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.
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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37 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
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- 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
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- 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
- Monitoring Changes in the Enhanced Vegetation Index to Inform the Management of Forests P. Rodriguez et al. 10.3390/rs16162919
- 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
- Perspectives on modifiable spatiotemporal unit problems in remote sensing of agriculture: evaluating rice production in Vietnam and tools for analysis B. Peter et al. 10.3389/frsen.2024.1042624
- 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
- Tri-Clustering Based Exploration of Temporal Resolution Impacts on Spatio-Temporal Clusters in Geo-Referenced Time Series X. Wu & D. Zheng 10.3390/ijgi9040210
- 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
- Regional divergent evolution of vegetation greenness and climatic drivers in the Sahel-Sudan-Guinea region: nonlinearity and explainable machine learning Y. Zeng et al. 10.3389/ffgc.2024.1416373
- 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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