Detecting trend and seasonal changes in satellite image time series

Verbesselt, Jan; Hyndman, Rob J.; Newnham, Glenn; Culvenor, Darius

doi:10.1016/j.rse.2009.08.014

Cited by 1,408 publications

(1,116 citation statements)

References 32 publications

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“…To detect recent trends at each of the boxes we used the Breaks for Additive Seasonal and Trend (BFAST) method developed by Verbesselt et al (2010) and available as an R package (R Development Core Team, 2011) from the Comprehensive R Archive Network (http://cran.r-project.org/package= bfast). This method integrates an iterative decomposition of time series into a trend, seasonal and noise components, and includes methods for detecting and characterizing changes (breakpoints) within time series.…”

Section: Methodsmentioning

confidence: 99%

“…The number and position of the breakpoints are estimated from the seasonally adjusted data (Yt -Ŝt) with the method proposed by Bai and Perron (2003), which minimizes the Bayesian information criterion (BIC) to determine the optimal number of breaks and iteratively minimizes the residual sum of squares to estimate the optimum break position. Verbesselt et al (2010) give a full description and validation of the method, which has been applied as a normalized difference vegetation index (NDVI; Verbesselt et al, 2010Verbesselt et al, , 2012de Jong et al, 2012). We tested the method suitability for monthly temperature values.…”

Section: Methodsmentioning

confidence: 99%

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Recent trends in sea surface temperature off Mexico

et al. 2013

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RESUMENLos cambios de temperatura promedio del océano a nivel global tienen el potencial de afectar negativamente los sistemas naturales y socioeconómicos actuales; sin embargo, los registros para proyectar las tendencias de cambio a nivel regional son escasos y, en algunos casos, contradictorios. En este estudio se analizan las señales de cambio de la temperatura superficial en mares mexicanos, y se comparan con otras regiones del planeta y con indicadores climáticos clave, tanto del Pacífico Norte como de la franja tropical en el Atlántico y el Pacífico. Se identificaron ocho regiones con diferente exposición a la variabilidad climática: en el Pacífico, la costa occidental de la península de Baja California no muestra una tendencia clara, el Golfo de California exhibe una tendencia modesta de enfriamiento durante los últimos 20 a 25 años, en la parte más oceánica del Pacífico mexicano se nota una tendencia intensa de enfriamiento, la región más tropical muestra una tendencia intensa de calentamiento, y entre ambas regiones se forma una banda de transición sin tendencia; en el Atlántico, la parte noreste del Golfo de México muestra una tendencia de enfriamiento, en tanto que la parte oeste, junto con el Caribe, se han estado calentando por lo menos durante los últimos 30 años. Se analizan las interacciones potenciales de estas tendencias con algunas pesquerías principales y la presencia de ecosistemas costeros sensibles. ABSTRACTChanges in global mean sea surface temperature may have potential negative implications for natural and socioeconomic systems; however, measurements to predict trends in different regions have been limited and sometimes contradictory. In this study, an assessment of sea surface temperature change signals in the seas off Mexico is presented and compared to other regions and the world ocean, and to selected basin scale climatic indices of the North Pacific, the Atlantic and the tropical Pacific variability. We identified eight regions with 538 S. E. Lluch-Cota et al. different exposure to climate variability: In the Pacific, the west coast of the Baja California peninsula with mostly no trend, the Gulf of California with a modest cooling trend during the last 20 to 25 years, the oceanic area with the most intense recent cooling trend, the southern part showing an intense warming trend, and a band of no trend setting the boundary between North-Pacific and tropical-Pacific variability patterns; in the Atlantic, the northeast Gulf of Mexico shows cooling, while the western Gulf of Mexico and the Caribbean have been warming for more than three decades. Potential interactions with fisheries and coastal sensitive ecosystems are discussed.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Recent trends in sea surface temperature off Mexico

et al. 2013

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“…The synoptic view provided by our imagery gives us a spatial perspective where our expectations of "normal" conditions support certain beliefs regarding how the processes constituting the environmental system perform [20]. Image-derived indicators not only document the ambient state of the environment, but also to communicate curious, conspicuous, and unanticipated patterns that emerge from an otherwise homogeneous background.…”

Section: Temporal Monitoring and Assessmentmentioning

confidence: 54%

Tracking Environmental Compliance and Remediation Trajectories Using Image-Based Anomaly Detection Methodologies

Lein

2011

Remote Sensing

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Recent interest in use of satellite remote sensing for environmental compliance and remediation assessment has been heightened by growing policy requirements and the need to provide more rapid and efficient monitoring and enforcement mechanisms. However, remote sensing solutions are attractive only to the extent that they can deliver environmentally relevant information in a meaningful and time-sensitive manner. Unfortunately, the extent to which satellite-based remote sensing satisfies the demands for compliance and remediation assessment under the conditions of an actual environmental accident or calamity has not been well documented. In this study a remote sensing solution to the problem of site remediation and environmental compliance assessment was introduced based on the use of the RDX anomaly detection algorithm and vegetation indices developed from the Tasseled Cap Transform. Results of this analysis illustrate how the use of standard vegetation transforms, integrated into an anomaly detection strategy, enable the time-sequenced tracking of site remediation progress. Based on these results credible evidence can be produced to support compliance evaluation and remediation assessment following major environmental disasters.

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“…To study sudden and gradual changes in land surface, the Break For Additive Season and Trend (BFAST) algorithm was used, [43] which decomposes the series into trend, seasonal and reminder components to evaluate gradual and seasonal dynamics occurring within indices derived from satellite image time series such as NDVI [46][47][48]. The season-trend model [47] (i.e., linear trend and harmonic component) was fitted to pre-processed monthly NDVI time series, and the stability of the model was assessed using a test that determines the significance of structural trend breaks.…”

Section: Trend Analysismentioning

confidence: 99%

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

et al. 2016

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Ukraine has experienced immense environmental and institutional changes during the last three decades. We have conducted this study to analyze important land surface dynamics and to assess processes underlying the changes. This research was conducted in two consecutive steps. To analyze monotonic changes we first applied a Mann-Kendall trend analysis of the Normalized Difference Vegetation Index (NDVI3g) time series. Gradual and abrupt changes were studied by fitting a seasonal trend model and detecting the breakpoints. Secondly, essential environmental factors were used to quantify their possible relationships with land surface changes. These factors included soil moisture as well as gridded air temperature and precipitation data. This was done using partial rank correlation analysis based on annually aggregated time-series. Our results demonstrate that positive NDVI trends characterize approximately one-third of Ukraine's land surface, located in the northern and western areas of the country. Negative trends occurred less frequently, covering less than 2% of the area and are distributed irregularly across the country. Monotonic trends were rarely found; shifting trends were identified with a greater frequency. Trend shifts were seen to occur with an increased frequency following the period of the 2000s. We determined that land surface dynamics and climate variability are functionally interdependent; however, the relative influence of the drivers varies in different locations. Among the factors analyzed, the air temperature variable explains the largest portion of NDVI variability. High air temperature/NDVI correlation coefficients (r = 0.36´0.77) are observed over the entire country. The soil moisture content is of significant influence in the eastern portion of Ukraine (r = 0.68); precipitation (r = 0.65) was most influential in the central regions of the country. These results increase our understanding of ecosystem responses to climatic changes and anthropogenic activities.

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Detecting trend and seasonal changes in satellite image time series

Cited by 1,408 publications

References 32 publications

Recent trends in sea surface temperature off Mexico

Recent trends in sea surface temperature off Mexico

Tracking Environmental Compliance and Remediation Trajectories Using Image-Based Anomaly Detection Methodologies

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

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