977 resultados para Normalize different vegetation indices


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Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI. The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions.

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Satellite image data have become an important source of information for monitoring vegetation and mapping land cover at several scales. Beside this, the distribution and phenology of vegetation is largely associated with climate, terrain characteristics and human activity. Various vegetation indices have been developed for qualitative and quantitative assessment of vegetation using remote spectral measurements. In particular, sensors with spectral bands in the red (RED) and near-infrared (NIR) lend themselves well to vegetation monitoring and based on them [(NIR - RED) / (NIR + RED)] Normalized Difference Vegetation Index (NDVI) has been widespread used. Given that the characteristics of spectral bands in RED and NIR vary distinctly from sensor to sensor, NDVI values based on data from different instruments will not be directly comparable. The spatial resolution also varies significantly between sensors, as well as within a given scene in the case of wide-angle and oblique sensors. As a result, NDVI values will vary according to combinations of the heterogeneity and scale of terrestrial surfaces and pixel footprint sizes. Therefore, the question arises as to the impact of differences in spectral and spatial resolutions on vegetation indices like the NDVI and their interpretation as a drought index. During 2012 three locations (at Salamanca, Granada and Córdoba) were selected and a periodic pasture monitoring and botanic composition were achieved. Daily precipitation, temperature and monthly soil water content were measurement as well as fresh and dry pasture weight. At the same time, remote sensing images were capture by DEIMOS-1 and MODIS of the chosen places. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is conceived for obtaining Earth images with a good enough resolution to study the terrestrial vegetation cover (20x20 m), although with a great range of visual field (600 km) in order to obtain those images with high temporal resolution and at a reduced cost. By contranst, MODIS images present a much lower spatial resolution (500x500 m). The aim of this study is to establish a comparison between two different sensors in their NDVI values at different spatial resolutions. Acknowledgements. This work was partially supported by ENESA under project P10 0220C-823. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. MTM2009-14621 and i-MATH No. CSD2006-00032 is greatly appreciated.

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Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

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Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

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Understanding the pattern in which adult drosophilids of different species are distributed across and within different vegetation types is necessary for accurate interpretation of their local ecology and diversity. Such studies have been conducted mainly in temperate regions, and there is no basis for extrapolating their conclusions to tropical areas. This study describes the vertical distribution (0-20 m) of drosophilids attracted to banana baits in five different vegetation types in subtropical eastern Australia including open woodland, and rain-forest types. The distribution of most of the 15 common species could be characterized three-dimensionally by vegetation type and height above forest floor. Only one species, Scaptodrosophila lativittata, was common in all vegetation types and it was a canopy species in rain forests and a ground-level species in open woodland. Vertical distribution of some species clearly matched that of their larval hosts, but it did not in others. For example, the fungivore Leucophenga scutellata was mostly trapped well above the forest floor, yet it breeds at ground level, suggesting behavioural mode can influence vertical distributions. We conclude that the vertical dimension, although still poorly understood in relation to drosophilid habitats, needs to be taken into account when conducting and interpreting studies aimed at understanding drosophilid populations and communities in the subtropics.

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Deegan and Packel (1979) and Holler (1982) proposed two power indices for simple games: the Deegan–Packel index and the Public Good Index. In the definition of these indices, only minimal winning coalitions are taken into account. Using similar arguments, we define two new power indices. These new indices are defined taking into account only those winning coalitions that do not contain null players. The results obtained with the different power indices are compared by means of two real-world examples taken from the political field.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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ABSTRACT: BACKGROUND: The ability of different obesity indices to predict cardiovascular risk is still debated in youth and few data are available in sub Saharan Africa. We compared the associations between several indices of obesity and cardiovascular risk factors (CVRFs) in late adolescence in the Seychelles. METHODS: We measured body mass index (BMI), waist circumference, waist/hip ratio (WHiR), waist/height ratio (WHtR) and percent fat mass (by bioimpedance) and 6 CVRFs (blood pressure, LDL-cholesterol, HDL-cholesterol, triglycerides, fasting blood glucose and uric acid) in 423 youths aged 19-20 years from the general population. RESULTS: The prevalence of overweight/obesity and several CVRFs was high, with substantial sex differences. Except for glucose in males and LDL-cholesterol in females, all obesity indices were associated with CVRFs. BMI consistently predicted CVRFs at least as well as the other indices. Linear regression on BMI had standardized regression coefficients of 0.25-0.36 for most CVRFs (p<0.01) and ROC analysis had an AUC between 60%-75% for most CVRFs. BMI also predicted well various combinations of CVRFs: 36% of male and 16% of female lean subjects (BMI P90). CONCLUSION: There was an elevated prevalence of obesity and of several CVRFs in youths in Seychelles. BMI predicted single or combined CVRFs at least as well as other simple obesity indices.

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The Garanhuns Plateau in the Agreste region of the State of Pernambuco, Brazil is characterized by humid climatic conditions due to orographic rains, unlike the surrounding semiarid region. These soils are subjected to intense agricultural use and are extremely important for the regional economy. This study was carried out in the municipality of Brejão in the Agreste region with the aim of assessing changes in humic Haplustox soils subjected to different land uses. Four plots with different vegetation covers (native forest, secondary shrubby vegetation (capoeira), traditional cropping system, and planted pasture) were selected, and samples were taken from a soil profile and four small pits surrounding it at each site. Physical and chemical properties were assessed, including aggregate stability, humic organic fractions, and a microbiological evaluation through determination of basal respiration, microbial biomass carbon, and metabolic quotient. The soils under study showed physical and chemical properties typical of a Haplustox, such as low nutrient content, low cation exchange capacity, and high levels of acidity and Al saturation. The total organic carbon (TOC) contents were high regardless of the type of land use. Aggregates < 2 mm were dominant in all the conditions under study. The TOC content was higher in the soil under capoeira, 43.91 g kg-1 on the surface, while 34.36 and 33.43 g kg-1 of TOC were observed in the first layer of forest and pasture soils, respectively. While the microbial biomass C (MBC) was greater than 700 mg kg-1 in the forest and pasture areas (in the 0-5 cm layer), and 588 mg kg-1 in the soil under capoeira, these numbers were not statistically different. In the cultivated soil area, there was a reduction of around 28 % in TOC and MBC contents. Agricultural activity contributed to degradation of the humic horizon, as can be seen from a significant decrease in the TOC and changes in the relative distribution of the humic fractions. In contrast, aggregate stability was not altered as a function of the different land uses; the soil under planted pasture and capoeira were similar to the soil under native forest. Humin was the most important humified fraction for C reserves, contributing over 40 % of the TOC in these soils.

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An area's innate potential to regenerate represents a crucial factor for its conservation and management. The seed rain and seed bank are important agents in the regeneration process. Seed banks are particularly important in communities where there is a high proportion of obligate seeders. Rocky outcrops are habitats where most part of the plant species depends on their seeds to reproduce and maintain viable populations. Therefore, seed banks ought to be important in this vegetation physiognomy. We test the hypotheses that the seed bank of the rocky outcrops found in the rupestrian fields of "Serra do Cipó", Brazil, is richer in species and denser than those formed on different vegetation physiognomies neighboring the outcrops. We then compared species abundance, species richness and composition in the rocky outcrops' seed banks with those of sandy and peaty bogs, forests, gallery forests, and "cerrados". Furthermore, we report on the natural regeneration potential of these soils by assessing a greenhouse study on seedling emergence. Soil samples were collected from 0 to 5 and 5 to 10 cm of depth. Rocky outcrops had the poorest in species and less dense seed bank and showed segregation in species composition. Emergence was greater in the most superficial layer. However, soils on rocky outcrops showed the greatest proportion of endemic threatened species in their seed banks, demonstrating their importance for biodiversity conservation of the "Serra do Cipó" rupestrian fields.

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RÉSUMÉ - Les images satellitales multispectrales, notamment celles à haute résolution spatiale (plus fine que 30 m au sol), représentent une source d’information inestimable pour la prise de décision dans divers domaines liés à la gestion des ressources naturelles, à la préservation de l’environnement ou à l’aménagement et la gestion des centres urbains. Les échelles d’étude peuvent aller du local (résolutions plus fines que 5 m) à des échelles régionales (résolutions plus grossières que 5 m). Ces images caractérisent la variation de la réflectance des objets dans le spectre qui est l’information clé pour un grand nombre d’applications de ces données. Or, les mesures des capteurs satellitaux sont aussi affectées par des facteurs « parasites » liés aux conditions d’éclairement et d’observation, à l’atmosphère, à la topographie et aux propriétés des capteurs. Deux questions nous ont préoccupé dans cette recherche. Quelle est la meilleure approche pour restituer les réflectances au sol à partir des valeurs numériques enregistrées par les capteurs tenant compte des ces facteurs parasites ? Cette restitution est-elle la condition sine qua non pour extraire une information fiable des images en fonction des problématiques propres aux différents domaines d’application des images (cartographie du territoire, monitoring de l’environnement, suivi des changements du paysage, inventaires des ressources, etc.) ? Les recherches effectuées les 30 dernières années ont abouti à une série de techniques de correction des données des effets des facteurs parasites dont certaines permettent de restituer les réflectances au sol. Plusieurs questions sont cependant encore en suspens et d’autres nécessitent des approfondissements afin, d’une part d’améliorer la précision des résultats et d’autre part, de rendre ces techniques plus versatiles en les adaptant à un plus large éventail de conditions d’acquisition des données. Nous pouvons en mentionner quelques unes : - Comment prendre en compte des caractéristiques atmosphériques (notamment des particules d’aérosol) adaptées à des conditions locales et régionales et ne pas se fier à des modèles par défaut qui indiquent des tendances spatiotemporelles à long terme mais s’ajustent mal à des observations instantanées et restreintes spatialement ? - Comment tenir compte des effets de « contamination » du signal provenant de l’objet visé par le capteur par les signaux provenant des objets environnant (effet d’adjacence) ? ce phénomène devient très important pour des images de résolution plus fine que 5 m; - Quels sont les effets des angles de visée des capteurs hors nadir qui sont de plus en plus présents puisqu’ils offrent une meilleure résolution temporelle et la possibilité d’obtenir des couples d’images stéréoscopiques ? - Comment augmenter l’efficacité des techniques de traitement et d’analyse automatique des images multispectrales à des terrains accidentés et montagneux tenant compte des effets multiples du relief topographique sur le signal capté à distance ? D’autre part, malgré les nombreuses démonstrations par des chercheurs que l’information extraite des images satellitales peut être altérée à cause des tous ces facteurs parasites, force est de constater aujourd’hui que les corrections radiométriques demeurent peu utilisées sur une base routinière tel qu’est le cas pour les corrections géométriques. Pour ces dernières, les logiciels commerciaux de télédétection possèdent des algorithmes versatiles, puissants et à la portée des utilisateurs. Les algorithmes des corrections radiométriques, lorsqu’ils sont proposés, demeurent des boîtes noires peu flexibles nécessitant la plupart de temps des utilisateurs experts en la matière. Les objectifs que nous nous sommes fixés dans cette recherche sont les suivants : 1) Développer un logiciel de restitution des réflectances au sol tenant compte des questions posées ci-haut. Ce logiciel devait être suffisamment modulaire pour pouvoir le bonifier, l’améliorer et l’adapter à diverses problématiques d’application d’images satellitales; et 2) Appliquer ce logiciel dans différents contextes (urbain, agricole, forestier) et analyser les résultats obtenus afin d’évaluer le gain en précision de l’information extraite par des images satellitales transformées en images des réflectances au sol et par conséquent la nécessité d’opérer ainsi peu importe la problématique de l’application. Ainsi, à travers cette recherche, nous avons réalisé un outil de restitution de la réflectance au sol (la nouvelle version du logiciel REFLECT). Ce logiciel est basé sur la formulation (et les routines) du code 6S (Seconde Simulation du Signal Satellitaire dans le Spectre Solaire) et sur la méthode des cibles obscures pour l’estimation de l’épaisseur optique des aérosols (aerosol optical depth, AOD), qui est le facteur le plus difficile à corriger. Des améliorations substantielles ont été apportées aux modèles existants. Ces améliorations concernent essentiellement les propriétés des aérosols (intégration d’un modèle plus récent, amélioration de la recherche des cibles obscures pour l’estimation de l’AOD), la prise en compte de l’effet d’adjacence à l’aide d’un modèle de réflexion spéculaire, la prise en compte de la majorité des capteurs multispectraux à haute résolution (Landsat TM et ETM+, tous les HR de SPOT 1 à 5, EO-1 ALI et ASTER) et à très haute résolution (QuickBird et Ikonos) utilisés actuellement et la correction des effets topographiques l’aide d’un modèle qui sépare les composantes directe et diffuse du rayonnement solaire et qui s’adapte également à la canopée forestière. Les travaux de validation ont montré que la restitution de la réflectance au sol par REFLECT se fait avec une précision de l’ordre de ±0.01 unités de réflectance (pour les bandes spectrales du visible, PIR et MIR), même dans le cas d’une surface à topographie variable. Ce logiciel a permis de montrer, à travers des simulations de réflectances apparentes à quel point les facteurs parasites influant les valeurs numériques des images pouvaient modifier le signal utile qui est la réflectance au sol (erreurs de 10 à plus de 50%). REFLECT a également été utilisé pour voir l’importance de l’utilisation des réflectances au sol plutôt que les valeurs numériques brutes pour diverses applications courantes de la télédétection dans les domaines des classifications, du suivi des changements, de l’agriculture et de la foresterie. Dans la majorité des applications (suivi des changements par images multi-dates, utilisation d’indices de végétation, estimation de paramètres biophysiques, …), la correction des images est une opération cruciale pour obtenir des résultats fiables. D’un point de vue informatique, le logiciel REFLECT se présente comme une série de menus simples d’utilisation correspondant aux différentes étapes de saisie des intrants de la scène, calcul des transmittances gazeuses, estimation de l’AOD par la méthode des cibles obscures et enfin, l’application des corrections radiométriques à l’image, notamment par l’option rapide qui permet de traiter une image de 5000 par 5000 pixels en 15 minutes environ. Cette recherche ouvre une série de pistes pour d’autres améliorations des modèles et méthodes liés au domaine des corrections radiométriques, notamment en ce qui concerne l’intégration de la FDRB (fonction de distribution de la réflectance bidirectionnelle) dans la formulation, la prise en compte des nuages translucides à l’aide de la modélisation de la diffusion non sélective et l’automatisation de la méthode des pentes équivalentes proposée pour les corrections topographiques.

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The combined use of both radiosonde data and three-dimensional satellite derived data over ocean and land is useful for a better understanding of atmospheric thermodynamics. Here, an attempt is made to study the ther-modynamic structure of convective atmosphere during pre-monsoon season over southwest peninsular India utilizing satellite derived data and radiosonde data. The stability indices were computed for the selected stations over southwest peninsular India viz: Thiruvananthapuram and Cochin, using the radiosonde data for five pre- monsoon seasons. The stability indices studied for the region are Showalter Index (SI), K Index (KI), Lifted In-dex (LI), Total Totals Index (TTI), Humidity Index (HI), Deep Convective Index (DCI) and thermodynamic pa-rameters such as Convective Available Potential Energy (CAPE) and Convective Inhibition Energy (CINE). The traditional Showalter Index has been modified to incorporate the thermodynamics over tropical region. MODIS data over South Peninsular India is also used for the study. When there is a convective system over south penin-sular India, the value of LI over the region is less than −4. On the other hand, the region where LI is more than 2 is comparatively stable without any convection. Similarly, when KI values are in the range 35 to 40, there is a possibility for convection. The threshold value for TTI is found to be between 50 and 55. Further, we found that prior to convection, dry bulb temperature at 1000, 850, 700 and 500 hPa is minimum and the dew point tem-perature is a maximum, which leads to increase in relative humidity. The total column water vapor is maximum in the convective region and minimum in the stable region. The threshold values for the different stability indices are found to be agreeing with that reported in literature.

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Climate controls upland habitats, soils and their associated ecosystem services; therefore, understanding possible changes in upland climatic conditions can provide a rapid assessment of climatic vulnerability over the next century. We used 3 different climatic indices that were optimised to fit the upland area classified by the EU as a Severely Disadvantaged Area (SDA) 1961–1990. Upland areas within the SDA covered all altitudinal ranges, whereas the maximum altitude of lowland areas outside of the SDA was ca. 300 m. In general, the climatic index based on the ratio between annual accumulated temperature (as a measure of growing season length) and annual precipitation predicted 96% of the SDA mapped area, which was slightly better than those indices based on annual or seasonal water deficit. Overall, all climatic indices showed that upland environments were exposed to some degree of change by 2071–2100 under UKCIP02 climate projections for high and low emissions scenarios. The projected area declined by 13 to 51% across 3 indices for the low emissions scenario and by 24 to 84% for the high emissions scenario. Mean altitude of the upland area increased by +11 to +86 m for the low scenario and +21 to +178 m for the high scenario. Low altitude areas in eastern and southern Great Britain were most vulnerable to change. These projected climatic changes are likely to affect upland habitat composition, long-term soil carbon storage and wider ecosystem service provision, although it is not yet possible to determine the rate at which this might occur.

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We examine the effect of ozone damage to vegetation as caused by anthropogenic emissions of ozone precursor species and quantify it in terms of its impact on terrestrial carbon stores. A simple climate model is then used to assess the expected changes in global surface temperature from the resulting perturbations to atmospheric concentrations of carbon dioxide, methane, and ozone. The concept of global temperature change potential (GTP) metric, which relates the global average surface temperature change induced by the pulse emission of a species to that induced by a unit mass of carbon dioxide, is used to characterize the impact of changes in emissions of ozone precursors on surface temperature as a function of time. For NOx emissions, the longer-timescale methane perturbation is of the opposite sign to the perturbations in ozone and carbon dioxide, so NOx emissions are warming in the short term, but cooling in the long term. For volatile organic compound (VOC), CO, and methane emissions, all the terms are warming for an increase in emissions. The GTPs for the 20 year time horizon are strong functions of emission location, with a large component of the variability owing to the different vegetation responses on different continents. At this time horizon, the induced change in the carbon cycle is the largest single contributor to the GTP metric for NOx and VOC emissions. For NOx emissions, we estimate a GTP20 of −9 (cooling) to +24 (warming) depending on assumptions of the sensitivity of vegetation types to ozone damage.

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Aim Earth observation (EO) products are a valuable alternative to spectral vegetation indices. We discuss the availability of EO products for analysing patterns in macroecology, particularly related to vegetation, on a range of spatial and temporal scales. Location Global. Methods We discuss four groups of EO products: land cover/cover change, vegetation structure and ecosystem productivity, fire detection, and digital elevation models. We address important practical issues arising from their use, such as assumptions underlying product generation, product accuracy and product transferability between spatial scales. We investigate the potential of EO products for analysing terrestrial ecosystems. Results Land cover, productivity and fire products are generated from long-term data using standardized algorithms to improve reliability in detecting change of land surfaces. Their global coverage renders them useful for macroecology. Their spatial resolution (e.g. GLOBCOVER vegetation, 300 m; MODIS vegetation and fire, ≥ 500 m; ASTER digital elevation, 30 m) can be a limiting factor. Canopy structure and productivity products are based on physical approaches and thus are independent of biome-specific calibrations. Active fire locations are provided in near-real time, while burnt area products show actual area burnt by fire. EO products can be assimilated into ecosystem models, and their validation information can be employed to calculate uncertainties during subsequent modelling. Main conclusions Owing to their global coverage and long-term continuity, EO end products can significantly advance the field of macroecology. EO products allow analyses of spatial biodiversity, seasonal dynamics of biomass and productivity, and consequences of disturbances on regional to global scales. Remaining drawbacks include inter-operability between products from different sensors and accuracy issues due to differences between assumptions and models underlying the generation of different EO products. Our review explains the nature of EO products and how they relate to particular ecological variables across scales to encourage their wider use in ecological applications.