119,713 research outputs found

    Land cover classification using multi-temporal MERIS vegetation indices

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    The spectral, spatial, and temporal resolutions of Envisat's Medium Resolution Imaging Spectrometer (MERIS) data are attractive for regional- to global-scale land cover mapping. Moreover, two novel and operational vegetation indices derived from MERIS data have considerable potential as discriminating variables in land cover classification. Here, the potential of these two vegetation indices (the MERIS global vegetation index (MGVI), MERIS terrestrial chlorophyll index (MTCI)) was evaluated for mapping eleven broad land cover classes in Wisconsin. Data acquired in the high and low chlorophyll seasons were used to increase inter-class separability. The two vegetation indices provided a higher degree of inter-class separability than data acquired in many of the individual MERIS spectral wavebands. The most accurate landcover map (73.2%) was derived from a classification of vegetation index-derived data with a support vector machine (SVM), and was more accurate than the corresponding map derived from a classification using the data acquired in the original spectral wavebands

    Is there a close association between "soils" and "vegetation"? : A case study from central western New South Wales

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    The assumption that ‘soils’ and ‘vegetation’ are closely associated was tested by describing soils and vegetation along a Travelling Stock Reserve west of Grenfell, New South Wales (lat 33° 55’S, long 147° 45’E). The transect was selected on the basis of (a) minimising the effects of non-soil factors (human interference, climate and relief) on vegetation and (b) the presence of various soil and vegetation types as indicated by previous mapping. ‘Soils’ were considered at three levels: soil landscapes (a broad mapping unit widely used in central western NSW), soil types (according to a range of classifications) and soil properties (depth, pH, etc.). ‘Vegetation’ was considered in three ways: vegetation type (in various classifications), density/floristic indices (density of woody species, abundance of native species, etc.) and presence/absence of individual species. Sites along the transect were grouped according to soil landscapes or soil types and compared to vegetation types or indices recorded at the sites. Various measures indicated low associations between vegetation types and soil landscapes or soil types. Except for infrequent occurrences of a soil type or landscape, any one soil type or landscape was commonly associated with a number of vegetation types and any one vegetation type was associated with a number of soil landscapes or soil types. However, significant associations between some vegetation indices, mainly density or numbers of woody species, and some soil landscapes and soil types were evident. Although many species were relatively ubiquitous, some groups of species that were restricted to one or two soil types were identified. Canonical Correspondence Analysis provided some suggestions as to which properties (e.g. texture) of these soils were associated with the presence of particular species

    An empirical, graphical, and analytical study of the relationship between vegetation indices

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    The development of formulae for the reduction of multispectral scanner measurements to a single value (vegetation index) for predicting and assessing vegetative characteristics is addressed. The origin, motivation, and derivation of some four dozen vegetation indices are summarized. Empirical, graphical, and analytical techniques are used to investigate the relationships among the various indices. It is concluded that many vegetative indices are very similar, some being simple algebraic transforms of others

    Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

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    Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p <0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p <0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management

    Estimation of photosynthetic capacity using MODIS polarization: 1988 proposal to NASA Headquarters

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    The remote sensing community has clearly identified the utility of NDVI (normalized difference vegetation index) and SR (simple ratio) and other vegetation indices for estimating such metrics of landscape ecology as green foliar biomass, photosynthetic capacity, and net primary production. Both theoretical and empirical investigations have established cause and effect relationships between the photosynthetic process in plant canopies and these combinations of remotely sensed data. Yet it has also been established that the relationships exhibit considerable variability that appears to be ecosystem-dependent and may represent a source of ecologically important information. The overall hypothesis of this proposal is that the ecosystem-dependent variability in the various vegetation indices is in part attributable to the effects of specular reflection. The polarization channels on MODIS provide the potential to estimate this specularly reflected light and allow the modification of the vegetation indices to better measure the photosynthetic process in plant canopies. In addition, these polarization channels potentially provide additional ecologically important information about the plant canopy

    A look at the commonly used LANDSAT vegetation indices

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    The origins, development, and logic of the indices are discussed. The relationships of the indices to ground-based measurements of vegetation are highlighted. An effort was made to preserve the order in which the various indices appeared in the literature in order to historically trace their underlying concepts

    Effect of Cultivar on Chlorophyll Meter and Canopy Reflectance Measurements in Cucumber

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    Optical sensors can be used to assess crop N status to assist with N fertilizer management. Differences between cultivars may affect optical sensor measurement. Cultivar effects on measurements made with the SPAD-502 (Soil Plant Analysis Development) meter and the MC-100 (Chlorophyll Concentration Meter), and of several vegetation indices measured with the Crop Circle ACS470 canopy reflectance sensor, were assessed. A cucumber (Cucumis sativus L.) crop was grown in a greenhouse, with three cultivars. Each cultivar received three N treatments, of increasing N concentration, being deficient (N1), sufficient (N2) and excessive (N3). There were significant differences between cultivars in the measurements made with both chlorophyll meters, particularly when N supply was sufficient and excessive (N2 and N3 treatments, respectively). There were no consistent differences between cultivars in vegetation indices. Optical sensor measurements were strongly linearly related to leaf N content in each of the three cultivars. The lack of a consistent effect of cultivar on the relationship with leaf N content suggests that a unique equation to estimate leaf N content from vegetation indices can be applied to all three cultivars. Results of chlorophyll meter measurements suggest that care should be taken when using sufficiency values, determined for a particular cultiva

    Performance of intrinsic and soil line-based vegetation indices to mangrove mapping in Malaysia.

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    The use of vegetation indices of remote sensing data in vegetation mapping has been long recognised. However, the accuracy of mapping through the use of vegetation indices model has limitations, and has so far not been investigated. This study analysed the performance of the several intrinsic-based vegetation indices (Normalized Difference Vegetation Index-NDVI and Ratio Vegetation Index- RVI) and soil line-based vegetation indices (Perpendicular Vegetation Index-PVI, Soil-Adjusted Vegetation Index-SAVI and Modified Soil-Adjusted Vegetation Index-MSAVI) for mangrove mapping in Kelantan Delta, Malaysia. Landsat TM was used as a primary data set to derive mangrove vegetation class from five vegetation indices model. A total of five mangrove classes consisting of Avicennia-Sonneratia, Avicennia, Acanthus-Sonneratia, Mixed-Acrostichum and Mixed Sonneratia with accuracy 72.67% were determined from unsupervised classification. Then the models were applied on classified image, resulting in mangrove classes which were mapped into three and four classes, respectively. The performance of each VI’s was analysed in accuracy assessment. The accuracy assessment of vegetation indices were ranged from 69.17% to 79.14%. The results revealed that the SAVI was the better performance discriminate mangrove class amongst the four classes compared to others indices with accuracy 79.14%. It might be due to sensitiveness of SAVI model in discriminating the full range of vegetation covers in muddy area. The capability of Landsat TM in mapping mangrove in this study using VI’s models showed the better result, However, the performance of VI’s need to be further investigated for specific use of mangrove resources. This is important where accurate information on mangrove biodiversity status in all habitat level is needed for conservation and monitoring towards achieving sustainable development to the country

    The Use of Landsat 8 and Sentinel-2 Data and Meterological Observations for Winter Wheat Yield Assessment

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    This study focuses on winter wheat yield assessment from NASA's Harmonized Landsat Sentinel-2 (HLS) product and meteorological observations through phenological fitting. Vegetation indices (VIs), namely difference vegetation index (DVI), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI2), extracted from satellite optical data, are fitted per pixel against accumulated growing degree days (AGDD) using a quadratic function. Accumulated VIs are correlated against winter wheat yields. Results show a better performance from DVI compared to NDVI and EVI2
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