This study analyses domestic market integration’s (DMI’s) dynamic influence on regional economic growth in China. The authors construct a matrix of annual DMI indices for 29 provinces for 1997–2015. They calculate the reciprocal matrix and combine it with the β-convergence model and spatial econometrics to analyse the relationships between DMI and regional economic growth. Their findings indicate that the relation between these two variables is not straightforward, and 2004 was a tipping-point year. Before 2004, the statistical relationship between DMI and regional economic growth was downward sloping, which suggests a trend of divergence and negative spillover effects across the 29 provinces. After 2004, the relationship between DMI and regional economic growth becomes positive: increased DMI now is strengthening (regional) economic growth. The authors provide the possible explanations for the unstable relationship combined with China’s reality as well.@en

Spatiotemporal residual noise in terrestrial earth observation products, often caused by unfavorable atmospheric conditions, impedes their broad applications. Most users prefer to use gap-filled remote sensing products with time series reconstruction (TSR) algorithms. Applying currently available implementations of TSR to large-volume datasets is time-consuming and challenging for non-professional users with limited computation or storage resources. This study introduces a new open-source software package entitled ‘HANTS-GEE’ that implements a well-known and robust TSR algorithm, i.e. Harmonic ANalysis of Time Series (HANTS), on the Google Earth Engine (GEE) platform for scalable reconstruction of terrestrial earth observation data. Reconstruction tasks can be conducted on user-defined spatiotemporal extents when raw datasets are available on GEE. According to site-based and regional-based case evaluation, the new tool can effectively eliminate cloud contamination in the time series of earth observation data. Compared with traditional PC-based HANTS implementation, the HANTS-GEE provides quite consistent reconstruction results for most terrestrial vegetated sites. The HANTS-GEE can provide scalable reconstruction services with accelerated processing speed and reduced internet data transmission volume, promoting algorithm usage by much broader user communities. To our knowledge, the software package is the first tool to support full-stack TSR processing for popular open-access satellite sensors on cloud platforms.

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