Global increasing carbon emissions have triggered a series of environmental problems and greatly affected the production and living of human beings. This study estimated carbon emissions from land use change in the Beijing-Tianjin-Hebei region during 1990–2020 with the carbon emission model and explored major influencing factors of carbon emissions with the Logarithmic Mean Divisia Index (LMDI) model. The results suggested that the cropland decreased most significantly, while the built-up area increased significantly due to accelerated urbanization. The total carbon emissions in the study area increased remarkably from 112.86 million tons in 1990 to 525.30 million tons in 2020, and the built-up area was the main carbon source, of which the carbon emissions increased by 370.37%. Forest land accounted for 83.58–89.56% of the total carbon absorption but still failed to offset the carbon emission of the built-up area. Carbon emissions were influenced by various factors, and the results of this study suggested that the gross domestic product (GDP) per capita contributed most to the increase of carbon emissions in the study area, resulting in a cumulative increase of carbon emissions by 9.48 million tons, followed by the land use structure, carbon emission intensity per unit of land, and population size. By contrast, the land use intensity per unit of GDP had a restraining effect on carbon emissions, making the cumulative carbon emissions decrease by 103.26 million tons. This study accurately revealed the variation of net carbon emissions from land use change and the effects of influencing factors of carbon emissions from land use change in the Beijing-Tianjin-Hebei region, which can provide a firm scientific basis for improving the regional land use planning and for promoting the low-carbon economic development of the Beijing-Tianjin-Hebei region.

Escalating urban issues in Beijing call for comprehensive exploration of urban construction land expansion towards the goal of carbon neutrality. Firstly, urban construction land in Beijing during the period 2005–2020 was accurately detected using Landsat images and impervious surface data, and then its expansion characteristics were revealed. Finally, the driving mechanism of urban construction land expansion was explored using geographically and temporally weighted regression from the input–output perspective. The results showed that the expansion speed and intensity of urban construction land in Beijing showed an overall tendency to slow down, and the center of urban expansion shifted to the new urban development zone and ecological function conservation zone. Urban construction land expansion in the central urban area was first scattered and then compact, while that in the new urban development zone and ecological function conservation zone primarily followed an outward pattern. The permanent population, per capita GDP, and per capita retail sales of social consumer goods were the primary driving factors of urban construction land expansion in Beijing, the impacts of which varied significantly among different districts of Beijing. All these results can provide a solid foundation for improving land use policies towards the goal of carbon neutrality in highly urbanized areas.

Exploring the thermal environment effects of built-up land expansion can lay a firm foundation for urban planning and design. This study revealed the spatiotemporal dynamic characteristics of built-up land and heat island center points in Shijiazhuang using land-use/land-cover data and land surface temperature (LST) products from 1996 to 2019, and the response mechanism between the percentage of built-up land (PLAND) and LST with the grid sampling method and statistical analysis. Results indicated that heat islands are mainly clustered in the downtown, built-up areas of counties and the Hutuo River Basin. The spatiotemporal shift direction of the center point of the urban heat island (UHI) and built-up land in the whole study area varied due to the eco-environmental transformation of the Hutuo River Basin. In areas far from the Hutuo River Basin, the center points of UHI and built-up land were shifted in a similar direction. There is a remarkable linear correlation between the PLAND and LST, the correlation coefficient of which was higher than 0.7 during the study period. Areas with PLAND > 60% are urban regions with stronger heat island effects, and areas with PLAND < 55% are villages and towns where the temperature raised more slowly.

Carbon sink enhancement is of great significance to achieving carbon peak and carbon neutrality. This study firstly estimated the carbon sink in the Beijing–Tianjin–Hebei Region using the carbon absorption coefficient method. Then, this study explored the differentiation of carbon sink enhancement potential with a carbon sink–economic carrying capacity index matrix based on carbon sink carrying capacity and economic carrying capacity under the baseline scenario and target scenario of land use. The results suggested there was a remarkable differentiation in total carbon sink in the study area, reaching 2,056,400 and 1,528,300 tons in Chengde and Zhangjiakou and being below 500,000 tons in Langfang and Hengshui, while carbon sink per unit land area reached 0.66 ton/ha in Qinhuangdao and only 0.28 t/ha in Tianjin under the baseline scenario. Increasing area and optimizing spatial distribution of arable land, garden land, and forest, which made the greatest contribution to total carbon sinks, is an important way of enhancing regional carbon sinks. A hypothetical benchmark city can be constructed according to Qinhuangdao and Beijing, in comparison with which there is potential for carbon sink enhancement by improving carbon sink capacity in Beijing, promoting economic carrying capacity in Qinhuangdao, and improving both in the other cities in the study area.

Ecological compensation provides innovative ecological solutions for addressing land degradation and guaranteeing the sustainable provision of essential ecosystem services. This study estimated the ecosystem service value and the opportunity cost of land use in the Poverty Belt of China—around Beijing and Tianjin—from 1980 to 2015 on the small watershed scale, and thereafter estimated the rational range of ecological compensation in this ecologically fragile zone. Results showed that the total ecosystem service value in the study area gradually decreased from CNY 54.198 billion in 1980 to CNY 53.912 billion in 2015. Moreover, the annual total ecological compensation of the whole study area ranged between CNY 2.67 billion and 2.83 billion. More specifically, areas with higher ecological compensation standards are mainly concentrated in the northwestern and northern parts of the study area, with a lower economic development level, while areas with lower ecological compensation standards are mainly located in areas with a relatively high level of economic development, e.g., the southern and southeastern parts of the study area. These results can provide valuable decision-support information for the design and optimization of ecological compensation to address land degradation along with rapid urbanization in the Beijing–Tianjin–Hebei region.

Based on a linear spectral mixture model and multiple endmember spectral mixture analysis, using daily advanced very-high-resolution radiometer (AVHRR/2) data of the Qinghai–Tibet Plateau, a subpixel snow mapping algorithm was proposed in this paper, for prolonging the historical time series of the fractional snow cover data to 40 years. In particular, the normalized difference vegetation index (NDVI), and channels 1 and 2 of AVHRR/2 data were used to automatically select the end-members directly, from a certain AVHRR/2 image. A look-up table of sample spectra of mixed pixels and their respective snow cover percentages was introduced for one AVHRR/2 image. According to the established look-up tables, the fractional snow cover of each mixed pixel can then be extracted from the AVHRR/2 images. Before the subpixel snow mapping, the cloud pollution of the AVHRR/2 images was mitigated, with both the thick and thin clouds almost removed from the AVHRR/2 images. It turns out that the processing speed of the subpixel snow mapping is three times faster than the process not using the look-up table. The mapping algorithm was validated against the snow-covered area from Thematic Mapper (TM) data, with the root-mean-square errors (RMSEs) well below 0.12. Results show that the proposed algorithm for subpixel snow mapping is both effective and efficient, especially in such a mountainous region as the Qinghai–Tibet Plateau.