Search results for "leaf area"
showing 10 items of 124 documents
Mapping Leaf Area Index with a Smartphone and Gaussian Processes
2020
Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies. Smartphones are nowadays ubiquitous sensor devices with high computational power, moderate cost, and high-quality sensors. A smartphone app, which is called PocketLAI, was recently presented and tested for acquiring ground LAI estimates. In this letter, we explore the use of state-of-the-art nonlinear Gaussian process regression (GPR) to derive spatially explicit LAI estimates over rice using ground data from PocketLAI and Landsat 8 imagery. GPR has gained popularity in recent years because of its solid Bayesian foundations that offer not only high accuracy but also…
Biometrical and ecological observations on Cistus salvifolius L.
1993
Abstract Biometrical observations on Cistus salvifolius L. (Cistaceae), a species with a very variable morphology, are presented: data, collected in Sicily, are relative to three environments in which populations of Cistus salvifolius live: garigue, maquis, pinewood. Measurements are compared with other ones, found in the literature, and in some cases they disagree or supply useful indications. On the basis of the different light regimes in the three environments, and of the parameters in which the difference among the three populations is most evident, some observations about the reaction to shade in Cistus salvifolius were made. On the basis of the few data collected, the intraspecific di…
Varied response of underground and aboveground plant matter: functional diversity of three different vegetational types after translocation to reclai…
2019
The indicators of functional diversity are increasingly used to assess the conservation effectiveness of the most valuable habitats. However, little is known about the response of functional traits, their diversity, and divergence in plant communities after translocation. To assess how functional diversity changes on dry heath, meadow, and fen after translocation of entire turfs of vegetation from an airport area to the Botanical Garden in Radzionkow, we used leaf–height–seed (LHS) traits (specific leaf area, height, and seed mass) and vegetative traits (bud bank size, bud bank depth, and lateral spread). We also measured community weighted means and multifunctional diversity metrics (funct…
A red-edge spectral index for remote sensing estimation of green LAI over agroecosystems
2013
Abstract Leaf area index (LAI) is a key biophysical parameter for the monitoring of agroecosystems. Conventional two-band vegetation indices based on red and near-infrared relationships such as the normalized difference vegetation index (NDVI) are well known to suffer from saturation at moderate-to-high LAI values (3–5). To bypass this saturation effect, in this work a robust alternative has been proposed for the estimation of green LAI over a wide variety of crop types. By using data from European Space Agency (ESA) campaigns SPARC 2003 and 2004 (Barrax, Spain) experimental LAI values over 9 different crop types have been collected while at the same time spaceborne imagery have been acquir…
A directional spectral mixture analysis method: application to multiangular airborne measurements
2006
This study aims at developing an operational approach-namely, directional spectral mixture analysis (DISMA)-for retrieving vegetation parameters like fractional vegetation cover (FVC) and leaf area index (LAI) from multispectral and multiangular data. The approach attempts to highlight the consistency of one-dimensional models and linear mixture approaches. DISMA combines spectral signatures of soil and vegetation components with an analytical approximation of the radiative transfer equation, giving rise to a fast invertible bidirectional reflectance distribution function (BRDF) model of discontinuous canopies. Both the forward model and its inversion using a simple technique based on looku…
Effects of partial rootzone drying and rootstock vigour on growth and fruit quality of 'Pink Lady' apple trees in Mediterranean environments
2008
We investigated the effects of partial rootzone drying (PRD) and rootstock vigour on water relations, and vegetative and productive performance of ‘Pink Lady’ apple (Malus domestica Borkh.) trees in central Sicily. In a first field trial, trees on MM.106 rootstock were subjected to: Conventional irrigation (CI), maintaining soil moisture above 80% of field capacity; PRD irrigation, where only one alternated side of the rootzone received 50% of the CI irrigation water; and continuous deficit irrigation (DI), where 50% of the CI water was equally applied to both sides of the rootzone. In a second trial, trees on M.9 or MM.106 were subjected to CI and PRD irrigation. PRD reduced stomatal condu…
Fusing optical and SAR time series for LAI gap filling with multioutput Gaussian processes
2019
The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among…
Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection
2013
Monitoring spatial and temporal variability of vegetation is important to manage land and water resources, with significant impact on the sustainability of modern agriculture. Cloud cover noticeably reduces the temporal resolution of retrievals based on optical data. COSMO-SkyMed (the new Italian Synthetic Aperture RADAR-SAR) opened new opportunities to develop agro-hydrological applications. Indeed, it represents a valuable source of data for operational use, due to the high spatial and temporal resolutions. Although X-band is not the most suitable to model agricultural and hydrological processes, an assessment of vegetation development can be achieved combing optical vegetation indices (V…
Time series of Cosmo-SkyMed data for landcover classification and surface parameter retrieval over agricultural sites
2012
This paper reports on the results of an Italian project aimed at investigating the use of X-band COSMO-SkyMed (CSK) SAR data for applications in agriculture and hydrology. Existing classification and retrieval algorithms have been tailored to CSK data and time series of crop, leaf area index and soil moisture maps have been retrieved and assessed through the comparison with in situ data collected over three agricultural sites. In addition, the CSK-derived surface parameters have been integrated into crop growth and hydrologic models and the resulting improvements have been assessed. Results indicate that multi-temporal dual-polarized CSK data are very well-suited for agricultural crop class…
Power sensitivity analysis of multi-frequency, multi-polarized, multi-temporal SAR data for soil-vegetation system variables characterization
2017
Abstract: The knowledge of spatial and temporal variability of soil water content and others soil-vegetation variables (leaf area index, fractional cover) assumes high importance in crop management. Where and when the cloudiness limits the use of optical and thermal remote sensing techniques, synthetic aperture radar (SAR) imagery has proven to have several advantages (cloud penetration, day/night acquisitions and high spatial resolution). However, measured backscattering is controlled by several factors including SAR configuration (acquisition geometry, frequency and polarization), and target dielectric and geometric properties. Thus, uncertainties arise about the more suitable configurati…