ArcGIS Geostatistical Analysis: Spatial Interpolation (IDW)
5:22
YouTubeGeospatial Geeks
ArcGIS Geostatistical Analysis: Spatial Interpolation (IDW)
Spatial Analysis means to manipulate geographic data to extract new meaningful information. Interpolation is one of such geostatistical methods in which we use known values at sampled points to generate a continuous surface giving us prediction of values at unknown points. IDW is an interpolation technique in which values of cells are predicted ...
120.5K viewsJan 11, 2017
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#Inverse Distance Weighting Explained
🗺️ 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
🗺️ 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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