{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T23:12:15Z","timestamp":1770765135139,"version":"3.50.0"},"reference-count":61,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,17]],"date-time":"2016-05-17T00:00:00Z","timestamp":1463443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Basic Research Program of China","award":["2015CB953702"],"award-info":[{"award-number":["2015CB953702"]}]},{"name":"SAFEA Long-term Projects of the 1000 Talent Plan for High-Level Foreign Experts","award":["WQ20141100224"],"award-info":[{"award-number":["WQ20141100224"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The time lag between anomalies in precipitation and vegetation activity plays a critical role in early drought detection as agricultural droughts are caused by precipitation shortages. The aim of this study is to explore a new approach to estimate the time lag between a forcing (precipitation) and a response (NDVI) signal in the frequency domain by applying cross-spectral analysis. We prepared anomaly time series of image data on TRMM3B42 precipitation (accumulated over antecedent durations of 10, 60, and 150 days) and NDVI, reconstructed and interpolated MOD13A2 and MYD13A2 to daily interval using a Fourier series method to model time series affected by gaps and outliers (iHANTS) for a dry and a wet year in a drought-prone area in the northeast region of China. Then, the cross-spectral analysis was applied pixel-wise and only the phase lag of the annual component of the forcing and response signal was extracted. The 10-day antecedent precipitation was retained as the best representation of forcing. The estimated phase lag was interpreted using maps of land cover and of available soil water-holding capacity and applied to investigate the difference in phenology responses between a wet and dry year. In both the wet and dry year, we measured consistent phase lags across land cover types. In the wet year with above-average precipitation, the phase lag was rather similar for all land cover types, i.e., 7.6 days for closed to open grassland and 14.5 days for open needle-leaved deciduous or evergreen forest. In the dry year, the phase lag increased by 7.0 days on average, but with specific response signals for the different land cover types. Interpreting the phase lag against the soil water-holding capacity, we observed a slightly higher phase lag in the dry year for soils with a higher water-holding capacity. The accuracy of the estimated phase lag was assessed through Monte Carlo simulations and presented reliable estimates for the annual component.<\/jats:p>","DOI":"10.3390\/rs8050422","type":"journal-article","created":{"date-parts":[[2016,5,17]],"date-time":"2016-05-17T10:20:11Z","timestamp":1463480411000},"page":"422","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Early Drought Detection by Spectral Analysis of Satellite Time Series of Precipitation and Normalized Difference Vegetation Index (NDVI)"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1836-805X","authenticated-orcid":false,"given":"Mattijn","family":"Van Hoek","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Li","family":"Jia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1199-4261","authenticated-orcid":false,"given":"Jie","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CN Delft, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6085-8274","authenticated-orcid":false,"given":"Chaolei","family":"Zheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Massimo","family":"Menenti","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CN Delft, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1175\/BAMS-88-9-1383","article-title":"The WCRP CMIP3 multimodel dataset: A new era in climate change research","volume":"88","author":"Meehl","year":"2007","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"17905","DOI":"10.1073\/pnas.1101766108","article-title":"Increase of extreme events in a warming world","volume":"108","author":"Rahmstorf","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1080\/02508068508686328","article-title":"Understanding: The drought phenomenon: The role of definitions","volume":"10","author":"Wilhite","year":"1985","journal-title":"Water Int."},{"key":"ref_4","unstructured":"Beran, M.A., and Rodier, J.A. (1985). Hydrological Aspects of Drought: A Contribution to the International Hydrological Programme, Unesco."},{"key":"ref_5","unstructured":"Demuth, S., and Bakenhus, A. (1994). Hydrological Drought\u2014A Literature Review, University of Freiburg."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1002\/wcc.81","article-title":"Drought under global warming: A review","volume":"2","author":"Dai","year":"2011","journal-title":"Wiley Interdiscip. Rev. Clim. Chang."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Vogt, J.V., and Somma, F. (2000). Drought and Drought Mitigation in Europe, Springer Netherlands.","DOI":"10.1007\/978-94-015-9472-1"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1175\/1520-0477-83.8.1167","article-title":"The quantification of drought: An evaluation of drought indices","volume":"83","author":"Keyantash","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1175\/1520-0477-83.8.1149","article-title":"A review of twentieth-century drought indices used in the United States","volume":"83","author":"Heim","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1175\/1520-0477-83.8.1181","article-title":"The drought monitor","volume":"83","author":"Svoboda","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1175\/2009JCLI2909.1","article-title":"A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index","volume":"23","year":"2010","journal-title":"J. Clim."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.jhydrol.2010.07.012","article-title":"A review of drought concepts","volume":"391","author":"Mishra","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_13","unstructured":"Rouse, J.W., Haas, R.H., and Schell, J.A. (1974). Monitoring The Vernal Advancement and Retrogradation (Greenwave Effect) of Natural Vegetation, Texas A & M University, Remote Sensing Center. Report RSC 1978-4."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0273-1177(95)00079-T","article-title":"Application of vegetation index and brightness temperature for drought detection","volume":"15","author":"Kogan","year":"1995","journal-title":"Adv. Space Res."},{"key":"ref_15","first-page":"71","article-title":"Drought monitoring with NDVI-based standardized vegetation index","volume":"68","author":"Peters","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2875","DOI":"10.1016\/j.rse.2010.07.005","article-title":"Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data","volume":"114","author":"Rhee","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.rse.2013.02.023","article-title":"Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data","volume":"134","author":"Zhang","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1061\/(ASCE)0733-9496(1998)124:5(246)","article-title":"Drought contingency planning: Evaluating the effectiveness of plans","volume":"124","author":"Shepherd","year":"1998","journal-title":"J. Water Res. Plan. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1006\/jare.2001.0847","article-title":"Landscape change and desertification development in the MU US Sandland, Northern China","volume":"50","author":"Wu","year":"2002","journal-title":"J. Arid Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3519","DOI":"10.5194\/nhess-12-3519-2012","article-title":"Development of a combined drought indicator to detect agricultural drought in Europe","volume":"12","author":"Horion","year":"2012","journal-title":"Natl. Hazards Earth Syst. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0034-4257(03)00174-3","article-title":"Assessing vegetation response to drought in the northern great plains using vegetation and drought indices","volume":"87","author":"Ji","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.gloplacha.2012.09.007","article-title":"The relationship between precipitation anomalies and satellite-derived vegetation activity in central Asia","volume":"110","author":"Gessner","year":"2013","journal-title":"Glob. Planet. Chang."},{"key":"ref_23","unstructured":"Stoica, P., and Moses, R.L. (2004). Spectral Analysis of Signals, Prentice Hall, Inc."},{"key":"ref_24","unstructured":"Bloomfield, P. (2005). Fourier Analysis of Time Series, John Wiley & Sons."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Percival, D.B., and Walden, A.T. (1993). Spectral Analysis for Physical Applications, Cambridge University Press.","DOI":"10.1017\/CBO9780511622762"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.neuroimage.2005.05.043","article-title":"Measuring temporal dynamics of functional networks using phase spectrum of FMRI data","volume":"28","author":"Sun","year":"2005","journal-title":"NeuroImage"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s00703-004-0101-z","article-title":"Regional trends in recent precipitation indices in China","volume":"90","author":"Qian","year":"2005","journal-title":"Meteorol. Atmos. Phys."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3056","DOI":"10.3390\/rs70303056","article-title":"Monitoring of evapotranspiration in a semi-arid inland river basin by combining microwave and optical remote sensing observations","volume":"7","author":"Hu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zou, X., Zhai, P., and Zhang, Q. (2005). Variations in droughts over China: 1951\u20132003. Geophys. Res. Lett., 32.","DOI":"10.1029\/2004GL021853"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1002\/joc.3701","article-title":"Are droughts becoming more frequent or severe in China based on the standardized precipitation evapotranspiration index: 1951\u20132010?","volume":"34","author":"Yu","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_31","first-page":"D21114","article-title":"Regional atmospheric anomalies responsible for the 2009\u20132010 severe drought in China","volume":"116","author":"Lu","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1175\/JHM-D-11-074.1","article-title":"The October 2009 drought in China: Possible causes and impacts on vegetation","volume":"13","author":"Barriopedro","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_33","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_34","doi-asserted-by":"crossref","unstructured":"Huete, A.R., Didan, K., Shimabukuro, Y.E., Ratana, P., Saleska, S.R., Hutyra, L.R., Yang, W., Nemani, R.R., and Myneni, R. (2006). Amazon rainforests green-up with sunlight in dry season. Geophys. Res. Lett., 33.","DOI":"10.1029\/2005GL025583"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/0273-1177(93)90550-U","article-title":"Mapping agroecological zones and time lag in vegetation growth by means of fourier analysis of time series of NDVI images","volume":"13","author":"Menenti","year":"1993","journal-title":"Adv. Space Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1080\/01431169608949001","article-title":"Cover a colour composite of NOAA-AVHRR-NDVI based on time series analysis (1981\u20131992)","volume":"17","author":"Verhoef","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","unstructured":"Maselli, F., Menenti, M., and Brivio, P.A. (2010). Remote Sensing Optical Observation of Vegetation Properties, Research Signpost."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.1080\/014311600209814","article-title":"Reconstructing cloudfree NDVI composites using fourier analysis of time series","volume":"21","author":"Roerink","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","unstructured":"Jia, L., Li, J., and Menenti, M. Drought Monitoring And Prediction by Time Series Analysis of Greenness and Thermal Anomalies at Large Scale. Available online: http:\/\/adsabs.harvard.edu\/abs\/2009EGUGA..11.9659J."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Zhou, J., Jia, L., Hu, G., and Menenti, M. (2012, January 8\u201311). Evaluation of harmonic analysis of time series (HANTS): Impact of gaps on time series reconstruction. Proceedings of the Earth Observation and Remote Sensing Applications (EORSA), 2012 Second International Workshop, Shanghai, Chian.","DOI":"10.1109\/EORSA.2012.6261129"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.rse.2015.03.018","article-title":"Reconstruction of global MODIS NDVI time series: Performance of harmonic analysis of time series (HANTS)","volume":"163","author":"Zhou","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1272","DOI":"10.1080\/01431161.2013.876118","article-title":"Multi-scale evaluation of six high-resolution satellite monthly rainfall estimates over a humid region in China with dense rain gauges","volume":"35","author":"Hu","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_43","unstructured":"Arino, O., Ramos Perez, J.J., Kalogirou, V., Bontemps, S., Defourny, P., and Van Bogaert, E. (2012). Global Land Cover Map for 2009 (Globcover 2009), ESA and CUL."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1175\/JHM-D-12-0149.1","article-title":"Development of a China dataset of soil hydraulic parameters using pedotransfer functions for land surface modeling","volume":"14","author":"Dai","year":"2013","journal-title":"J. Hydrometeorol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.agwat.2004.07.003","article-title":"Crop water deficit estimation and irrigation scheduling in western Jilin province, Northeast China","volume":"71","author":"Li","year":"2005","journal-title":"Agric. Water Manag."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/BF02446290","article-title":"Biomedical signal processing (in four parts)","volume":"29","author":"Challis","year":"1991","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_47","unstructured":"Salter, P.J., and Goode, J.E. (1967). Crop Responses to Water at Different Stages of Growth, Commonwealth Agricultural Bureaux. Research Review No. 2."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"168","DOI":"10.2151\/sola.2006-043","article-title":"Study on influence of rainfall distribution on NDVI anomaly over the arid regions in Mongolia using an operational weather radar","volume":"2","author":"Iwasaki","year":"2006","journal-title":"SOLA"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/BF00138369","article-title":"A comparison of the vegetation response to rainfall in the sahel and East Africa, using normalized difference vegetation index from NOAA AVHRR","volume":"17","author":"Nicholson","year":"1990","journal-title":"Clim. Chang."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1080\/014311698216198","article-title":"Estimating relations between Avhrr Ndvi and rainfall in east Africa at 10-day and monthly time scales","volume":"19","author":"Eklundh","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.rse.2006.08.009","article-title":"Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa","volume":"106","author":"Camberlin","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_52","first-page":"30","article-title":"Spatiotemporal drifts in AVHRR\/NDVI\u2013precipitation relationship and their linkage to land use change in central Kazakhstan","volume":"7","author":"Propastin","year":"2008","journal-title":"EARSeL eProceedings"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1016\/j.jaridenv.2005.01.015","article-title":"Inter-annual variability and interaction of remote-sensed vegetation index and atmospheric precipitation in the Aral Sea region","volume":"62","author":"Nezlin","year":"2005","journal-title":"J. Arid Environ."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Granger, C.W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econ. J. Econom. Soc.","DOI":"10.2307\/1912791"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.jeconom.2005.02.004","article-title":"Testing for short-and long-run causality: A frequency-domain approach","volume":"132","author":"Breitung","year":"2006","journal-title":"J. Econ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1126\/science.1227079","article-title":"Detecting causality in complex ecosystems","volume":"338","author":"Sugihara","year":"2012","journal-title":"Science (N.Y.)"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"561","DOI":"10.5194\/npg-11-561-2004","article-title":"Application of the cross wavelet transform and wavelet coherence to geophysical time series","volume":"11","author":"Grinsted","year":"2004","journal-title":"Nonlinear Process. Geophys."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1175\/1520-0477(1998)079<0061:APGTWA>2.0.CO;2","article-title":"A practical guide to wavelet analysis","volume":"79","author":"Torrence","year":"1998","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","article-title":"The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis","volume":"454","author":"Huang","year":"1998","journal-title":"Royal Soc."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1080\/014311602753474192","article-title":"Relations between AVHRR NDVI and ecoclimatic parameters in China","volume":"23","author":"Li","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Bond-Lamberty, B., Bunn, A.G., and Thomson, A.M. (2012). Multi-year lags between forest browning and soil respiration at high northern latitudes. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0050441"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/5\/422\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:24:01Z","timestamp":1760210641000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/5\/422"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,5,17]]},"references-count":61,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2016,5]]}},"alternative-id":["rs8050422"],"URL":"https:\/\/doi.org\/10.3390\/rs8050422","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,5,17]]}}}