The main goal of this study is to produce a landslide susceptibility map in the Wanzhou section of the Three Gorges reservoir area (China) with a weighted gradient boosting decision tree (weighted GBDT) model. According to the current research on landslide susceptibility mapping (LSM), the GBDT method is rarely used in LSM. Furthermore, previous studies have rarely considered the imbalance of landslide samples and simply regarded the LSM problem as a binary classification problem. In this paper, we considered LSM as an imbalanced learning problem and obtained a better predictive model using the weighted GBDT method. The innovations of the article mainly include the following two points: introducing the GBDT model into the evaluation of landslide susceptibility; using the weighted GBDT method to deal with the problem of landslide sample imbalance. The logistic regression (LR) model and gradient boosting decision tree (GBDT) model were also used in the study to compare with the weighted GBDT model. Five kinds of data from different data source were used in the study: geology, topography, hydrology, land cover, and triggered factors (rainfall, earthquake, land use, etc.). Twenty nine environmental parameters and 233 landslides were used as input data. The receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC) value, and the recall value were used to estimate the quality of the weighted GBDT model, the GBDT model, and the LR model. The results showed that the GBDT model and the weighted GBDT model had a higher AUC value (0.977, 0.976) than the LR model (0.845); the weighted GBDT model had a little higher AUC value (0.977) than the GBDT model (0.976); and the weighted GBDT model had a higher recall value (0.823) than the GBDT model (0.426) and the LR model (0.004). The weighted GBDT method could be considered to have the best performance considering the AUC value and the recall value in landslide susceptibility mapping dealing with imbalanced landslide data.

Urban growth and development can be interpreted as a combined process of “urban spillover” and “local urban sprawl”, from overall urban–rural development to urban–rural integration (URI). The process of suburban development in western China is a complex system, which reflects the characteristics of industrialization and urbanization in western China. Chengdu is the most representative of the big cities for economic and social structure change in western China. To analyze the changes on URI degree based on the built-up land change, and to explore the practical URI paths in both the suburbs and exurbs of Chengdu, we use land-use remote-sensing monitoring data from 2000, 2005, 2010, and 2015 in this paper, whereafter URI indexes are built from space, economy, and society. The land-use change of the suburbs and exurbs of Chengdu from 2000 to 2015 are analyzed by ArcGIS. Results indicate that the biggest growth part of built-up land is other built-up land, followed by commercial/industrial land, and the last is residential land. The built-up land spreads quickly from 2000 to 2005, and shows distinct separation characteristics in the suburbs of Chengdu. It is relatively slow in the exurbs. Moreover, built-up land connects better in the suburbs than in the exurbs. Based on the change of built-up land in Chengdu from 2000 to 2015, spatial integration data are calculated, economic integration and social integration data are chosen from statistics, and the change of URI levels in the suburbs and exurbs of Chengdu is calculated. The results show that first, economic integration and social integration have great influence on URI, and their effects are increasing. The significance of spatial integration in URI has gradually reduced. Second, URI levels in counties of the suburbs and exurbs of Chengdu rose from 2000 to 2015, more highly in the suburbs than in the exurbs. URI in counties of the exurbs showed a marked difference. URI in the southeast counties of the exurbs is generally high. The foundation of URI is weaker in the counties and districts in the southwest counties of the exurbs in Chengdu, but it is growing steadily in URI, and the northern counties in the exurbs of Chengdu are in the process of rapid URI. The paths of URI in the suburbs and exurbs in Chengdu can be roughly divided into an industry-developing model in the suburbs, service-industry-developing model in the suburbs, agriculture-developing model in the exurbs, service-industry-developing model in the exurbs and infrastructure-developing model in the exurbs.

Water Resource Sustainability Management plays a vitally important role in ensuring sustainable development, especially in water-stressed arid regions throughout the world. In order to achieve sustainable development, it is necessary to study and monitor the water quality in the arid region of Central Asia, an area that is increasingly affected by climate change. In recent decades, the rapid deterioration of water quality in the Ebinur Lake basin in Xinjiang (China) has severely threatened sustainable economic development. This study selected the Ebinur Lake basin as the study target, with the purpose of revealing the response between the water quality index and water body reflectivity, and to describe the relationship between the water quality index and water reflectivity. The methodology employed remote sensing techniques that establish a water quality index monitoring model to monitor water quality. The results of our study include: (1) the Water Quality Index (WQI) that was used to evaluate the water environment in Ebinur Lake indicates a lower water quality of Ebinur Lake, with a WQI value as high as 4000; (2) an introduction of the spectral derivative method that realizes the extraction of spectral information from a water body to better mine the information of spectral data through remote sensing, and the results also prove that the spectral derivative method can improve the relationship between the water body spectral and WQI, whereby R² is 0.6 at the most sensitive wavelengths; (3) the correlation between the spectral sensitivity index and WQI was greater than 0.6 at the significance level of 0.01 when multi-source spectral data were integrated with the spectral index (DI, RI and NDI) and fluorescence baseline; and (4) the distribution map of WQI in Ebinur Lake was obtained by the optimal model, which was constructed based on the third derivative data of Sentinel 2 data. We concluded that the water quality in the northwest of Ebinur Lake was the lowest in the region. In conclusion, we found that remote sensing techniques were highly effective and laid a foundation for water quality detection in arid areas.

Keywords: Spectral Clustering, Trajectory data, Spatiotemporal Clustering, DTW, Multi-Thread, Urban Computing Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral clustering lacks the temporal expansion on the algorithm and limited in its applicability to large-scale problems due to its high computational complexity. This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions to make the algorithm more effective and efficient, the performance is proved due to the experiment carried out on the massive taxi trajectory dataset in Wuhan city, China.

Keywords: Urban growth, Land use change, Flow matrix, Instability, Belt and Road It has long recognized that there exists three different terrain belt in China, i.e. east, central, and west can have very different impacts on the land use changes. It is therefore better understand how spatiotemporal patterns linked with processes and instability of land use change are evolving in China across different regions. This paper compares trends of the similarities and differences to understand the spatiotemporal characteristics and the linked processes i.e. states, incidents and instability of land use change of 5 Chinese cities which are located in the nodes of The Silk Road in China. The results show that on the whole, the more land transfer times and the more land categories involved changes happens in Quanzhou City, one of eastern China than those in central and western China. Basically, cities in central and western China such as Changsha, Kunming and Urumuqi City become instable while eastern city like Quanzhou City turns to be stable over time.