0000000000082324
AUTHOR
Fabio Maselli
Assessment of MODIS imagery to track light-use efficiency in a water-limited Mediterranean pine forest
Abstract Daily values of gross primary production ( GPP ) derived from an eddy-covariance flux tower have been used to analyze the information content of the MODIS Photochemical Reflectance Index ( PRI ) on the light-use efficiency ( e ). The study has been conducted in a Mediterranean Pinus pinaster forest showing summer water stress. Advanced processing techniques have been used to analyze the effect of various external factors on e and PRI temporal variations. The intra-annual correlation between these two variables has been found to be mostly attributable to concurrent variations in sun and view zenith angles. The PRI has been normalized from these angular effects ( NPRI ), and its abil…
Use of NOAA-AVHRR NDVI data for environmental monitoring and crop forecasting in the Sahel. Preliminary results
Abstract Several studies have shown that the NDVI calculated from NOAA-AVHRR data is related to annual rainfall and primary productivity in Sahelian areas. Such correlations, however, are affected by several environmental factors and have been tested only with data accumulated during rainy seasons, which is not ideal for the prediction of crop yield. In the present study a methodology of NOAA AVHRR data processing is presented which utilizes NDVI computed only in the first part of some rainy seasons and statistically takes into account the geographical variability in land resources and atmospheric conditions. From the first results of the application of the methodology in Niger, its potenti…
Tracking seasonal drought effects on ecosystem light use efficiency in a mediterranean forest using climatic and remote sensing data
Daily values of light use efficiency (LUE) of a Mediterranean forest throughout five years have been analyzed in terms of different spectral indices obtained from MODIS products and which are informative on the water stress conditions. Although correlations between LUE and the different indices are rather high, the inter-annual variation of LUE due to the summer water stress is not well identified in most of them. In particular, the PRI (photochemical reflectance index) inter-annual variation has been found to be mostly attributable to concurrent variations in sun and view zenith angles. For the study area and at MODIS spatial resolution, the different indices are informative on changes in …
Growing stock volume from multi-temporal landsat imagery through google earth engine
Growing stock volume (GSV) is one of the most important variables for.forest management and is traditionally- estimated from ground measurements. These measurements are expensive and therefore sparse and hard to maintain in time on a regular basis. Remote sensing data combined with national forest inventories constitute a helpful tool to estimate and map forest attributes. However, most studies on GSV estimation from remote sensing data focus on small forest areas with a single or only a few species. The current study aims to map GSV in peninsular Spain, a rather large and very heterogeneous area. Around 50 000 wooded land plots from the Third Spanish National Forest Inventory (NFI3) were u…
Optimized Application of Biome-BGC for Modeling the Daily GPP of Natural Vegetation Over Peninsular Spain
A methodology for improving the application of Biome-BGC in peninsular Spain was developed focusing on the optimization of the rooting depth (zroot), which is not available for the study area on a spatially distributed basis. The optimal zroot was identified by comparing daily gross primary production (GPP) simulations with varying zroot to GPP estimations from a production efficiency model previously optimized for and validated in the study area. The methodology was first tested in four eddy covariance (EC) sites representative of Mediterranean ecosystems and next applied at a regional scale to the whole study area. As a result, daily GPP simulated maps for the 2005-2012 period and an opti…
Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments
Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…
Start of the dry season as a main determinant of inter-annual Mediterranean forest production variations
Abstract Recent investigations have highlighted the dependence of Mediterranean forest production on spring rainfall. The current work introduces the concept of the start of the dry season (SDS) and performs a three-step analysis to determine the effect of SDS on Mediterranean forest production. Seven forest zones of Tuscany (Central Italy), which present differently pronounced Mediterranean features, are considered. First, a statistical analysis investigates the influence of spring water budget on forest Normalized Difference Vegetation Index (NDVI) inter-annual variations during July–August. The analysis is then extended to assess the impact of inter-annual SDS variability on forest gross…
Quantifying water stress effect on daily light use efficiency in Mediterranean ecosystems using satellite data
16 pages, 2 figures, 6 tables, supplemental material https://dx.doi.org/10.1080/17538947.2016.1247301
Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data
The accurate representation of terrestrial CO2 uptake (GPP) using Monteith's approach requires a frequent and site-specific parameterization of the model inputs. In this work, an optimization of this approach has been carried out by adjusting the inputs (f(APAR), PAR and epsilon) for the study area, peninsular Spain, a typical Mediterranean region. The daily GPP images have been calculated for 2008 and 2011 with a 1-km spatial resolution and validated by comparison with in situ GPP estimates from the eddy covariance data (direct validation) and by inter-comparison with the MODIS GPP product. The direct validation has evidenced an excellent agreement with correlations up to 0.98 in 2008 and …
Monitoring water stress in Mediterranean semi-natural vegetation with satellite and meteorological data
In arid and semi-arid environments, the characterization of the inter-annual variations of the light use efficiency ε due to water stress still relies mostly on meteorological data. Thus the GPP estimation based on procedures exclusively driven by remote sensing data has not found yet a widespread use. In this work, the potential to characterize the water stress in semi-natural vegetation of three spectral indices (NDWI, SIWSI and NDI7) – from MODIS broad spectral bands – has been analyzed in comparison to a meteorological factor (Cws). The study comprises 70 sites (belonging to 7 different ecosystems) uniformly distributed over Tuscany, and three eddy covariance tower sites. An operational…