Operational monitoring of daily evapotranspiration by the combination of MODIS NDVI and ground meteorological data: Application and evaluation in Central Italy

2014 ◽  
Vol 152 ◽  
pp. 279-290 ◽  
Author(s):  
Fabio Maselli ◽  
Dario Papale ◽  
Marta Chiesi ◽  
Giorgio Matteucci ◽  
Luca Angeli ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Central Italy ◽  
Operational Monitoring ◽  
Modis Ndvi ◽  
Data Application ◽  
Daily Evapotranspiration

scholarly journals STUDY OF MAOWUSU SANDY LAND VEGETATION COVERAGE CHANGE BASED ON MODIS NDVI

2018 ◽  
Vol XLII-3 ◽  
pp. 2127-2133
Author(s):  
Q. Ye ◽  
H. Liu ◽  
Y. Lin ◽  
R. Han
Keyword(s):  
Vegetation Cover ◽  
Meteorological Data ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Growth Period ◽  
Vegetation Coverage ◽  
Sandy Land ◽  
Vegetation Growth ◽  
Modis Ndvi ◽  
Temperature And Precipitation

This paper selected 2006-2016 MODIS NDVI data with a spatial resolution of 500m and time resolution of 16d, got the 11 years’ time series NDVI data of Maowusu sandy land through mosaicking, projection transformation, cutting process in batch. Analysed the spatial and temporal distribution and variation characteristics of vegetation cover in year, season and month time scales by maximum value composite, and unary linear regression analysis. Then, we combined the meteorological data of 33 sites around the sandy area, analysed the response characteristics of vegetation cover change to temperature and precipitation through Pearson correlation coefficient. Studies have shown that: (1) The NDVI value has a stable increase trend, which rate is 0.0075 / a. (2) The vegetation growth have significantly difference in four seasons, the NDVI value of summer > autumn > spring > winter. (3) The NDVI value change trend is conformed to the gauss normal distribution in a year, and it comes to be largest in August, its green season is in April, and yellow season is in the middle of November, the growth period is about 220 d. (4) The vegetation has a decreasing trend from the southeast to the northwest, most part is slightly improved, and Etuokeqianqi improved significantly. (5) The correlation indexes of annual NDVI with temperature and precipitation are −0.2178 and 0.6309, the vegetation growth is mainly affected by precipitation. In this study, a complete vegetation cover analysis and evaluation model for sandy land is established. It has important guiding significance for the sand ecological environment protection.

Decoupling the effect of the forest pest damage from the effects of meteorology using space-borne remote sensing and modelling

2021 ◽  
Author(s):  
Hrvoje Marjanovic ◽  
Aniko Kern
Keyword(s):  
Climate Change ◽  
Greenhouse Gas Emission ◽  
Carbon Sink ◽  
Meteorological Data ◽  
Environmental Data ◽  
Forest Pest ◽  
Modis Ndvi ◽  
Pest Damage ◽  
Lace Bug ◽  
The Impact

<p>The EU’s climate change mitigation plans of 55% reduction in greenhouse gas emission by 2030 and reaching climate-neutrality by 2050 rely significantly on maintaining and increasing the carbon sink in European forests. In addition to direct consequences of climate change and ageing forests, this sink is becoming threatened by the new invasive forest pests which can decrease forest productivity. The Oak lace bug (Corythucha arcuata, Say 1832), native to North America, is a new invasive species rapidly spreading since 2012 from the east to the west of Europe. The oak lace bug (OLB) after establishment in an area shows no signs of retreating and negatively affects the tree photosynthetic capacity by feeding on leaf sap. The consequences of such new and persistent pest, which are not imminently life-threatening to trees but are long-lasting, have yet to be determined.</p><p>In our study, we used remotely sensed MODIS NDVI (MOD09Q1), gridded meteorological data (FORESEE), soil water content (ERA5 Land), available national forest management and land cover data to develop methods for detecting the presence and the assessment of the impact of the OLB. The study was focused on the modelling tools to decouple the effects caused by the environmental variables from the pest damage on the measured NDVI. To this different NDVI models were created based on the Least Absolute Shrinkage and Selection Operator (LASSO) technique and the most influential periods, to support accurate forest pest detection. We investigated forests containing oak trees in the transboundary area of Hungary and Croatia. The results show that the LASSO technique is a promising tool in NDVI modelling using meteorological and environmental data. The performance of the models based on the Most Influential Periods (MIP) of the different variables showed just slightly worse results, although their application is more intuitive. In the case of the OLB, the damage assessment results with the LASSO and MIP methods showed that the pest-caused NDVI decrease in pure oak stands during the late August to early September period can be as much as -14.5% and -15.6%, respectively.</p><p> </p><p>Asknowledgments:</p><p>The research has been supported by the Croatian Science Foundation project MODFLUX (HRZZ IP-2019-04-6325), by the Hungarian Scientific Research Fund (OTKA FK-128709) and by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.</p>

scholarly journals Neuro-fuzzy systems to estimate reference evapotranspiration

Water SA ◽  
2019 ◽  
Vol 45 (2 April) ◽  
Author(s):  
Mousaab Zakhrouf ◽  
Hamid Bouchelkia ◽  
Madani Stamboul
Keyword(s):  
Meteorological Data ◽  
Regional Scale ◽  
Subtractive Clustering ◽  
Efficiency Coefficient ◽  
Climate Data ◽  
Neuro Fuzzy ◽  
Physically Based ◽  
Fuzzy C Means Clustering ◽  
Daily Evapotranspiration ◽  
Semi Empirical

Routine and rapid estimation of evapotranspiration (ET) at regional scale is of great significance for agricultural, hydrological and climatic studies. A large number of empirical or semi-empirical equations have been developed for assessing ET from meteorological data. The FAO-56 PM is one of the most important methods used to estimate evapotranspiration. The advantage of FAO-56 PM is a physically based method that requires a large number of climatic parameter data. In this paper, the potential of two types of neuro-fuzzy system, including ANFIS based on subtractive clustering (S_ANFIS), ANFIS based on the fuzzy C-means clustering method (F_ANFIS), and multiple linear regression (MLR), were used in modelling daily evapotranspiration (ET0). For this purpose various daily climate data – air temperature (T), relative humidity (RH), wind speed (U) and insolation duration (ID) – from Dar El Beidain Algiers, Algeria, were used as inputs for the ANFIS and MLR models to estimate the ET0 obtained by FAO-56 based on the Penman-Monteith equation. The obtained results show that the performances of S_ANFIS model yield superior to those of F_ANFIS and MLR models. It can be judged from results of the Nash-Sutcliffe efficiency coefficient (EC) where S_ANFIS (EC = 94.01%) model can improve the performances of F_ANFIS (EC = 93.00%) and MLR (EC = 92.12%) during the test period, respectively.

Assessment of forest GPP variations in central Italy

2007 ◽  
Vol 37 (10) ◽  
pp. 1944-1953 ◽  
Author(s):  
A. Rodolfi ◽  
M. Chiesi ◽  
G. Tagliaferri ◽  
P. Cherubini ◽  
F. Maselli
Keyword(s):  
Vegetation Index ◽  
Management Practices ◽  
Forest Ecosystems ◽  
Normalized Difference Vegetation Index ◽  
Deciduous Forest ◽  
Meteorological Data ◽  
Central Italy ◽  
Mountain Forest ◽  
Italian Regions ◽  
Local Station

A debate is in progress concerning the possible effects of climate changes on the primary production of both natural and artificial ecosystems. The current investigation builds on the hypothesis that trends of increasing air temperature observed in several Italian regions should positively affect productivity of mountain forest ecosystems. Temperature rise in the Mugello valley (central Italy) in the period 1986–2001 was first confirmed by the analysis of data from a local station. The effects of this rise on the productivity of deciduous forest ecosystems (dominated by beech, Fagus sylvatica L.) were then analysed through estimates of the fraction of absorbed photosynthetically active radiation (FAPAR) derived from the US National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer satellite normalized difference vegetation index (NDVI) data. The use of a simplified parametric model (C-Fix) then allowed the combination of these FAPAR estimates with meteorological data (temperature and radiation) to produce annual values of forest gross primary productivity (GPP). Finally, validation of these GPP estimates was carried out by a comparison with dendrochronological measurements taken in the study forests. Because tree measurements were affected by external factors not exclusively related to forest GPP (stand aging, management practices, etc.), the comparison gave positive results only after applying a detrending operation to both series of annual GPP estimates and dendrochronological data. These results are a first indication that the rise in temperature that has occurred in Italy in the last decades has positively affected the productivity of mountain forest ecosystems.

A handy irrigation management method through meteorological data. Case study in N. Greece

2014 ◽  
Vol 16 (2) ◽  
pp. 219-228
Keyword(s):  
Irrigation Water ◽  
Land Reclamation ◽  
Meteorological Data ◽  
Irrigation Management ◽  
Daily Evapotranspiration ◽  
The Common ◽  
Management Method ◽  
The Times ◽  
First Time

<div> <p>Crop irrigation, especially in irrigation networks, often consumes larger quantities of irrigation water than necessary since most of the times irrigation is carried out empirically and not based on actual crop requirements. The aim of this work is the management of irrigation water though the use of meteorological data. This approach was utilized for the first time in Greece and applied in a pilot area of about 6,000 ha at the Local Organization of Land Reclamation in Nigrita. The method is based on accurate calculation of daily evapotranspiration of the common cultivations at the area (maize, cotton, alfalfa), using meteorological data. Thus irrigation is organized based on actual water consumption of the crops ensuring the qualitative and quantitative characteristics of their products.</p> </div> <p>&nbsp;</p>

scholarly journals Hydrochemical determination of source water contributions to Lake Lungo and Lake Ripasottile (central Italy)

2016 ◽  
Author(s):  
Claire Archer ◽  
Paula Noble ◽  
David Kreamer ◽  
Vincenzo Piscopo ◽  
Marco Petitta ◽  
...  
Keyword(s):  
Lake Water ◽  
Dissolved Inorganic Carbon ◽  
Meteorological Data ◽  
Central Italy ◽  
Ion Concentration ◽  
Supporting Evidence ◽  
Environmental Tracers ◽  
Major Ion ◽  
Temperature And Precipitation ◽  
Different Response

<p>Lake Lungo and Lake Ripasottile are two shallow (4-5 m) lakes located in the Rieti Basin, central Italy, that have been described previously as surface outcroppings of the groundwater table. In this work, the two lakes as well as springs and rivers that represent their potential source waters are characterized physio-chemically and isotopically, using a combination of environmental tracers. Temperature and pH were measured and water samples were analyzed for alkalinity, major ion concentration, and stable isotope (δ<sup>2</sup>H, δ<sup>18</sup>O, δ<sup>13</sup>C of dissolved inorganic carbon, and δ<sup>34</sup>S and δ<sup>18</sup>O of sulfate) composition.  Chemical data were also investigated in terms of local meteorological data (air temperature, precipitation) to determine the sensitivity of lake parameters to changes in the surrounding environment. Groundwater represented by samples taken from Santa Susanna Spring was shown to be distinct with SO<sub>4</sub><sup>2- </sup>and Mg<sup>2+ </sup>content of 270 and 29 mg/L, respectively, and heavy sulfate isotopic composition (δ<sup>34</sup>S=15.2 ‰ and δ<sup>18</sup>O=10‰). Outflow from the Santa Susanna Spring enters Lake Ripasottile <em>via</em> a canal and both spring and lake water exhibits the same chemical distinctions and comparatively low seasonal variability. Major ion concentrations in Lake Lungo are similar to the Vicenna Riara Spring and are interpreted to represent the groundwater locally recharged within the plain. The δ<sup>13</sup>C<sub>DIC</sub> exhibit the same groupings as the other chemical parameters, providing supporting evidence of the source relationships. Lake Lungo exhibited exceptional ranges of δ<sup>13</sup>C<sub>DIC </sub>(±5 ‰) and δ<sup>2</sup>H, δ<sup>18</sup>O (±5 ‰ and ±7 ‰, respectively), attributed to sensitivity to seasonal changes. The hydrochemistry results, particularly major ion data, highlight how the two lakes, though geographically and morphologically similar, represent distinct hydrochemical facies. These data also show a different response in each lake to temperature and precipitation patterns in the basin that may be attributed to lake water retention time. The sensitivity of each lake to meteorological patterns can be used to understand the potential effects from long-term climate variability.</p>

scholarly journals Analysis of rainfed alfalfa evapotranspiration measured by an eddy covariance system

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
A. Vinci ◽  
L. Vergni ◽  
F. Todisco ◽  
F. Mannocchi
Keyword(s):  
Soil Water ◽  
Eddy Covariance ◽  
Statistical Tests ◽  
Meteorological Data ◽  
Central Italy ◽  
Original Data ◽  
Water Model ◽  
Growth Stages ◽  
Concentration Data ◽  
Eddy Covariance System

The aim of this study was to quantify the evapotranspiration (ETec) of a rainfed alfalfa crop using the eddy covariance technique. The study was carried out during the alfalfa growing seasons (April- August 2009, April-August 2010) at the experimental farm of the University of Perugia. In central Italy alfalfa is grown for 3 to 4 years continuously, with at least 3 cutting cycles for year (usually between April and August) and a dormant period in winter. For the quantification of ETec an open-path eddy covariance system (EC) was used. The derivation of water and energy fluxes starting from raw wind, temperature and gas concentration data by means of the EC technique implies a remarkably long sequence of operations including calibration, corrections and statistical tests for assessing data quality. These operations were carried out by the EddyPro® software. After that, the output data were used for the flux-partitioning and all original data, flagged with a quality indicator with non-turbulent conditions, were dismissed. Then the gap-filling of the EC and meteorological data was performed to obtain reliable values. Furthermore the test of the energy balance closure gave satisfactory results. The ETec dynamics were consistent with the growth stages and the cuttings during both 2009 and 2010. Furthermore the comparison between the tabulated crop coefficients (Kc) and the ratio of ETec to reference evapotranspiration (ET0) was performed. This analysis showed a good agreement during the 2nd cutting cycle (May-June) for both 2009 and 2010, whilst during the 3rd cutting cycle (July-August) the ratio ETec/ET0 was considerably lower than Kc for both years. The reason of this behavior was found in the presence of water stress conditions during the last cutting cycle. This fact was confirmed by the application of a bucket soil water model, used as an exploratory, not confirmatory, tool to analyze the soil water availability dynamics during the growing season. Additional measurement campaigns will be carried out in order to deepen the knowledge about the Kc dynamics in rainfed crops and to assess the productivity of water under various meteorological and agricultural conditions.

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