An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSC-KSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e.g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures

A monitoring protocol for the integration of multiple-level wetlands monitoring using innovative technologies. WETMUST -INTEGRATED MULTIPLE LEVEL WETLANDS MONITORING SYSTEM USING INNOVATIVE TECHNOLOGIES- WP 3 – DL1

Deliverable di progetto internazional

Combining remotely sensed surface energy fluxes and GIS analysis of groundwater parameters for irrigation system assessment

Despite being necessary for effective water management, the assessment of an irrigation system requires a large amount of input data for the estimation of related parameters and indicators, which are seldom measured in a regular and reliable manner. In this work, spatially distributed surface energy balance fluxes and geographical information systems analysis of multiple groundwater parameters were used to estimate water availability, supply, and demand, in order to calculate water-accounting indicators. This methodology was used to evaluate the performance of an irrigation system in the Pinios river basin (Greece) at two selected years of high and low water availability. Time series of archived satellite images and groundwater measurements have been used for past years to support comparative analyses, due to the limited availability of actual water measurements. The resulting maps from the proposed methodology show that the performance of the irrigation system varied across space and time due to differences in its characteristics and changes in its operation, driven by fluctuation of water availability and the response of stakeholders to water depletion. Irrigation districts with unsustainable water management were identified and, together with those with slow and/or limited groundwater recharge, were brought to the attention of water managers. The observed differences in the system operation between the wet and dry years were attributed not only to the hydrological conditions of each year, but also to the changing behaviour of farmers and the improvement actions of the water managers

Remote Sensing and GIS Techniques for Selecting a Sustainable Scenario for Lake Koronia, Greece

During recent decades, Lake Koronia has undergone severe degradation as a result of human activities around the lake and throughout the basin. Surface and groundwater abstraction and pollution from agricultural, industrial, and municipal sources are the major sources of degradation. Planning a restoration project was hampered by lack of sufficient data, with gaps evident in both spatial and temporal dimensions. This study emphasized various remote sensing and geographic information system techniques, such as digital image processing and geographic overlay, to fill gaps using satellite imagery and other spatial environmental, hydrological, and hydrogeological data in the process of planning the restoration of Lake Koronia, following Ramsar guidelines. Current and historical remote sensing data were used to assess the current status and level of degradation, set constraints and define the ideotype for the restoration, and, finally, define and select the best restoration scenario

Monitoring Wetland Ditch Water Levels Using Landsat TM and Ground-Based Measurements.

Abstract not availableJRC.G-Institute for the Protection and the Security of the Citizen (Ispra