Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy

Reduction of nutrient run-off by the use of coated slow-release fertilizers on two container-grown nursery crops

The agricultural district of Pistoia (Tuscany, Italy) is one of the most important sites in Europe for the production of Hardy Ornamental Nursery Stock (HONS). One of the main problems of this sector is the environmental impact of the pot cultivation, mainly due to an incorrect irrigation scheduling that leads to high nitrogen and phosphorus losses. The aim of this research has been to compare the effects of the traditional fertigation versus new fertilization strategies, based on the use of controlled slow-release fertilizers (CRFs), on plant growth and on nitrogen and phosphorus run-off in two container HONS species (Photinia × fraseri and Prunus laurocerasus). Every week, plant height, cumulate irrigation and drainage volume were measured on four replicates for each treatment and species. Every four weeks two average samples of drainage water and irrigation water for each treatment and species were analysed, determining total nitrogen and phosphorus content, in order to draft a water and nutrient balance. The three different fertilization strategies did not produce any relevant effect on the final plant height and all plants were ranked in the top quality market category. The data confirmed that the use of CRFs could contribute to a huge reduction of nitrogen and phosphorus run-off in the environment and could be a winning strategy for the fertilization of HONS in nitrate vulnerable zones

Prioritizing management actions for invasive non-native plants through expert-based knowledge and species distribution models

Given the high number of non-native plants that are being introduced worldwide and the time required to process formal pest risk analyses, a framework for the prioritization of management actions is urgently required. We therefore propose a framework for a replicable and standardized prioritization for management actions (eradication, control and monitoring) of invasive non-native plants, combining expert knowledge, current and future climatic suitability estimated by species distribution models (SDMs), clustering and ordination techniques. Based on expert consultation and using Italy as case study, invasive non-native plant species were selected and three categories of management actions were identified: eradication, control and containment, and monitoring. Finally, two further classes of priorities were proposed for each of the management actions: “high” and “low” priority. Overall, SDMs highlighted a high and very high suitability for Continental and Mediterranean bioregions for most invasive plants. Cluster analysis revealed three distinct clusters with varying levels of suitability for the Italian bioregions. Cluster 1 exhibited a higher suitability across all Italian bioregions, whereas non-native plants grouped in Cluster 2 predominantly featured high suitability in Mediterranean areas. Finally, Cluster 3 showed the lowest suitability values. Two ordination analysis highlighted the variability in bioclimatic suitability for each non-native plant within each cluster, as well as their current distribution pattern. Lastly, a third ordination, integrating bioclimatic suitability and spatial patterns, has allowed the differentiation of management actions for each non-native plant at both national and bioregional scales. Specifically, seven non-native plants were earmarked for eradication action, six for monitoring action, while the remaining species were deemed suitable for control and containment. Our results and the methodology proposed meet the demand for replicable new early warning tools; that is to predict the location of new outbreaks, to establish priorities for eradication, control and containment, and to monitor invasive non-native species

Monitoring Urban Expansion by Coupling Multi-Temporal Active Remote Sensing and Landscape Analysis: Changes in the Metropolitan Area of Cordoba (Argentina) from 2010 to 2021

Uncontrolled and unsustainable urban sprawl are altering the Earth’s surface at unprecedented rates. This research explores the potential of active remote sensors for mapping urban areas, for monitoring urban expansion processes and for depicting landscape pattern dynamics in a metropolis of South America. Based on multi-temporal urban cover maps of Cordoba, Argentina, purposely derived from COSMO-SkyMed SAR data by urban extraction algorithms, we quantified urban surface increase and described urbanization processes that occurred during 2010–2021 in sectors with different degrees of soil sealing. We extracted urban extent in four time-steps using an Urban EXTent extraction (UEXT) algorithm and quantified urban expansion, identifying newly built areas on 2.5 ha cells. For these cells, we computed urban cover and a set of landscape pattern indices (PIs), and by projecting them in a composition vs. configuration Cartesian space we performed a trajectory analysis. SAR-based urban extraction and cover change proved to be very accurate. Overall accuracy and Cohen’s Kappa statistic evidenced very high values, always above 91.58% and 0.82, respectively, for urban extraction, and also above 90.50% and 0.72 concerning the accuracy of urban expansion. Cordoba’s urban surface significantly increased (≈900 ha in 10 years) following three main spatial processes in different city sectors (e.g., edge-expansion and outlying on peri-urban areas, and infill inside the ring road), which may have contrasting effects on the sustainability of the metropolitan area. Trajectory analysis highlighted non-linear relations between the urban cover and the PIs. Areas with very low and low urban intensity underwent a steep rise of both urban cover and PI values (e.g., urban patch dimension, complexity and number), depicting urban edge-expansion and outlying processes. In the areas with medium and high urban intensity the increase in patch dimension, along with the decrease in patch number and complexity, evidence the coalescence of urban areas that incorporate in the urban fabric the remnants of non-built up zones and fill the few residual green spaces. The proposed SAR mapping procedure coupled with landscape analysis proved to be useful to detect and depict different moments of urban expansion and, pending more tests on other cities and geographical conditions, it could be postulated among the RS indicators to monitor the achievement of the Sustainable Development Goals established by the United Nations

COSMO SkyMed AO projects -multi-temporal SAR and optical data integrated approach for weed infested inland waters

In this paper we deal with the integrated use of time-series of SAR and MODIS images to derive the temporal behavior, the abundance and the distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria). The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the highest infestation of water hyacinth with significant socio-economic impact on riparian populations. The information provided by satellite can play an important role in supporting a decision system for the management of the water resources allowing also an easy and inexpensive way of monitoring the environment response to any action that might be undertaken to contrast its degradation. This paper aims at assessing the capability of medium/high resolution (Wideregion and Stripmap) COSMO-SkyMed ScanSAR time series imagery to support/supplement optical data, frequently affected by clouds, in the knowledge of temporal macrophytes growing cycles and sustain the monitor and management of the Lake Victoria waters. © 2012 IEEE

Invasion success on European coastal dunes

Many invasive plants are threatening the already highly vulnerable habitats of coastal dunes in Europe. Setting priority target species to control is mandatory for an effective planning of invasion management strategies at European level. This can be possible after identifying the species that currently have greater invasion success, in consideration of their ecological traits and origin. We quantified the three main components of invasion success for the extra-European alien plants found on European coastal dunes: local abundance, regional distribution and niche breadth, and related them to their life forms and origins. We found that life form was a better predictor of invasion success. In particular, geophytes and therophytes were the species with the greatest invasion success. Quite surprisingly, alien plants from Africa appeared as the group with slightly higher mean invasion success although this result was no statistically significant. We also highlighted the species deserving special attention. Among these, Xanthium orientale, Erigeron canadensis and Oenothera gr. biennis showed the widest levels of niche breadth and regional distribution, and had overall the greatest invasion success, but other species also had high levels in one of the three components of invasion success

Synergetic use of unmanned aerial vehicle and satellite images for detecting non-native tree species: An insight into Acacia saligna invasion in the Mediterranean coast

Invasive alien plants (IAPs) are increasingly threatening biodiversity worldwide; thus, early detection and monitoring tools are needed. Here, we explored the potential of unmanned aerial vehicle (UAV) images in providing intermediate reference data which are able to link IAP field occurrence and satellite information. Specifically, we used very high spatial resolution (VHR) UAV maps of A. saligna as calibration data for satellite-based predictions of its spread in the Mediterranean coastal dunes. Based on two satellite platforms (PlanetScope and Sentinel-2), we developed and tested a dedicated procedure to predict A. saligna spread organized in four steps: 1) setting of calibration data for satellite-based predictions, by aggregating UAV-based VHR IAP maps to satellite spatial resolution (3 and 10 m); 2) selection of monthly multispectral (blue, green, red, and near infra-red bands) cloud-free images for both satellite platforms; 3) calculation of monthly spectral variables depicting leaf and plant characteristics, canopy biomass, soil features, surface water and hue, intensity, and saturation values; 4) prediction of A. saligna distribution and identification of the most important spectral variables discriminating IAP occurrence using a fandom forest (RF) model. RF models calibrated for both satellite platforms showed high predictive performances (R (2) > 0.6; RMSE < 0.008), with accurate spatially explicit predictions of the invaded areas. While Sentinel-2 performed slightly better, the PlanetScope-based model effectively delineated invaded area edges and small patches. The summer leaf chlorophyll content followed by soil spectral variables was regarded as the most important variables discriminating A. saligna patches from native vegetation. Such variables depicted the characteristic IAP phenology and typically altered leaf litter and soil organic matter of invaded patches. Overall, we presented new evidence of the importance of VHR UAV data to fill the gap between field observation of A. saligna and satellite data, offering new tools for detecting and monitoring non-native tree spread in a cost-effective and timely manner

Wind energy potential analysis using Sentinel-1 satellite: A review and a case study on Mediterranean islands

A method for assessing and mapping the wind energy potential of near- and off-shore areas by means of multi sensor satellites (i.e. the recently launched Sentinel 1) is shown in this paper and applied to a case study area in the north-west coast of the Sicily island. The presented method aims at i) preliminary identifying the best sites for wind turbine generators installation and/or ii) estimating the average wind potential in small areas (e.g. archipelagos) for energy planning purposes. Firstly, a detailed literature review of existing techniques for wind speed estimation has been carried out, considering the most traditional methods (e.g. meteorological masts), remote sensing techniques and including a thorough review on the use of Synthetic Aperture Radar (SAR) methods integrated with Geophysical Model Functions (GMFs) for wind speed retrieval. This review enables to identify CMOD5 (C Geophysical model function 5) as the best performing GMF overcoming the CMOD4 accuracy issues in high wind speed conditions. Thus, the method has been detailly described and showcased through the analysis of the case study. SAR images from the Sentinel 1 satellite have been processed by means of the Sentinel Application Platform (SNAP) software. Afterwards, the wind speed and direction have been mapped through a Geographic Information System software. Lastly, the mean wind climate has been extrapolated for a specific Region Of Interest by the Environment for Visualizing Images (ENVI) 4.8 software. Consequentially, six hot spots characterized by high-energy potential have been identified as possible sites for possible installations of wind turbine generators