{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T23:29:30Z","timestamp":1773012570242,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2016,2,19]],"date-time":"2016-02-19T00:00:00Z","timestamp":1455840000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"German Research Foundation","award":["Ap 243\/1-2, Na 783\/5-1, Na 783\/5-2"],"award-info":[{"award-number":["Ap 243\/1-2, Na 783\/5-1, Na 783\/5-2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>While satellite-based monitoring of vegetation activity at the earth\u2019s surface is of vital importance for many eco-climatological applications, the degree of agreement among certain sensors and products providing estimates of the Normalized Difference Vegetation Index (NDVI) has been found to vary considerably. In order to assess the extent of such differences in highly heterogeneous terrain, we analyze and compare intra-annual seasonal fluctuations and long-term monotonic trends (2003\u20132012) in the Kilimanjaro region, Tanzania. The considered NDVI datasets include the Moderate Resolution Imaging Spectroradiometer (MODIS) products from Terra and Aqua, Collections 5 and 6, and the 3rd Generation Global Inventory Modeling and Mapping Studies (GIMMS) product. The degree of agreement in seasonal fluctuations is assessed by calculating a pairwise Index of Association (IOAs), whereas long-term trends are derived from the trend-free pre-whitened Mann\u2013Kendall test. On the seasonal scale, the two Terra-MODIS products (and, accordingly, the two Aqua-MODIS products) are best associated with each other, indicating that the seasonal signal remained largely unaffected by the new Collection 6 calibration approach. On the long-term scale, we find that the negative impacts of band ageing on Terra-MODIS NDVI have been accounted for in Collection 6, which now distinctly outweighs Aqua-MODIS in terms of greening trends. GIMMS NDVI, by contrast, fails to capture small-scale seasonal and trend patterns that are characteristic for the highly fragmented landscape which is likely owing to the coarse spatial resolution. As a short digression, we also demonstrate that the amount of false discoveries in the determined trend fraction is distinctly higher for  p &lt;               0.05                                  (                                       52.6               %                                 ) than for  p &lt;               0.001                                  (                                       2.2               %                                 ) which should point the way for any future studies focusing on the reliable deduction of long-term monotonic trends.<\/jats:p>","DOI":"10.3390\/rs8020159","type":"journal-article","created":{"date-parts":[[2016,2,19]],"date-time":"2016-02-19T11:29:39Z","timestamp":1455881379000},"page":"159","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Comparative Study of Cross-Product NDVI Dynamics in the Kilimanjaro Region\u2014A Matter of Sensor, Degradation Calibration, and Significance"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2755-5332","authenticated-orcid":false,"given":"Florian","family":"Detsch","sequence":"first","affiliation":[{"name":"Environmental Informatics, Faculty of Geography, Philipps-Universit\u00e4t Marburg, Deutschhausstr. 12, 35032 Marburg, Germany"}]},{"given":"Insa","family":"Otte","sequence":"additional","affiliation":[{"name":"Environmental Informatics, Faculty of Geography, Philipps-Universit\u00e4t Marburg, Deutschhausstr. 12, 35032 Marburg, Germany"}]},{"given":"Tim","family":"Appelhans","sequence":"additional","affiliation":[{"name":"Environmental Informatics, Faculty of Geography, Philipps-Universit\u00e4t Marburg, Deutschhausstr. 12, 35032 Marburg, Germany"}]},{"given":"Thomas","family":"Nauss","sequence":"additional","affiliation":[{"name":"Environmental Informatics, Faculty of Geography, Philipps-Universit\u00e4t Marburg, Deutschhausstr. 12, 35032 Marburg, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2016,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1111\/j.1365-2486.2009.01956.x","article-title":"Debating the greening vs. browning of the North American boreal forest: Differences between satellite datasets","volume":"16","author":"Chuvieco","year":"2010","journal-title":"Glob. Chang. Biol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4485","DOI":"10.1080\/01431160500168686","article-title":"An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data","volume":"26","author":"Tucker","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"324","DOI":"10.5589\/m05-024","article-title":"Generating historical AVHRR 1 km baseline satellite data records over Canada suitable for climate change studies","volume":"31","author":"Latifovic","year":"2005","journal-title":"Can. J. Remote Sens."},{"key":"ref_5","unstructured":"Helsel, D.R., and Hirsch, R.M. (2002). Statistical Methods in Water Resources (Techniques of Water-Resources Investigation, Book 4, Chapter A3), Elsevier."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.rse.2011.12.015","article-title":"Evaluation of Earth Observation based global long term vegetation trends\u2014Comparing GIMMS and MODIS global NDVI time series","volume":"119","author":"Fensholt","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3147","DOI":"10.1111\/gcb.12647","article-title":"Vegetation productivity patterns at high northern latitudes: A multi-sensor satellite data assessment","volume":"20","author":"Guay","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.rse.2011.12.001","article-title":"Impact of sensor degradation on the MODIS NDVI time series","volume":"119","author":"Wang","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4353","DOI":"10.5194\/amt-7-4353-2014","article-title":"Scientific impact of MODIS C5 calibration degradation and C6+ improvements","volume":"7","author":"Lyapustin","year":"2014","journal-title":"Atmos. Meas. Tech."},{"key":"ref_10","unstructured":"Didan, K., Munoz, A.B., Solano, R., and Huete, A. (2015). MODIS Vegetation Index User\u2019s Guide (MOD13 Series), Vegetation Index and Phenology Lab, The University of Arizona. Version 3.0.0 (Collection 6)."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Detsch, F., Otte, I., Appelhans, T., and Nauss, T. (2016). Seasonal and long-term vegetation dynamics from NDVI time series at Mt. Kilimanjaro, Tanzania. Remote Sens. Environ., under review.","DOI":"10.1016\/j.rse.2016.03.007"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6929","DOI":"10.3390\/rs6086929","article-title":"A non-stationary 1981-2012 AVHRR NDVI3g time series","volume":"6","author":"Pinzon","year":"2014","journal-title":"Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Appelhans, T., Mwangomo, E., Otte, I., Detsch, F., Nauss, T., and Hemp, A. (2015). Eco-Meteorological Characteristics of the Southern Slopes of Mt. Kilimanjaro, Tanzania. Int. J. Climatol., Available online: http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/joc.4552\/full.","DOI":"10.1002\/joc.4552"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1111\/j.1466-8238.2010.00585.x","article-title":"Potential impacts of climate change on the environmental services of humid tropical alpine regions","volume":"20","author":"Buytaert","year":"2011","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1111\/j.1365-2486.2005.00968.x","article-title":"Climate change-driven forest fires marginalize the impact of ice cap wasting on Kilimanjaro","volume":"11","author":"Hemp","year":"2005","journal-title":"Glob. Chang. Biol."},{"key":"ref_16","unstructured":"Otte, I., Detsch, F., Mwangomo, E., Nauss, T., and Appelhans, T. (2016). Decadal trends and interannual variability of atmospheric parameters as observed from local and remote sensing time series at Mt. Kilimanjaro, Tanzania. Clim. Dyn., under review."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"199","DOI":"10.3354\/cr028199","article-title":"Influence of topography on monthly rainfall distribution over East Africa","volume":"28","author":"Oettli","year":"2005","journal-title":"Clim. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1111\/j.1365-2028.2006.00679.x","article-title":"Vegetation of Kilimanjaro: Hidden endemics and missing bamboo","volume":"44","author":"Hemp","year":"2006","journal-title":"Afr. J. Ecol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1007\/s00704-013-1082-y","article-title":"Spatiotemporal characterization of land surface temperature in Mount Kilimanjaro using satellite data","volume":"118","author":"Maeda","year":"2014","journal-title":"Theor. Appl. Climatol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_21","unstructured":"Solano, R., Didan, K., Jacobson, A., and Huete, A. (2010). MODIS Vegetation Index User\u2019s Guide (MOD13 Series), Vegetation Index and Phenology Lab, The University of Arizona. Version 2.00, May 2010 (Collection 5)."},{"key":"ref_22","unstructured":"LPDAAC NASA Land Data Products and Services, Available online: https:\/\/lpdaac.usgs.gov\/."},{"key":"ref_23","unstructured":"MODIS Land Team: MODIS Grids, Available online: http:\/\/modis-land.gsfc.nasa.gov\/MODLAND_grid.html."},{"key":"ref_24","unstructured":"MODIS Land Team: MODIS News, Available online: http:\/\/modis-land.gsfc.nasa.gov\/news.html."},{"key":"ref_25","unstructured":"Hyndman, R.J. Forecast: Forecasting Functions for Time Series and Linear Models. Available online: http:\/\/rpackages.ianhowson.com\/cran\/forecast\/."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1080\/17538947.2010.505664","article-title":"A time series for monitoring vegetation activity and phenology at 10-daily time steps covering large parts of South America","volume":"4","author":"Atzberger","year":"2011","journal-title":"Int. J. Digit. Earth"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/BF01245391","article-title":"Area-averaged vegetative cover fraction estimated from satellite data","volume":"38","author":"Wittich","year":"1995","journal-title":"Int. J. Biometeorol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1109\/TGRS.2005.860205","article-title":"Evaluation of the Consistency of Long-Term NDVI Time Series Derived From AVHRR, SPOT-Vegetation, SeaWIFS, MODIS, and Landsat ETM+ Sensors","volume":"44","author":"Brown","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","unstructured":"ECOCAST Data Directory, Available online: http:\/\/ecocast.arc.nasa.gov\/data\/pub\/gimms\/3g.v0\/."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s00484-014-0839-z","article-title":"Determining the relative importance of climatic drivers on spring phenology in grassland ecosystems of semi-arid areas","volume":"59","author":"Zhu","year":"2015","journal-title":"Int. J. Biometeorol."},{"key":"ref_31","unstructured":"Detsch, F. Gimms: Download and Process GIMMS NDVI3g Data. Available online: http:\/\/CRAN.R-project.org\/package=gimms."},{"key":"ref_32","unstructured":"Matloff, N. (2011). The Art of R Programming, No Starch Press."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v065.i10","article-title":"remote: Empirical Orthogonal Teleconnections in R","volume":"65","author":"Appelhans","year":"2015","journal-title":"J. Stat. Softw."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1016\/j.rse.2010.10.011","article-title":"Analysis of monotonic greening and browning trends from global NDVI time-series","volume":"115","author":"Schaepman","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1807","DOI":"10.1002\/hyp.1095","article-title":"The influence of autocorrelation on the ability to detect trend in hydrological series","volume":"16","author":"Yue","year":"2002","journal-title":"Hydrol. Process."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1111\/j.1467-9671.2011.01280.x","article-title":"A Contextual Mann\u2013Kendall Approach for the Assessment of Trend Significance in Image Time Series","volume":"15","author":"Neeti","year":"2011","journal-title":"Trans. GIS"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the Regression Coefficient Based on Kendall\u2019s Tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_38","unstructured":"Bronaugh, D., and Werner, A. Zyp: Zhang + Yue-Pilon Trends Package. Available online: http:\/\/CRAN.R-project.org\/package=zyp."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2307\/1907187","article-title":"Nonparametric tests against trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econometrica"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1093\/biomet\/30.1-2.81","article-title":"A new measure of rank correlation","volume":"30","author":"Kendall","year":"1938","journal-title":"Biometrika"},{"key":"ref_41","unstructured":"Meals, D.W., Spooner, J., Dressing, S.A., and Harcum, J.B. (2011). Statistical Analysis for Monotonic Trends, National Nonpoint Source Monitoring Program. Tech Notes 6."},{"key":"ref_42","unstructured":"McLeod, A.I. Kendall: Kendall Rank Correlation and Mann\u2013Kendall Trend Test. Available online: http:\/\/CRAN.R-project.org\/package=Kendall."},{"key":"ref_43","first-page":"247","article-title":"The Power of Statistical Tests for Trend Detection","volume":"27","author":"Bayazit","year":"2003","journal-title":"Turk. J. Eng. Environ. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Colquhoun, D. (2014). An investigation of the false discovery rate and the misinterpretation of p-values. R. Soc. Open Sci., 1.","DOI":"10.1098\/rsos.140216"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Miller, D.A. (1966). \u201cSignificant\u201d and \u201cHighly Significant\u201d. Nature, 210.","DOI":"10.1038\/2101190a0"},{"key":"ref_47","unstructured":"Map Data: Google, TerraMetrics. Available online: http:\/\/maps.googleapis.com\/maps\/api\/staticmap?center=-3.123553240247,37.366348380164&zoom=10&size=640x497&maptype=satellite&format=gif&sensor=false&scale=2."},{"key":"ref_48","unstructured":"Ong\u2019injo, J., Lambrechts, C., and Hemp, A. (Personal communication, 2015). Personal communication."},{"key":"ref_49","unstructured":"OpenStreetMap Copyright and License. Available online: http:\/\/www.openstreetmap.org\/copyright."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1657\/1523-0430(06-127)[DUANE]2.0.CO;2","article-title":"General Characteristics of Temperature and Humidity Variability on Kilimanjaro, Tanzania","volume":"40","author":"Duane","year":"2008","journal-title":"Arct. Antarct. Alp. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1002\/jgrg.20115","article-title":"In the hot seat: Insolation, ENSO, and vegetation in the African Tropics","volume":"118","author":"Ivory","year":"2013","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_52","first-page":"539","article-title":"Remote Sensing of Tropical Forest Phenology: Issues and Controversies","volume":"38","author":"Huete","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Rutten, G., Ensslin, A., Hemp, A., and Fischer, M. (2015). Vertical and Horizontal Vegetation Structure across Natural and Modified Habitat Types at Mount Kilimanjaro. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0138822"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3364","DOI":"10.3390\/rs4113364","article-title":"How Normalized Difference Vegetation Index (NDVI) Trends from Advance Very High Resolution Radiometer (AVHRR) and Syst\u00e8me Probatoire d\u2019Observation de la Terre VEGETATION (SPOT VGT) Time Series Differ in Agricultural Areas: An Inner Mongolian Case Study","volume":"4","author":"Yin","year":"2012","journal-title":"Remote Sens."},{"key":"ref_55","unstructured":"Kidwell, K.B. NOAA POLAR ORBITER DATA USER\u2019S GUIDE (TIROS-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-10, NOAA-11, NOAA-12, NOAA-13 AND NOAA-14), Available online: https:\/\/www.ncdc.noaa.gov\/oa\/pod-guide\/ncdc\/docs\/podug\/index.htm."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.rse.2015.03.031","article-title":"Evaluating temporal consistency of long-term global NDVI datasets for trend analysis","volume":"163","author":"Tian","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_57","unstructured":"Barreto-Munoz, A. (2013). Multi-Sensor Vegetation Index and Land Surface Phenology Earth Science Data Records in Support of Global Change Studies: Data Quality Challenges and Data Explorer System. [Ph.D. Thesis, Department of Agricultural and Biosystems Engineering, The University of Arizona]."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/2\/159\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:19:24Z","timestamp":1760210364000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/2\/159"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,2,19]]},"references-count":57,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2016,2]]}},"alternative-id":["rs8020159"],"URL":"https:\/\/doi.org\/10.3390\/rs8020159","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,2,19]]}}}