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ee.Algorithms.TemporalSegmentation.Ccdc
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實作「持續變化偵測和分類」時間中斷點演算法。這個演算法會透過反覆將諧波函式套用至資料,找出圖片集合中的時間中斷點。系統會為所有輸入頻帶產生擬合係數,但可用於偵測中斷點的頻帶可透過「breakpointBands」引數指定。
詳情請參閱 Zhu, Z. 和 Woodcock, C.E.,2014 年。使用所有可用的 Landsat 資料,持續偵測土地覆蓋的變化並進行分類。Remote sensing of Environment, 144, pp.152-171.
用量 | 傳回 |
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ee.Algorithms.TemporalSegmentation.Ccdc(collection, breakpointBands, tmaskBands, minObservations, chiSquareProbability, minNumOfYearsScaler, dateFormat, lambda, maxIterations) | 圖片 |
引數 | 類型 | 詳細資料 |
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collection | ImageCollection | 要執行 CCDC 的圖片集合。 |
breakpointBands | 清單,預設值為空值 | 用於變更偵測的波段名稱或索引。如未指定,則會使用所有頻帶。 |
tmaskBands | 清單,預設值為空值 | 用於疊代 TMask 雲端偵測的波段名稱或索引。通常是綠色波段和 SWIR1 波段。如未指定,則不會使用 TMask。如要指定「tmaskBands」,「breakpointBands」中必須包含該項目。 |
minObservations | 整數,預設值為 6 | 標記變更所需的觀察次數。 |
chiSquareProbability | 浮點值,預設值為 0.99 | 用於偵測變更的卡方機率門檻,範圍為 [0, 1]。 |
minNumOfYearsScaler | 浮點值,預設值為 1.33 | 套用新裝配的最低年數係數。 |
dateFormat | 整數,預設值為 0 | 要在擬合期間使用的時間表示法:0 = jDays、1 = 分數年、2 = 以毫秒為單位的 Unix 時間。每個時間區段的開始、結束和休息時間都會以這種方式編碼。 |
lambda | 浮點數,預設值為 20 | 適用於 LASSO 迴歸擬合的 Lambda。如果設為 0,系統會使用一般 OLS,而非 LASSO。 |
maxIterations | 整數,預設值為 25000 | LASSO 迴歸收斂的執行次數上限。如果設為 0,系統會使用一般 OLS,而非 LASSO。 |
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上次更新時間:2025-07-26 (世界標準時間)。
[null,null,["上次更新時間:2025-07-26 (世界標準時間)。"],[[["\u003cp\u003eImplements the Continuous Change Detection and Classification (CCDC) algorithm to identify temporal breakpoints (changes over time) within an image collection.\u003c/p\u003e\n"],["\u003cp\u003eUses harmonic functions to fit the image data and detect changes based on specified bands and statistical thresholds.\u003c/p\u003e\n"],["\u003cp\u003eOffers customization options such as selecting specific bands for change detection, adjusting sensitivity parameters, and configuring the time format for results.\u003c/p\u003e\n"],["\u003cp\u003eProvides fit coefficients for all input bands, aiding in understanding the nature of the detected changes.\u003c/p\u003e\n"],["\u003cp\u003eRelies on iterative fitting and statistical analysis to pinpoint breakpoints and ensure robust change detection.\u003c/p\u003e\n"]]],[],null,["# ee.Algorithms.TemporalSegmentation.Ccdc\n\nImplements the Continuous Change Detection and Classification temporal breakpoint algorithm. This algorithm finds temporal breakpoints in an image collection by iteratively fitting harmonic functions to the data. Fit coefficients are produced for all input bands, but the bands used for breakpoint detection can be specified with the 'breakpointBands' argument.\n\n\u003cbr /\u003e\n\nFor more details, see Zhu, Z. and Woodcock, C.E., 2014. Continuous change detection and classification of land cover using all available Landsat data. Remote sensing of Environment, 144, pp.152-171.\n\n| Usage | Returns |\n|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|\n| `ee.Algorithms.TemporalSegmentation.Ccdc(collection, `*breakpointBands* `, `*tmaskBands* `, `*minObservations* `, `*chiSquareProbability* `, `*minNumOfYearsScaler* `, `*dateFormat* `, `*lambda* `, `*maxIterations*`)` | Image |\n\n| Argument | Type | Details |\n|------------------------|-------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `collection` | ImageCollection | Collection of images on which to run CCDC. |\n| `breakpointBands` | List, default: null | The name or index of the bands to use for change detection. If unspecified, all bands are used. |\n| `tmaskBands` | List, default: null | The name or index of the bands to use for iterative TMask cloud detection. These are typically the green band and the SWIR1 band. If unspecified, TMask is not used. If specified, 'tmaskBands' must be included in 'breakpointBands'. |\n| `minObservations` | Integer, default: 6 | The number of observations required to flag a change. |\n| `chiSquareProbability` | Float, default: 0.99 | The chi-square probability threshold for change detection in the range of \\[0, 1\\]. |\n| `minNumOfYearsScaler` | Float, default: 1.33 | Factors of minimum number of years to apply new fitting. |\n| `dateFormat` | Integer, default: 0 | The time representation to use during fitting: 0 = jDays, 1 = fractional years, 2 = unix time in milliseconds. The start, end and break times for each temporal segment will be encoded this way. |\n| `lambda` | Float, default: 20 | Lambda for LASSO regression fitting. If set to 0, regular OLS is used instead of LASSO. |\n| `maxIterations` | Integer, default: 25000 | Maximum number of runs for LASSO regression convergence. If set to 0, regular OLS is used instead of LASSO. |"]]