|
ai-generated content (aigc) |
6 |
|
generative ai |
6 |
|
generative method |
6 |
|
generative urban design |
6 |
|
human-machine collaboration |
6 |
|
ltds |
6 |
|
ndvi |
6 |
|
sdna |
6 |
|
street trees |
6 |
|
urban form generation |
6 |
|
urban green |
6 |
|
urban morphology |
6 |
|
walking |
6 |
|
built environment |
5 |
|
gis |
5 |
|
green space |
5 |
|
park shape |
5 |
|
park size |
5 |
|
walkability |
5 |
|
high-density |
4 |
|
hong kong |
4 |
|
land cover |
4 |
|
remote sensing |
4 |
|
spatial scale |
4 |
|
uncertainty |
4 |
|
urban design |
4 |
|
anthropogenic methane |
3 |
|
ch4 |
3 |
|
china |
3 |
|
connectivity |
3 |
|
global warming |
3 |
|
greenhouse gases |
3 |
|
high-density city |
3 |
|
pedestrian network |
3 |
|
sectoral emissions |
3 |
|
three-dimensional |
3 |
|
age structure |
2 |
|
cellular automata |
2 |
|
change detection |
2 |
|
change detection algorithms |
2 |
|
chinese cities |
2 |
|
chinese city |
2 |
|
covid-19 |
2 |
|
hukou |
2 |
|
human mobility |
2 |
|
infectious disease |
2 |
|
kibs |
2 |
|
land development |
2 |
|
load-balancing |
2 |
|
location dynamics |
2 |
|
migration |
2 |
|
new firm formation |
2 |
|
object-oriented methods |
2 |
|
parallel computing |
2 |
|
polarimetric remote sensing |
2 |
|
polarimetric sar |
2 |
|
polarimetric synthetic aperture radar |
2 |
|
prd |
2 |
|
radarsat-2 |
2 |
|
ridesourcing |
2 |
|
short term |
2 |
|
social and behavioral sciences |
2 |
|
spatial proximity |
2 |
|
spatial spread |
2 |
|
spatiotemporal analysis |
2 |
|
synthetic aperture radar |
2 |
|
urban hierarchy |
2 |
|
urban simulation |
2 |
|
urban spatial structure |
2 |
|
urban system |
2 |
|
zero-covid |
2 |
|
anthropogenic heat |
1 |
|
artificial immune system |
1 |
|
autonomous scooters |
1 |
|
autonomous vehicles |
1 |
|
bike sharing |
1 |
|
city |
1 |
|
complementary |
1 |
|
covid-19 pandemic |
1 |
|
data integration |
1 |
|
data mining |
1 |
|
deep learning |
1 |
|
didi |
1 |
|
distributed energy systems |
1 |
|
dockless bike sharing |
1 |
|
dockless/stationless bike sharing |
1 |
|
e-scooter sharing |
1 |
|
economic resilience |
1 |
|
eigendecomposition |
1 |
|
energy consumption |
1 |
|
energy transition |
1 |
|
epidemic |
1 |
|
eui |
1 |
|
first- and last-mile transportation. |
1 |
|
fleet management |
1 |
|
full life cycle |
1 |
|
geographical information science |
1 |
|
geographically weighted regression |
1 |
|
geospatial technologies |
1 |
|
gps data |
1 |
|
guangzhou |
1 |
|
income inequality |
1 |
|
infectious diseases |
1 |
|
influential factors |
1 |
|
innovation |
1 |
|
irregular convolution |
1 |
|
k-means |
1 |
|
machine learning |
1 |
|
mixed logit models |
1 |
|
mixed pixels |
1 |
|
mixed-label analysis (mla) |
1 |
|
mobility on demand |
1 |
|
modal shift |
1 |
|
multi-agent system |
1 |
|
multi-objective optimization |
1 |
|
multivariate time series analysis |
1 |
|
non-pharmaceutical interventions |
1 |
|
patent |
1 |
|
patent invention |
1 |
|
poisson regression |
1 |
|
population movement |
1 |
|
public health policymaking |
1 |
|
public transit |
1 |
|
random forest classification |
1 |
|
regularity |
1 |
|
scooter sharing |
1 |
|
segregation |
1 |
|
service efficiency |
1 |
|
simulation |
1 |
|
smart card transactions |
1 |
|
soft classification |
1 |
|
solar energy |
1 |
|
spatial analysis |
1 |
|
spatial characteristics |
1 |
|
spatial–temporal analysis |
1 |
|
spatio-temporal |
1 |
|
spatio-temporal scales |
1 |
|
spatiotemporal distribution |
1 |
|
stated preference |
1 |
|
street |
1 |
|
street view images |
1 |
|
substitution |
1 |
|
sustainability |
1 |
|
sustainable building construction |
1 |
|
sustainable micro-mobility |
1 |
|
taxi data |
1 |
|
taxis |
1 |
|
technology innovation |
1 |
|
transit ridership |
1 |
|
travel demand analysis |
1 |
|
travel demand forecast |
1 |
|
urban planning |
1 |
|
vehicle occupancy rate |
1 |
|
visual quality |
1 |
|
人工免疫系统 (artificial immune system) |
1 |
|
元胞自动机 (cellular automata) |
1 |
|
城市模拟 (urban simulation) |
1 |
|
珠江三角洲 (pearl river delta) |
1 |
|
规划目标 (urban planning objective) |
1 |
