemporal data fusion methods have been developed to produce synthesized images with both high spatial and temporal resolutions from two types of satellite images, frequent coarse-resolution images, and sparse fine-resolution images. These methods were designed based on different principles and strategies, and therefore show different strengths and limitations. This diversity brings difficulties for users to choose an appropriate method for their specific applications and data sets. To this end, this review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.

This study investigated GIS students' perspectives on emergency online learning (EOL) during the Covid-19 pandemic through a case study at National University of Singapore.Questionnaire surveys administered to three GIS courses were conducted, the result of which suggests that the GIS teaching could be completed effectively online during the crisis. In addition, the positive and negative influences of this learning mode have been discussed in connection to relevant student perspectives on social media and relevant findings in the literature. Relatively, senior and independent learners adapted better to the EOL, while beginners and less self-disciplined learners may need more face-to-face guidance, interactions, and direct supervision. It is worth pointing out that despite some students seeing the demand for a higher level of self-discipline as being negative, others saw this property contributed to them being better independent learners with self-motivation, suggesting the need for a nuanced interpretation of the results that consider perspectives. Based on the pros and cons of the EOL investigated, this article further stresses the need to cultivate a post-pandemic blended GIS learning pedagogy for enhancing higher GIS education's quality and resilience in times of crisis.

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