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• We propose a novel UGE evaluation approach from a spatial differentiation perspective. • The approach detects subtle inequities missed by existing approaches. • Significant urban green inequities and spatial variations observed in the study area. • location and accessibility of green space are key factors in urban green inequity. • The approach identifies green feature impacts and suggests planning policies. Current assessment methods of Urban green equity (UGE) ignore the social differentiation of urban space, which may lead to a misallocation of green space resources, exacerbating differentiation, and potentially giving rise to green gentrification (GG). This study employs a novel evaluation framework and approach for UGE, considering the impact of landscape and greening on Spatial Differentiation of Residential Areas (SDORA), to evaluate the UGE of the west bank core area in Changsha city, Hunan Province, China, and explores its influencing mechanisms. The results show that (1) The study area exhibits significant greening differentiation, and residential areas with high property prices have higher quality landscapes and greening than those with low property prices. (2) The region displays significant green equity disparity (GEI = 0.497) and GG. (3) The cumulative contribution of landscape and greening to SDORA reaches 39.04 %, with the features of water body and mountain proximity as well as accessibility having the most significant impact on urban green space differentiation. This study enhances the understanding of UGE assessment, emphasizing the importance of considering spatial differentiation during UGE evaluation, and provides technical support and scientific guidance for the planning and construction of urban green space systems. [ABSTRACT FROM AUTHOR]

Current studies have quantified landscape value based on the quantity of social media, ignoring public preference, emotional tendency and intensity. Our objective is to quantify and map landscape value by developing a novel intelligent landscape value evaluation method based on online texts. We argue that online texts can be converted into quantities through deep learning technology, which allows the measurement of public preference, emotional tendency and intensity. We selected perception frequency, perception heat, perception preference and the value index as indicators to quantify landscape value, which is the product of perception heat and perception preference. We collected more than 14,000 online texts about the Orange Islands in Changsha city from 2010 to 2020, analysed the perception heat using Python to extract data, and analysed the perception preference using Baidu API sentiment analysis technology. The results show that the novel method has a wide range of data sources and represents the real public perception and value orientation, demonstrating that online texts with a wealth of mined information can be used to evaluate landscape value. The model calculating the landscape value overcomes the shortcomings of current methods that ignore public preference, emotional tendency and intensity. The results also show that the conservation mode of Orange Island is successful, and the conservation method suggested by the recommendation on the historic urban landscape is feasible. The study highlights the contribution of public preferences to landscape value and provides insight into the situations and variations of value types on Orange Island. The novel method is highly intelligent, time-saving, has low labour costs, and is applicable and can be applied to the evaluation of landscape value, especially in cases where value conflicts exist. • Perception frequency, perception heat, perception preference and the value index are selected as indicators. • It is feasible that landscape value is considered to be the product of perception heat and perception preference. • The novel method overcomes the shortcomings of current methods that ignore public preference, emotional tendency and intensity. • The novel method analyses public preferences with high accuracy by using Baidu API sentiment analysis technology. • The conservation mode of Orange Island is successful, and the conservation method is feasible. [ABSTRACT FROM AUTHOR]