A Weekly Indicator of Surface Moisture Status from Satellite Data for Operational Monitoring of Crop Conditions.

The triangle method has been applied to derive a weekly indicator of evaporative fraction on vegetated areas in a temperate region in Northern Italy. Daily MODIS Aqua Land Surface Temperature (MYD11A1) data has been combined with air temperature maps and 8-day composite MODIS NDVI (MOD13Q1/MYD13Q1) data to estimate the Evaporative Fraction (EF) at 1 km resolution, on a daily basis. Measurements at two eddy covariance towers located within the study area have been exploited to assess the reliability of satellite based EF estimations as well as the robustness of input data. Weekly syntheses of the daily EF indicator (EFw) were then derived at regional scale for the years 2010, 2011 and 2012 as a proxy of overall surface moisture condition. EFw showed a temporal behavior consistent with growing cycles and agro-practices of the main crops cultivated in the study area (rice, forages and corn). Comparison with official regional corn yield data showed that variations in EFw cumulated over summer are related with crop production shortages induced by water scarcity. These results suggest that weekly-averaged EF estimated from MODIS data is sensible to water stress conditions and can be used as an indicator of crops' moisture conditions at agronomical district level. Advantages and disadvantages of the proposed approach to provide information useful to issue operational near real time bulletins on crop conditions at regional scale are discussed.

Comparative analysis of normalised difference spectral indices derived from MODIS for detecting surface water in flooded rice cropping systems.

Identifying managed flooding in paddy fields is commonly used in remote sensing to detect rice. Such flooding, followed by rapid vegetation growth, is a reliable indicator to discriminate rice. Spectral indices (SIs) are often used to perform this task. However, little work has been done on determining which spectral combination in the form of Normalised Difference Spectral Indices (NDSIs) is most appropriate for surface water detection or which thresholds are most robust to separate water from other surfaces in operational contexts. To address this, we conducted analyses on satellite and field spectral data from an agronomic experiment as well as on real farming situations with different soil and plant conditions. Firstly, we review and select NDSIs proposed in the literature, including a new combination of visible and shortwave infrared bands. Secondly, we analyse spectroradiometric field data and satellite data to evaluate mixed pixel effects. Thirdly, we analyse MODIS data and Landsat data at four sites in Europe and Asia to assess NDSI performance in real-world conditions. Finally, we test the performance of the NDSIs on MODIS temporal profiles in the four sites. We also compared the NDSIs against a combined index previously used for agronomic flood detection. Analyses suggest that NDSIs using MODIS bands 4 and 7, 1 and 7, 4 and 6 or 1 and 6 perform best. A common threshold for each NDSI across all sites was more appropriate than locally adaptive thresholds. In general, NDSIs that use band 7 have a negligible increase in Commission Error over those that use band 6 but are more sensitive to water presence in mixed land cover conditions typical of moderate spatial resolution analyses. The best performing NDSI is comparable to the combined index but with less variability in performance across sites, suggesting a more succinct and robust flood detection method.

Tracing the fate of PCBs in forest ecosystems.

Forests were shown to play an important role in influencing atmospheric concentrations and transport of persistent organic pollutants (POPs) in the environment. World forests cover more than 4 billion hectares and contain up to 80% of the above ground organic carbon. Given the lipophilic nature of POPs, this suggests that forests can influence the environmental fate of POPs at a global scale. POP accumulation in forest canopies still presents points of concern given the complexity of these ecosystems. In particular, the role of ecological parameters such as LAI (leaf area index) and SLA (specific leaf area) and their dynamics during the growing season was not sufficiently investigated yet. This paper reviews, compares and interprets a unique case study in which air and leaf concentrations and deposition fluxes for selected polychlorinated biphenyls (PCBs) were measured in three different forest types exposed to the same air masses. In order to trace the air-leaf-soil path of these compounds, a dynamic model of POP accumulation into forest canopy was applied. The dynamics of the canopy biomass strongly affected the trend of leaf concentration with time. Growth dilution effect can prevent the more chlorinated compounds from reaching the partitioning equilibrium before litter fall, while the more volatile compounds can approach equilibrium in the range of few weeks. An amount of up to 60 ng of PCBs per square metre of ground surface was predicted to be stored in each of the selected forests at fully developed canopy. Dry gaseous deposition fluxes to forest canopy were estimated to reach a maximum value of about 0.5-1.5 ng m(-2) d(-1) during the spring period.