In the context of uneven development studies of China, urban built-up area changes are the index of the impact of power, as the local government is the only party that is able to acquire agricultural land and convert it to construction urban land. Existing studies generally use statistical data to describe the built-up area changes and struggle to meet the requirement of an updated and inexpensive monitoring of uneven development, especially for western cities with tight budgets. Open access NPP-VIIRS (Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite), NDVI (Normalized Difference Vegetation Index), and nighttime LST (Land Surface Temperature) data ranging from 2015 to 2019 were analyzed with a stratified SVM (Support Vector Machine) method in this study to track urban built-up area changes in Chengdu, one of the biggest cities in Western China. The SDE (Standard Deviation Ellipse) and Moran’s I were then applied to evaluate the spatial variations of the built-up area changes. It was revealed that the spatial evolution of built-up area change in Chengdu over the period 2015–2019 demonstrated a “northwest-southeast” spatial expansion pattern, and the change distance in the center of gravity in 2018 and 2019 was greater than that from 2015 to 2017, which reflected the faster uneven development in 2018 and 2019 in Chengdu. The results were verified with finer resolution Landsat-8 OLI images; the high OA (all larger than 92%) and KAPPA (all larger than 0.6) values showed the accuracy of the method. The methodology proposed in this study offers a practical way for cities with tight budgets to monitor uneven development, and this study suggests a further adaption using higher-resolution remote sensing images and field experiments.

Urban spatial interaction integrates cities into closely related urban network systems in continuous urban regions. However, it also brings differentiation and has mutual negative impacts between each location. Unbalanced development is one such impacts and needs closely monitoring. The housing vacancy rate (HVR) in a continuous urban region is an important index in the unbalanced development of a continuous urban region since it indicates the uneven distribution of population and investment across cities. This study uses NPP-VIIRS NTL data and Landsat 8 OLT images to estimate HVRs at the district level. Additionally, this study tracks the spatial–temporal dynamics of HVR distributions in the Pearl River Delta (PRD) region. The comparison between the sampled HVRs and estimated HVRs verifies the effectiveness of the estimated HVRs in identifying dynamic changes in HVRs. This study has found that although overall decreasing HVRs are observed in the PRD, speculations and irrational real estate investment exist in cities on the west bank of the Pearl River Estuary and in some isolated districts in other cities. Furthermore, increasing proportions of vacant pixels in most cities indicate rising real estate development, requiring further supervision. This study suggests that more precise data and advanced techniques could help to improve the accuracy of the estimation techniques.