Understanding urban spatial pattern of land use is of great significance to urban land management and resource allocation. Urban space has strong heterogeneity, and thus there were many researches focusing on the identification of urban land use. The emergence of multiple new types of geospatial data provide an opportunity to investigate the methods of mapping essential urban land use. The popularization of street view images represented by Baidu Maps is benificial to the rapid acquisition of high-precision street view data, which has attracted the attention of scholars in the field of urban research. In this study, OpenStreetMap (OSM) was used to delineate parcels which were recognized as basic mapping units. A semantic segmentation of street view images was combined to enrich the multi-dimensional description of urban parcels, together with point of interest (POI), Sentinel-2A, and Luojia-1 nighttime light data. Furthermore, random forest (RF) was applied to determine the urban land use categories. The results show that street view elements are related to urban land use in the perspective of spatial distribution. It is reasonable and feasible to describe urban parcels according to the characteristics of street view elements. Due to the participation of street view, the overall accuracy reaches 79.13%. The contribution of street view features to the optimal classification model reached 20.6%, which is more stable than POI features.

Given the situation of urban expansion and environmental deterioration, the government and researchers are paying considerable attention to ventilation corridors. The construction of urban ventilation corridors requires quantitative data support. Computational fluid dynamics (CFD) has advantages in the fine assessment of wind environment, and a geographic information system (GIS) has excellent performance in spatial analysis. With Changchun City used as an example, this study proposes the establishment of ventilation corridors on an urban scale to mitigate the urban-heat-island effect, and to accelerate the diffusion of air pollution. CFD simulations provided detailed spatiotemporal characteristics of wind speed and wind direction at various heights. These simulations were useful for identifying potential ventilation corridors. In general, the wind-speed and wind-direction characteristics at a height of 30 m clearly indicated potential ventilation corridors. Potential paths existed in the leading wind and south–north directions. The areas that required improvement were favorably situated in the path of potential ventilation corridors. The main roads, green spaces, and water had good connectivity. A total of five ventilation corridors were constructed, and they will directly affect the poor urban thermal environment, and enhance the mobility of air.

An urban fringe area, depicted as a typical ecotone, is a region where both social and environmental problems are concentrated. Identifying and evaluating the spatial–temporal characteristics of urban fringe areas is significant for future development. On the basis of the land use data extracted from remote sensing data, the Shannon diversity index (SHDI) of each unit can be calculated, and identifying the urban fringe area by the breakpoint method is reliable. By using the rapidly growing Changchun as example, this study identifies the urban fringe of Changchun in 1995, 2005, and 2015 by applying the breakpoint method. The expansion amount, change mode, direction of expansion, landscape, and influence factors are evaluated. Policy and planning are the main factors influencing the development direction of the Changchun fringe area. The urban fringe area of Changchun City is extended to the east, southeast, and north. From 1995 to 2005, the outlying expansion was the dominant type. The main change mode was the infilling type due to the reduction of available land, from 2005 to 2015. In accordance with the landscape metrics, the landscape within the urban fringe transformed from fragmentation to regularization. The development of the urban fringe also transformed from a disorderly to an orderly manner.

The urban functional area is critical to an understanding of the complex urban system, resource allocation, and management. However, due to urban surveys’ focus on geographic objects and the mixture of urban space, it is difficult to obtain such information. The function of a place is determined by the activities that take place there. This study employed mobile phone signaling data to extract temporal features of human activities through discrete Fourier transform (DFT). Combined with the features extracted from the point of interest (POI) data and Sentinel images, the urban functional areas of Changchun City were identified using a random forest (RF) model. The results indicate that integrating features derived from remote sensing and social sensing data can effectively improve the identification accuracy and that features derived from dynamic mobile phone signaling have a higher identification accuracy than those derived from POI data. The human activity characteristics on weekends are more distinguishable for different functional areas than those on weekdays. The identified urban functional layout of Changchun is consistent with the actual situation. The residential functional area has the highest proportion, accounting for 33.51%, and is mainly distributed in the central area, while the industrial functional area and green-space are distributed around.

Hyperspectral remote sensing is widely used to detect petroleum hydrocarbon pollution in soil monitoring. Different spectral pretreatment methods seriously affect the prediction and analysis of petroleum hydrocarbon contents (PHCs). This study adopted a combined spectral data preprocessing technique that improves the prediction accuracy of petroleum hydrocarbons in soil. We combined continuum removal and wavelet packet decomposition (CR–Daubechies 3 (db3)) to process the hyperspectral reflectance data of 26 soil samples in the oil production work area in China and judged the correlation between spectral reflectance and petroleum hydrocarbons in soil. Partial least squares regression was used to construct an optimal model for the inversion of PHCs in soil and the leave-one-out cross-validation was used to select the best factor number. The best model of soil petroleum hydrocarbon inversion was determined by comprehensively comparing the initial spectrum, db3 to high-frequency spectrum, db3 to low-frequency spectrum, after-continuum removal spectrum, CR-db3 to high-frequency spectrum, and CR-db3 to low-frequency spectrum comprehensively. The main contributions of this study are as follows: (1) three-layer decomposition with CR-db3 can improve the correlation between spectral reflectance and PHCs and effectively improve the sensitivity of the spectrum to PHCs; (2) the prediction accuracy of the high-frequency spectrum of wavelet packet decomposition for PHCs in soil is higher than that of low-frequency information; (3) the proposed petroleum hydrocarbon prediction model based on CR-db3 processed spectra to obtain high-frequency information is optimal (coefficient of determination = 0.977, root mean square error of calibration = 3.078, root mean square error of cross-validation = 4.727, root mean square error of prediction = 4.498, ratio of performance to deviation = 6.12).

An urban agglomeration is a growth pole of regional development. However, the land uses have changed significantly due to the impacts of intense human activities. Analyzing the overall change characteristics of land use and hotspots has direct reference value for the formulation and implementation of land use management measures. This study used a complex network of analysis methods and a cluster and outlier analysis to study the land use changes and hotspots in the Harbin–Changchun urban agglomeration (HCUA). The results showed that farmland exhibited a high weighted degree of centrality, indicating that it is the key land type in the HCUA land use change network. From 1990 to 2000, the land use change in each city mainly manifested as the loss of ecological land, whereas from 2000 to 2010 it manifested as the restoration of ecological land. From 1990 to 2020, the average path length of the network in 11 cities was less than 1.4, which was reduced in 10 cities, indicating that the stability weakened and land use change more likely occurred. Specifically, the area of ecological land reduction hotspots gradually decreased from 15,237.81 km² to 11,533.95 km². In the ecological land concentration area, the change hotspots for ecological land use and ecological function had strong consistency. The distribution and changes of hotspots were affected by policies and the terrain. The increase in ecological land around urban built-up areas, however, did not improve the landscape connectivity. Therefore, in the planning of ecological land use, attention should be paid to the landscape pattern.