Table 7 Geographic detection results of ESV for each land use type.

From: Assessing spatio-temporal patterns and driving force of ecosystem service value in the main urban area of Guangzhou

ESV types

Driving forces

q

p

ESV types

Driving forces

q

p

Forest

NDVI

0.2147

0.0000

Cultivated land

NDVI

0.0038

0.0937

Population

0.0547

0.0000

Population

0.0022

0.0625

Elevation

0.6923

0.0000

Elevation

0.0004

0.9888

Slope

0.3862

0.0000

Slope

0.0020

0.5138

Distance from road

0.0473

0.0000

Distance from road

0.0018

0.5008

Distance from railway

0.4258

0.0000

Distance from railway

0.0007

0.9270

Land cover type

0.6167

0.0000

Land cover type

0.0036

0.0499

GDP

0.0547

0.0000

GDP

0.0002

0.6250

Secondary industry GDP

0.0519

0.0000

Secondary industry GDP

0.0005

0.5921

Investment in fixed assets

0.0520

0.0000

Investment in fixed assets

0.0001

0.5921

Grassland

NDVI

0.0012

0.8421

Water body

NDVI

0.0306

0.0000

Population

0.0076

0.0000

Population

0.1045

0.0000

Elevation

0.0011

0.8221

Elevation

0.1393

0.0000

Slope

0.0036

0.1647

Slope

0.1497

0.0000

Distance from road

0.0006

0.9654

Distance from road

0.0126

0.0000

Distance from railway

0.0053

0.0077

Distance from railway

0.0671

0.0000

Land cover type

0.0020

0.3252

Land cover type

0.1211

0.0000

GDP

0.0077

0.0000

GDP

0.1045

0.0000

Secondary industry GDP

0.0015

0.1143

Secondary industry GDP

0.0462

0.0000

Investment in fixed assets

0.0015

0.1143

Investment in fixed assets

0.0462

0.0000

Bare land

NDVI

0.3905

0.0000

    

Population

0.0356

0.0000

    

Elevation

0.0333

0.0000

    

Slope

0.0270

0.0000

    

Distance from road

0.0108

0.0000

    

Distance from railway

0.0053

0.0071

    

Land cover type

0.3398

0.0000

    

GDP

0.0356

0.0000

    

Secondary industry GDP

0.0356

0.0000

    

Investment in fixed assets

0.0356

0.0000