🗺️ GIS 空間內插（Spatial Interpolation）：從測站點，變成一整張溫度地圖 在 GIS 中，許多我們習以為常的地圖，其實都不是「量測」出來的，而是「算」出來的。 氣溫、雨量、空氣品質，這些現象只在少數測站被實際觀測，卻必須被轉譯為連續的空間分布，這正是空間內插的核心任務。 以常見的 IDW（Inverse Distance Weighting，反距離加權） 為例，其邏輯非常直觀： 距離越近的測站，影響力越大；距離越遠，權重越低。 測站以 3D 溫度柱呈現數值高低，顏色由冷到熱； 當內插計算進行時，掃描線會連結網格與周圍測站，線條粗細即代表權重大小，讓距離如何影響結果一目了然。 最後，所有計算即時渲染為平滑的熱力圖，離散點正式轉化為連續曲面。 更重要的是，當你調整 Power 參數時，地圖會從平滑過渡逐漸出現典型的「牛眼效應（Bull’s eye）」，清楚展示參數選擇如何改變空間解讀。 #GIS #SpatialInterpolation #IDW #空間分析 #資料視覺化 | GeoLab空間資訊實驗室
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🗺️ GIS 空間內插（Spatial Interpolation）：從測站點，變成一 …
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