Name
Title | ||
|---|---|---|
Improving Leaf Area Index Retrieval Over Heterogeneous Surface by Integrating Textural and Contextual Information: A Case Study in the Heihe River Basin |
Abstract | ||
|---|---|---|
Spatial heterogeneity of land surface induces scaling bias in leaf area index (LAI) products. In optical remote sensing of vegetation, spatial heterogeneity arises both by textural and contextual effects. A case study made in the middle reach of the Heihe River Basin shows that the scaling bias in LAI retrieval is large up to 26% if the spatial heterogeneity within low-resolution pixels is ignored. To reduce the influence of spatial heterogeneity on LA! products, a correcting method combining both textural and contextual information is adopted, and the scaling bias may decrease to less than 2% in producing resolution-invariant LAI products. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/LGRS.2014.2341925 | IEEE Geosci. Remote Sensing Lett. |
Keywords | Field | DocType |
geophysical techniques,remote sensing,textural information,vegetation optical remote sensing,land surface,leaf area index retrieval,surface texture,contextual information,spatial resolution,surface structures,heihe river basin,heterogeneous surface,low-resolution pixels,resolution-invariant lai products,textural effects,vegetation,contextual effects | Leaf area index,Vegetation,Contextual information,Drainage basin,Remote sensing,Pixel,Spatial heterogeneity,Image resolution,Scaling,Mathematics | Journal |
Volume | Issue | ISSN |
12 | 2 | 1545-598X |
Citations | PageRank | References |
11 | 0.74 | 3 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gaofei Yin | 1 | 61 | 13.33 |
| Jing Li | 2 | 17 | 5.26 |
| Qinhuo Liu | 3 | 280 | 85.97 |
| Longhui Li | 4 | 28 | 3.21 |
| Yelu Zeng | 5 | 68 | 11.63 |
| Baodong Xu | 6 | 66 | 10.21 |
| Le Yang | 7 | 273 | 33.24 |
| Jing Zhao | 8 | 57 | 9.49 |