DocumentCode
255140
Title
The Correction ground spectral model for estimating above-ground net primary productivity at the peak of growing season on Meadow Steppe, Hulunbeier, Inner Mongolia, China
Author
Zhaoyan Diao ; Shihai Lv ; Chaoyang Feng ; Derong Su ; Liang Sun ; Xue Tian
Author_Institution
Key Lab. of Silviculture & Conservation of Minist. of Educ., Beijing Forestry Univ., Beijing, China
fYear
2014
fDate
11-14 Aug. 2014
Firstpage
1
Lastpage
4
Abstract
On the surface of hyperspectral data of remote sensing to estimate grassland biomass, the soil water content, organic matter content important impact on the model application. An ASD Fieldspec 3 spectroradiometer was used for spectral measurements of the Hulunbeier Meadow Steppe, Inner Mongolia, China, in late July, 2013. Ground spectral models were built to estimate the Above-ground Net Primary Productivity (ANPP) at the peak of the growing season from the Correction Normalized Difference Vegetation Index (CNDVI) measured in the field. The SPSS software were used to assess relationships between ANPP and CNDVI. Based on the coefficient of determination (R2), quadratic model (R2=0.808) and exponential model (R2=0.717) were batter than others. Error analysis shows that the linear equation has the biggest standard error of the prediction (SE = 82.42g/m2), the logarithmic curve equation has the smallest SE (SE=18.59g/m2). After considering all factors, a quadratic equation between ANPP and CNDVI (ANPP=3738.048 NDVIMODIS2-259.1588NDVIMODIS+1309.847, R2=0.808, SE=66.25g/m2, MEC=0.820, P <; 0.001) was selected and used for the study area at the peak of the growing season.
Keywords
geophysical techniques; remote sensing; vegetation; AD 2013 07; ASD Fieldspec 3 spectroradiometer; China; Hulunbeier Meadow Steppe; Inner Mongolia; SPSS software; above-ground net primary productivity; correction ground spectral model; correction normalized difference vegetation index; grassland biomass; growing season; hyperspectral data surface; organic matter content; quadratic model; remote sensing; soil water content; Biological system modeling; Biomass; Indexes; Mathematical model; Remote sensing; Soil; Vegetation mapping; Correction Normalized Difference Vegetation Index (CNDVI ); Meadow Steppe; ground spectral models;
fLanguage
English
Publisher
ieee
Conference_Titel
Agro-geoinformatics (Agro-geoinformatics 2014), Third International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/Agro-Geoinformatics.2014.6910596
Filename
6910596
Link To Document