Long-Term Monitoring and Prediction of Ecosystem Using Remote Sensing and the CLUE-S Model: Sakaerat Environmental Research Station

2012 ◽  
pp. 309-319 ◽  
Author(s):  
Yongyut Trisurat
Keyword(s):  
Remote Sensing ◽  
Environmental Research ◽  
Research Station ◽  
Long Term Monitoring ◽  
S Model ◽  
Term Monitoring

scholarly journals Long-term monitoring of NDVI changes by remote sensing to assess the vulnerability of threatened plants

2022 ◽  
Vol 265 ◽  
pp. 109428
Author(s):  
L. Matas-Granados ◽  
M. Pizarro ◽  
L. Cayuela ◽  
D. Domingo ◽  
D. Gómez ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Threatened Plants ◽  
Long Term Monitoring ◽  
Term Monitoring

LONG-TERM MONITORING OF WETLANDS VIA REMOTE SENSING AND GIS: A CASE STUDY FROM TURKEY

2018 ◽  
Author(s):  
Nebiye Musaoglu ◽  
◽  
Aysegul Tanik ◽  
M. Umit Gumusay ◽  
Adalet Dervisoglu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing And Gis ◽  
Long Term Monitoring ◽  
Term Monitoring

scholarly journals Long-term monitoring of persistent organic pollutants (POPs) at the Norwegian Troll station in Dronning Maud Land, Antarctica

2013 ◽  
Vol 13 (14) ◽  
pp. 6983-6992 ◽  
Author(s):  
R. Kallenborn ◽  
K. Breivik ◽  
S. Eckhardt ◽  
C. R. Lunder ◽  
S. Manø ◽  
...  
Keyword(s):  
Long Range ◽  
Organic Pollutants ◽  
Persistent Organic Pollutants ◽  
Long Range Transport ◽  
Research Station ◽  
Range Transport ◽  
Dronning Maud Land ◽  
Long Term Monitoring ◽  
Term Monitoring

Abstract. A first long-term monitoring of selected persistent organic pollutants (POPs) in Antarctic air has been conducted at the Norwegian research station Troll (Dronning Maud Land). As target contaminants 32 PCB congeners, α- and γ-hexachlorocyclohexane (HCH), trans- and cis-chlordane, trans- and cis-nonachlor, p,p'- and o,p-DDT, DDD, DDE as well as hexachlorobenzene (HCB) were selected. The monitoring program with weekly samples taken during the period 2007–2010 was coordinated with the parallel program at the Norwegian Arctic monitoring site (Zeppelin mountain, Ny-Ålesund, Svalbard) in terms of priority compounds, sampling schedule as well as analytical methods. The POP concentration levels found in Antarctica were considerably lower than Arctic atmospheric background concentrations. Similar to observations for Arctic samples, HCB is the predominant POP compound, with levels of around 22 pg m−3 throughout the entire monitoring period. In general, the following concentration distribution was found for the Troll samples analyzed: HCB > Sum HCH > Sum PCB > Sum DDT > Sum chlordanes. Atmospheric long-range transport was identified as a major contamination source for POPs in Antarctic environments. Several long-range transport events with elevated levels of pesticides and/or compounds with industrial sources were identified based on retroplume calculations with a Lagrangian particle dispersion model (FLEXPART).

Remote sensing data and field survey activities for monitoring the evolution of forest systems after coppicing and soil erosion: A case study in Sardinia (Italy)

2020 ◽  
Author(s):  
Filippo Giadrossich ◽  
Antonio Ganga ◽  
Sergio Campus ◽  
Ilenia Murgia ◽  
Irene Piredda ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Vegetation Indices ◽  
Monitoring Network ◽  
Remote Sensing Data ◽  
Forest Stands ◽  
Sensing Data ◽  
Long Term Monitoring ◽  
Term Monitoring

<p>The practice of coppicing is debated in the literature for the risk factors associated with soil erosion. Although erosion experiments provide useful data for estimating the susceptibility to soil erosion, there are many open questions that cannot be solved in isolated experiments, but which can be assessed by activating a long-term monitoring process. In this way, it is possible to correctly frame the spatial and temporal scale of soil erosion in coppice forests. </p><p>The aim of the work is to evaluate the effectiveness of the use of remote sensing data in combination with field data, for monitoring the evolution of forest stands interested by coppicing in relation to soil erosion. </p><p>We have installed a long-term monitoring network for erosion estimation, while Sentinel-2C satellite data were used for the period 2016-2018. Starting from this dataset, a selection of vegetation indices was calculated and compared to the morphological and topographical parameters of the study area, as well as the above-ground data collected during field activities. Using the Canonical Correspondences Analysis (CCA) the relationships between the matrix of vegetation indices, topographic and vegetational parameters and the respective performances of this protocol have been explored in order to describe the evolution of the forest stands in the study area associated to soil losses.</p>

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