本文以中國長株潭城市群綠色基礎設施與居民步行體力活動的頻率和強度為研究對象，分析步行體力活動的空間分布特征，并運用多元線性回歸模型分析城市群綠色基礎設施對居民步行體力活動頻率和強度的影響機制。研究發現，長株潭城市群居民的步行體力活動軌跡主要分布在綠色基礎設施的連接廊道和小型場地中。綠色基礎設施的內部環境、外部環境與空間格局均對居民步行體力活動存在不同程度的影響。最后，本文提出城市群綠色基礎設施的建設及更新策略，以期改善居民步行體力活動環境，充分發揮城市群綠色基礎設施的生態和社會價值。
關鍵詞
綠色基礎設施；步行體力活動；影響機制；長株潭城市群；空間格局
中國長株潭城市群綠色基礎設施對步行體力活動的影響機制研究
Research of the Influence Mechanisms of Green Infrastructure on Walking Physical Activities in Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China
作 者
步行體力活動是降低慢性疾病發生率、改善居民健康和提高生活質量的重要途經之一。綠色基礎設施（green infrastructure，以下簡稱GI）是一種由自然區域和其他開放空間組成的相互連接的網絡及其附帶的工程設施。GI的構成要素為網絡中心、連接廊道和小型場地，是可供步行體力活動的主要場所。現有對GI體系的系統性研究較少探討其對步行體力活動的影響。相關研究還需探索GI整體格局與步行體力活動的相關性，以及進一步綜合分析GI對運動頻率和強度的影響差異和影響機制。
城市群GI將是保障大部分城鄉居民進行步行體力活動的基本設施。為了進一步理解城市群GI和步行體力活動之間的關系，本文對中國長株潭城市群GI和居民步行體力活動展開研究。通過構建多元線性回歸模型進行差異分析，探索城市群GI對步行體力活動頻率和強度的影響機制，并制定有利于促進居民步行運動和健康城市環境建設的策略，以期提升城市居民福祉。
本文研究區域為湖南省長株潭城市群（長沙市、株洲市、湘潭市）的中心城區，包括長沙市的天心區、芙蓉區、開福區、雨花區和岳麓區；株洲市的天元區、蘆淞區、石峰區和荷塘區；以及湘潭市的岳塘區和雨湖區。
研究所用的步行體力活動數據來源于“多銳運動”APP上記錄的2016~2019年的運動數據在數據采集期間，研究區域的用戶量為3785人。采集到的步行軌跡數據的內容包含空間位置、運動類型、運動時長、運動距離、運動日期和運動頻率等信息。
本研究中的城市用地分類數據采用長株潭相關城市總體規劃數據。路網數據基于由“開放街道地圖”獲取到的數據進行分類處理。2016~2020年日平均降水和日平均氣溫數據來源于國家氣象信息中心。歸一化植被指數（NDVI）數據來源于USGS網站2019年12月Landsat 8數據。房價數據通過獲取安居客、鏈家和房天下三個房地產平臺2016~2019年的月度數據，并進行去重處理后計算平均值得出。人口數據來源于第七次全國人口普查統計數據。最終，通過高德地圖爬取2019年12月的各類POI數據，并進行糾偏與清洗。
已被廣泛認可和應用的GI范圍的劃定方法一般包括確定GI的目標和定位，確定其構成要素（即網絡中心、連接廊道和小型場地），以及識別網絡格局三個步驟。
網絡中心是指較少受到外界干擾、面積較大的自然棲息地斑塊，包括處于原生狀態的土地、生態保護區、郊野公園、森林、湖泊、濕地、農田、牧場和林地等。連接廊道是指線性的、連接網絡中心和小型場地的生態廊道，主要包括河流和城市道路周邊，以及防護綠帶等帶狀綠地。小型場地是對網絡中心和連接廊道的補充，為人們提供兼具生態和社會價值的休閑場地，主要包括小型城市公園、廣場、街旁綠地、社區公園等。
本文中格網尺度的選擇主要依據人均步行10分鐘的運動距離（800m）來判定。通過ArcGIS 10.6對研究區構建800m×800m的格網體系，并篩選出1436個包含城市群GI的網格單元作為研究樣本區域。
研究區居民步行體力活動軌跡與網格單元分布圖 ? 李博，歐陽浩，劉秋宏
本文參考相關研究成果結合研究區現狀，從GI的外部環境、內部環境和景觀格局三個層面構建GI指標體系，得到分析模型的自變量。
外部環境指標包括人口指標，即人口密度、居住密度；經濟指標，即房價水平、土地利用混合度；環境指標，即日平均氣溫、日平均降水。內部環境指標指GI內部的基礎服務設施，即公共廁所、停車場地、城市廣場和公交站點密度；以及景觀要素，包括運動路徑（步道交叉口數量、步道密度），水體（水體面積占比、距水體距離）和綠地（NDVI、綠地面積占比）指標。空間格局指標包括景觀數量，即斑塊密度（PD）、最大斑塊面積占比（LPI）；景觀形狀，即景觀形狀指數（LSI）、斑塊邊緣密度（ED）；景觀斑塊間關系，即斑塊聚合度指數（AI）、斑塊分離指數（DIVISION）、斑塊蔓延度指數（CONTAG）。步行體力活動指標體系主要包括步行體力活動的頻率和強度，是分析模型的因變量。
將各項指標數據轉換為柵格數據（像素精度為30m），通過Fragstats4.0移動窗口命令進行計算，并在ArcGIS軟件中，分別計算每個網格單元內所有像素各個指標的平均值。本研究采用Z-Scores法對計算所得網格單元中的平均值進行標準化處理。
研究運用方差膨脹因子對23項指標進行多重共線性檢驗，剔除具有顯著共線性的4個自變量（斑塊密度、斑塊邊緣密度、斑塊分離度指數和斑塊蔓延度指數），最終得到19項自變量指標進行后續分析。
本研究利用多元線性回歸模型對19項城市群GI指標進行差異分析，討論GI外部環境、內部環境和空間格局指標與步行體力活動頻率和強度之間的關系。
通過對長株潭城市群GI的功能分析和空間識別，劃定9類GI空間，占城市群總面積的44%。網絡中心主要包括長株潭城市群綠心和大型城市公園。連接廊道的識別主要包括湘江景觀帶、芙蓉大道綠帶，以及城市主、次、支三級道路沿線的其他城市道路綠帶。小型場地主要包括小型城市綠地、城市廣場、社區公園和小型城市公園。
城市群GI網絡中心及連接廊道分布圖 ? 李博，歐陽浩，劉秋宏
經計算GI內部的軌跡數量與步行體力活動軌跡總數的百分比，結果顯示88.3%的步行活動發生在GI內部，且集中分布在三個城市中心城區的城市綠道、綠地和公園等區域。在空間結構上，連接廊道中有最多的步行軌跡數量和最大的軌跡總長，而網絡中心擁有最少的步行軌跡數量和最短的長度。從具體類型來看，其他城市道路綠帶和其他城市綠地這兩類中的軌跡數量和長度均較大，城市群綠心、大型城市公園的軌跡數量和長度均較小。
城市群GI小型場地分布圖 ? 李博，歐陽浩，劉秋宏
通過對1436個網格單元內的指標進行計算（最小值、最大值和平均值），并在SPSS軟件中對標準化后的數據進行回歸分析。多元回歸分析結果顯示多元線性回歸模型擬合效果較好，且自變量之間不存在多重共線性，回歸模型顯著性檢驗成立。
部分城市群GI指標對步行體力活動的頻率或強度均表現出顯著影響（P≤0.05），包括居住密度、房價水平、公共廁所密度、城市廣場密度、公交站點密度、綠地公園占比、最大斑塊面積占比和斑塊聚合度指數，其中公共廁所密度、LPI和步行體力活動的頻率與強度呈負相關關系。而部分城市群GI指標則對步行體力活動的頻率或強度影響均不顯著（P＞0.05），包括人口密度、日平均降水、距水體距離、NDVI和LSI。
部分城市群GI指標對步行體力活動的頻率或強度的影響存在差異。在外部環境指標中，LM和日平均氣溫和步行體力活動強度具有顯著正相關關系，而對步行體力活動頻率影響不顯著；在內部環境指標中，步道密度和步行體力活動頻率有顯著正相關關系，而水體面積占比和步行體力活動強度顯著負相關。
整體而言，居住密度、房價水平、步道密度對步行體力活動頻率的影響最顯著（P≤0.01），居住密度、房價水平、LM、日平均氣溫、公共廁所密度、城市廣場密度、公交站點密度、步道交叉口數量、綠地面積占比和AI對步行體力活動強度的影響最顯著（P≤0.01）。
步行體力活動主要集中在連接廊道和小型場地中，說明居民更傾向于沿綠道等線性空間或者是在小型城市開放空間中開展步行體力活動。連接廊道可以有效連接各類城市開放空間，適宜的步行尺度使其可以滿足健身鍛煉和休閑游憩的多種需求。小型場地常見于居住地周邊，距離居民通勤路線較近，具備相對完善的基礎設施和趣味靈活的游線，從而易于提高居民的步行活動體驗。
此外，僅少部分步行體力活動軌跡分布在城市群綠心和大型城市公園中（如岳麓山、石燕湖等）。因自然保護管控政策要求，城市群綠心和大型城市公園較少分布在土地開發強度較大的高密度城市中心區域，而更多分布在市郊、鄉村等區域，對于居住在城市中的居民來說，路程中花費的時間較長且游憩設施較少，因而出現在網絡中心的步行體力活動較少。
從外部環境指標來看，回歸分析結果顯示城市群GI中居住密度和房價水平與步行體力活動的頻率和強度呈正相關關系。居住密度較高的區域可能人口數量更多，總體出行需求更高，同時，這類區域具有更高的街道連通性、可達性，更易于為居民帶來良好的步行運動體驗。其次，LM與步行體力活動的強度呈現正相關關系，LM越高的區域往往在步行范圍內分布有多種設施，以便于居民在一次步行活動過程中完成多項任務；日平均氣溫對居民步行體力活動的強度具有顯著正向影響，本研究中步行軌跡數據主要集中在春季和秋季，較高的溫度可以提高人體感知舒適度，減少疲憊感。
城市群GI可以為人們提供多樣的活動場所 ? 歐陽浩
從內部環境指標中來看，長株潭城市群GI中城市廣場和公交站點密度與步行體力活動的頻率和強度均呈正相關關系，這表明可以通過適當增加城市廣場和公交站點來提高基礎設施的可達性。而公共廁所密度和步行體力活動的頻率和強度均呈負相關關系。這與以往相關研究存在一定的差異，后續需要進一步細分研究繼續探討公共廁所空間配置與步行體力活動之間的關系。運動路徑方面，步道密度和步行活動頻率呈正相關關系；步道交叉口數量和步行活動強度呈正相關關系，步道交叉口數量和步道密度往往代表了一個地區連通性的強弱，更好的連通性不僅易于行走，還能有效疏解聚集性人群；同時步道交叉口能有效降低道路交通中的機動車車速，提高步行環境的安全性。水體面積占比和步行體力活動的強度呈負相關關系，長株潭城市群GI中的水體主要為面積較大的江河湖泊或水源涵養區，生態保護和水源保護的要求限制了公眾的親水活動，從而在一定程度上限制了步行體力活動。
從景觀格局指標來看，LPI與步行體力活動的頻率和強度呈負相關關系，而AI與步行體力活動的頻率和強度呈正相關關系，說明城市群核心GI斑塊面積越大，相應的居民步行活動的頻率和強度越低；而斑塊間聚合關系越好，越能促進居民步行活動的頻率和強度。長株潭GI大型景觀斑塊主要位于城郊，遠離城市核心區，可達性相對較差，并且因生態保護要求在一定程度上限制步行等人為活動。城市群GI中良好的景觀聚合關系則可以在加強各景觀類型之間的連通性、保障步行運動通暢和步行運動中的可選擇性，從而提高居民進行步行體力活動的意愿。
從城市群GI對頻率和強度的影響差異來看，景觀格局指標對頻率的影響更顯著，而外部環境指標和內部環境指標對強度的影響更顯著。這表明城市群GI的景觀空間結構和內部景觀連接關系會直接影響居民步行體力活動的頻率，原因可能在于頻率代表了居民進行周期性步行體力活動的意向，而連接性更強、聚合度更高的GI斑塊通常具有更有序、更穩定的景觀系統為步行提供有利的城市群環境。強度表示居民進行步行體力活動持續的時間和運動狀態，豐富的土地利用和基礎設施類型，以及適宜的環境溫度和降水能有效滿足居民在長時間、長距離運動中對景觀多樣化的需求，降低高負荷運動的疲憊感，提升高強度活動的體驗感。
基于GI相關理論，本研究識別并構建了長株潭城市群GI體系，探討了在長株潭城市群GI中步行體力活動的空間分布和各項GI指標對步行體力活動頻率和強度的影響差異。
依據本文研究結果，研究團隊提出三項城市群GI建設策略。在外部環境方面，打造與公園、步行綠道和其他綠地臨近的多業態、功能型住區環境，可以整體增強居民步行體力活動強度。在內部環境方面，增加GI中城市廣場、公交站點等設施的數量，構建相對集中的人行步道網絡，并適當增加步道交叉口數量，可有效提升居民進行步行體力活動的頻率。在空間格局方面，在保障生態功能的前提下適當控制大型綠地面積，增加可步行的中小型綠地面積和數量，合理規劃連接各類GI的步行綠道系統，可以保證步行運動過程的連續性，進而全面提升步行體力活動的頻率和強度。
受采集到的數據所限，本研究還存在一些不足。首先，多銳APP的主要用戶是青年和中年人，因此本文未能體現城市群GI對未成年人和老年人步行體力活動的影響，未來將進一步采集這兩類人群的步行體力活動數據開展專項研究。其次，本研究僅使用客觀環境要素作為自變量來研究GI與步行體力活動的關系，缺少對居民環境感知、心理感受等主觀因素的探討，后續將進一步拓展這方面的研究。
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本文引用格式 / PLEASE CITE THIS ARTICLE AS
Li, B., Ouyang, H., & Liu, Q. (2023). Research of the influence mechanisms of green infrastructure on walking physical activities in Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China. Landscape Architecture Frontiers, 11(1), 30–57. https://doi.org/10.15302/J-LAF-1-020075
編輯 | 高雨婷，田樂，王穎
翻譯 | 王越，高雨婷，田樂
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