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

The Glob Wetland Symposium: Summary and way forward

In Proceedings, GlobWetland: Looking at Wetlands from Space, Frascati, Italy, 19-20 October 200

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

Stochastic Simulation and Management of an Over-Exploited Aquifer Using an Integrated Modeling System

A modeling system for the stochastic simulation and management of the overexploited groundwater resources of Lake Karla Basin in Central Greece is presented. The uncertainty of the hydrogeological environment which arises from the lack of the hydraulic conductivity data and aquifer's heterogeneity necessitates the stochastic simulation of the underlying aquifer. For the conditional stochastic simulation of hydraulic conductivity, the geostatistical approach was used generating Monte-Carlo realizations. The impact of Lake Karla (or reservoir) restoration and the accompanying projects on the aquifer, is examined through various management scenarios taking into consideration this parameter uncertainty. The target of the restoration plan is to rehabilitate aquifer's water table. This will be achieved through shutting down a great number of irrigation wells, as the irrigation needs of cultivations will be covered by the reservoir. The project with the highest environmental impact on the aquifer is the construction of 50 water supply wells at the lakeside zone of Lake Karla. Nowadays, due to the intense agricultural cultivation, the study area faces a serious water deficit problem, which has led to the over-exploitation of non-renewable groundwater and to a dramatic drawdown of aquifer's water table. The results of the stochastic simulation and management indicates that the operation of the new water supply wells will lead, despite the operation of the new reservoir, to a further drawdown of aquifer's water table, and will increase the effect of parameter uncertainty on hydraulic heads estimation by groundwater model