Correcting AVHRR Long Term Data Record V3 estimated LST from orbital drift effects
Abstract NOAA (National Oceanic and Atmospheric Administration) satellite series is known to suffer from what is known as the orbital drift effect. The Long Term Data Record (LTDR [Pedelty et al., 2007]), which provides AVHRR (Advanced Very High Resolution Radiometer) data from these satellites for the 80s and the 90s, is also affected by this orbital drift. To correct this effect on Land Surface Temperature (LST) time series, a novel method is presented here, which consists in adjusting retrieved LST time series on the basis of statistical information extracted from the time series themselves. This method is as simple and straightforward as possible, in order to be implemented easily for s…
Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data
Abstract NDVI (Normalized Difference Vegetation Index) time series usually suffer from remaining cloud presence, even after data pre-processing. To address this issue, numerous gap-filling (or reconstruction) techniques have been developed in the literature, although their comparison has mainly been local to regional, with only two global studies to date, and has led to sometimes contradictory results. This study builds on these different comparisons, by testing different parameterizations for five NDVI temporal profile reconstruction techniques, namely HANTS (Harmonic Analysis of Time Series), IDR (iterative Interpolation for Data Reconstruction), Savitzky-Golay, Asymmetric Gaussian and Do…
Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran
Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach…
Trend Analysis of Global MODIS-Terra Vegetation Indices and Land Surface Temperature Between 2000 and 2011
Previous works have shown that the combination of vegetation indices with land surface temperature (LST) improves the analysis of vegetation changes. Here, global MODIS-Terra monthly data from 2000 to 2011 were downloaded and organized into LST, NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) time series. These time series were then corrected from cloud and atmospheric residual contamination through the IDR (iterative Interpolation for Data Reconstruction) method. Then, statistics were retrieved from both corrected time series, and the YLCD (Yearly Land Cover Dynamics) approach has been applied to data sources (NDVI-LST and EVI-LST) to analyze changes in th…
Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001
In past decades, the Iberian Peninsula has been shown to have suffered vegetation changes such as desertification and reforestation. Normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters, estimated from data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard the National Oceanic and Atmospheric Administration (NOAA) satellite series, are particularly adapted to assess these changes. This work presents an application of the yearly land-cover dynamics (YLCD) methodology to analyse the behaviour of the vegetation, which consists of a combined multitemporal study of the NDVI and LST parameters on a yearly basis. Throughout the 1…
Using NASA'S Long Term Data Record version 3 for the monitoring of land surface vegetation
Numerous datasets have been made available for the observation of our planet from space. The aim of this work is the observation of changes in vegetation, through the use of a recent remote sensing dataset, NASA's Long Term Data Record (LTDR). Several authors have pointed out that vegetation monitoring benefits of the simultaneous use of Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST). Therefore, this work presents the procedure developed to monitor vegetation with the LTDR dataset, using both NDVI and LST parameters. This procedure includes data preprocessing (estimation of NDVI and LST, orbital drift correction, atmospherically contaminated data reconstruc…
Land use classification from multitemporal Landsat imagery using the Yearly Land Cover Dynamics (YLCD) method
Abstract Several previous studies have shown that the inclusion of the LST (Land Surface Temperature) parameter to a NDVI (Normalized Difference Vegetation Index) based classification procedure is beneficial to classification accuracy. In this work, the Yearly Land Cover Dynamics (YLCD) approach, which is based on annual behavior of LST and NDVI, has been used to classify an agricultural area into crop types. To this end, a time series of Landsat-5 images for year 2009 of the Barrax (Spain) area has been processed: georeferenciation, destriping and atmospheric correction have been carried out to estimate NDVI and LST time series for year 2009, from which YLCD parameters were estimated. Then…
Global land surface phenology trends from GIMMS database
A double logistic function has been used to describe global inventory mapping and monitoring studies (GIMMS) normalized difference vegetation index (NDVI) yearly evolution for the 1981 to 2003 period, in order to estimate land surface phenology parameter. A principal component analysis on the resulting time series indicates that the first components explain 36, 53 and 37% of the variance for the start, end and length of growing season, respectively, and shows generally good spatial homogeneity. Mann-Kendall trend tests have been carried out, and trends were estimated by linear regression. Maps of these trends show a global advance in spring dates of 0.38 days per year, a global delay in aut…
Sentinel 2 and 3 for Temperature Monitoring Over the Amazon
In this work we present results of an early assessment of the performance of the Land Surface Temperature (LST) product retrieved from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellite (S3/SLSTR) over the Amazon basin. Results are validated from comparison of S3/SLSTR retrievals against in situ measurements of surface temperature collected over one instrumented site in the Peruvian Amazon. The validation exercise was performed on the standard S3/SLSTR Level-2 LST product as well as on a dedicated LST split-window algorithm with an explicit dependence on surface emissivity. Surface emissivity maps obtained from the high spatial resolution of S2/MSI are…
NDVI seasonal amplitude and its variability
NDVI (Normalized Difference Vegetation Index) is a remotely sensed index of vegetation greenness. Its yearly cycle gives information on vegetation type or health, and monitoring its temporal evolut...
Trends in column integrated water vapour over Europe from 1973 to 2003
The spatial and temporal variations of atmospheric precipitable water (PW) content anomalies were analysed over Europe from 1973 to 2003 using daily data (0000 and 1200 UTC) from National Center of Environmental Prediction and National Center of Atmospheric Research Reanalysis project (NCEP-1) and in situ radiosonde data. Mann–Kendall trend tests were applied to long-term PW time series. Technology changes influence PW radiosonde trends, although these are in agreement with NCEP-1 trends. Over the south of the Iberian Peninsula, trends are negative and statistically significant ( 0.04 mm year−1; p < 0.05). Seasonal trends revealed negative and significant trends over the Iberian Peninsula f…
Comparison of cloud-reconstruction methods for time series of composite NDVI data
Land cover change can be assessed from ground measurements or remotely sensed data. As regards remotely sensed data, such as NDVI (Normalized Difference Vegetation Index) parameter, the presence of atmospherically contaminated data in the time series introduces some noise that may blur the change analysis. Several methods have already been developed to reconstruct NDVI time series, although most methods have been dedicated to reconstruction of acquired time series, while publicly available databases are usually composited over time. This paper presents the IDR (iterative Interpolation for Data Reconstruction) method, a new method designed to approximate the upper envelope of the NDVI time s…
Global vegetation monitoring through multitemporal analysis of pathfinder AVHRR land database
We have applied a Land Surface Temperature algorithm to the whole Pathfinder AVHRR Land (PAL) database, aiming at studying the evolution of the vegetation at a global scale. The Land Surface Temperature parameter, along with NDVI, will allow retrieving vegetation changes between July 1981 and September 2001. We have also built a classification which takes into account both vegetation variations and thermal patterns, from NDVI and Air Temperature at 2 meters height data. This classification allows differentiating areas which present close vegetation changes throughout the year, but totally different climates, as for example in mountainous and semiarid regions. The main quality of this classi…
Monitoring global vegetation with the Yearly Land Cover Dynamics (YLCD) method
Global vegetation has been traditionally monitored mainly through the use of the Normalized Difference Vegetation Index (NDVI). Land surface temperature (LST) provides additional information, and is generally less affected by atmospheric conditions when water vapor is taken into account. The Yearly Land Cover Dynamics (YLCD) method can then be used to retrieve 3 parameters which allow for a good differentiation between biomes at the global and local levels. Using NASA's Long Term Data Record (LTDR), the YLCD method has been applied to IDR (iterative Interpolation for Data Reconstruction) reconstructed LTDR data, in order to account for atmospheric contamination of part of the dataset for a …
Thermal remote sensing from Airborne Hyperspectral Scanner data in the framework of the SPARC and SEN2FLEX projects: an overview
Abstract. The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004. This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for …
Global trends in NDVI-derived parameters obtained from GIMMS data
The Normalized Difference Vegetation Index (NDVI) has been proven to be useful to assess vegetation changes around the world, in spite of limitations such as sensitivity to cloud or snow contamination. In order to map vegetation changes at global scale, this study uses NDVI time series provided by the GIMMS (Global Inventory Modeling and Mapping Studies) group, which were fitted annually to a double logistic function. This fitting procedure allowed for retrieval of NDVI-derived parameters which were tested for trends using Mann-Kendall statistics. These trends were validated by comparison at 73 ground control points documented as change hotspots. The obtained trends for NDVI-derived paramet…
Exploring the Validity of the Long-Term Data Record V4 Database for Land Surface Monitoring
A new version of the long-term data record (LTDR)—Version 4—has been released recently by NASA. This database includes daily information for all advanced very high resolution radiometer channels, as well as ancillary data, from July 1981 up to present. This dataset is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the daily estimation of vegetation indices, as well as the estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring, especially as regards long-term trends and their validity. To that end, we estimated normalized difference vegetation index (NDVI), LST, as well …
Phenology Estimation From Meteosat Second Generation Data
Many studies have focused on land surface phenology, for example as a means to characterize both water and carbon cycles for climate model inputs. However, the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) sensor onboard Meteosat Second Generation (MSG) geostationary satellite has never been used for this goal. Here, five years of MSG-SEVIRI data have been processed to retrieve Normalized Difference Vegetation Index (NDVI) daily time series. Due to existing gaps as well as atmospheric and cloud contamination in the time series, an algorithm based on the iterative Interpolation for Data Reconstruction (IDR) has been developed and applied to SEVIRI NDVI time series, from which phenologi…
Thermal remote sensing in the framework of the SEN2FLEX project: field measurements, airborne data and applications
A description of thermal radiometric field measurements carried out in the framework of the European project SENtinel-2 and Fluorescence Experiment (SEN2FLEX) is presented. The field campaign was developed in the region of Barrax (Spain) during June and July 2005. The purpose of the thermal measurements was to retrieve biogeophysical parameters such as land surface emissivity (LSE) and temperature (LST) to validate airborne-based methodologies and to characterize different surfaces. Thermal measurements were carried out using two multiband field radiometers and several broadband field radiometers, pointing at different targets. High-resolution images acquired with the Airborne Hyperspectral…
Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999
Abstract We used land surface temperature (LST) algorithms and NDVI values to estimate changes in vegetation in the European continent between 1982 and 1999 from the Pathfinder AVHRR Land (PAL) dataset. These two parameters are monitored through HANTS (Harmonic ANalysis of Time Series) software, which allows the simultaneous observation of mean value, first harmonic amplitude and phase behaviors in the same image. These results for each complete year of data show the effect of volcanic aerosols and orbital drift on PAL data. Comparison of time series of HANTS cloud-free time series with the original time series for various land cover proves that this software is useful for LST analysis, alt…
Near real-time estimation of Sea and Land surface temperature for MSG SEVIRI sensors
Abstract Land and Sea Surface Temperatures (LST and SST) are both recognized as Essential Climate Variables, and are routinely retrieved by a wealth of satellites. However, for validated approaches, the latest data are usually not available to the general public. We offer to bridge this gap, by using Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI), with its 15 min temporal resolution. Here, we present generic algorithms for the retrieval of both LST and SST, valid for the SEVIRI instrument onboard MSG platforms 8–11, which we validate using hourly data of 4 ground stations and 11 buoys in Spain over the years 2015 to 2018. These validations show that …
NOAA-AVHRR Orbital Drift Correction From Solar Zenithal Angle Data
This paper presents a new method for NOAA's (National Ocean and Atmospheric Administration) orbital drift correction. This method is pixel-based, and in opposition with most methods previously developed, does not need explicit knowledge of land cover. This method is applied to AVHRR (Advanced Very High Resolution Radiometer) channel information, and relies only on the additional knowledge of solar zenithal angle (SZA) and acquisition date information. In a first step, anomalies in SZA and channel time series are retrieved, and screened out for anomalous values. Then, the part of the parameter anomaly which is explained by SZA anomaly is removed from the data, to estimate new parameter anoma…
Emissivity mapping over urban areas using a classification-based approach: Application to the Dual-use European Security IR Experiment (DESIREX)
Abstract In this work a methodology to provide an emissivity map of an urban area is presented. The methodology is applied to the city of Madrid (Spain) using data provided by the Airborne Hyperspectral Scanner (AHS) in 2008. From the data a classification map with twelve different urban materials was created. Each material was then characterized by a different emissivity, whose values were obtained from the application of the TES algorithm to in situ measurements and values extracted from the ASTER spectral library. This new emissivity map could be used as a basis for determining the temperature of the city and to understand the urban heat island effect in terms of spatial distribution and…
SHIFTS OF START AND END OF SEASON IN RESPONSE TO AIR TEMPERATURE VARIATION BASED ON GIMMS DATASET IN HYRCANIAN FORESTS
Abstract. Climate change is one of the most important environmental challenges in the world and forest as a dynamic phenomenon is influenced by environmental changes. The Hyrcanian forests is a unique natural heritage of global importance and we need monitoring this region. The objective of this study was to detect start and end of season trends in Hyrcanian forests of Iran based on biweekly GIMMS (Global Inventory Modeling and Mapping Studies) NDVI3g in the period 1981-2012. In order to find response of vegetation activity to local temperature variations, we used air temperature provided from I.R. Iran Meteorological Organization (IRIMO). At the first step in order to remove the existing g…
Multitemporal analysis of PAL images for the study of land cover dynamics in South America
Pathfinder AVHHR Land (PAL) database has been used for the retrieval of Land Surface Temperature (LST) over South America, which, along with NDVI parameter, will allow the studying of the evolution of the vegetation between July 1981 and September 2001. To this end, a classification has been built, based on PAL NDVI and Reanalysis air temperature at 2 m height data. This classification takes into account both vegetation and thermal patterns, and has been validated by a comparison with CAZALAC's map of arid zones (Centro del Agua para Zonas Aridas y semiaridas de Latino-America y el Caribe), as well as with Global Land Cover Characteristics' classification built by the USGS (United States Ge…
Mapping sub-pixel burnt percentage using AVHRR data. Application to the Alcalaten area in Spain
The purpose of this work is to estimate at sub-pixel scale the percentage of burnt land using the Advanced Very High Resolution Radiometer AVHRR through a simple approach. This methodology is based on multi-temporal spectral mixture analysis MSMA, which uses a normalized difference vegetation index NDVI and a land-surface temperature LST image as input bands. The area of study is located in the Alcalaten region in Castellon Spain, a typical semi-arid Mediterranean region. The results have shown an extension of approximately 55 km2 affected by fire, which is only 5% lower than the statistic reports provided by the Environmental Ministry of Spain. Finally, we include a map of the area showing…
Fluorescence estimation in the framework of the CEFLES2 campaign
International audience; Chlorophyll fluorescence (ChF) is a relevant indicator of the actual plant physiological status. In this article different methods to measure ChF from remote sensing are evaluated: The Fraunhofer Line Discrimination (FLD), theFluorescence Radiative Method (FRM) and the improved Fraunhofer Line Discrimination (iFLD). The three methods have been applied to data acquired in the framework of the CarboEurope, FLEX and Sentinel-2 (CEFLES2) campaign in Les Landes, France in September 2007. Comparing with in situ measurements, the results indicate that the methods that provide the best results are the FLD and the iFLD with root mean square errors (RMSEs) of 0.4 and 0.5 mW m-…
Changes in vegetation spring dates in the second half of the twentieth century
This study aims at estimating trends in spring phenology from vegetation index and air temperature at 2 m height. To this end, we have developed a methodology to infer spring phenological dates from Global Inventory Modeling and Mapping Studies GIMMS Normalized Difference Vegetation Index NDVI time-series, which are then extrapolated to the period 1948–2006 with the help of Reanalysis data, using its 2 m height air temperature parameter. First, yearly NDVI is fitted to a double-logistic function for the whole extent of the GIMMS database 1981–2003. This fitting procedure allows us to describe, on a yearly basis, the NDVI evolution for each pixel through the estimation of six parameters whic…
Mapping wild pear trees (Pyrus bourgaeana) in Mediterranean forest using high-resolution QuickBird satellite imagery
Recent advances in spatial and spectral resolution of satellite imagery as well as in processing techniques are opening new possibilities of fine-scale vegetation analysis with interesting applications in natural resource management. Here we present the main results of a study carried out in Sierra Morena, Cordoba southern Spain, aimed at assessing the potential of remote-sensing techniques to discriminate and map individual wild pear trees Pyrus bourgaeana in Mediterranean open woodland dominated by Quercus ilex . We used high spatial resolution 2.4 m multispectral/0.6 m panchromatic QuickBird satellite imagery obtained during the summer of 2008. Given the size and features of wild pear tr…
Retrieving and broadcasting near-real-time biophysical parameters from MODIS and SEVIRI receiving stations at the global change unit of the University of Valencia
We present here the automatic processing chains implemented at the Global Change Unit of the University of Valencia. These allow for a near-real-time retrieval of various biophysical parameters from both Sun-synchronous TERRA/AQUA Moderate Resolution Imaging Spectroradiometer MODIS and geostationary Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager MSG SEVIRI sensors. Retrieved parameters, namely sea and land surface temperatures SST and LST, respectively, normalized difference vegetation index NDVI, and vegetation condition index VCI, are similar for both sensors, and specific approaches have been developed and implemented for near-real-time parameter retrievals: htt…
Vegetation monitoring through retrieval of NDVI and LST time series from historical databases.
The PhD dissertation presented here falls into the Earth Observation field, specifically vegetation monitoring. This work consists in the extensive exploitation of historical databases of satellite images for vegetation monitoring through two parameters, which are the land surface temperature (LST) and a vegetation index (NDVI). Up to now, vegetation monitoring has been limited to the use of vegetation indices, so the addition of the land surface temperature parameter represents the main innovative character of this PhD study.This dissertation is divided into 5 chapters. The first chapter begins by introducing the theoretical aspects of NDVI and LST parameters, addressing the means for retr…
Time Series Corrections and Analyses in Thermal Remote Sensing
The time span of surface thermal data bases now reaches a few decades. However, studies using surface thermal time series are seldom, due to the difficulty of obtaining temporally coherent estimations for this parameter. Applications for surface thermal multitemporal analysis range from climate change studies and modeling to anomaly detection for natural or industrial hazard detection. This chapter presents methods to improve the temporal coherence of temperature time series, through data reconstruction of atmospheric and cloud contaminated observations, and through the correction of the orbital drift effect which hinders the use of the longest data sets. Then, methods for the analysis of t…
TISSBERT: A benchmark for the validation and comparison of NDVI time series reconstruction methods
[EN] This paper introduces the Time Series Simulation for Benchmarking of Reconstruction Techniques (TISSBERT) dataset, intended to provide a benchmark for the validation and comparison of time series reconstruction methods. Such methods are routinely used to estimate vegetation characteristics from optical remotely sensed data, where the presence of clouds decreases the usefulness of the data. As for their validation, these methods have been compared with previously published ones, although with different approaches, which sometimes lead to contradictory results. We designed the TISSBERT dataset to be generic so that it could simulate realistic reference and cloud-contaminated time series …
CloudSim: A fair benchmark for comparison of methods for times series reconstruction from cloud and atmospheric contamination
Cloud contamination of optical data is a constant and annoying feature of time series analyses, whether while using vegetation indices or surface temperatures, since it tends to decrease artificially the values taken by these parameters. Therefore, any time series analysis of optical data needs a previous step for gap-filling reconstruction of the time series. Numerous techniques have been presented in the literature to carry out this preliminary and mandatory step. However, the evaluation and comparison of these techniques is difficult, since no “truth” time series is available. We present here a probabilistic model (CloudSim) to provide global typical annual time series for NDVI (Normaliz…
Near-Real-Time Estimation of Water Vapor Column From MSG-SEVIRI Thermal Infrared Bands: Implications for Land Surface Temperature Retrieval
The Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) instrument provides observations of half the globe every 15 min, at low spatial resolution. These data are an invaluable tool to observe daily to yearly cycle of land surface temperature (LST), as well as for various early warning systems. However, advanced algorithms for LST estimation requires a previous estimation of the water vapor (WV) column above the observed pixel, for which no instantaneous retrieval methods are yet available, and therefore hinders their implementation in a near-real-time processing chain for MSG-SEVIRI data. This work analyzes three different formulations for such WV retrieva…
The Yearly Land Cover Dynamics (YLCD) method: An analysis of global vegetation from NDVI and LST parameters
NDVI (Normalized Difference Vegetation Index) has been widely used to monitor vegetation changes since the early eighties. On the other hand, little use has been made of land surface temperatures (LST), due to their sensitivity to the orbital drift which affects the NOAA (National Oceanic and Atmospheric Administration) platforms flying AVHRR sensor. This study presents a new method for monitoring vegetation by using NDVI and LST data, based on an orbital drift corrected dataset derived from data provided by the GIMMS (Global Inventory Modeling and Mapping Studies) group. This method, named Yearly Land Cover Dynamics (YLCD), characterizes NDVI and LST behavior on a yearly basis, through the…
Using MSG-Seviri Data to Monitor the Planet in Near Real Time
The SEVIRI (Spinning Enhanced Visible and Infra Red Imager) instrument onboard MSG (Meteosat Second Generation) satellite series provides valuable data for the observation of our planet. We describe here the processing chain implemented at the Global Change Unit of the University of Valencia to provide information such as vegetation index, temperatures of both land and sea, synthetic quicklooks for an easy interpretation of the data as well as fire hotspots. Vegetation index and temperature data are available for download from a dedicated portal updated every 3 hours with the most recent processed data. Additionally, a web page displays this information for a non scientific public in near r…
Vicarious Calibration of Landsat-8 Thermal Data Collections and its Influence on Split-Window Algorithm Validation
Landsat 8 (L8) satellite was launched on February 11, 2013 with two thermal bands located in the atmospheric window between $10-12\ \mu \mathrm{m}$ . Continuous monitoring of the Thermal Infrared Sensor (TIRS) onboard of L8 was performed over two Spanish test sites – Barrax and Donana – in order to contribute to the quality of TIRS data. In this work, a Vicarious Calibration (VC) of the TIRS bands was performed between years 2013–2016 in order to assess the new Stray Light (SL) data correction. The results of VC show us that band 10 and 11 provide accurate results (bias near to zero, and precision around 0.8 K) which is an improvement – especially for band 11 – in comparison to preprocessed…
New geo-portal for MODIS/SEVIRI image products with geolocation-based retrieval functionality
A large number of remote sensing data sets have been collected in recent years by Earth observation instruments such as the moderate resolution imaging spectroradiometer (MODIS) aboard the Terra/Aqua satellite and the spinning enhanced visible and infrared imager (SEVIRI) aboard the geostationary platform Meteosat Second Generation. The advanced remote sensing products resulting from the analysis of these data are useful in a wide variety of appli- cations but require significant resources in terms of storage, retrieval, and analysis. Despite the wide availability of these MODIS/SEVIRI products, the data coming from these instruments are spread among different locations and retrieved from d…
Exploring the validity of the long term data record V4 database for land surface monitoring
The last (and final) version of the Long Term Data Record (LTDR) — Version 4 — has been released recently by NASA. This database includes daily information for all AVHRR (Advanced Very High Resolution Radiometer) channels, as well as ancillary data, since July 1981 up to present. This database is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the estimation of vegetation indices at daily resolution, as well as the daily estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring. To that end, we first estimated NDVI (Normalized Difference Vegetation Index), LST, as well as e…
Introducing the Time Series Change Visualization and Interpretation (TSCVI) method for the interpretation of global NDVI changes
Abstract This paper presents a novel method for the visualization of changes in vegetation related variables. This method, termed Time Series Change Visualization and Interpretation (TSCVI), allows to summarize changes associated to both vegetation productivity and phenology in a single map. To that end, three metrics are retrieved on an annual basis from plotting NDVI (Normalized Difference Vegetation Index) values on a polar plot. Changes in these metrics are then analyzed and mapped in an IHS (Intensity Hue Saturation) image, where colors indicate changes regarding the growing-season (earlier or later occurrence, stronger or weaker seasonality), while changes associated to productivity a…
Surface Temperature trends in the Mediterranean Sea from MODIS data during years 2003–2019
Abstract Sea Surface Temperature is a variable recognized as an Essential Climate Variable (ECV) by the Global Climate Observation System (GCOS), due to its determinant influence on climate dynamics, from micro scale to global levels The aim of this paper is to estimate Sea Surface Temperature trends in the Mediterranean Sea during years 2003–2019 by using the MODIS Level 3 SST Thermal IR 8 Day 4km V2019.0. Results show an SST increase of 0.040 ± 0.001 °C/yr. The seasonal maximum trend is associated to summer 0.070 ± 0.001 °C/yr, followed by winter, (0.040 ± 0.001) °C/yr, autumn 0.030 ± 0.001 °C/yr and spring, 0.020 ± 0.001 °C/yr. The total period analyzed has been divided into ten-year tim…
NOAA-AVHRR Orbital Drift Correction: Validating Methods Using MSG-SEVIRI Data as a Benchmark Dataset
National Oceanic and Atmospheric Administration–Advanced Very High Resolution Radiometer (NOAA-AVHRR) data provides the possibility to build the longest Land Surface Temperature (LST) dataset to date, starting in 1981 up to the present. However, due to the orbital drift of the NOAA platforms, no LST dataset is available before 2000 and the arrival of newer platforms. Although numerous methods have been developed to correct this orbital drift effect on the LST, a lack of validation has prevented their application. This is the gap we bridge here by using the 15 min temporal resolution of Meteosat Second Generation–Spinning Enhanced Visible and Infra-Red Imager (MSG-SEVIRI) data to simulate dr…