ABSTRACT
To better understand the habitat preferences and behavioural ecology of Sparus latus, we performed an experiment using box-shaped reefs as habitat enrichment materials, allowing us to determine the behavioural strategies and drivers involved in the response to different enrichment structures. The results showed that the first contact time of S. latus was negatively correlated (Pearson's correlation, p < 0.005) with the distribution rate in the artificial reef area. Enrichment structures affected the habitat preferences of S. latus, and there was a significant difference in the average distribution rate between the control and treatment groups (Adonis, p < 0.001). The opening ratio (Adonis, R2 = 0.36) explained the distribution difference of S. latus better than the opening shape (Adonis, R2 = 0.12). In the absence of an enrichment structure, S. latus remained more active during the daytime, exhibiting poor clustering, while in the presence of an enrichment structure, S. latus exhibited clustered movement at night. The opening ratio was negatively correlated with the average interindividual distance (Spearman's correlation, p < 0.01) and showed a significant positive correlation with the average distribution rate in the reef area (Spearman's correlation, p < 0.001), indicating that the reef opening ratio significantly affected the reef-tropism and clustering behaviours of S. latus. The light intensity was negatively correlated with the average distance moved, and the average speed (Spearman's correlation, p < 0.05) was significantly positively correlated with the reef first contact time (Spearman's correlation, p < 0.001), indicating that the light intensity affected the exploration and activity patterns of S. latus. These results provide a research basis for analysing the pattern and process of fish proliferation induced by artificial reef habitats.
ABSTRACT
Peshawar is one of the most densely populated cities of Pakistan with high urbanization rate. The city overexploits groundwater resources for household and commercial usage which has caused land subsidence. Land subsidence has long been an issue in Peshawar due to insufficient groundwater removal. In this research, we employ the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique with Sentinel-1 imaging data to observe the yearly land subsidence and generate accumulative time-series maps for the years (2018 to 2020) using the SAR PROcessing tool (SARPROZ). The PS-InSAR findings from two contiguous paths are combined by considering the variance over the overlapping area. The subsidence rates in the Peshawar are from -59 to 17 mm/yr. The results show that subsidence is -28.48 mm/yr in 2018, the subsidence reached -49.02 mm/yr in 2019, while in 2020, the subsidence reached -49.90 mm/yr. The findings indicate a notable rise in land subsidence between the years 2018 and 2020. Subsidence is predicted in the research region primarily due to excessive groundwater removal and soil consolidation induced by surficial loads. The correlation of land subsidence observations with groundwater levels and precipitation data revealed some relationships. Overall, the proposed method efficiently monitors, maps, and detects subsidence-prone areas. The utilization of land subsidence maps will enhance the efficiency of urban planning, construction of surface infrastructure, and the management of risks associated with subsidence.
Subject(s)
Groundwater , Radar , Pakistan , Environmental Monitoring/methods , InterferometryABSTRACT
The Crested Ibis (Nipponia nippon) is an endangered animal with an extremely high ecological, humanistic, and scientific value. However, this species still faces survival challenges, due to rapidly shrinking foraging grounds, the serious interference of human behavior, and increased habitat requirements. Geographical environment is a significant factor affecting Crested Ibis behavior-pattern analysis and habitat protection. The spatial and temporal trajectory contains habitat location and period information, a vital record of the Crested Ibis' habits, and the basis of all research. Nevertheless, there are only a handful of studies on the missing trajectory data and fusing multiple sources of environmental data-research methods. We studied the spatial and temporal habitat use of the tracked Crested lbis by fusing multiple data-sources in China. This paper adopts the LSTM (long short-term memory) model to supplement the missing trajectory data and perform cluster mining; and a random forest model is used to predict the habitat of the Crested Ibis with high fitting accuracy (R2 = 84.9%). The results show that the Crested Ibis distribution-pattern is characterized by high altitude and proximity to woodland and rivers. Additionally, the habitat dependence on the village implicates human agricultural activities in positively impacting its reproduction. This paper provides a complete method for analyzing Crested Ibis' spatial and temporal trajectory by fusing multi-source data, which is crucial for protecting the survival and reproduction of the Crested Ibis.
ABSTRACT
Landslides are the most catastrophic geological hazard in hilly areas. The present work intends to identify landslide susceptibility along Karakorum Highway (KKH) in Northern Pakistan, using landslide susceptibility mapping (LSM). To compare and predict the connection between causative factors and landslides, the random forest (RF), extreme gradient boosting (XGBoost), k nearest neighbor (KNN) and naive Bayes (NB) models were used in this research. Interferometric synthetic aperture radar persistent scatterer interferometry (PS-InSAR) technology was used to explore the displacement movement of retrieved models. Initially, 332 landslide areas alongside the Karakorum Highway were found to generate the landslide inventory map using various data. The landslides were categorized into two sections for validation and training, of 30% and 70%. For susceptibility mapping, thirteen landslide-condition factors were created. The area under curve (AUC) of the receiver operating characteristic (ROC) curve technique was utilized for accuracy comparison, yielding 83.08, 82.15, 80.31, and 72.92% accuracy for RF, XGBoost, KNN, and NB, respectively. The PS-InSAR technique demonstrated a high deformation velocity along the line of sight (LOS) in model-sensitive areas. The PS-InSAR technique was used to evaluate the slope deformation velocity, which can be used to improve the LSM for the research region. The RF technique yielded superior findings, integrating with the PS-InSAR outcomes to provide the region with a new landslide susceptibility map. The enhanced model will help mitigate landslide catastrophes, and the outcomes may help ensure the roadway's safe functioning in the study region.
Subject(s)
Landslides , Algorithms , Bayes Theorem , Geographic Information Systems , Machine LearningABSTRACT
Karachi is located in the southern part of Pakistan along the Arabian Sea coast. Relevant institutions are concerned about the possibility of ground subsidence in the city, contributing to the comparative sea-level rise. So yet, no direct measurement of the subsidence rate and its relation to city submergence danger has been made. SAR (Synthetic Aperture Radar) interferometry is a powerful method for obtaining millimeter-accurate surface displacement measurements. The Sentinel-1 satellite data provide extensive geographical coverage, regular acquisitions, and open access. This research used the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technology with Sentinel-1 SAR images to monitor ground subsidence in Karachi, Pakistan. The SARPROZ software was used to analyze a series of Sentinel-1A images taken from November 2019 to December 2020 along ascending and descending orbit paths to assess land subsidence in Karachi. The cumulative deformation in Line of Sight (LOS) ranged from - 68.91 to 76.06 mm/year, whereas the vertical deformation in LOS ranged from - 67.66 to 74.68 mm/year. The data reveal a considerable rise in subsidence from 2019 to 2020. The general pattern of subsidence indicated very high values in the city center, whereas locations outside the city center saw minimal subsidence. Overall, the proposed technique effectively maps, identifies, and monitors land areas susceptible to subsidence. This will allow for more efficient planning, construction of surface infrastructure, and control of subsidence-induced risks.
Subject(s)
Environmental Monitoring , Radar , Cities , Environmental Monitoring/methods , Interferometry/methods , PakistanABSTRACT
Urban fires threaten the economic stability and safety of urban residents. Therefore, the limited number of fire stations should cover as many places as possible. Moreover, places with high fire risk should be covered by more fire stations. To optimize the location of urban fire stations, we construct a multi-objective optimization model for fire station planning based on the backup coverage model. The improved value of environment and ecosystem (SAVEE) model is introduced to quantify the spatial heterogeneity of urban fires. The main city zone of Wuhan is used as the study area to validate the proposed method. The results show that, considering the existing fire stations (85 facilities), the proposed model achieves a significant 38.56% in high-risk areas that can be covered by more than one fire station. If the existing fire stations are not considered when building 95 fire stations, the proposed model can achieve coverage of 50.07% in high-risk areas by utilizing more than one fire station. As a result, the proposed backup coverage model would perform better if the protection of high-risk areas is improved with as few fire stations as possible to guarantee more places covered.
Subject(s)
Ecosystem , CitiesABSTRACT
In recent years, the generative adversarial network (GAN)-based image translation model has achieved great success in image synthesis, image inpainting, image super-resolution, and other tasks. However, the images generated by these models often have problems such as insufficient details and low quality. Especially for the task of map generation, the generated electronic map cannot achieve effects comparable to industrial production in terms of accuracy and aesthetics. This paper proposes a model called Map Generative Adversarial Networks (MapGAN) for generating multitype electronic maps accurately and quickly based on both remote sensing images and render matrices. MapGAN improves the generator architecture of Pix2pixHD and adds a classifier to enhance the model, enabling it to learn the characteristics and style differences of different types of maps. Using the datasets of Google Maps, Baidu maps, and Map World maps, we compare MapGAN with some recent image translation models in the fields of one-to-one map generation and one-to-many domain map generation. The results show that the quality of the electronic maps generated by MapGAN is optimal in terms of both intuitive vision and classic evaluation indicators.
ABSTRACT
Under the rapid development of urbanization, fire service becomes one of the biggest contributive factors to personal health and property safety. A reasonable plan of fire services should first address the issue of service area delimitation for fire emergency facilities. Specifically, there are two key factors for fire services including rescue efficiency and load balancing, which are usually handled by the space partitioning methods (e.g., Voronoi diagram). The traditional methods tend to model the space in a homogeneous plane with Euclidean distance, while in reality, the movement of rescuing is constrained by the street network. In addition, the built environment is complex by its variation of fire risk across places. Therefore, we propose a novel constrained Voronoi diagram for fire service area delimitation by adding the datasets of street network and historical fire incidents. Considering the prior knowledge that a fire engine is expected to reach the location of incident within five minutes, which is also called Golden 5 min, we propose a network partitioning algorithm which is able to increase the five-minute coverage of fire stations. Through a case study in Nanjing, China, we demonstrate the practicability of the proposed method in delimitating service areas of fire stations across time.
Subject(s)
Fires , Risk Assessment , Urbanization , China , Emergencies , HumansABSTRACT
Hemangioma (HA) is tumor formed by hyper-proliferation of vascular endothelial cells. However, the role and mechanisms of epidermal growth factor (EGF) on the progression of HA are not well illustrated. Our present study revealed that EGF can significantly promote the in vitro proliferation and motility of HA cells, which was confirmed by the up regulation of Bcl-2, proliferating cell nuclear antigen (PCNA), and metalloproteinase-2 (MMP-2) and MMP-9. The pharmacological inhibition of NF-κB, while not ERK1/2 or PI3K/Akt, attenuated EGF induced cell proliferation and expression of MMP-2 and MMP-9. EGF treatment also increased the phosphorylation, nuclear translocation and transcriptional activities of NF-κB in HA cells. These data suggested that NF-κB plays an essential role in EGF induced malignancy of HA cells. Furthermore, EGF treatment also increased the phosphorylation of IκB and IKKα, while not IKKß or IKKγ. The knockdown of IKKα reversed EGF induced activation of NF-κB. EGF treatment also decreased the phosphorylation of GSK-3ß and increased its activities in both HDEC and CRL-2586 EOMA cells. LiCl, a potent GSK-3ß inhibitor, can obviously reverse EGF induced up regulation of p65 phosphorylation. Collectively, our study revealed that EGF can trigger the malignancy of HA cells via induction of proliferation and invasion. The activation of NF-κB through IKKα/IκBα and GSK-3ß signal is essential for this process. It suggested that EGF/NF-κB signal may represent a novel therapeutic target for the treatment of human HA.
Subject(s)
Epidermal Growth Factor/pharmacology , Hemangioma/pathology , NF-kappa B/metabolism , Signal Transduction/drug effects , Cell Line, Tumor , Cell Movement/drug effects , Cell Proliferation/drug effects , Cell Survival/drug effects , Enzyme Activation/drug effects , Glycogen Synthase Kinase 3 beta/metabolism , Hemangioma/enzymology , HumansABSTRACT
The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper.