| Title
|
Global Positive Trend of Climate-Adjusted NDVI (1981-2003) |
| Date
|
2008-10-22T07:00:00 |
| Date type
|
Publication: Date identifies when the resource was issued
|
| Edition
|
First edition |
| Presentation form
|
Digital map: Map represented in raster or vector form
|
| Abstract
|
Land improvement, or bright spots, is identified by combination of: 1) a positive trend in sum NDVI for those areas where
NDVI does not depend on rainfall; 2) for areas where NDVI is correlated with rainfall, a positive trend in rain-use efficiency;
and 3) a positive trend in energy-use efficiency, i.e., climate-adjusted NDVI.
Energy-use efficiency(EUE) is represented by the ratio of annual sum NDVI to annual accumulated temperature (day degrees
above 0oC), calculated from CRU 2.1 monthly data. CRU TS 2.1 comprises monthly values of station-observed meteorological
data from the beginning of the 20th century, gridded at 0.5 degree resolution (Mitchell and Jones 2005). Monthly temperature
values since January 1981 are used to calculate energy-use efficiency.
|
| Purpose
|
Land improvement, or a successful story of land management, is as same important as degradation for a reference of sustainably
land management. Bright spots are also identified in the study case where land is being used sustainably or is showing improved
quality and productivity.
|
| Status
|
Completed: Production of the data has been completed
|
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| Descriptive keywords
|
NDVI . |
| Descriptive keywords
|
Land degradation . |
| Descriptive keywords
|
Land improvement , Remote sensing , Rain-use efficiency , GLADA . |
| Descriptive keywords
|
World (place). |
| Spatial representation type
|
Grid: Grid data is used to represent geographic data
|
| Language
|
English |
| Character set
|
UTF8: 8-bit variable size UCS Transfer Format, based on ISO/IEC 10646
|
| Topic category code
|
Environment |
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| Supplemental Information
|
Within the FAO program Land Degradation Assessment in Drylands (LADA), the present "Global Assessment of Land Degradation
and Improvement" uses remote sensing to identify areas where significant biological change is happening, both hot spots of
land degradation and bright spots of land improvement. In the next phase of the program, hot spots and bright spots will
be further characterised in the field by national teams.
|
