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Regional soil erosion assessment from remote sensing data in rehabilitated high density canopy forests of southern China

Auteur(s) et Affiliation(s)

ZHANG, H.
State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Sciences, CAS, Nanjing, Chine
Univ. of Chinese Academy of Sciences, Beijing, Chine
YU, D.
State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Sciences, CAS, Nanjing, Chine
Univ. of Chinese Academy of Sciences, Beijing, Chine
DONG, L.
State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Sciences, CAS, Nanjing, Chine
Univ. of Chinese Academy of Sciences, Beijing, Chine
SHI, X.
State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Sciences, CAS, Nanjing, Chine
Univ. of Chinese Academy of Sciences, Beijing, Chine
WARNER, E.
Office for Remote Sensing of earth Resources, Pennsylvania State Univ., University Park, Etats-Unis
GU, Z.
State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Sciences, CAS, Nanjing, Chine
SUN, J.
State Key Lab. of Soil and Sustainable Agriculture, Inst. of Soil Sciences, CAS, Nanjing, Chine


Description :
A mapping method was developed by integrating remote sensing parameters to identify eroded areas under high density canopy in the Changting County, Fujian Province. The remotely sensed vegetation indices, vegetation fractional canopy (VFC) and leaf area index (LAI) were calibrated based on soil erosion measurements from previous runoff plot experiments and extrapolated from USLE modeling to a regional scale. It is highlighted that the vegetation restoration degree determined from LAI is more sensitive to subcanopy soil erosion than from VFC. Therefore, the remote sensing based method can be used for operational erosion monitoring in southern China.


Type de document :
Article de périodique

Source :
Catena (Giessen), issn : 0341-8162, 2014, vol. 123, p. 106-112, nombre de pages : 7, Références bibliographiques : 38 ref.

Date :
2014

Editeur :
Pays édition : Allemagne, Cremlingen-Destedt, Catena

Langue :
Anglais
Droits :
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