Chapter 1 說明(About)

這裡是東華大學陸域生態研究室的資料清單網頁。這裡提供了一些了檔案連結供研究室成員及相關研究人員參考使用。

Welcome to LTER Lab’s archive page. In this page, we offer some useful file links for our labmates and co-op researchers.

清單說明

這個清單說明陸域生態研究室例行性資料的處理流程，包含了在各個樣區中以自動或半自動儀器所蒐集到的各項原始資料， 以及經過資料篩選、品管、合併與重製後二級資料的產製流程。這個清單主要是作為目錄的功能，方便研究室成員能比較快找到需要的資料。

例行性資料多半指的是定期需要更新數值資料，但實際在使用上則不受限於數值類型，凡用來檢測儀器是否運作正常的圖、表、文件亦包含本文收納的範圍內。各種類型的資料依照產製時程大致區分為Tier 0 至 Tier 3級，說明如下：

  • Tier 0 為最原始的數據，通常是由資料紀錄器依所設定的取樣頻率所獲取到的各項感應器資訊（像是 DNDF的CR1000x 的1分鐘原始數據檔）， 或是透過資料紀錄器整併的資料檔案（如Smartflux 30 分鐘通量檔）。
    • 0a. 資料記錄器原始檔，例如：DNDF的CR1000x 的1分鐘原始數據檔、CR1000 土壤10分鐘原始檔、移動性取樣的 LI-850 或 LI-7810IRGA濃度、能見度或WXT520、Sapflow P-box等。
    • 0b. 跨資料記錄器整併過的檔案，例如 DNDF Smartflux GHG通量原始檔、30分鐘摘要檔、日摘要檔等。
    • 0c. 其他單位取得的檔案，例如中央氣象局自動測站檔案。
  • Tier 1 通常是 Tier 0 資料在研究室中初步統計、重新計算或整併過後的檔案，像是將不同來源的資料整併為30分鐘檔案， 或是因為調整模型架構重新計算所產出的資料。
    • 1a 原始資料經過不同模型或參數設定，所重新計算所產出的檔案，像是通量資料用 EddyPro 改以standard 或 advanced mode重新計算的通量檔。另一種情況是針對某些儀器的數值，做事後的數值校正等。
    • 1b 原始資料經過統計計算所得到的特定參數值，像是 Sapflow P-box 資料換算出的 T0。
    • 1c 合併不同來源的資料，重新產製出的新檔案。產出的檔案時序與空間尺度，可能與原始檔不同。
  • Tier 2 資料經過品管、篩選、補遺所產製出的檔案。
    • 2a Eddy 經過繁複的填補過程產製出的檔案，如全年通量檔。
  • Tier 3(未決定)係指供發表或上傳至其他單位的資料表，資料可以是原始檔或是經過繁複產製的檔案。

[In English]

This catalogue file shows how we deal the data and where to put the files. The data mentioned are the files, figures, documents, and data sheets we collected or generated from the field and prepared for future use. Type of data can be diverse, ether quantity or quality, numeric or descriptive. Format of data can also be very different, such as text(.csv) or spread sheets(.xls) . In this catalog, I focus more on numerical data.

In this catalogue, I define any data collected from the field directly are so called ‘raw data’ or ‘raws’. This raws are usually the first hand data from the sensors we’ve set. It is recorded in data logger and without any further changed or converted.

Raws can be converted and generate new data afterward. Like unit change, we change air temperature from Celsius (°C) to Kelvin scale (K). Raws can also be summarized to other values, for example, we sum up 1 minute precipitation (rainfull) from rain gage to half-hour (30 mins) data. Generally, raws changing is taken afterward in the lab, instead of in the field, and it creates another new data tables, files, even figures.

Due to the diverse sources and uses of data, we have to clarify data we have in very beginning. In this aspect, I categorized data into 4 different tiers(0-4) based on how we handle with it.

  • Tier 0 are the raws, the untouched data recorded in data logger. Typically data loggers keep the original signal data from the sensors. In some cases, i.e., Smartflux, it not only store sensors data, but also collect data from other loggers.

    • 0a. Untouched data from logger. For example, DNDF 1 min Biomet form CR1000x, DNDF 10 mins Soil data from CR1000, data of home-made sap flow sensors, and soil respiration data from portable instruments(LI-850, LI-7810).

    • 0b. Raws combined across different loggers. Like Smartflux, it collected data from other loggers and calculate the results to 1 min, 30mins and daily summaries files.

    • 0c. Data are measured from other institute/site/company instead of ourselves. Weather data from Center Weather Bureau(CWB) website is the case.

  • Tier 1 data are summaries, averaged or recalculated from Tier 0. In tier 1, data could be came from :

    • 1a. Re-calculated raws of different models or mode. For example, we use a software called ‘EddyPro’ to recalculate flux data by different mode. The output data gives us more detail about the flux measurements.
    • 1b. Re-calculated raws of new parameters. For examples, we calculated sapflow velocity from the raws of home-made Pbox.
    • 1c. Combined different raws. For mergeing data to longer time series or larger spatial scales.

  • Tier 2 data are the data which pass the quality control(QC), quality assurance(QA) and also gap-filled.

    • 2a. Data is gap filled, QA/QCs. The Annual Eddy Flux of a forest is an example.

  • Tier 3 (undetermined)