Articles | Volume 9, issue 1
https://doi.org/10.5194/bg-9-71-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-9-71-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
05 Jan 2012
Research article |
| 05 Jan 2012
Linear trends in seasonal vegetation time series and the modifiable temporal unit problem
R. de Jong
Laboratory of Geo-Information and Remote Sensing, Wageningen University, The Netherlands
ISRIC – World Soil Information, Wageningen, The Netherlands
S. de Bruin
Laboratory of Geo-Information and Remote Sensing, Wageningen University, The Netherlands
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34 citations as recorded by crossref.
- Analysis on spatio-temporal trends and drivers in vegetation growth during recent decades in Xinjiang, China J. Du et al. 10.1016/j.jag.2015.01.006
- Trend analysis of MODIS NDVI time series and its relationship to temperature and precipitation in Northeastern of Iran M. Dastigerdi et al. 10.1007/s10661-024-12463-y
- Satellite-based decadal change assessments of pan-Arctic environments L. Jenkins et al. 10.1007/s13280-019-01249-z
- Autumn NDVI contributes more and more to vegetation improvement in the growing season across the Tibetan Plateau J. Du et al. 10.1080/17538947.2017.1282547
- Joint assessment of temporal segmentation, time unit and detection algorithms in syndromic surveillance S. Brilleaud et al. 10.1016/j.prevetmed.2022.105619
- Time to address the spatiotemporal uncertainties in COVID-19 research: Concerns and challenges M. Helbich et al. 10.1016/j.scitotenv.2020.142866
- Identification of environmental anomaly hot spots in West Africa from time series of NDVI and rainfall M. Boschetti et al. 10.1016/j.isprsjprs.2013.01.003
- Change of plant phenophases explained by survival modeling B. Templ et al. 10.1007/s00484-016-1267-z
- Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology J. Allen et al. 10.1111/gcb.12364
- Identifying Temporal Aggregation Effect on Crash-Frequency Modeling B. Bae et al. 10.3390/su13116214
- Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013 G. Ghazaryan et al. 10.3390/rs8080617
- Developing a Flexible Framework for Spatiotemporal Population Modeling D. Martin et al. 10.1080/00045608.2015.1022089
- Vegetation Trend Detection Using Time Series Satellite Data as Ecosystem Condition Indicators for Analysis in the Northwestern Highlands of Ethiopia B. Alemayehu et al. 10.3390/rs15205032
- Multidecadal trend analysis of in situ aerosol radiative properties around the world M. Collaud Coen et al. 10.5194/acp-20-8867-2020
- Environmental change in the Sahel: reconciling contrasting evidence and interpretations K. Rasmussen et al. 10.1007/s10113-015-0778-1
- Defining Landscapes and Scales to Model Landscape–Organism Interactions M. Boyce et al. 10.1007/s40823-017-0027-z
- Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases N. Hamm et al. 10.1371/journal.pntd.0004164
- Effects of the prewhitening method, the time granularity, and the time segmentation on the Mann–Kendall trend detection and the associated Sen's slope M. Collaud Coen et al. 10.5194/amt-13-6945-2020
- Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change X. Huang et al. 10.3390/ijerph16183452
- High Resolution Forest Masking for Seasonal Monitoring with a Regionalized and Colourimetrically Assisted Chorologic Typology R. Aravena et al. 10.3390/rs15143457
- Comparative study of three satellite image time-series decomposition methods for vegetation change detection A. Ben Abbes et al. 10.1080/22797254.2018.1465360
- Spatial Pattern of Agricultural Productivity Trends in Malawi L. Mungai et al. 10.3390/su12041313
- Does the integration of the dynamic nitrogen cycle in a terrestrial biosphere model improve the long-term trend of the leaf area index? B. Guenet et al. 10.1007/s00382-012-1388-y
- Modifiable Temporal Unit Problem (MTUP) and Its Effect on Space-Time Cluster Detection T. Cheng et al. 10.1371/journal.pone.0100465
- Spatiotemporal variation and influencing factors of vegetation dynamics based on Geodetector: A case study of the northwestern Yunnan Plateau, China H. Huo & C. Sun 10.1016/j.ecolind.2021.108005
- Non-stationarity in MODIS fAPAR time-series and its impact on operational drought detection C. Cammalleri & J. Vogt 10.1080/01431161.2018.1524603
- Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence A. Araujo Navas et al. 10.1371/journal.pntd.0005208
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- Temporal aggregation bias and Gerrymandering urban time series S. Stehle 10.1007/s10707-021-00452-z
- Visual Discovery of Synchronisation in Weather Data at Multiple Temporal Resolutions X. Wu et al. 10.1179/1743277413Y.0000000067
- Tendências temporais de índices de vegetação nos campos do Pampa do Brasil e do Uruguai A. Wagner et al. 10.1590/S0100-204X2013000900002
- Co-clustering geo-referenced time series: exploring spatio-temporal patterns in Dutch temperature data X. Wu et al. 10.1080/13658816.2014.994520
- The role of spatial scale in drought monitoring and early warning systems: a review J. Mardian 10.1139/er-2021-0102
- Crop climate suitability mapping on the cloud: a geovisualization application for sustainable agriculture B. Peter et al. 10.1038/s41598-020-72384-x
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