scholarly journals Estimation of vegetation cover resilience from satellite time series

2008 ◽  
Vol 5 (1) ◽  
pp. 511-546 ◽  
Author(s):  
T. Simoniello ◽  
M. Lanfredi ◽  
M. Liberti ◽  
R. Coppola ◽  
M. Macchiato
Keyword(s):  
Time Series ◽  
Vegetation Cover ◽  
Initial State ◽  
Dynamic Component ◽  
State Recovery ◽  
Vegetation Activity ◽  
Recovery Times ◽  
The Mediterranean ◽  
Cover Class ◽  
High Level

Abstract. Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity. In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis methodologies, 8 km AVHRR-NDVI data could be useful for capturing details on vegetation cover activity at local scale even in complex territories such as that of the Italian peninsula.

scholarly journals Estimation of vegetation cover resilience from satellite time series

2008 ◽  
Vol 12 (4) ◽  
pp. 1053-1064 ◽  
Author(s):  
T. Simoniello ◽  
M. Lanfredi ◽  
M. Liberti ◽  
R. Coppola ◽  
M. Macchiato
Keyword(s):  
Time Series ◽  
Vegetation Cover ◽  
Initial State ◽  
Dynamic Component ◽  
State Recovery ◽  
Vegetation Activity ◽  
Recovery Times ◽  
The Mediterranean ◽  
Cover Class ◽  
High Level

Abstract. Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity. In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis methodologies, 8 km AVHRR-NDVI data could be useful for capturing details on vegetation cover activity at local scale even in complex territories such as that of the Italian peninsula.

scholarly journals The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm

2017 ◽  
Vol 9 (11) ◽  
pp. 1095 ◽  
Author(s):  
Emmihenna Jääskeläinen ◽  
Terhikki Manninen ◽  
Johanna Tamminen ◽  
Marko Laine
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Land Cover Class ◽  
Cover Class ◽  
Aerosol Index

scholarly journals Long-term monitoring programme of the hydrological variability in the Mediterranean Sea: a first overview of the HYDROCHANGES network

Ocean Science ◽  
2013 ◽  
Vol 9 (2) ◽  
pp. 301-324 ◽  
Author(s):  
K. Schroeder ◽  
C. Millot ◽  
L. Bengara ◽  
S. Ben Ismail ◽  
M. Bensi ◽  
...  
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Sampling Interval ◽  
Global Changes ◽  
Hydrological Variability ◽  
Long Term Monitoring ◽  
The Mediterranean ◽  
Set Up ◽  
Term Monitoring

Abstract. The long-term monitoring of basic hydrological parameters (temperature and salinity), collected as time series with adequate temporal resolution (i.e. with a sampling interval allowing the resolution of all important timescales) in key places of the Mediterranean Sea (straits and channels, zones of dense water formation, deep parts of the basins), constitute a priority in the context of global changes. This led CIESM (The Mediterranean Science Commission) to support, since 2002, the HYDROCHANGES programme (http//www.ciesm.org/marine/programs/hydrochanges.htm), a network of autonomous conductivity, temperature, and depth (CTD) sensors, deployed on mainly short and easily manageable subsurface moorings, within the core of a certain water mass. The HYDROCHANGES strategy is twofold and develops on different scales. To get information about long-term changes of hydrological characteristics, long time series are needed. But before these series are long enough they allow the detection of links between them at shorter timescales that may provide extremely valuable information about the functioning of the Mediterranean Sea. The aim of this paper is to present the history of the programme and the current set-up of the network (monitored sites, involved groups) as well as to provide for the first time an overview of all the time series collected under the HYDROCHANGES umbrella, discussing the results obtained thanks to the programme.

scholarly journals Mediterranean Sea climatic indices: monitoring long term variability and climate changes

2018 ◽  
Author(s):  
Athanasia Iona ◽  
Athanasios Theodorou ◽  
Sarantis Sofianos ◽  
Sylvain Watelet ◽  
Charles Troupin ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Mediterranean Sea ◽  
Climate Changes ◽  
Salt Content ◽  
Climatic Indices ◽  
In Situ Observations ◽  
The Mediterranean

Abstract. We present a new product composed of a set of thermohaline climatic indices from 1950 to 2015 for the Mediterranean Sea such as decadal temperature and salinity anomalies, their mean values over selected depths, decadal ocean heat and salt content anomalies at selected depth layers as well as their long times series. It is produced from a new high-resolution climatology of temperature and salinity on a 1/8° regular grid based on historical high quality in situ observations. Ocean heat and salt content differences between 1980–2015 and 1950–1979 are compared for evaluation of the climate shift in the Mediterranean Sea. The spatial patterns of heat and salt content shifts demonstrate in greater detail than ever before that the climate changes differently in the several regions of the basin. Long time series of heat and salt content for the period 1950 to 2015 are also provided which indicate that in the Mediterranean Sea there is a net mean volume warming and salting since 1950 with acceleration during the last two decades. The time series also show that the ocean heat content seems to fluctuate on a cycle of about 40 years and seems to follow the Atlantic Multidecadal Oscillation climate cycle indicating that the natural large scale atmospheric variability could be superimposed on to the warming trend. This product is an observations-based estimation of the Mediterranean climatic indices. It relies solely on spatially interpolated data produced from in-situ observations averaged over decades in order to smooth the decadal variability and reveal the long term trends with more accuracy. It can provide a valuable contribution to the modellers' community, next to the satellite-based products and serve as a baseline for the evaluation of climate-change model simulations contributing thus to a better understanding of the complex response of the Mediterranean Sea to the ongoing global climate change. The product is available here: https://doi.org/10.5281/zenodo.1210100.

scholarly journals The wind and wave atlas of the Mediterranean Sea - the calibration phase

2005 ◽  
Vol 2 ◽  
pp. 255-257 ◽  
Author(s):  
L. Cavaleri
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Extreme Values ◽  
Grid Point ◽  
Local Geometry ◽  
Weather Forecasts ◽  
Medium Range ◽  
Best Fitting ◽  
The Mediterranean ◽  
Calibration Coefficients

Abstract. Within the WW-Medatlas project, sponsored by the Italian, French and Greek Navies, an extensive atlas of the wind and wave conditions in the Mediterranean Sea has been completed. The atlas is based on the information derived from the archive of the European Centre for Medium-Range Weather Forecasts, UK, then calibrated on the base of the data available from the ERS1-2 and Topex satellites. The calibration is required because the wind, hence the wave, data are normally strongly underestimated in the enclosed seas. The calibration has been done deriving the model values at each satellite position, typically at 7 km intervals. The co-located values have then been assigned to the closest grid point. This has provided a substantial number of couples of data at each point, then used to derive, by best-fitting technique, the correction required. This turns out to vary amply throughout the basin, according to the local geometry and orography. The calibration coefficients, different for wind and waves, have been used to correct the original fields and the time series at the single points. Using the calibrated data, extensive statistics have been derived, both as fields and at each point, including extreme values.

scholarly journals A simple approach for monitoring vegetation change using time series remote sensing analysis: A case study from the Thathe Vondo Area in Limpopo Province, South Africa

2021 ◽  
Vol 117 (7/8) ◽  
Author(s):  
Nndanduleni Muavhi
Keyword(s):  
Time Series ◽  
Vegetation Cover ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Simple Approach ◽  
Limpopo Province ◽  
Difference Image ◽  
Normalised Difference Vegetation Index ◽  
Gain And Loss ◽  
The Difference

This study presents a simple approach of spatiotemporal change detection of vegetation cover based on analysis of time series remotely sensed images. The study was carried out at Thathe Vondo Area, which is characterised by episodic variation of vegetation gain and loss. This variation is attributable to timber and tea plantations and their production cycles, which periodically result in either vegetation gain or loss. The approach presented here was implemented on two ASTER images acquired in 2007 and 2017. It involved the combined use of band combination, unsupervised image classification and Normalised Difference Vegetation Index (NDVI) techniques. True colour composite (TCC) images for 2007 and 2017 were created from combination of bands 1, 2 and 3 in red, blue and green, respectively. The difference image of the TCC images was then generated to show the inconsistencies of vegetation cover between 2007 and 2017. For analytical simplicity and interpretability, the difference image was subjected to ISODATA unsupervised classification, which clustered pixels in the difference image into eight classes. Two ISODATA derived classes were interpreted as vegetation gain and one as vegetation loss. These classes were confirmed as regions of vegetation gain and loss by NDVI values of 2007 and 2017. In addition, the polygons of vegetation gain and loss regions were created and superimposed over the TCC images to further demonstrate the spatiotemporal vegetation change in the area. The vegetation change statistics show vegetation gain and loss of 10.62% and 2.03%, respectively, implying a vegetation gain of 8.59% over the selected decade.

Effects of vegetation as an ecosystem service on the changes in runoff and sediment yield in a Mediterranean semi-arid basin

2021 ◽  
Author(s):  
María Rosario Vidal-Abarca Gutiérrez ◽  
Alberto Martínez-Salvador ◽  
Carmelo Conesa-García ◽  
María Luisa Suárez-Alonso ◽  
Francisco Alonso-Sarria ◽  
...  
Keyword(s):  
Sediment Yield ◽  
Ecosystem Service ◽  
Vegetation Cover ◽  
Pressure Sensors ◽  
Erosion Control ◽  
Water Levels ◽  
Event Scale ◽  
Dynamic Component ◽  
Sediment Loads ◽  
Runoff And Sediment Yield

<p>Semiarid basins contribute significantly to sediment loads, as they are often characterized by torrential flows, source areas with high sediment-producing rates, great availability of erodible material subjected to intense weathering processes, and poor vegetation cover. Vegetation, despite its scarce presence, is a dynamic component of this environment, which provides a range of important ecosystem services such as biodiversity, flood retention, nutrient sink, erosion control and groundwater recharge. This study examines the vegetation responses to the magnitude of peak flows and its contribution to the changes in runoff and sediment yield during the period 1997-2020 in a catchment Mediterranean semiarid basin: The Rambla de la Azohía (southeastern Spain).Vegetation type, density, preferred location and degree of permanence in each sub-basin were analyzed in order to determine their degree of influence on surface runoff and erosion control. Changes in riparian vegetation cover was quantified at large scale for the analysis period (1997-2020), using remotely sensed spatial information, such as satellite images and aerial photographs separated by two years on average (at scales from 1:15000 to 1:30000, and resolution between 0.22 and 0.50 m/pixel). A geo-spatial erosion prediction model was applied to estimate the runoff and sediment load generated at the event scale, taking into account the variability of the vegetation cover in each sub-basin. The simulated outputs of this model were previously calibrated with water levels measured by pressure sensors and suspended sediment records.The results showed both a poor response of vegetation (low incidence in the runoff coefficient) in steep metamorphic watersheds, capable of supplying large sediment loads, and functioned as an efficient ecosystem service (stabilization of slopes and decrease in peak flow) in less steep sub-basins with slopes in the shadow, composed of limestone formations and alluvial fans. This suggests important spatial differences in the vegetation impact, according to other environmental conditions intrinsic to each sub-basin, but also a low overall influence on the temporal variability of sediment fluxes at the event scale. This research was funded by FEDER/Spanish Ministry of Science, Innovation and Universities—State Research Agency (AEI)/Projects CGL2017-84625-C2-1-R and CGL2017-84625-C2-2-R; State Program for Research, Development and Innovation Focused on the Challenges of Society.</p>

scholarly journals Assessing Spatial Limits of Sentinel-2 Data on Arable Crops in the Context of Checks by Monitoring

2020 ◽  
Vol 12 (14) ◽  
pp. 2195 ◽  
Author(s):  
Blanka Vajsová ◽  
Dominique Fasbender ◽  
Csaba Wirnhardt ◽  
Slavko Lemajic ◽  
Wim Devos
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Policy Framework ◽  
Pixel Size ◽  
Control Approach ◽  
Continuous State ◽  
Ndvi Time Series ◽  
High Level ◽  
Sentinel 2

The availability of large amounts of Sentinel-2 data has been a trigger for its increasing exploitation in various types of applications. It is, therefore, of importance to understand the limits above which these data still guarantee a meaningful outcome. This paper proposes a new method to quantify and specify restrictions of the Sentinel-2 imagery in the context of checks by monitoring, a newly introduced control approach within the European Common Agriculture Policy framework. The method consists of a comparison of normalized difference vegetation index (NDVI) time series constructed from data of different spatial resolution to estimate the performance and limits of the coarser one. Using similarity assessment of Sentinel-2 (10 m pixel size) and PlanetScope (3 m pixel size) NDVI time series, it was estimated that for 10% out of 867 fields less than 0.5 ha in size, Sentinel-2 data did not provide reliable evidence of the activity or state of the agriculture field over a given timeframe. Statistical analysis revealed that the number of clean or full pixels and the proportion of pixels lost after an application of a 5-m (1/2 pixel) negative buffer are the geospatial parameters of the field that have the highest influence on the ability of the Sentinel-2 data to qualify the field’s state in time. We specified the following limiting criteria: at least 8 full pixels inside a border and less than 60% of pixels lost. It was concluded that compliance with the criteria still assures a high level of extracted information reliability. Our research proved the promising potential, which was higher than anticipated, of Sentinel-2 data for the continuous state assessment of small fields. The method could be applied to other sensors and indicators.

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