Assessment and monitoring of land condition in the Iberian Peninsula, 1989-2000

Diagnosis of land condition is a basic prerequisite for finding the degradation of a territory under climatic and human pressures leading to desertification. Ecosystemic approaches, such as the one presented here, address ecosystem maturity or resilience. They are low cost, not very prone to error propagation and well-suited to implementation on remotely sensed time-series data covering large areas. The purposes of this work were to develop a land condition surveillance methodology based on the amount of biomass produced per unit rainfall, and to test it on the Iberian Peninsula.In this article, we propose parallel and complementary synchronic assessment and diachronic monitoring procedures to overcome the paradox of monitoring as a sequence of assessments. This is intrinsically contradictory when dealing with complex landscape mosaics, as relative estimators commonly produced for assessment are often difficult to set in a meaningful time sequence. Our approach is built on monthly time-series of two types of data, a vegetation density estimator (Green Vegetation Fraction-GVF) derived from Global Environmental Monitoring satellite archives, and corresponding interpolated climate fields. Rain Use Efficiency (RUE) is computed on two time scales to generate assessment classes. This enables detrended comparisons across different climate zones and provides automatic detection of reference areas to obtain relative RUE. The monitoring procedure uses raw GVF change rates over time and aridity in a stepwise regression to generate subclasses of discriminated trends for those drivers. The results of assessment and monitoring are then combined to yield the land condition diagnostics through explicit rules that associate their respective categories.The approach was tested in the Iberian Peninsula for the period 1989 to 2000 using monthly GVF images derived from the 1-km MEDOKADS archive based on the NOAA-AVHRR sensors, and a corresponding archive of climate variables. The resulting land condition was validated against independent data from the Natura 2000 network of conservation reserves. In very general terms, land was found to be healthier than expected, with localised spots of ongoing degradation that were associated with current or recent intensive land use. Static or positive vegetation growth rates were detected almost everywhere, including Mediterranean areas that had undergone increased aridification during the study period. Interestingly, degrading or static trends prevailed in degraded or unusually degraded land, whereas trends to improve were most represented in land in good or unusually good condition.     

Variability in ice phenology on Great Bear Lake and Great Slave Lake, Northwest Territories, Canada, from SeaWinds/QuikSCAT: 2000-2006

The temporal evolution of the backscatter coefficient, sigma-nought (σ°) from QuikSCAT was evaluated for monitoring ice phenology on Great Bear Lake (66°N, 121°W) and Great Slave Lake (61°40′N, 114°W), Northwest Territories, Canada. Results indicated that σ° from QuikSCAT can be used to detect melt onset, water clear of ice and freeze onset dates on both lakes. An ice phenology algorithm was then developed to assess the spatiotemporal variability on both lakes from QuikSCAT for the period 2000-2006. Results showed that for Great Slave Lake, the average melt onset date occurred on year day (YD) 123, the average water clear of ice date was on YD164, and the average freeze onset date was on YD330. On Great Bear Lake, the average melt onset date occurred on YD139, the average water clear of ice date was YD191, and the average freeze onset date was YD321. Ice cover remained present for at least five weeks longer on Great Bear Lake than on Great Slave Lake and most of the difference can be explained by earlier ice melt on Great Slave Lake. Spatially, on Great Bear Lake, melt onset took place first in the eastern arm, water clear of ice occurred first in southeastern and western arms, and freeze onset appeared first in the northern arm and along the shorelines. On Great Slave Lake, melt onset began first in the central basin and then progressed to the northern and eastern arms later in the season. The central basin of Great Slave Lake cleared earlier than the periphery due to the discharge from the Slave River. Freeze onset on Great Slave Lake occurred first within the east arm, closely followed by the north and west arms, and then finally in the centre of the main basin.