Assessment and Dynamic Prediction of Green Space Ecological Service Value in Guangzhou City, China DOI Creative Commons
Zhaoxi Li,

Z.C. Zhou,

Zhenhua Liu

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4180 - 4180

Published: Nov. 8, 2024

As an important part of the urban ecosystem, green space provides a variety ecosystem services, including climate regulation, soil conservation, carbon sink and oxygen release, biodiversity protection. However, existing remote sensing evaluation methods for ecological service value lack indicators Guangzhou, China, method depends on land cover type. Based technology random forest algorithm, this study addresses these gaps by integrating with algorithm to enhance accuracy rationality ESV assessments. Focusing we improved system conducted dynamic predictions based land-use change scenarios. Our results indicate that total Guangzhou’s was USD 7.323 billion in 2020, projected decline 6.496 2030, representing 12.37% reduction due urbanization-driven changes. This research highlights noticeable role spaces sustainability robust, data-driven insights policymakers design more effective protection management strategies. The assessment framework offers novel approach accurately quantifying services predicting future trends.

Language: Английский

Configuration of Green–Blue–Grey Spaces for Efficient Cooling of Urban Physical and Perceptual Thermal Environments DOI Creative Commons

Wenxia Zeng,

Kun Yang, Shaohua Zhang

et al.

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 645 - 645

Published: March 18, 2025

Blue and green spaces are well-known for their benefits in improving urban thermal environments. However, the optimal configuration of green, blue, grey (GBGSs) physical mental health residents remains unclear. Therefore, we employed land surface temperature (LST), near-surface air (SAT), Humidex to analyze GBGS. The results indicated following: (1) spatial distribution Perceptual Urban Thermal Environments (PTEs) is consistent with that Surface (STEs). most perceptual indicators lower than daytime LST higher SAT. (2) have cooling efficiency spaces. (3) coverage space less 40%, at least 35% space, blue covers between 15% 25%, which balance environment. Moreover, increasing simplifying recommended where below 30%. In areas 30–40% enhancing complexity fragmentation boundaries more effective. Maintaining 30% optimizing aggregation improves over 40%. This study provides scientific foundation GBGSs development renovations.

Language: Английский

Citations

0
Assessment and Dynamic Prediction of Green Space Ecological Service Value in Guangzhou City, China DOI Creative Commons
Zhaoxi Li,

Z.C. Zhou,

Zhenhua Liu

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4180 - 4180

Published: Nov. 8, 2024

As an important part of the urban ecosystem, green space provides a variety ecosystem services, including climate regulation, soil conservation, carbon sink and oxygen release, biodiversity protection. However, existing remote sensing evaluation methods for ecological service value lack indicators Guangzhou, China, method depends on land cover type. Based technology random forest algorithm, this study addresses these gaps by integrating with algorithm to enhance accuracy rationality ESV assessments. Focusing we improved system conducted dynamic predictions based land-use change scenarios. Our results indicate that total Guangzhou’s was USD 7.323 billion in 2020, projected decline 6.496 2030, representing 12.37% reduction due urbanization-driven changes. This research highlights noticeable role spaces sustainability robust, data-driven insights policymakers design more effective protection management strategies. The assessment framework offers novel approach accurately quantifying services predicting future trends.

Language: Английский

Citations

0