Automatic classification of land cover from LUCAS in-situ landscape photos using semantic segmentation and a Random Forest model

Martinez-Sanchez, Laura; See, Linda; Yordanov, Momchil; Verhegghen, Astrid; Elvekjaer, Neija; Muraro, Davide; d’Andrimont, Raphaël; van der Velde, Marijn

doi:10.1016/j.envsoft.2023.105931

Cited by 6 publications

(1 citation statement)

References 58 publications

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“…Mobile phones and low-cost sensors can provide new streams of information through mobile apps that facilitate data collection [9] or that collect information in the background [10], as well as a variety of different sensors that are being used for environmental monitoring [11,12]. Data from social media, including geotagged photographs from sites such as Flickr or street-level photographs from providers such as Google Street View and Mapillary, can be processed using computer vision and segmentation to extract information related to land cover and land use [13,14].…”

Section: Introductionmentioning

confidence: 99%

Integrating Remote Sensing and Geospatial Big Data for Land Cover and Land Use Mapping and Monitoring

See,

Lesiv,

Schepaschenko

2024

Land

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Section: Introductionmentioning

confidence: 99%

Integrating Remote Sensing and Geospatial Big Data for Land Cover and Land Use Mapping and Monitoring

See,

Lesiv,

Schepaschenko

2024

Land

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Semantic segmentation dataset of Land Use/Cover Area frame Survey (LUCAS) rural landscape Street View Images

Martinez-Sanchez,

Hufkens,

Kearsley

et al. 2024

Data in Brief

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Assessing Buffer Gradient Synergies: Comparing Objective and Subjective Evaluations of Urban Park Ecosystem Services in Century Park, Shanghai

Wei,

Wang,

Yan

et al. 2024

Land

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Urban parks provide essential ecosystem services (ESs) that enhance human wellbeing. However, discrepancies often arise between objective assessments of these services and stakeholders’ subjective perceptions. This study addresses a research gap concerning the synergies and tradeoffs between objective evaluations and subjective perceptions of key ecosystem services across various spatial scales. We investigated six key ecosystem services in Century Park, Shanghai, across seven buffer radii (8–100 m). Objective data were obtained from park view images (PVIs) and spatial analysis, while subjective perceptions were gathered through a scoring survey of 33 stakeholders. The key finding is that a buffer radius of 35 m offers optimal synergy between objective and subjective assessments for most ESs, particularly in pollution mediation, temperature regulation, and cultural services. Professionals showed stronger alignment in regulatory services like pollution mediation and temperature regulation, while residents exhibited higher synergy in net primary production (NPP) beyond a 75 m radius. Notably, cultural services displayed nuanced differences, with professionals preferring simpler landscapes and residents demonstrating varied aesthetic preferences. These findings emphasize the importance of integrating objective data and human perceptions in urban green space planning and governance. By incorporating diverse stakeholders and identifying optimal buffer zones, planners and designers can effectively balance ESs with human experiences. This approach ultimately fosters more sustainable and wellbeing-centered urban environments.

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Automatic classification of land cover from LUCAS in-situ landscape photos using semantic segmentation and a Random Forest model

Cited by 6 publications

References 58 publications

Integrating Remote Sensing and Geospatial Big Data for Land Cover and Land Use Mapping and Monitoring

Integrating Remote Sensing and Geospatial Big Data for Land Cover and Land Use Mapping and Monitoring

Semantic segmentation dataset of Land Use/Cover Area frame Survey (LUCAS) rural landscape Street View Images

Assessing Buffer Gradient Synergies: Comparing Objective and Subjective Evaluations of Urban Park Ecosystem Services in Century Park, Shanghai

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