Automatic and improved radiometric correction of Landsat imagery using reference values from MODIS surface reflectance images - Pons, X; Pesquer, L; Cristóbal, J; González-Guerrero, O (International Journal of Applied Earth Observation and Geoinformation, 2014)
Radiometric correction is a prerequisite for generating high-quality scientific data, making it possible to discriminate between product artefacts and real changes in Earth processes as well as accurately produce land cover maps and detect changes. This work contributes to the automatic generation of surface reflectance products for Landsat satellite series. Surface reflectances are generated by a new approach developed from a previous simplified radiometric (atmospheric+topographic) correction model. The proposed model keeps the core of the old model (incidence angles and cast-shadows through a digital elevation model [DEM], Earth–Sun distance, etc.) and adds new characteristics to enhance and automatize ground reflectance retrieval. The new model includes the following new features: (1) A fitting model based on reference values from pseudoinvariant areas that have been automatically extracted from existing reflectance products (Terra MODIS MOD09GA) that were selected also automatically by applying quality criteria that include a geostatistical pattern model. This guarantees the consistency of the internal and external series, making it unnecessary to provide extra atmospheric data for the acquisition date and time, dark objects or dense vegetation. (2) A spatial model for atmospheric optical depth that uses detailed DEM and MODTRAN simulations. (3) It is designed so that large time-series of images can be processed automatically to produce consistent Landsat surface reflectance time-series. (4) The approach can handle most images, acquired now or in the past, regardless of the processing system, with the exception of those with extremely high cloud coverage. The new methodology has been successfully applied to a series of near 300 images of the same area including MSS, TM and ETM+ imagery as well as to different formats and processing systems (LPGS and NLAPS from the USGS; CEOS from ESA) for different degrees of cloud coverage (up to 60%) and SLC-off. Reflectance products have been validated with some example applications: time series robustness (for a pixel in a pseudoinvariant area, deviations are only 1.04% on average along the series), spectral signatures generation (visually coherent with the MODIS ones, but more similar between dates), and classification (up to 4 percent points better than those obtained with the original manual method or the CDR products). In conclusion, this new approach, that could also be applied to other sensors with similar band configurations, offers a fully automatic and reasonably good procedure for the new era of long time-series of spatially detailed global remote sensing data.
Keywords: Landsat; MODIS; Pseudoinvariant area; Radiometric correction

Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models - Huesca, Margarita; Litago, Javier; Merino-de-Miguel, Silvia; Cicuendez-López-Ocaña, Victor; Palacios-Orueta, Alicia (International Journal of Applied Earth Observation and Geoinformation, 2014)
The aim of this research was to model and forecast MODIS-based Fire Potential Index (FPI), implemented with Normalized Difference Water Index (NDWI), as a proxy of forest fire risk, in Navarre (Spain) on a pixel basis using time series models with a forecasting horizon of one year. We forecast FPINDWI for 2009 based on time series from 2001 to 2008. In the modeling process, the Box and Jenkins methodology was applied in two consecutive stages. First, several generic models based on average FPINDWI time series from different “fuel type-ecoregion” combinations were developed. In a second stage, the generic models were implemented at the pixel level for the entire study region. The usefulness of the proposed autoregressive (AR) model, using the original data and introducing significant seasonal AR parameters, was demonstrated. Results show that 93.18% of the estimated models (EMs) are highly accurate and present good fore- casting ability, precisely reproducing the original FPINDWI dynamics. Best results were found in the Mediterranean areas dominated by grasslands; slightly lower accuracies were found in the temperate and alpine regions, and especially in the transition areas between them and the Mediterranean region
Keywords: Autoregressive models; MODIS; time series analysis

Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements - Hmimina, G; Dufrêne, E; Pontailler, J.-Y.; Delpierre, N; Aubinet, M; Caquet, B; de Grandcourt, A; Burban, B; Flechard, C; GRANIER, a; Gross, P; Heinesch, B; et al. (Remote Sensing of Environment, 2013)
Abstract Vegetation phenology is the study of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote sensing of vegetation phenology, phenological metrics are derived from time series of optical data. For that purpose, considerable effort has been specifically focused on developing noise reduction and cloud-contaminated data removal techniques to improve the quality of remotely-sensed time series. Comparative studies between time series composed of satellite data acquired under clear and cloudy conditions and from radiometric data obtained with high accuracy from ground-based measurements constitute a direct and effective way to assess the operational use and limitations of remote sensing for predicting the main plant phenological events. In the present paper, we sought to explicitly evaluate the potential use of MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing data for monitoring the seasonal dynamics of different types of vegetation cover that are representative of the major terrestrial biomes, including temperate deciduous forests, evergreen forests, African savannah, and crops. After cloud screening and filtering, we compared the temporal patterns and phenological metrics derived from in situ NDVI time series and from MODIS daily and 16-composite products. We also evaluated the effects of residual noise and the influence of data gaps in MODIS NDVI time series on the identification of the most relevant metrics for vegetation phenology monitoring. The results show that the inflexion points of a model fitted to a MODIS NDVI time series allow accurate estimates of the onset of greenness in the spring and the onset of yellowing in the autumn in deciduous forests (RMSE ≤ one week). Phenological metrics identical to those provided with the MODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately two weeks or more during the autumn phenological transitions. In the evergreen forests, in situ NDVI time series describe the phenology with high fidelity despite small temporal changes in the canopy foliage. However, MODIS is unable to provide consistent phenological patterns. In crops and savannah, MODIS NDVI time series reproduce the general temporal patterns of phenology, but significant discrepancies appear between MODIS and ground-based NDVI time series during very localized periods of time depending on the weather conditions and spatial heterogeneity within the MODIS pixel. In the rainforest, the temporal pattern exhibited by a MODIS 16-day composite NDVI time series is more likely due to a pattern of noise in the NDVI data structure according to both rainy and dry seasons rather than to phenological changes. More investigations are needed, but in all cases, this result leads us to conclude that MODIS time series in tropical rainforests should be interpreted with great caution.
Keywords: Crops; Deciduous forests; evergreen forests; Ground-based NDVI; MODIS; Phenology

Phenological variability drives the distribution of wildfires in Sardinia - Angelis, Antonella; Bajocco, Sofia; Ricotta, Carlo (Landscape Ecology, 2012)
Fuel characteristics play an important role in driving ﬁre ignition and propagation; at the landscape scale fuel availability and ﬂammability are closely related to vegetation phenology. In this view, the NDVI proﬁles obtained from high temporal resolution satellites, like MODIS, are an effective tool for monitoring the coarse-scale vegetation seasonal timing. The aim of this paper is twofold: our ﬁrst objective consists in classifying by means of multitemporal NDVI proﬁles the coarse-scale vegetation of Sardinia into ‘phenological clusters’ in which ﬁre incidence is higher (preferred) or lower (avoided) than expected from a random null model. If ﬁres would burn unselectively, then ﬁres would occur randomly across the landscape such that the number of ﬁres in a given phenological cluster would be nearly proportional to the relative area of that land cover type in the analyzed landscape. Actually, certain vegetation types are more ﬁre-prone than others. That is, they are burnt more frequently than others. In this framework, our second objective consists in investigating the temporal parameters of the remotely sensed NDVI proﬁles that best characterize the observed phenology–ﬁre selectivity relationship. The results obtained show a good association between the NDVI temporal proﬁles and the spatio-temporal wildﬁre distribution in Sardinia, emphasizing the role of bioclimatic timing in driving ﬁre regime characteristics.
Keywords: Clustering; Fire selectivity; Image segmentation; MODIS; NDVI proﬁles; Residuals

The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficienciesA review and meta-analysis - Garbulsky, Martín F.; Penuelas, Josep; Gamon, John; Inoue, Yoshio; Filella, Iolanda (Remote Sensing of Environment, 2011)
Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon ﬂuxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reﬂectance Index (PRI) derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efﬁciency. We examined and synthesized the scientiﬁc literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efﬁciency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efﬁciency (RUE; the ratio between carbon uptake and light absorbed by vegetation) variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE–PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efﬁciencies. PRI accounted for 42%, 59% and 62% of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation (FPAR), estimated with NDVI-like indices, PRI enables improved assessment of carbon ﬂuxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors.
The following values have no corresponding Zotero field: publisher: Elsevier Inc.
Keywords: ciency; gross primary productivity; index; MODIS; photochemical re fl ectance; photochemical reflectance index; radiation use ef fi; radiation use efficiency

Generation of a Species-Specific Look-Up Table for Fuel Moisture Content Assessment - Yebra, M; Chuvieco, E (Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 2009)
This study involved the generation of a species-specific Look-Up Table (LUT) for the retrieval of Fuel Moisture Content (FMC) in natural areas dominated by Quercus ilex (Holm oak). Parameter combinations observed in drying Q. ilex samples were used as inputs into the linked PROSPECT and SAILH Radiative Transfer Models (RTM) to avoid unrealistic simulated spectra in the LUT. Terra/MODIS reflectance data, extracted over five plots dominated by Q. ilex, were used to carry out the LUT inversion. This inversion was based on the search for the minimum relative root mean square error (RMSErho*) between observed and simulated reflectance found in the LUT. Different inversion options were tested in order to search for the optimal spectral sampling necessary for accurately estimating FMC. The minimum number of solutions required for the calculation of the estimated FMC was also investigated. The retrieval performance was evaluated with FMC values measured at the five study plots. The most accurate FMC estimation was obtained when using the normalized difference infrared index (NDII6 ) and selecting the ten best cases as the solution (RMSE=26.28%). Finally, a non-oak-specific LUT (generic LUT) was used in the same way to evaluate whether or not the species-specific LUT retrieved FMC more accurately. The results showed that the species-specific LUT provided more accurate FMC estimations than the generic LUT. Only when the number of solutions was higher than 35 was the accuracy of the two LUT similar. Future work will focus on the possibility of generating a LUT adapted to a wider range of species based on data extracted from field measurements and literature.
Keywords: Fuel moisture content (FMC); Holm oak; MODIS; Quercus ilex; Radiative Transfer Models (RTM)

Generation of a Species-Specific Look-Up Table for Fuel Moisture Content Assessment - Yebra, M.; Chuvieco, E. (Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 2009)
This study involved the generation of a species-specific Look-Up Table (LUT) for the retrieval of Fuel Moisture Content (FMC) in natural areas dominated by Quercus ilex (Holm oak). Parameter combinations observed in drying Q. ilex samples were used as inputs into the linked PROSPECT and SAILH Radiative Transfer Models (RTM) to avoid unrealistic simulated spectra in the LUT. Terra/MODIS reflectance data, extracted over five plots dominated by Q. ilex, were used to carry out the LUT inversion. This inversion was based on the search for the minimum relative root mean square error (RMSErho*) between observed and simulated reflectance found in the LUT. Different inversion options were tested in order to search for the optimal spectral sampling necessary for accurately estimating FMC. The minimum number of solutions required for the calculation of the estimated FMC was also investigated. The retrieval performance was evaluated with FMC values measured at the five study plots. The most accurate FMC estimation was obtained when using the normalized difference infrared index (NDII6 ) and selecting the ten best cases as the solution (RMSE=26.28%). Finally, a non-oak-specific LUT (generic LUT) was used in the same way to evaluate whether or not the species-specific LUT retrieved FMC more accurately. The results showed that the species-specific LUT provided more accurate FMC estimations than the generic LUT. Only when the number of solutions was higher than 35 was the accuracy of the two LUT similar. Future work will focus on the possibility of generating a LUT adapted to a wider range of species based on data extracted from field measurements and literature.
Keywords: Fuel moisture content (FMC); Holm oak; MODIS; Quercus ilex; Radiative Transfer Models (RTM)

Remote estimation of carbon dioxide uptake by a Mediterranean forest - GARBULSKY, MARTÍN F; Penuelas, Josep; Papale, Dario; Filella, Iolanda (Global Change Biology, 2008)
The estimation of the carbon balance in ecosystems, regions, and the biosphere is currently one of the main concerns in the study of the ecology of global change. Current remote sensing methodologies for estimating gross primary productivity are not satisfactory because they rely too heavily on (i) the availability of climatic data, (ii) the definition of land-use cover, and (iii) the assumptions of the effects of these two factors on the radiation-use efficiency of vegetation (RUE). A new methodology is urgently needed that will actually assess RUE and overcome the problems associated with the capture of fluctuations in carbon absorption in space and over time. Remote sensing techniques such as the widely used reflectance vegetation indices (e.g. NDVI, EVI) allow green plant biomass and therefore plant photosynthetic capacity to be assessed. However, there are vegetation types, such as the Mediterranean forests, with a very low seasonality of these vegetation indices and a high seasonality of carbon uptake. In these cases it is important to detect how much of this capacity is actually realized, which is a much more challenging goal. The photochemical reflectance index (PRI) derived from freely available satellite information (MODIS sensor) presented for a 5-year analysis for a Mediterranean forest a positive relationship with the RUE. Thus, we show that it is possible to estimate RUE and GPP in real time and therefore actual carbon uptake of Mediterranean forests at ecosystem level using the PRI. This conceptual and technological advancement would avoid the need to rely on the sometimes unreliable maximum RUE.
Keywords: carbon cycle; CO2 uptake; eddy covariance; Mediterranean forests; MODIS; primary productivity; radiation use efficiency; Remote sensing; Vegetation

Remote estimation of carbon dioxide uptake by a Mediterranean forest - Garbulsky, Martín F.; Penuelas, Josep; Papale, Dario; Filella, Iolanda (Global Change Biology, 2008)
The estimation of the carbon balance in ecosystems, regions, and the biosphere is currently one of the main concerns in the study of the ecology of global change. Current remote sensing methodologies for estimating gross primary productivity are not satisfactory because they rely too heavily on (i) the availability of climatic data, (ii) the definition of land-use cover, and (iii) the assumptions of the effects of these two factors on the radiation-use efficiency of vegetation (RUE). A new methodology is urgently needed that will actually assess RUE and overcome the problems associated with the capture of fluctuations in carbon absorption in space and over time. Remote sensing techniques such as the widely used reflectance vegetation indices (e.g. NDVI, EVI) allow green plant biomass and therefore plant photosynthetic capacity to be assessed. However, there are vegetation types, such as the Mediterranean forests, with a very low seasonality of these vegetation indices and a high seasonality of carbon uptake. In these cases it is important to detect how much of this capacity is actually realized, which is a much more challenging goal. The photochemical reflectance index (PRI) derived from freely available satellite information (MODIS sensor) presented for a 5-year analysis for a Mediterranean forest a positive relationship with the RUE. Thus, we show that it is possible to estimate RUE and GPP in real time and therefore actual carbon uptake of Mediterranean forests at ecosystem level using the PRI. This conceptual and technological advancement would avoid the need to rely on the sometimes unreliable maximum RUE.
The following values have no corresponding Zotero field: publisher: Blackwell Publishing Ltd
Keywords: carbon cycle; CO2 uptake; eddy covariance; Mediterranean forests; MODIS; primary productivity; radiation use efficiency; Remote sensing; Vegetation