engleski

Appendix B - Use of Remote Sensing-Derived Land Productive Capacity Dynamics for the New World Atlas of Desertification

The European Commission’s Joint Research Centre of the (JRC), together with UNEP and supported by a global network of international research institutions and experts, is developing the new World Atlas of Desertification (WAD). Monitoring and assessing land degradation dynamics involves extracting the most relevant information from time series of global satellite observations. The dynamics of the Earth’s standing vegetation biomass is considered a valid approximation of land system productive capacity dynamics thus, also reflecting the underlying ecological conditions and possible constraints for primary productivity, such as soil fertility, water availability, land use/management, etc., and hence related to land degradation. In fact, reduction or loss of land productive capacity, mostly biological and/or economical, is one common denominator in the various definitions of land degradation. The longest available satellite observation datasets with global coverage at 1-km resolution, from, e.g., the SPOT VGT sensor, have a continuous frequent temporal sampling over a long enough period, now 15 years, to allow extraction of proxy information on the phenology and seasonal productivity for each 1-km2 area on Earth. Even longer continuous time series, more than 30 years, are available through the GIMMS NDVI product, dating back as far as to 1981. However, its spatial resolution is only 8 × 8 km, which may well be suitable for the analysis of broader landatmosphere interaction but which has limitations for monitoring and assessing the human-ecosystem interactions at landscape level. These operate and function typically at smaller scales than can be depicted at the spatial resolution of GIMMS. Nevertheless, the length of this NDVI time series raises interest in ways to combine it with higher-resolution products for enhanced analysis.

Land Productive Capacity Dynamics, land degradation

nije evidentirano