527 resultados para MODIS-NDVI


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"Narratio brevis rervm à Societate in regno magni Mogor gestarum, transcripta ex literis p. Hieronymi Xavier Societatis Iesv, anni 1598. & p. Emmanyelis Pigneiro, anni 1598.": p. 122-144.

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Thesis (Master's)--University of Washington, 2016-06

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The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

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Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference

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In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

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A cikkben egy nemesnyárültetvény őszi lombszíneződésének kutatását összegezzük, mellyel előkészítjük egy – a 21. században várható éghajlatváltozás hatására bekövetkező lombszíneződés-változást elemző – fenológiai modell építését. Bemutatjuk a kutatásba vont taxon (Populus X canadensis) kiválasztásának szempontjait, valamint a vizsgálati helyszín (Tiszaroff) kijelölésének fontosabb ismérveit. Áttekintjük a szabadon hozzáférhető adatokat szolgáltató szenzorokat és a lombszínre vonatkozó, korábban publikált, különböző mérőszámokat. A MODIS-szenzor három kiválaszott színcsatornájára építve újabb lombszíneződési mérőszámokat alkotunk, és ezeket kiértékeljük abból a szempontból, hogy várhatóan mennyire alkalmazhatóak az őszi lombszíneződés jövőbeli fenológiai eltolódásának és megváltozásának modellezése során.

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Established as a National Park in 1980, Biscayne National Park (BISC) comprises an area of nearly 700 km2 , of which most is under water. The terrestrial portions of BISC include a coastal strip on the south Florida mainland and a set of Key Largo limestone barrier islands which parallel the mainland several kilometers offshore and define the eastern rim of Biscayne Bay. The upland vegetation component of BISC is embedded within an extensive coastal wetland network, including an archipelago of 42 mangrove-dominated islands with extensive areas of tropical hardwood forests or hammocks. Several databases and vegetation maps describe these terrestrial communities. However, these sources are, for the most part, outdated, incomplete, incompatible, or/and inaccurate. For example, the current, Welch et al. (1999), vegetation map of BISC is nearly 10 years old and represents the conditions of Biscayne National Park shortly after Hurricane Andrew (August 24, 1992). As a result, a new terrestrial vegetation map was commissioned by The National Park Service Inventory and Monitoring Program South Florida / Caribbean Network.