Repository logo
  • English
  • 中文
Log In
Have you forgotten your password?
  1. Home
  2. College of Bioresources and Agriculture / 生物資源暨農學院
  3. Agricultural Chemistry / 農業化學系
  4. Prediction of soil depth using a soil-landscape regression model: a case study on forest soils in southern Taiwan.
 
  • Details

Prediction of soil depth using a soil-landscape regression model: a case study on forest soils in southern Taiwan.

Journal
Proceedings of the National Science Council, Republic of China. Part B, Life sciences
Journal Volume
25
Journal Volume
25
Journal Issue
1
Journal Issue
1
Pages
34-39
Start Page
34
End Page
39
ISSN
02556596
Date Issued
2001-01
Author(s)
Tsai, C.C.
ZUENG-SANG CHEN  
Duh, C.T.
Horng, F.W.
URI
http://www.scopus.com/inward/record.url?eid=2-s2.0-0035229922&partnerID=MN8TOARS
http://scholars.lib.ntu.edu.tw/handle/123456789/292683
2-s2.0-0035229922
Abstract
Techniques for conventional forest soil surveys in Taiwan need to be further developed in order to save time and money. Although some soil-landscape regression models have been developed to describe and predict soil properties and depths, they have seldom been studied in Taiwan. This study establishes linear soil-landscape regression models related to soil depths and landscape factors found in the forest soils of southern Taiwan. These models were evaluated by validating the models according to their mean errors and root mean square errors. The study was carried out at the 60,000 ha Chishan Forest Working Circle. About 310 soil pedons were collected. The landscape factors included elevation, slope, aspect, and surface stone contents. Sixty percent of the total field samples were used to establish the soil-landscape regression models, and forty % were used for validation. The sampling strategy indicated that each representative pedon covers an area of about 147 ha. The number of samples was appropriate considering the available time and budget. The single variate and/or multivariate linear regression soil-landscape models were successfully established. Those models revealed significant inter-relations among the soil depths of the B and B+BC horizons, solum thickness, and landscape factors, including slope and surface stone contents (p < 0.003). The mean errors in the validation of the soil-landscape model were low and acceptable for this case study. In addition, the slope data derived from the DEM (digital elevation model) database in this case study were used to predict the soil depths of the B, B+BC horizons and the solum thickness without carrying out a field survey. Surface stone should be collected in a field soil survey to increase the precision of soil depth prediction of the B and B+BC horizons, and the solum thickness.
SDGs

[SDGs]SDG15

Type
journal article

臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

總館學科館員 (Main Library)
醫學圖書館學科館員 (Medical Library)
社會科學院辜振甫紀念圖書館學科館員 (Social Sciences Library)

開放取用是從使用者角度提升資訊取用性的社會運動,應用在學術研究上是透過將研究著作公開供使用者自由取閱,以促進學術傳播及因應期刊訂購費用逐年攀升。同時可加速研究發展、提升研究影響力,NTU Scholars即為本校的開放取用典藏(OA Archive)平台。(點選深入了解OA)

  • 請確認所上傳的全文是原創的內容,若該文件包含部分內容的版權非匯入者所有,或由第三方贊助與合作完成,請確認該版權所有者及第三方同意提供此授權。
    Please represent that the submission is your original work, and that you have the right to grant the rights to upload.
  • 若欲上傳已出版的全文電子檔,可使用Open policy finder網站查詢,以確認出版單位之版權政策。
    Please use Open policy finder to find a summary of permissions that are normally given as part of each publisher's copyright transfer agreement.
  • 網站簡介 (Quickstart Guide)
  • 使用手冊 (Instruction Manual)
  • 線上預約服務 (Booking Service)
  • 方案一:臺灣大學計算機中心帳號登入
    (With C&INC Email Account)
  • 方案二:ORCID帳號登入 (With ORCID)
  • 方案一:定期更新ORCID者,以ID匯入 (Search for identifier (ORCID))
  • 方案二:自行建檔 (Default mode Submission)
  • 方案三:學科館員協助匯入 (Email worklist to subject librarians)

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science