A5051563850- Remote Sensing in Agriculture
- Soil Moisture and Remote Sensing
- Soil Geostatistics and Mapping
- Irrigation Practices and Water Management
- Remote Sensing and LiDAR Applications
- Plant Water Relations and Carbon Dynamics
- Horticultural and Viticultural Research
- Precipitation Measurement and Analysis
- Leaf Properties and Growth Measurement
- Geochemistry and Geologic Mapping
- Remote Sensing and Land Use
- Climate change impacts on agriculture
- Cryospheric studies and observations
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Rice Cultivation and Yield Improvement
- Plant Physiology and Cultivation Studies
- Spectroscopy and Chemometric Analyses
- Remote-Sensing Image Classification
- Greenhouse Technology and Climate Control
- Wheat and Barley Genetics and Pathology
- Phytoplasmas and Hemiptera pathogens
- Climate change and permafrost
- Hydrology and Watershed Management Studies
- Cocoa and Sweet Potato Agronomy
- Land Use and Ecosystem Services
Cereal Research Centre
2013-2025
Centro Agricoltura Ambiente (Italy)
2014-2024
University of Bari Aldo Moro
2023
Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria
2009-2018
Istituto Sperimentale per la Frutticoltura
2009-2013
This study investigated the application of high-resolution satellite imagery from SuperDove satellites combined with machine learning algorithms to estimate spatiotemporal variability some winter wheat parameters, including relative leaf chlorophyll content (RCC), water (RWC), and aboveground dry matter (DM). The research was carried out within an experimental field in Southern Italy during 2024 growing season. Different (ML) were trained compared using spectral band data calculated...
Water scarcity, exacerbated by climate change and increasing agricultural water demands, highlights the necessity for efficient irrigation management. This study focused on estimating actual evapotranspiration (ETa) in watermelons under semi-arid Mediterranean conditions integrating high-resolution satellite imagery agro-meteorological data. Field experiments were conducted Rutigliano, southern Italy, over a 2.80 ha area. ETa was measured with eddy covariance (EC) technique predicted using...
Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in world. Identified 2013 olive trees south–eastern Italy, it spreading to Mediterranean countries. The bacterium transmitted by insects that feed on sap, and causes rapid wilting trees. paper explores use Unmanned Aerial Vehicle (UAV) combination with a multispectral radiometer for early detection infection. study was carried out three groves Apulia region (Italy) involved four drone flights from 2017 2019....
In some regions of Italy, low-intensity farming systems, together with variable climate conditions, have lowered soil organic carbon (SOC) content and quality attributes. This work aims to investigate on aspects (1) total (TOC) prediction using Vis-NIR reflectance spectroscopy in combination partial least squares regression (PLSR); (2) the most appropriate pre-processing techniques absorbance spectra; (3) composition importance (VIP). The study area was an olive grove, located at...
Xylella fastidiosa is a bacterial pathogen affecting many plant species worldwide. Recently, the subspecies pauca (Xfp) has been reported as causal agent of devastating disease on olive trees in Salento area (Apulia region, southeastern Italy), where centenarian and millenarian plants constitute great agronomic, economic, landscape trait, well an important cultural heritage. It is, therefore, to develop diagnostic tools able detect early, even when infected are still asymptomatic, reduce...
Biomass sorghum (Sorghum bicolor L. Moench) is a crop that can be used for energy production in the bioethanol chain and greater knowledge of its potential response to irrigation water levels could help assess diffusion Mediterranean areas. A two-year field experiment was carried out Southern Italy; two regimes were compared biomass sorghum, optimal watered (irrigation supplies than actual evapotranspiration, ETc) stressed (about 65% one). Growth analysis, soil content aboveground dry (ADM)...
The development and implementation of both economically environmentally sustainable precision crop management systems can be greatly enhanced through the use hyperspectral sensing. In this study, potential narrow‐waveband observations for discrimination water‐stressed tomato plants ( Solanum lycopersicum L.) was investigated in a field experiment conducted southern Italy. grown 1.8‐ha test that split into two plots with different irrigation treatments: optimal deficit water supplies, supply...
The objective of this paper is to report on the activities carried out during first year Italian project "Use COSMO-SkyMed data for LANDcover classification and surface parameters retrieval over agricultural sites" (COSMOLAND), funded by Space Agency. intends contribute mission objectives in agriculture hydrology application domains.
This paper reports on the results of an Italian project aimed at investigating use X-band COSMO-SkyMed (CSK) SAR data for applications in agriculture and hydrology. Existing classification retrieval algorithms have been tailored to CSK time series crop, leaf area index soil moisture maps retrieved assessed through comparison with situ collected over three agricultural sites. In addition, CSK-derived surface parameters integrated into crop growth hydrologic models resulting improvements...
AQUATER is a Decision Support System (DSS) developed to drive crop management decisions at district level in Mediterranean area; it integrates information from soil and climatic databases with growth simulation model provides estimates of yield regional scale. can assimilate LAI maps derived Earth observation data order mitigate the risk erroneous predictions over large areas. In this study, time-series COSMO-SkyMed SAR images, acquired Capitanata plain (Puglia region) 2010 2011, have been...
In this paper, an algorithm using Sentinel-1 (S-1) and Sentinel-2 (S-2) data to identify changes of tillage over agricultural fields at approximately ~100m resolution is presented. The methodology implements a multiscale temporal change detection on S-1 VH backscatter in order single out due practices only. can be applied bare or scarcely vegetated fields, which are identified from S-2 NDVI measurements. An initial assessment farm scale situ SPOT5-Take5 data, acquired the Apulian Tavoliere...
Conventional machine learning methods are often unable to achieve high degrees of accuracy when only spectral data involved in the classification process. The main reason that inaccuracy can be brought back omission spatial information classification. present paper suggests a way combine effectively and improve classification's accuracy. In practice, Bayesian two-stage methodology is proposed embodying two enhancements: i) geostatistical non-parametric approach, universal indicator kriging...
The climate change requires thrifty use of water resources in agriculture since irrigation is became common also for those crops like olive orchard that were traditionally grown rainfed conditions. requirement imperative semi-arid conditions the Mediterranean basin especially if orchards are cultivated super high density. For a correct scheduling, methods to measure transpiration (Tr) at plant level used. Among most spread determine Tr, thermal dissipation method (TDM) has been applied on...
The objective of this paper was to assess the use multi-frequency SAR data for mapping and monitoring spatial temporal variability land surface parameters agricultural practices. In particular, focus on retrieval soil moisture (SSM) vegetation water content (VWC) classification irrigation extent tillage practices at high resolution. illustrates basis collected over three European sites, namely Apulian Tavoliere (Southern Italy), Jolanda di Savoia (Northern Castilla y Leon (Spain), main results.
Vegetation indices obtained from remote sensed data can be used to characterize crop canopy on a large scale using non-destructive method. With the recent launch of IKONOS satellite, very high spatial resolution (1 meter) images are available for detailed monitoring ecosystems as well precision agriculture. The aim this study is evaluate accuracy leaf area index (LAI) retrieval over agricultural that by empirical relationships between different spectral vegetation (VI) and LAI measured three...