The relationship between the land cover (LC) characteristics and the land surface temperature (LST) is significant for surface urban heat island (SUHI) study and for sustainability research. To better understand how the land surface temperature (LST) responds to LC, two urban areas, Vienna and Madrid, with different climatic conditions are selected and compared, using Landsat-8 OLI data and urban atlas data. To determine a suitable scale for analyzing the relationship between LC and LST, a correlation analysis at different sizes of spatial analytical scales is applied. To demonstrate the LC composition effects on LST, a regression analysis of the whole study area and in the specific circumstance is undertaken. The results show that: (1) In the summer, Vienna presents high temperature in the urban areas and low temperature in the surrounding rural areas, while Madrid displays the opposite appearance, being relatively cooler in the urban areas as compared to the rural areas, with the main different factors affecting elevated urban LST; (2) Suitable analytical scales are suggested in studying the LC–LST relationship between different LC characteristics in the two study areas; (3) Negative effects on the LST appear when the area of cooling sources, such as water or urban greenery, reaches 10% at a 990 × 990 m² scale in Vienna. Built-up area is the main factor affecting elevated urban LST where such areas cover the majority at a 990 × 990 m² scale in Madrid. These findings provide a valuable view regarding how to balance the urban surface thermal environment through urban planning.

Quarry sites result from human activity, which includes the removal of original vegetation and the overlying soil to dig out stones for building use. Therefore, the dynamics of the quarry area provide a unique view of human mining activities. Actually, the topographic changes caused by mining activities are also a result of the development of the local economy. Thus, monitoring the quarry area can provide information about the policies of the economy and environmental protection. In this paper, we developed a combined method of machine learning classification and quarry region analysis to estimate the quarry area in a quarry region near Beijing. A temporal smoothing based on the classification results of all years was applied in post-processing to remove outliers and obtain gently changing sequences along the monitoring term. The method was applied to Landsat images to derive a quarry distribution map and quarry area time series from 1984 to 2017, revealing significant inter-annual variability. The time series revealed a five-stage development of the quarry area with different growth patterns. As the study region lies on two jurisdictions—Tianjin and Hebei—a comparison of the quarry area changes in the two jurisdictions was applied, which revealed that the different policies in the two regions could impose different impacts on the development of a quarry area. An analysis concerning the relationship between quarry area and gross regional product (GRP) was performed to explore the potential application on socioeconomic studies, and we found a strong positive correlation between quarry area and GRP in Langfang City, Hebei Province. These results demonstrate the potential benefit of annual monitoring over the long-term for socioeconomic studies, which can be used for mining decision making.

Ice storms greatly affect the structure, dynamics, and functioning of forest ecosystems. Studies on the impact of such disasters, as well as the post-disaster recovery of forests, are important contents in forest biology, ecology, and geography. Remote-sensing technology provides data and methods that can support the study of disasters at the large-to-medium scale and over long time periods. This study took Chebaling National Nature Reserve in Guangdong Province, China, as the study area. First, field-survey data and remote-sensing data were comprehensively analyzed to demonstrate the feasibility of replacing the forest stock volume with the mean annual value of the Enhanced Vegetation Index (EVI), to study forest growth and change. We then used the EVI from 2007 to 2017, together with a variety of other remote-sensing and forest sub-compartment data, to analyze the impact of the 2008 ice storm and the subsequent post-disaster recovery of the forest. Finally, we drew the following conclusions: (1) Topography had a considerable effect on disaster impact and forest recovery in Chebaling. The forest at high altitudes (700–1000 m) and on steep slopes (25–40°) was seriously affected by this disaster but had a stronger post-disaster recovery ability. Meanwhile, the hardest-hit area for coniferous forest was higher and steeper than that for broad-leaved forest. (2) In the same terrain conditions, coniferous forests were less affected by the disaster than broad-leaved forests and showed less variation during the post-disaster recovery process. Nevertheless, broad-leaved forests had faster recovery rates and higher recovery degrees; (3) Under the influence of human activities, the recovery and fluctuation degree for planted forest in the post-disaster recovery process was significantly higher than that for natural forest. The study suggests that forest has high disaster resistance and self-recovery ability after the ice storm, and this ability has a strong correlation with the type of forest and the topographic factors such as elevation and slope. At the same time, human intervention can speed up the recovery of forests after disasters.

Clouds play an important role in the energy and moisture cycle of the earth–atmosphere system, which affects many important processes in nature and human societies. However, there are very few fine-grained and high-precision global cloud climatology data available for high-resolution models. In this paper, we produced a fine-grained (1 km resolution) global land cloud climatology (GLHCC) report based on MOD09 cloud masks from 2001 to 2016, with a temporal resolution of 10 days. The two improvements (short-wave infrared and Band 2/6 ratio threshold method) on the original MOD09 cloud mask have reduced the snow, ice, and bright areas mistakenly classified as clouds. The preliminary cloud products undergo the removal of orbital artifacts by Variational Stationary Noise Remover (VSNR) and the removal of abnormal albedo areas to generate the final cloud climatology data. The new product was directly validated by ground-based cloud observations collected from 3777 global weather stations. PATMOS-X from the Advanced Very High Resolution Radiometer (AVHRR) and MOD/MYD35 served as comparison products for consistency check of GLHCC. The assessment results show that GLHCC demonstrated a strong correlation with ground station observations, MOD/MYD35, and PATMOS-X. When the ground observations were taken as the truth value, GLHCC and MOD/MYD35 displayed higher accuracy than PATMOS-X. In most selected interested areas where the three behave differently, GLHCC matched the facts better than MOD/MYD35 and PATMOS-X. The GLHCC can well represent the cloud distribution over the past 16 years and will play an important role in the fine-grained demands of many aspects of nature and human society.

Polynyas are an important factor in the Antarctic and Arctic climate, and their changes are related to the ecosystems in the polar regions. The phenomenon of polynyas is influenced by the combination of inherent persistence and dynamic factors. The dynamics of polynyas are greatly affected by temporal dynamical factors, and it is difficult to objectively reflect the internal characteristics of their formation. Separating the two factors effectively is necessary in order to explore their essence. The Special Sensor Microwave/Imager (SSM/I) passive microwave sensor has been making observations of Antarctica for more than 20 years, but it is difficult for existing current sea ice concentration (SIC) products to objectively reflect how the inherent persistence factors affect the formation of polynyas. In this paper, we proposed a long-term multiple spatial smoothing method to remove the influence of dynamic factors and obtain stable annual SIC products. A halo located on the border of areas of low and high ice concentration around the Antarctic coast, which has a strong similarity with the local seabed in outline, was found using the spatially smoothed SIC products and seabed. The relationship of the polynya location to the wind and topography is a long-understood relationship; here, we quantify that where there is an abrupt slope and wind transitions, new polynyas are best generated. A combination of image expansion and threshold segmentation was used to extract the extent of sea ice and coastal polynyas. The adjusted record of changes in the extent of coastal polynyas and sea ice in the Southern Ocean indicate that there is a negative correlation between them.

Water-energy dynamics broadly regulate species richness gradients but are being altered by climate change and anthropogenic activities; however, the current methods used to quantify this phenomenon overlook the non-linear dynamics of climatic time-series data. To analyze the gradient of species richness in China using water-energy dynamics, this study used linear regression to examine how species richness is related to (1) the long-term mean of evapotranspiration (ET) and potential evapotranspiration (PET) and (2) the temporal stability of ET and PET. ET and PET were used to represent the water-energy dynamics of the terrestrial area. Changes in water-energy dynamics over the 14-year period (2000 to 2013) were also analyzed. The long-term mean of ET was strong and positively ( $R^2\in \left(0.40~0.67\right),p<0.05$ ) correlated with the species richness gradients. Regions in which changes in land cover have occurred over the 14-year period (2000 to 2013) were detected from long-term trends. The high level of species richness in all groups (birds, mammals, and amphibians) was associated with relatively high ET, determinism (i.e., predictability), and entropy (i.e., complexity). ET, rather than PET or temporal stability measures, was an effective proxy of species richness in regions of China that had moderate energy (PET > 1000 mm/year), especially for amphibians. In addition, predictions of species richness were improved by incorporating information on the temporal stability of ET with long-term means. Amphibians are more sensitive to the long-term ET mean than other groups due to their unique physiological requirements and evolutionary processes. Our results confirmed that ET and PET were strongly and significantly correlated with climatic and anthropogenic induced changes, providing useful information for conservation planning. Therefore, climate management based on changes to water-energy dynamics via land management practices, including reforestation, should be considered when planning methods to conserve natural resources to protect biodiversity.