IJGI, Free Full-Text
Por um escritor misterioso
Descrição
Portraying functional urban areas provides useful insights for understanding complex urban systems and formulating rational urban plans. Mobile phone user trajectory data are often used to infer the individual activity patterns of people and for functional area identification, but they are difficult to obtain because of personal privacy issues and have the drawback of a sparse spatial and temporal distribution. Deep learning models have been widely utilized in functional area recognition but are limited by the difficulty of acquiring training samples with large data volumes. This paper aims to achieve a fast and automatic identification of large-scale urban functional areas without prior knowledge. This paper uses Nanjing city as a test area, and a self-organizing map (SOM) neural network model based on an improved dynamic time warping (Ndim-DTW) distance is used to automatically identify the function of each building using mobile phone aggregated data containing work and residence attributes. The results show that the recognition accuracy reaches 88.7%, which is 12.4% higher than that of the K-medoids method based on the DTW distance using a single attribute and 7.8% higher than that of the K-medoids method based on the Ndim-DTW distance with multiple attributes, confirming the effectiveness of the multi-attribute mobile phone aggregated data and the SOM model based on the Ndim-DTW distance. Furthermore, at the traffic analysis zone (TAZ) level, this paper detects that Nanjing has seven functional area hotspots with a high degree of mixing. The results can provide a data basis for urban studies on, for example, the urban spatial structure, the separation of occupations and residences, and environmental suitability evaluation.
Frontiers Projected 21st-Century Glacial Lake Evolution in High Mountain Asia
IJGI Free Full-Text UAV Photogrammetry-Based 3D Road Distress Detection
Full article: Landslide susceptibility mapping in three Upazilas of Rangamati hill district Bangladesh: application and comparison of GIS-based machine learning methods
IJGI, Free Full-Text
IJGI, Free Full-Text
PDF) phenofit: An R package for extracting vegetation phenology from time series remote sensing
IJGI, Free Full-Text
IJGI, Free Full-Text
Frontiers Projected 21st-Century Glacial Lake Evolution in High Mountain Asia
Frontiers Monitoring Changes and Soil Characterization in Mangrove Forests of the United Arab Emirates Using the Canonical Correlation Forest Model by Multitemporal of Landsat Data
Hartford Ct Gis Data Download - Colaboratory
Full article: Volunteered geographic information research in the first decade: a narrative review of selected journal articles in GIScience
World Tiling/Grid - Theory - Thrive Development Forum
Free-Format RPG IV: The Express Guide to Learning Free Format: Martin, Jim: 9781583474136: : Books
The viscoelastic properties of chromatin and the nucleoplasm revealed by scale-dependent protein mobility - IOPscience
de
por adulto (o preço varia de acordo com o tamanho do grupo)
:max_bytes(150000):strip_icc()/476537143-56a9fefd5f9b58b7d0006917.jpg)
/cloudfront-us-east-2.images.arcpublishing.com/reuters/B6ZNIOAF5ZP7BG4JTJVX2A237Q.jpg)
