973 resultados para Saranac Lake Region (N.Y.)--Remote-sensing maps.


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In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

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ZUSAMMENFASSUNG Langzeitbeobachtungsstudien zur Landschaftsdynamik inSahelländern stehen generell einem defizitären Angebot anquantitativen Rauminformationen gegenüber. Der in Malivorgefundene lokal- bis regionalräumliche Datenmangelführte zu einer methodologischen Studie, die die Entwicklungvon Verfahren zur multi-temporalen Erfassung und Analyse vonLandschaftsveränderungsdaten beinhaltet. Für den RaumWestafrika existiert in großer Flächenüberdeckunghistorisches Fernerkundungsmaterial in Form hochauflösenderLuftbilder ab den 50er Jahren und erste erdbeobachtendeSatellitendaten von Landsat-MSS ab den 70er Jahren.Multitemporale Langzeitanalysen verlangen zur digitalenReproduzierbarkeit, zur Datenvergleich- undObjekterfaßbarkeit die a priori-Betrachtung derDatenbeschaffenheit und -qualität. Zwei, ohne verfügbare, noch rekonstruierbareBodenkontrolldaten entwickelte Methodenansätze zeigen nichtnur die Möglichkeiten, sondern auch die Grenzen eindeutigerradiometrischer und morphometrischerBildinformationsgewinnung. Innerhalb desÜberschwemmungsgunstraums des Nigerbinnendeltas im ZentrumMalis stellen sich zwei Teilstudien zur Extraktion vonquantitativen Sahelvegetationsdaten den radiometrischen undatmosphärischen Problemen:1. Präprozessierende Homogenisierung von multitemporalenMSS-Archivdaten mit Simulationen zur Wirksamkeitatmosphärischer und sensorbedingter Effekte2. Entwicklung einer Methode zur semi-automatischenErfassung und Quantifizierung der Dynamik derGehölzbedeckungsdichte auf panchromatischenArchiv-Luftbildern Die erste Teilstudie stellt historischeLandsat-MSS-Satellitenbilddaten für multi-temporale Analysender Landschaftsdynamik als unbrauchbar heraus. In derzweiten Teilstudie wird der eigens, mittelsmorphomathematischer Filteroperationen für die automatischeMusterkennung und Quantifizierung von Sahelgehölzobjektenentwickelte Methodenansatz präsentiert. Abschließend wird die Forderung nach kosten- undzeiteffizienten Methodenstandards hinsichtlich ihrerRepräsentativität für die Langzeitbeobachtung desRessourceninventars semi-arider Räume sowie deroperationellen Transferierbarkeit auf Datenmaterial modernerFernerkundungssensoren diskutiert.

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The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

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Successful conservation of tropical montane forest, one of the most threatened ecosystems on earth, requires detailed knowledge of its biogeochemistry. Of particular interest is the response of the biogeochemical element cycles to external influences such as element deposition or climate change. Therefore the overall objective of my study was to contribute to improved understanding of role and functioning of the Andean tropical montane forest. In detail, my objectives were to determine (1) the role of long-range transported aerosols and their transport mechanisms, and (2) the role of short-term extreme climatic events for the element budget of Andean tropical forest. In a whole-catchment approach including three 8-13 ha microcatchments under tropical montane forest on the east-exposed slope of the eastern cordillera in the south Ecuadorian Andes at 1850-2200 m above sea level I monitored at least in weekly resolution the concentrations and fluxes of Ca, Mg, Na, K, NO3-N, NH4-N, DON, P, S, TOC, Mn, and Al in bulk deposition, throughfall, litter leachate, soil solution at the 0.15 and 0.3 m depths, and runoff between May 1998 and April 2003. I also used meteorological data from my study area collected by cooperating researchers and the Brazilian meteorological service (INPE), as well as remote sensing products of the North American and European space agencies NASA and ESA. My results show that (1) there was a strong interannual variation in deposition of Ca [4.4-29 kg ha-1 a-1], Mg [1.6-12], and K [9.8-30]) between 1998 and 2003. High deposition changed the Ca and Mg budgets of the catchments from loss to retention, suggesting that the additionally available Ca and Mg was used by the ecosystem. Increased base metal deposition was related to dust outbursts of the Sahara and an Amazonian precipitation pattern with trans-regional dry spells allowing for dust transport to the Andes. The increased base metal deposition coincided with a strong La Niña event in 1999/2000. There were also significantly elevated H+, N, and Mn depositions during the annual biomass burning period in the Amazon basin. Elevated H+ deposition during the biomass burning period caused elevated base metal loss from the canopy and the organic horizon and deteriorated already low base metal supply of the vegetation. Nitrogen was only retained during biomass burning but not during non-fire conditions when deposition was much smaller. Therefore biomass burning-related aerosol emissions in Amazonia seem large enough to substantially increase element deposition at the western rim of Amazonia. Particularly the related increase of acid deposition impoverishes already base-metal scarce ecosystems. As biomass burning is most intense during El Niño situations, a shortened ENSO cycle because of global warming likely enhances the acid deposition at my study forest. (2) Storm events causing near-surface water flow through C- and nutrient-rich topsoil during rainstorms were the major export pathway for C, N, Al, and Mn (contributing >50% to the total export of these elements). Near-surface flow also accounted for one third of total base metal export. This demonstrates that storm-event related near-surface flow markedly affects the cycling of many nutrients in steep tropical montane forests. Changes in the rainfall regime possibly associated with global climate change will therefore also change element export from the study forest. Element budgets of Andean tropical montane rain forest proved to be markedly affected by long-range transport of Saharan dust, biomass burning-related aerosols, or strong rainfalls during storm events. Thus, increased acid and nutrient deposition and the global climate change probably drive the tropical montane forest to another state with unknown consequences for its functions and biological diversity.

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Il telerilevamento rappresenta un efficace strumento per il monitoraggio dell’ambiente e del territorio, grazie alla disponibilità di sensori che riprendono con cadenza temporale fissa porzioni della superficie terrestre. Le immagini multi/iperspettrali acquisite sono in grado di fornire informazioni per differenti campi di applicazione. In questo studio è stato affrontato il tema del consumo di suolo che rappresenta un’importante sfida per una corretta gestione del territorio, poiché direttamente connesso con i fenomeni del runoff urbano, della frammentazione ecosistemica e con la sottrazione di importanti territori agricoli. Ancora non esiste una definizione unica, ed anche una metodologia di misura, del consumo di suolo; in questo studio è stato definito come tale quello che provoca impermeabilizzazione del terreno. L’area scelta è quella della Provincia di Bologna che si estende per 3.702 km2 ed è caratterizzata a nord dalla Pianura Padana e a sud dalla catena appenninica; secondo i dati forniti dall’ISTAT, nel periodo 2001-2011 è stata la quarta provincia in Italia con più consumo di suolo. Tramite classificazione pixel-based è stata fatta una mappatura del fenomeno per cinque immagini Landsat. Anche se a media risoluzione, e quindi non in grado di mappare tutti i dettagli, esse sono particolarmente idonee per aree estese come quella scelta ed inoltre garantiscono una più ampia copertura temporale. Il periodo considerato va dal 1987 al 2013 e, tramite procedure di change detection applicate alle mappe prodotte, si è cercato di quantificare il fenomeno, confrontarlo con i dati esistenti e analizzare la sua distribuzione spaziale.

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The present work belongs to the PRANA project, the first extensive field campaign of observation of atmospheric emission spectra covering the Far InfraRed spectral region, for more than two years. The principal deployed instrument is REFIR-PAD, a Fourier transform spectrometer used by us to study Antarctic cloud properties. A dataset covering the whole 2013 has been analyzed and, firstly, a selection of good quality spectra is performed, using, as thresholds, radiance values in few chosen spectral regions. These spectra are described in a synthetic way averaging radiances in selected intervals, converting them into BTs and finally considering the differences between each pair of them. A supervised feature selection algorithm is implemented with the purpose to select the features really informative about the presence, the phase and the type of cloud. Hence, training and test sets are collected, by means of Lidar quick-looks. The supervised classification step of the overall monthly datasets is performed using a SVM. On the base of this classification and with the help of Lidar observations, 29 non-precipitating ice cloud case studies are selected. A single spectrum, or at most an average over two or three spectra, is processed by means of the retrieval algorithm RT-RET, exploiting some main IR window channels, in order to extract cloud properties. Retrieved effective radii and optical depths are analyzed, to compare them with literature studies and to evaluate possible seasonal trends. Finally, retrieval output atmospheric profiles are used as inputs for simulations, assuming two different crystal habits, with the aim to examine our ability to reproduce radiances in the FIR. Substantial mis-estimations are found for FIR micro-windows: a high variability is observed in the spectral pattern of simulation deviations from measured spectra and an effort to link these deviations to cloud parameters has been performed.

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Global climate change in recent decades has strongly influenced the Arctic generating pronounced warming accompanied by significant reduction of sea ice in seasonally ice-covered seas and a dramatic increase of open water regions exposed to wind [Stephenson et al., 2011]. By strongly scattering the wave energy, thick multiyear ice prevents swell from penetrating deeply into the Arctic pack ice. However, with the recent changes affecting Arctic sea ice, waves gain more energy from the extended fetch and can therefore penetrate further into the pack ice. Arctic sea ice also appears weaker during melt season, extending the transition zone between thick multi-year ice and the open ocean. This region is called the Marginal Ice Zone (MIZ). In the Arctic, the MIZ is mainly encountered in the marginal seas, such as the Nordic Seas, the Barents Sea, the Beaufort Sea and the Labrador Sea. Formed by numerous blocks of sea ice of various diameters (floes) the MIZ, under certain conditions, allows maritime transportation stimulating dreams of industrial and touristic exploitation of these regions and possibly allowing, in the next future, a maritime connection between the Atlantic and the Pacific. With the increasing human presence in the Arctic, waves pose security and safety issues. As marginal seas are targeted for oil and gas exploitation, understanding and predicting ocean waves and their effects on sea ice become crucial for structure design and for real time safety of operations. The juxtaposition of waves and sea ice represents a risk for personnel and equipment deployed on ice, and may complicate critical operations such as platform evacuations. The risk is difficult to evaluate because there are no long-term observations of waves in ice, swell events are difficult to predict from local conditions, ice breakup can occur on very short time-scales and wave-ice interactions are beyond the scope of current forecasting models [Liu and Mollo-Christensen, 1988,Marko, 2003]. In this thesis, a newly developed Waves in Ice Model (WIM) [Williams et al., 2013a,Williams et al., 2013b] and its related Ocean and Sea Ice model (OSIM) will be used to study the MIZ and the improvements of wave modeling in ice infested waters. The following work has been conducted in collaboration with the Nansen Environmental and Remote Sensing Center and within the SWARP project which aims to extend operational services supporting human activity in the Arctic by including forecast of waves in ice-covered seas, forecast of sea-ice in the presence of waves and remote sensing of both waves and sea ice conditions. The WIM will be included in the downstream forecasting services provided by Copernicus marine environment monitoring service.

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Climate is an important control on biomass burning, but the sensitivity of fire to changes in temperature and moisture balance has not been quantified. We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.