Optical remote sensing of coastal plumes and run-off in the Mediterranean region

1998 ◽  
Vol 4 (1) ◽  
pp. 51-58 ◽  
Author(s):  
V. Barale ◽  
D. Larkin
Keyword(s):  
Remote Sensing ◽  
Mediterranean Region ◽  
Optical Remote Sensing ◽  
Run Off ◽  
The Mediterranean

scholarly journals Vegetation Water Use Based on a Thermal and Optical Remote Sensing Model in the Mediterranean Region of Doñana

2018 ◽  
Vol 10 (7) ◽  
pp. 1105 ◽  
Author(s):  
Maria Moyano ◽  
Monica Garcia ◽  
Alicia Palacios-Orueta ◽  
Lucia Tornos ◽  
Joshua Fisher ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Use ◽  
Mediterranean Region ◽  
Optical Remote Sensing ◽  
Remote Sensing Model ◽  
Sensing Model ◽  
The Mediterranean ◽  
Vegetation Water

Open Waters Optical Remote Sensing of the Mediterranean Sea

2008 ◽  
pp. 103-116 ◽  
Author(s):  
R. Santoleri ◽  
G. Volpe ◽  
S. Marullo ◽  
B. Buongiorno Nardelli
Keyword(s):  
Remote Sensing ◽  
Mediterranean Sea ◽  
Optical Remote Sensing ◽  
The Mediterranean

scholarly journals Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece

2019 ◽  
Author(s):  
Polina Lemenkova
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Environmental Factors ◽  
Spectral Reflectance ◽  
Mediterranean Region ◽  
The World ◽  
Seagrass Mapping ◽  
Resolution Imaging ◽  
The Mediterranean ◽  
Remote Sensing Techniques

Type: Master's Thesis (M.Sc.).School: University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC).Supervisors: Albertus G. (Bert) Toxopeus, Valentijn Venus. Location: Netherlands, Enschede (Overijssel Province).The seagrasses, a unique group of aquatic plants, create complex, extremely diversified and productive ecological systems in the littoral coastal zones. The only flowering plant in the world that is able to live completely submerged, seagrasses play vital role in the marine ecosystems of the World Ocean. Seagrasses are the most important component in the environmental food chain of the coastal ecosystems, being a vital food source for various marine species (e.g. fish, dugongs, turtles, swans), and a producer of organic matter, which is the very basis of the food web. The P.oceanica seagrass is an endemic for the Mediterranean region, and a main species in the marine coastal environment of Greece. Meadows of P.oceanica are subjected to the human activities, because they occur in coastal areas, where they are affected both by anthropogenic and by climatic and environmental factors. Nowadays P.oceanica is in the alarming state of regression, because of the deterioration of the environment in the Mediterranean Sea. Due to these reasons, P.oceanica is a protected species since 1988 in some European countries (France). Monitoring P.oceanica is therefore an important contribution to the saving and protecting the environment of Mediterranean region. The current MSc thesis focuses on the monitoring of seagrass P.oceanica along the northern coasts of Crete Island, Greece, and investigates the application of the remote sensing techniques for the seagrass mapping. This research was articulated in two parts, where the first one involves an ecological approach to the seagrass distribution in various regions around the globe and the experience of seagrass monitoring nowadays. The second part of this work has technical character and investigates the application of the remote sensing techniques towards seagrass mapping. It, furthermore, focuses on the optical properties of the P.oceanica and other seafloor cover types, and studies distinguishability of various seafloor cover types. Studies of the optical characteristics of separate seafloor cover types were made with purpose to clarify, whether their spectral properties change with varying environmental conditions.Special attention has been drawn on the role of environmental factors on the distribution of P.oceanica along the coasts of Crete, and in particular, how the optical properties of the seafloor cover types, i.e. spectral reflectance, are being changed under varying external conditions, e.g. water column, amount of suspended particles and sediments in the seawater, and water temperature. For this purpose we studied differences in the spectral reflectance of P.oceanica and other bottom cover types at three distinct depths. The diverse spectral values entail variations in optical properties of the seafloor cover types at changing environmental conditions. We applied WASI Water Color Simulator (WASI) simulation techniques for the modelling of the optical parameters of various seafloor cover types by various spaceborne imaging spectrometers (MEdium Resolution Imaging Spectrometer (MERIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Coastal Zone Color Scanner (CZCS) and MODerate resolution Imaging Spectroradiometer (MODIS)), in order to understand their suitability and possible limitations for the seagrass mapping. Fieldwork research sites were presented by separate locations on the northern coast of Crete region (Ligaria, Agia Pelagia, Xerocampos). The additional measurements of the reflectance spectra of the seawater with and without sediments have been made in aquarium tank in 2009 by means of Trios-RAMSES spectroradiometer. Parallel to the collection of spectra signatures, we captured the imagery for the seagrass mapping, which consists of the aerial images from the Google Earth website and the satellite Landsat TM and ETM+ scenes.

Trophic State Index derivation through the remote sensing of Case-2 water bodies in the Mediterranean region

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Christiana Papoutsa ◽  
Evangelos Akylas ◽  
Diofantos Hadjimitsis
Keyword(s):  
Remote Sensing ◽  
Regression Model ◽  
Regression Models ◽  
Mediterranean Region ◽  
Trophic State ◽  
Landsat Tm ◽  
Water Bodies ◽  
Trophic State Index ◽  
State Index ◽  
The Mediterranean

AbstractThe main goal of this study is the derivation of Carlson’s Trophic State Index (TSI) through the remote sensing of four different Case-2 waters in the Mediterranean region such as Cyprus and Greece. TSISD is derived through extensive field ground campaign of Secchi Disk Depth measurements for the Asprokremmos Dam, located in Paphos District in Cyprus; Alyki Salt Lake, located in Larnaca District in Cyprus; and in Karla Lake, located in Volos District in Greece; and finally to three coastal water areas in the Limassol coastal area. Several regression models have been applied in order to develop the best regression model between the TSISD and in-band reflectance values for Landsat TM/ETM derived from spectroradiometric measurements using a GER-1500 field spectroradiometer over the main case study area in Asprokremmos Dam in Cyprus. Finally, we apply several regression models for Asprokremmos Dam for retrieving the suitable Landsat TM/ETM band or band combinations (obtained from field spectroradiometric measurements) in which TSISD can be determined. Indeed, the best regression model has been obtained by correlating ‘TSI Versus Band2/Band3’, with R2=0.89. All field TSISD and in-band reflectance values from the four different water bodies have been used to develop the best fitted model for the established TSI SD Versus Band2/Band3 model. We find that the exponential regression model provides the best fitted equation over the four different water bodies.

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