Modelling stakeholder perceptions to assess Green Infrastructures potential in agriculture through fuzzy logic: A tool for participatory governance

Abstract Solutions like Green Infrastructures can restore and maintain key regulative ecosystem services capable of mitigating disaster risk and contributing to climate change adaptation. Given the vulnerabilities that affect agriculture and its role in national economies, GI can play an important role in managing trade-offs between conflicting ecosystem services. However, their use is still lagging behind, and socio-economic dynamics in their uptake in the agricultural sector are partially disregarded. The uncertainty involved in the modelling of ecological processes can be reduced through the use of participatory processes and the involvement of relevant stakeholders to sustain decision-making processes. This article intends to assess stakeholders' perceptions on the implementation of Green Infrastructures in agriculture by capturing critical barriers and facilitators. The implementation of such Green Infrastructures policies is associated to different climate change trends in order to understand the effect of different scenarios on rural development. The study uses fuzzy logic to elicit the stakeholders' needs. The key results show that when there is uncertainty in the state of climate change trends, it is always more efficient to adopt progressive policies investing in the development and diffusion of Green Infrastructures

Monitoring environmental and climate goals for European agriculture: User perspectives on the optimization of the Copernicus evolution offer

Abstract A vicious cycle exists between agricultural production and climate change, where agriculture is both a driver and a victim of the changing climate. While new and ambitious environmental and climate change-oriented goals are being introduced in Europe, the monitoring of these objectives is often jeopardized by a lack of technological means and a reliance on heavy administrative procedures. In particular, remote sensing technologies have the potential to significantly improve the monitoring of such goals but the characteristics of such missions should take into consideration the needs of users to guarantee return on investments and effective policy implementation. This study aims at identifying gaps in the current offer of Copernicus products for the monitoring of the agricultural sector through the elicitation of stakeholder requirements. The methodology is applied to the case study of Italy while the approach is scalable at European level. The elicitation process associates user needs to the European and national legislative framework to create a policy-oriented demand of Copernicus Earth Observation services. Results show the limitations faced by environmental managers in relation to the use of Remote Sensing technologies and the shortcomings associated with a purely technology driven approach to the development of satellite missions. Through the introduction of this flexible and user centred approach instead, this paper provides a clear overview of agro-environmental user requirements and represents the basis for the definition of an integrated agricultural service

Agreement Index for Burned Area Mapping: Integration of Multiple Spectral Indices Using Sentinel-2 Satellite Images

Identifying fire-affected areas is of key importance to support post-fire management strategies and account for the environmental impact of fires. The availability of high spatial and temporal resolution optical satellite data enables the development of procedures for detailed and prompt post-fire mapping. This study proposes a novel approach for integrating multiple spectral indices to generate more accurate burned area maps by exploiting Sentinel-2 images. This approach aims to develop a procedure to combine multiple spectral indices using an adaptive thresholding method and proposes an agreement index to map the burned areas by optimizing omission and commission errors. The approach has been tested for the burned area classification of four study areas in Italy. The proposed agreement index combines multiple spectral indices to select the actual burned pixels, to balance the omission and commission errors, and to optimize the overall accuracy. The results showed the spectral indices singularly performed differently in the four study areas and that high levels of commission errors were achieved, especially for wildfires which occurred during the fall season (up to 0.93) Furthermore, the agreement index showed a good level of accuracy (minimum 0.65, maximum 0.96) for all the study areas, improving the performance compared to assessing the indices individually. This suggests the possibility of testing the methodology on a large set of wildfire cases in different environmental conditions to support the decision-making process. Exploiting the high resolution of optical satellite data, this work contributes to improving the production of detailed burned area maps, which could be integrated into operational services based on the use of Earth Observation products for burned area mapping to support the decision-making process

Indications of dynamic effects on scaling relationships between channel sinuosity and vegetation patch size across a salt marsh platform

Salt marshes are important coastal areas that consist of a vegetated intertidal marsh platform and a drainage network of tidal channels. How salt marshes and their drainage networks develop is not fully understood, but it has been shown that the biogeomorphic interactions and feedbacks between vegetation development and channel formation play an important role. We examined the relationships among tidal channel sinuosity, marsh roughness, vegetation type (pioneer, Elymus athericus or Phragmites australis), and patch size at different spatial scales using a high-resolution vegetation map (derived from aerial photography) and lower-resolution satellite imagery processed with linear spectral mixture analysis. The patch-size distribution in all vegetation types corresponded to a power law, suggesting the presence of self-organizational processes. While small vegetation patches are more dominant in pioneer vegetation, they were present in all vegetation types. The largest patch size is restricted to E. athericus. We observed an inverse logarithmic relationship between channel sinuosity and vegetation patch size in all vegetation types. The fact that this relationship is observed in both pioneer and later successional stages suggests that after the establishment of a drainage network in the dynamic pioneer stages of salt marsh development, the later stages of salt marsh succession largely inherit the meandering pattern of the early successional stages. Our study confirms recent evidence that no significant changes in the specific features of tidal channel networks (e.g., channel width, drainage density, and efficiency) take place during the later stages of salt marsh development

Non-Parametric Statistical Approaches for Leaf Area Index Estimation from Sentinel-2 Data: A Multi-Crop Assessment

The leaf area index (LAI) is a key biophysical variable for agroecosystem monitoring, as well as a relevant state variable in crop modelling. For this reason, temporal and spatial determination of LAI are required to improve the understanding of several land surface processes related to vegetation dynamics and crop growth. Despite the large number of retrieved LAI products and the efforts to develop new and updated algorithms for LAI estimation, the available products are not yet capable of capturing site-specific variability, as requested in many agricultural applications. The objective of this study was to evaluate the potential of non-parametric approaches for multi-temporal LAI retrieval by Sentinel-2 multispectral data, in comparison with a VI-based parametric approach. For this purpose, we built a large database combining a multispectral satellite data set and ground LAI measurements collected over two growing seasons (2018 and 2019), including three crops (i.e., winter wheat, maize, and alfalfa) characterized by different growing cycles and canopy structures, and considering different agronomic conditions (i.e., at three farms in three different sites). The accuracy of parametric and non-parametric methods for LAI estimation was assessed by cross-validation (CV) at both the pixel and field levels over mixed-crop (MC) and crop-specific (CS) data sets. Overall, the non-parametric approach showed a higher accuracy of prediction at pixel level than parametric methods, and it was also observed that Gaussian Process Regression (GPR) did not provide any significant difference (p-value > 0.05) between the predicted values of LAI in the MC and CS data sets, regardless of the crop. Indeed, GPR at the field level showed a cross-validated coefficient of determination (R2CV) higher than 0.80 for all three crops

A gene expression signature associated with survival in metastatic melanoma

BACKGROUND: Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. METHODS: Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. RESULTS: SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. CONCLUSION: The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells

COMPARISON OF SRTM ELEVATION DATA WITH CARTOGRAPHICALLY DERIVED DEMS IN ITALY

In this study we evaluated the quality of the DEM acquired by the Shuttle Radar Topography Mission(SRTM) for Italy through comparison with cartographically derived DEMs, available for the Italian territory.Comparison was carried out analyzing differences in elevation and slope angle at regional scale. Thecomparisons carried out at the regional scale disclose a general increase in slope angle values with thechange in resolution and a moderate difference in mean elevation. From these results, we highlighted thatimproved surface-based DEMs, based on advanced SAR, have vertical values that approach or exceedthat of current medium resolution surface products. Moreover, this study helps to provide a benchmarkagainst which future DEM products can be evaluated

ASPHAA: A GIS-Based algorithm to calculate cell area on a latitude-longitude (Geographic) regular grid

One characteristic of a Geographic Information System (GIS) is that it addresses the necessity to handle a large amount of data at multiple scales. Lands span over an area greater than 15 million km2 all over the globe and information types are highly variable. In addition, multi-scale analyses involve both spatial and temporal integration of datasets deriving from different sources. The currently worldwide used system of latitude and longitude coordinates could avoid limitations in data use due to biases and approximations. In this article a fast and reliable algorithm implemented in Arc Macro Language (AML) is presented to provide an automatic computation of the surface area of the cells in a regularly spaced longitude-latitude (geographic) grid at different resolutions. The approach is based on the well-known approximation of the spheroidal Earth's surface to the authalic (i.e. equal-area) sphere. After verifying the algorithm's strength by comparison with a numerical solution for the reference spheroidal model, specific case studies are introduced to evaluate the differences when switching from geographic to projected coordinate systems. This is done at different resolutions and using different formulations to calculate cell areas. Even if the percentage differences are low, they become relevant when reported in absolute terms (hectares).</p

Modelling risk hurricane elements in potentially affected areas by a GIS system

In the last decade, modelling hurricanes in potentially affected areas using geographical information systems (GIS) and geospatial cyberinfrastracture (GCI) has become a major topic of research. Despite some basic approaches, some unsolved questions are still under discussion. The disastrous effects of hurricanes on communities are well known, however there is a need to better understand the hazard contributions of the different components related to a hurricane, such as storm surges, floods and high winds. In this paper, the selected approach is to determine an onset zoning from a set of attributes that are considered to govern the hurricane while examining the influence of each individual component that produces the final exposure. To this end, this study assesses the different components using parameters derived from topography, bathymetry and hurricane physical indexes. Key attributes are the river network, the topography, the wetness index and the offline bathymetry. Complementary data include the CMORPH rain dataset and the hurricane track together with its structure model, both based on National Oceanic and Atmospheric Administration (NOAA) datasets. Total hazard results were then overlaid with population data in the overall assessment of elements at risk. The approach, which made use of a number of available global and free datasets, was then validated on a regional basis using ground data collected by the World Food Programme (WFP) over the study area (Central America region) for a specific hurricane. © 2010 Taylor &amp; Francis