Accurate and effective mapping of forest aboveground biomass (AGB) in heterogeneous mountainous regions is a huge challenge but an urgent demand for resource managements and carbon storage monitoring. Conventional studies have related the plot-measured or LiDAR-based biomass to remote sensing data using pixel-based approaches. The object-based relationship between AGB and multi-source data from LiDAR, multi-frequency radar, and optical sensors were insufficiently studied. It deserves the further exploration that maps forest AGB using the object-based approach and combines LiDAR data with multi-sensor images, which has the smaller uncertainty of positional discrepancy and local heterogeneity, in heterogeneous mountainous regions. To address the improvement of mapping accuracy, satellite LiDAR data from GEDI and ICEsat-2, and images of ALOS-2 yearly mosaic L band SAR (Synthetic Aperture Radar), Sentinel-1 C band SAR, Sentinel-2 MSI, and ALOS-1 DSM were combined for pixel- and object-based forest AGB mapping in a vital heterogeneous mountainous forest. For the object-based approach, optimized objects during a multiresolution segmentation were acquired by the ESP (Estimation of the Scale Parameter) tool, and suitable predictors were selected using an algorithm named VSURF (Variable Selection Using Random Forests). The LiDAR variables at the footprint-level were extracted to connect field plots to the multi-sensor objects as a linear bridge. It was shown that forests’ AGB values varied by elevations with a mean value of 142.58 Mg/ha, ranging from 12.61 to 514.28 Mg/ha. The north slope with the lowest elevation (<1100 m) had the largest mean AGB, while the smallest mean AGB was located in the south slope with the altitude above 2000 m. Using independent validation samples, it was indicated by the accuracy comparison that the object-based approach performed better on the precision with relative improvement based on root-mean-square errors (RI_RMSE) of 4.46%. The object-based approach also selected more optimized predictors and markedly decreased the prediction time than the pixel-based analysis. Canopy cover and height explained forest AGB with their effects on biomass varying according to the elevation. The elevation from DSM and variables involved in red-edge bands from MSI were the most contributive predictors in heterogeneous temperate forests. This study is a pioneering exploration of object-based AGB mapping by combining satellite data from LiDAR, MSI, and SAR, which offers an improved methodology for regional carbon mapping in the heterogeneous mountainous forests.

Urban green spaces (UGSs) provide important support for the health of urban residents and the realization of sustainable urban development. However, the spatiotemporal pattern of urban resident exposure to UGSs in cities is unclear, especially at the national scale in China. Based on the annual 30 m resolution Normalized Difference Vegetation Index (NDVI) data of the Landsat satellite, we quantitatively analyzed the change in UGS coverage from 2000 to 2020 for 320 cities in China and combined it with population data to understand the changing patterns of urban population exposure to different UGS coverage. The results indicated that the average UGS coverage decreased from 63% to 44% from 2000 to 2020 in China, which could be divided into two stages: a rapid decline phase (2000–2014) and a progressive decline phase (2015–2020). Geographically, UGS coverage declined faster in southwestern and eastern cities than in other regions, particularly in medium-sized cities. We also found that urban pixel-based areas in cities with the highest UGS coverage (80–100%) decreased rapidly, and the proportion of the urban population exposed to the highest UGS coverage also declined significantly from 2000 to 2020. Urban pixel-based areas with low UGS coverage (20–40%) continued to expand, and there was a rapid increase in the proportion of the urban population exposed to low UGS coverage, with an increase of 146 million people from 2000 to 2020. The expansion of impervious surfaces had the most significant effect on the change in UGS coverage during different periods (2000–2020, 2000–2014, and 2015–2020). Natural factors such as precipitation, surface maximum temperature, and soil moisture also affected UGS coverage change. These findings provide insights into the impact of urbanization on the natural environment of cities, availability of UGS for residents, and sustainable urban development under rapid urbanization.

Atmospheric pollution caused by fine particulate matter (PM_2.5) seriously damages human health. Urban forests have the ecological function of purifying the atmosphere, which can effectively reduce the ambient PM_2.5 concentration. This paper analyzed the ability of different forest types to mitigate PM_2.5 pollution and explored the effects of forest quality and morphological parameters on PM_2.5 concentration on the forest patch level. The results concluded that the PM_2.5 concentration of the Landscape and Relaxation Forest (LF) was significantly lower than that of the Roadside Forest (RF) and Affiliated Forest (AF) due to the environmental quality of their location. The effective distance of LF on PM_2.5 reduction was 80 m, which was significantly higher than RF and AF. The Normalized Difference Vegetation Index (NDVI), which indicated forest growth status, was the most effective parameter for improving the urban forest PM_2.5 mitigation ability. The concentration of PM_2.5 decreased linearly with the increase in NDVI. The area and perimeter of the forest patches had a significant nonlinear negative correlation with PM_2.5 concentration. In addition, the more irregular the shape of the forest patch, the lower the PM_2.5 concentration of the forest. Moreover, the simpler shape of RF and AF helped to alleviate PM_2.5 pollution. The round shape of AF more efficiently reduced PM_2.5 concentration. Our study demonstrated that the surrounding environment, forest growth status, and patch forms determined the PM_2.5 reduction capacity of an urban forest. The corresponding management and adjustment methods should be implemented in future urban forest management.

Understanding of the relationship between structural and diversity attributes and biomass is important for plant biodiversity conservation, ecosystem service function enhancement and sustainable development of urban forest ecosystems. In this study, road forest (RF), attached forest (AF) and landscape and relaxation forest (LF) were selected as research objects. We systematically evaluated the diversity attributes and above ground biomass (AGB) at two dimensions of different diameter at breast height (DBH) grades and different tree height grades of urban forests in Changchun, Northeast China. Structural equation modeling (SEM) analyses of the correlation between structure attributes, diversity attributes and biomass among different types of urban forests were carried out. The results showed that species richness (SR) and Shannon–Wiener index (H′) of shrubs were lower than those of trees. Under the DBH grades, H′ in each forest type was highest in the 0–10 m grades and SR was highest in the 10–20 m grades. Under tree height grades, both H′ and SR of each type were at the top of the list. AGB was highest in each forest type under 5–10 m height grades. The relationship between AGB and H′ was better in LF, but with no significant relationships in the other forest types. SEM highlighted that in the overall aspect, the effect of forest type on biomass was mediated by structure and diversity attributes. Particularly in LF, there were direct and indirect effects between structure attributes and biomass mediated by diversity attributes. The improvement of the H′, evenness index (J′) and SR could enhance urban forest services, especially for the biomass and diversity of LF.

As a symbol of urban civilization and history, old and notable trees (ONTs) are facing challenges brought by rapid urbanization. Changchun is the fastest growing city in Northeast China, and throughout its development process of over 100 years it has preserved many ONTs. This study investigated all the ONTs in Changchun, and analyzed the species diversity, spatial distribution characteristics, dimension, age, and health status of trees by using ecological index and mathematical statistics, and trying to find out the underlying factors regulating their distribution. The results showed that there were 773 old trees belonging to 25 species and 2 notable trees from 1 species in Changchun. Pyrus ussuriensis was the dominant species, followed by Salix matsudana and Ulmus pumila. The urban area, population density, greening rate, and construction history did not influence the species and quantity of ONTs, while the types of land use and tree protection planning were important factors affecting the richness, diversity, and growth conditions of trees. To explore the potential reasons for their existence, the ONTs’ data in Changchun was compared with two nearby cities—Harbin and Shenyang. The comparison indicated that the geographical location and climatic conditions also controlled the distribution of ONTs. The number and dimensions of trees were driven by the history and development process of the city. Our findings suggested that preserving favorable living environments and maintaining a low intensity of human disturbance are critical factors for the survival of ONTs in cities.

Species diversity plays an important role in urban ecosystem stability and sustainability. Research on woody plant diversity among different administrative districts is vital to effectively improving urban biodiversity. In this study, a stratified random sampling method was used to set the sample plot, a spatial mapping of the diversity indices was conducted, and methods of principal component analysis and similarity analysis were used to analyze the species composition and dissimilarity among different administration districts. Finally, the model based on the relationship between the diversity indices and forest landscape pattern indices was built. The results showed that woody plant species diversity differed significantly among different administrative districts in Changchun. The species diversity levels in the Qikai (QK), Lvyuan (LY), and Kuancheng (KC) districts were higher, and those in the Nanguan (NG) and Erdao (ED) districts were lower. The species composition of every district basically complied with the 10/20/30 “rule of thumb”. The most common species, genera, and families in urban forests should not exceed the proportion of the total abundance of all species. There was a significant correlation between the diversity indices and the forest landscape indices of each district. The Margalef index (d_Ma) and the Shannon–Wiener index (H′) decreased significantly while CONTIG-MN increased, and increased significantly while LSI increased. Species evenness index J decreased significantly while LPI increased, and increased significantly while DIVISION increased. In future tree species selection, native tree species should be given priority as much as possible, the planting of Salicaceae should be reduced, and the species diversity of each district should be increased. Chaoyang (CY), ED, and LY districts should strengthen the links between forest patches.