2024-05-30
【學術亮點】臺灣2003年至2022年之縣市尺度作物災害資料集
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【學術亮點】臺灣2003年至2022年之縣市尺度作物災害資料集
Intelligent Detection: Development of expert diagnosis system for crop cultivation and management【Department of Agronomy / Bo-Jein Kuo / Professor】
智慧檢測：作物栽培管理專家診斷系統開發【農藝系郭寶錚教授】
上架日期：2024/2/14
Intelligent Detection: Development of expert diagnosis system for crop cultivation and management【Department of Agronomy / Bo-Jein Kuo / Professor】
智慧檢測：作物栽培管理專家診斷系統開發【農藝系郭寶錚教授】
| 論文篇名 | 英文：County-scale dataset indicating the effects of disasters on crops in Taiwan from 2003 to 2022 中文：臺灣2003年至2022年之縣市尺度作物災害資料集 |
| 期刊名稱 | Scientific Data |
| 發表年份, 卷數, 起迄頁數 | 2024, 11(1), 205 |
| 作者 | Yuan-Chih Su, Yuan Shen, Chun-Yi Wu & Bo-Jein Kuo* (郭寶錚) |
| DOI | 10.1038/s41597-024-03053-1 |
| 中文摘要 | 作物災害資料集的缺乏限制了對小規模災害對作物的影響進行探討。由於災害通常是基於對人類影響的定義，因此災害資料庫可能低估災害對作物生產的影響。此外，這些資料庫的解析度不足以評估災害對小區域的影響。本研究整理並建立2003年至2022年間臺灣作物災害和日氣象的資料集。臺灣作物災害損失報告中總共觀測到233次作物災害並造成9,245筆作物損害記錄。日氣象資料則蒐集自各個氣象站。完整的作物災害資訊包括數個災害、受影響作物別和區域，都被存儲在作物災害資料集中。所有資料集都經過清理與改善，以提高其質量，並添加災害和作物分類等特性，以增強這些資料集的應用性。這些資料集可用於判定不同災害類型與作物生產損失之間的關係。 |
| 英文摘要 | A lack of crop disaster datasets has limited the exploration of the influence of small-scale disasters on crops. Because disasters are often defined on the basis of human impact, disaster databases may underestimate the effect of disasters on crop production. Additionally, the resolution of such databases is insufficient for evaluating the effects of disasters on small areas. In this study, crop disaster and daily weather datasets covering the period from 2003 to 2022 in Taiwan were developed. Total 9,245 damage records from 233 observations of crop disasters were mined from the Report on Crop Production Loss Caused by Disasters of Taiwan. Daily weather data were collected from weather stations. Entire crop disaster information including multiple disasters, crops, and affected regions was stored in crop disaster dataset. All datasets were cleaned up and refined to enhance their quality, and characteristics such as disaster and crop classification were added to enhance the applicability of these datasets. These datasets can be used to determine the relationship between disaster type and crop production losses. |
| 發表成果與AI計畫研究主題相關性 | 此論文發表收集作物災害和日氣象的資料集並進一步將資料集經過清理與改善來提高數據質量，另外加入災害和作物分類等特性，以增強這些資料集的應用性。團隊開發的智慧專家診斷系統其中一項就包含氣象資料，將收集的日氣象資料集加以應用即可加速診斷系統於氣象領域的分析。 |
