A Combined Approach to Classifying Land Surface Cover of Urban Domestic Gardens Using Citizen Science Data and High Resolution Image Analysis
A Combined Approach to Classifying Land Surface Cover of Urban Domestic Gardens Using Citizen Science Data and High Resolution Image Analysis
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DOI：
10.3390/rs10040537
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发表时间：
2018-04-01
期刊：
影响因子：
5
通讯作者：
Cavan, Gina
中科院分区：
文献类型：
--
作者：
Baker, Fraser;Smith, Claire L.;Cavan, Gina
家庭花园是城市的重要组成部分，对城市绿色基础设施（GI）及其相关生态系统服务做出了重大贡献。然而，国内花园的异质性令人难以置信，这给量化其地理标志贡献和可持续城市发展的相关效益带来了挑战。本研究采用创新方法，将公民科学数据与高分辨率图像分析相结合，在英国曼彻斯特的案例研究城市创建花园数据集。一项在线公民科学调查 (CSS) 收集了 1031 名城市居民对 10 种花园用地表面类型的覆盖比例估计值。进行高分辨率图像分析以验证 CSS 估计，并对城市所有花园地块的 7 个土地表面覆盖类别进行分类。 CSS 土地表面估计的验证显示平均准确度为 76.63% (s = 15.24%)，表明公民能够提供花园表面覆盖比例的有效估计。基于对象的图像分析 (OBIA) 分类的估计总体准确度达到 82%，需要进一步处理才能对阴影对象进行分类。然后，通过计算图像类比例，在整个分类中外推 CSS 地表估计，以提供城市每个花园地块内 10 种花园地表类型（建筑物、硬性不透水表面、硬性透水表面、裸土、树木、灌木、割草、粗糙草、耕地、水）的比例覆盖。最终数据集让人们更好地了解国内花园中地理标志的组成以及整个城市的地理标志组成如何变化。曼彻斯特的平均花园有 50.23% GI，包括树木 (16.54%)、割草 (14.46%)、灌木 (9.19%)、耕地 (7.62%)、粗草 (1.97%) 和水 (0.45%)。在城市规模上，曼彻斯特拥有 49.0% 的地理标志，其中约五分之一（20.94%）位于国内花园内。这是为当地城市发展政策提供信息的有用证据。
Domestic gardens are an important component of cities, contributing significantly to urban green infrastructure (GI) and its associated ecosystem services. However, domestic gardens are incredibly heterogeneous which presents challenges for quantifying their GI contribution and associated benefits for sustainable urban development. This study applies an innovative methodology that combines citizen science data with high resolution image analysis to create a garden dataset in the case study city of Manchester, UK. An online Citizen Science Survey (CSS) collected estimates of proportional coverage for 10 garden land surface types from 1031 city residents. High resolution image analysis was conducted to validate the CSS estimates, and to classify 7 land surface cover categories for all garden parcels in the city. Validation of the CSS land surface estimations revealed a mean accuracy of 76.63% (s = 15.24%), demonstrating that citizens are able to provide valid estimates of garden surface coverage proportions. An Object Based Image Analysis (OBIA) classification achieved an estimated overall accuracy of 82%, with further processing required to classify shadow objects. CSS land surface estimations were then extrapolated across the entire classification through calculation of within image class proportions, to provide the proportional coverage of 10 garden land surface types (buildings, hard impervious surfaces, hard pervious surfaces, bare soil, trees, shrubs, mown grass, rough grass, cultivated land, water) within every garden parcel in the city. The final dataset provides a better understanding of the composition of GI in domestic gardens and how this varies across the city. An average garden in Manchester has 50.23% GI, including trees (16.54%), mown grass (14.46%), shrubs (9.19%), cultivated land (7.62%), rough grass (1.97%) and water (0.45%). At the city scale, Manchester has 49.0% GI, and around one fifth (20.94%) of this GI is contained within domestic gardens. This is useful evidence to inform local urban development policies.