0fe8ff82-b09f-41d8-9fbe-2d54e4ccec73 eng Zhanguo Bai 2012-02-22T15:19:18 ISO 19115:2003/19139 1.0 2 1870 0.072727 4943 0.072727 yes GCS_WGS_1984 Global Negative Trend in RUE-adjusted NDVI (1981-2003) 2008-10-22T07:00:00 First edition Land degradation means a loss of net primary productivity but a decrease in productivity is not necessarily land degradation. To distinguish between declining productivity caused by land degradation and decline due to other factors, it is necessary to eliminate false alarms arising from climatic variability and changes in land use and management. Rainfall variability has been taken into account by using both rain-use efficiency(RUE) and RESTREND. RUE is considered by, first, identifying pixels where there is a positive relationship between productivity and rainfall. For those areas where productivity depends on rainfall and where productivity declined but RUE increased, we attribute the decline of productivity to drought. Those areas are masked (urban areas are also masked). NDVI trends are presented for the remaining parts of the country as RUE-adjusted NDVI, or a proxy of land degradation. Areas of land degradation are identified by a sequence of analyses of remotely sensed data: 1. Simple NDVI indicators: NDVI minimum, maximum, maximum-minimum, mean, sum, standard deviation and coefficient of variation. Their trends are analysed over the 23-year period of the GIMMS data. 2. The annual sum NDVI, representing the aggregate of greenness over the year, period is chosen as the standard proxy for annual biomass productivity. NDVI is translated to net primary productivity (NPP) by correlation with MODIS data. 3. To distinguish between declining productivity caused by land degradation and decline owing to rainfall variability, the following procedure was adopted: a. Identify the areas where there is a positive relationship between productivity and rainfall, i.e. where rainfall determines NPP; b. For those areas where rainfall determines productivity, RUE is considered: where productivity declined but RUE increased, declining productivity is attributed to declining rainfall and these areas are masked; c. For the remaining areas with a positive relationship between productivity and rainfall but declining RUE, and also for areas where there is a negative relationship between NDVI and rainfall, i.e. humid and irrigated areas where rainfall does not determine NPP, NDVI trend was calculated as RUE-adjusted NDVI; d. Land degradation is indicated by a negative trend in RUE-adjusted NDVI and may be quantified as RUE-adjusted NPP. 4. Residual trends of NDVI (RESTREND). 5. Energy-use efficiency - ratio of annual sum NDVI to accumulated temperature, combined with RUE-adjusted NPP to arrive at climate-adjusted NPP. 6. Calculation of loss of NPP in degrading areas. 7. Comparison of climate-adjusted NPP with land cover and land use, aridity, soil and terrain, rural population density and indices of poverty. We have defined land degradation as a long-term loss of ecosystem function and we use net primary productivity (NPP) as an indicator. Land degradation here is an interpretation of GIMMS time series NDVI data, i.e. a measure of greenness, which is taken as a proxy for NPP. The proxy is several steps removed from recognisable symptoms of land degradation as it is commonly understood - such as soil erosion, salinity or nutrient depletion. Greenness is determined by several factors and, to interpret it in terms of land degradation and improvement, these other factors must be accounted for â?? in particular variability of rainfall and temperature and changes in land use and management, rain-use efficiency (RUE, NPP per unit of rainfall) accounts for rainfall variability and, to some extent, local soil and land characteristics. We assume that, where NPP is limited by rainfall, a declining trend in RUE indicates land degradation. Where rainfall is not limiting, NPP is the best indicator available. Taken together, the two indicators may provide a more robust assessment than either used alone. Food and Agriculture Organization of United Nations - HQs Viale delle Terme di Caracalla Rome 00153 Italy ISRIC - World Soil Information +31 (0)317 483 735 Duivendaal 9 Wageningen Wageningen 6701 AR The Netherlands soil.isric@wur.nl UN FAO - HQs Director of Land and Water Division Viale delle Terme di Caracalla Rome 00153 Italy NRL-Director@fao.org Fig5_s.gif thumbnail gif Fig5.gif large_thumbnail gif NDVI Land degradation Land improvement Remote sensing Rain-use efficiency GLADA World eng environment 1981-07-01T07:00:00 2003-12-01T13:56:00 -180 180 -90 90 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. http://www.isric.org WWW:LINK-1.0-http--link ISRIC - World Soil Information website http://www.fao.org/nr/lada/index.php?/Global.html WWW:LINK-1.0-http--link LADA - Land Degradation Assessment in Drylands - FAO 2008 Web site http://www.fao.org:80/geonetwork/srv/en/resources.get?id=37053&fname=Global negative trend of RUE_adjusted NDVI Fig 5.zip&access=private WWW:DOWNLOAD-1.0-http--download Global negative trend of RUE_adjusted NDVI Fig 5.zip Global negative trend in RUE-adjusted NDVI 1981-2003 http://www.fao.org:80/geonetwork/srv/en/resources.get?id=37053&fname=GLADA Report 5.pdf&access=private WWW:DOWNLOAD-1.0-http--download GLADA Report 5.pdf GLADA Report 5 - Global Assessment of Land Degradation and Improvement- PDF format http://data.fao.org/maps/wms?styles=geonetwork_fig5_37053_style OGC:WMS-1.1.1-http-get-map GEONETWORK:fig5_37053 Global Negative Trend in RUE-adjusted NDVI (1981-2003) Last Updated 2008-10-22T10:00:00