[
Abatzoglou, J.T., Dobrowski, S.Z., Parks, S.A., Hegewisch, K.C., 2018. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015. Sci. Data, 5, 1–12. https://doi.org/10.1038/sdata.2017.191
]Search in Google Scholar
[
Amer, R.A.-M., Baahmed, D., Cherif, E.-A., Iddou, A., 2021. Trend detection of hydroclimatic parameters in central coastal basin of Oran in Algeria: is there any impact on water resources? Arab. J. Geosci., 14, 1–20. https://doi.org/10.1007/s12517-021-07816-7
]Search in Google Scholar
[
Anyamba, A., Small, J.L., Tucker, C.J., Pak, E.W., 2014. Thirtytwo years of Sahelian zone growing season non-stationary NDVI3g patterns and trends. Remote Sens., 6, 4, 3101–3122. https://doi.org/10.3390/rs6043101
]Search in Google Scholar
[
Atzberger, C., Klisch, A., Mattiuzzi, M., Vuolo, F., 2014. Phenological metrics derived over the European continent from NDVI3g data and MODIS time series. Remote Sens., 6, 1, 257–284. https://doi.org/10.3390/rs6010257
]Search in Google Scholar
[
Ayantobo, O.O., Wei, J., 2019. Appraising regional multicategory and multi-scalar drought monitoring using standardized moisture anomaly index (SZI): A water-energy balance approach. J. Hydrol., 579, 124139. https://doi.org/10.1016/j.jhydrol.2019.124139
]Search in Google Scholar
[
Baahmed, D., Oudin, L., Errih, M., 2015. Current runoff variations in the Macta catchment (Algeria): is climate the sole factor? Hydrol. Sci. J., 60, 1331–1339. https://doi.org/10.1080/02626667.2014.975708
]Search in Google Scholar
[
Babüroğlu, E.S., Durmuşoğlu, A., Dereli, T., 2021. Novel hybrid pair recommendations based on a large-scale comparative study of concept drift detection. Expert Syst. Appl., 163, 113786. https://doi.org/10.1016/j.eswa.2020.113786
]Search in Google Scholar
[
Bai, X.Y., Fan, Z.M., Yue, T.X., 2023. Dynamic pattern-effect relationships between precipitation and vegetation in the semi-arid and semi-humid area of China. Catena, 232, 107425. https://doi.org/10.1016/j.catena.2023.107425
]Search in Google Scholar
[
Barbosa, H.A., Huete, A.R., Baethgen, W.E., 2006. A 20-year study of NDVI variability over the Northeast Region of Brazil. J. Arid Environ., 67, 288–307. https://doi.org/10.1016/j.jaridenv.2006.02.022
]Search in Google Scholar
[
Beddal, D., Achite, M., Baahmed, D., 2020. Streamflow prediction using data-driven models: Case study of Wadi Hounet, northwestern Algeria. J. Water Land Dev., 47, 1, 16-24. https://doi.org/10.24425/jwld.2020.135027
]Search in Google Scholar
[
Benaissa, H., Benabdeli, K., 2019. Evaluation de l’impact du parcours sur la végétation du Parc national de Tlemcen (Algérie nord-occidentale). Geo. Eco. Trop., 43, 129–136.
]Search in Google Scholar
[
Bentekhici, N., Bellal, S.A., Zegrar, A., 2020. Contribution of remote sensing and GIS to mapping the fire risk of Mediterranean forest case of the forest massif of Tlemcen (North-West Algeria). Nat. Hazards, 104, 811–831. https://doi.org/10.1007/s11069-020-04191-6
]Search in Google Scholar
[
Berhail, S., Tourki, M., Merrouche, I., Bendekiche, H., 2022. Geo-statistical assessment of meteorological drought in the context of climate change: case of the Macta basin (Northwest of Algeria). Model. Earth Syst. Environ., 8, 81–101. https://doi.org/10.1007/s40808-020-01055-7
]Search in Google Scholar
[
Birtwistle, A.N., Laituri, M., Bledsoe, B., Friedman, J.M., 2016. Using NDVI to measure precipitation in semi-arid landscapes. J. Arid Environ., 131, 15–24. https://doi.org/10.1016/j.jaridenv.2016.04.004
]Search in Google Scholar
[
Buyantuyev, A., Wu, J., 2009. Urbanization alters spatiotemporal patterns of ecosystem primary production: A case study of the Phoenix metropolitan region, USA. J. Arid Environ., 73, 512-520. https://doi.org/10.1016/j.jaridenv.2008.12.015
]Search in Google Scholar
[
Cai, Q., Liu, Y., Zhang, H., Song, H., Li, Q., Sun, C., Wang, L., Fang, C., Liu, R., 2021. Evolution of the dry-wet variations since 1834 CE in the Lüliang Mountains, north China and its relationship with the Asian summer monsoon. Ecol. Indic., 121, 107089. https://doi.org/10.1016/j.ecolind.2020.107089
]Search in Google Scholar
[
Cavalli, S., Penzotti, G., Amoretti, M., Caselli, S., 2021. A machine learning approach for NDVI forecasting based on Sentinel-2 data. In: Proceedings of the 16th International Conference on Software Technologies ICSOFT - Volume 1, 473–480. https://doi.org/10.5220/0010544504730480
]Search in Google Scholar
[
Chevan, A., Sutherland, M., 1991. Hierarchical partitioning. Am. Stat., 45, 90–96.
]Search in Google Scholar
[
Chrair, M., Khaldi, A., Hamadouche, M.A., Hamimed, A., Cernesson, F., Alkan, M., 2020. Evaluation of the effects of land cover changes and urbanization on land surface temperature: a remote sensing study of sub-watershed of Oued Fekan, Northwest Algeria. Sigma J. Eng. Nat. Sci., 38, 907–926.
]Search in Google Scholar
[
Dagnachew, M., Dagnachew, M., Kebede, A., Moges, A., Abebe, A., 2020. Effects of climate variability on Normalized Difference Vegetation Index (NDVI) in the Gojeb River Catchment, Omo-Gibe Basin, Ethiopia. Adv. Meteorol., 2020, 3263246. https://doi.org/10.1155/2020/8263246
]Search in Google Scholar
[
Fensholt, R., Langanke, T., Rasmussen, K., Reenberg, A., Prince, S.D., Tucker, C., Scholes, R.J., Le, Q.B., Bondeau, A., Eastman, R., 2012. Greenness in semi-arid areas across the globe 1981–2007—an Earth Observing Satellite based analysis of trends and drivers. Remote Sens. Environ., 121, 144–158. https://doi.org/10.1016/j.rse.2012.01.017
]Search in Google Scholar
[
Formica, A.F., Burnside, R.J., Dolman, P.M., 2017. Rainfall validates MODIS-derived NDVI as an index of spatiotemporal variation in green biomass across non-montane semi-arid and arid Central Asia. J. Arid Environ., 142, 11–21. https://doi.org/10.1016/j.jaridenv.2017.02.005
]Search in Google Scholar
[
Fu, B., Burgher, I., 2015. Riparian vegetation NDVI dynamics and its relationship with climate, surface water and groundwater. J. Arid Environ., 113, 59–68. https://doi.org/10.1016/j.jaridenv.2014.09.010
]Search in Google Scholar
[
Gang, Y.I.N., Zengyun, H.U., Xi, C., Tashpolat, T., 2016. Vegetation dynamics and its response to climate change in Central Asia. Journal of Arid Land, 8, 375–388. https://doi.org/10.1007/s40333-016-0043-6
]Search in Google Scholar
[
Gaughan, A.E., Stevens, F.R., Gibbes, C., Southworth, J., Binford, M.W., 2012. Linking vegetation response to seasonal precipitation in the Okavango–Kwando–Zambezi catchment of southern Africa. Int. J. Remote Sens., 33, 6783-6804. https://doi.org/10.1080/01431161.2012.692831
]Search in Google Scholar
[
Ghebrezgabher, M.G., Yang, T., Yang, X., Eyassu Sereke, T., 2020. Assessment of NDVI variations in responses to climate change in the Horn of Africa. Egypt. J. Remote Sens. Sp. Sci., 23, 249–261. https://doi.org/10.1016/j.ejrs.2020.08.003
]Search in Google Scholar
[
Gherissi, R., Kamila, B.-H., Abderrazak, B., 2021. Highlighting drought in the Wadi Lakhdar Watershed Tafna, Northwestern Algeria. Arab. J. Geosci., 14, 1–23. https://doi.org/10.1007/s12517-021-07094-3
]Search in Google Scholar
[
Giorgi, F., Lionello, P., 2008. Climate change projections for the Mediterranean region. Glob. Planet. Change, 63, 90–104. https://doi.org/10.1016/j.gloplacha.2007.09.005
]Search in Google Scholar
[
Han, J., Zhang, X., Wang, J., Zhai, J., 2023. geographic exploration of the driving forces of the NDVI spatial differentiation in the Upper Yellow River basin from 2000 to 2020. Sustainability, 15, 3, 1922; https://doi.org/10.3390/su15031922
]Search in Google Scholar
[
Harris, I., Jones, P.D., Osborn, T.J., Lister, D.H., 2014. Updated high‐resolution grids of monthly climatic observations–the CRU TS3. 10 Dataset. Int. J. Climatol., 34, 623–642. https://doi.org/10.1002/joc.3711
]Search in Google Scholar
[
Hawinkel, P., Thiery, W., Lhermitte, S., Swinnen, E., Verbist, B., Van Orshoven, J., Muys, B., 2016. Vegetation response to precipitation variability in East Africa controlled by biogeographical factors. J. Geophys. Res. Biogeosciences, 121, 2422–2444. https://doi.org/10.1002/2016JG003436
]Search in Google Scholar
[
Hou, W., Gao, J., Wu, S., Dai, E., 2015. Interannual variations in growing-season NDVI and its correlation with climate variables in the southwestern karst region of China. Remote Sens., 7, 11105–11124. https://doi.org/10.3390/rs70911105
]Search in Google Scholar
[
Hu, C.H., Ran, G., Li, G., Yu, Y., Wu, Q., Yan, D., Jian, S., 2021. The effects of rainfall characteristics and land use and cover change on runoff in the Yellow River basin, China. J. Hydrol. Hydromech., 69, 29–40. https://doi.org/10.2478/johh-2020-0042
]Search in Google Scholar
[
Huang, K., Xia, J., Wang, Y., Ahlström, A., Chen, J., Cook, R.B., Cui, E., Fang, Y., Fisher, J.B., Huntzinger, D.N., 2018. Enhanced peak growth of global vegetation and its key mechanisms. Nat. Ecol. Evol., 2, 1897–1905. https://doi.org/10.1038/s41559-018-0714-0
]Search in Google Scholar
[
Huang, S., Kong, J., 2016. Assessing land degradation dynamics and distinguishing human-induced changes from climate factors in the Three-North Shelter forest region of China. ISPRS Int. J. Geo-Information, 5, 158. https://doi.org/10.3390/ijgi5090158
]Search in Google Scholar
[
IPCC, 2022. Climate Change 2022 - Mitigation of Climate Change. Full Report. Cambridge University Press.
]Search in Google Scholar
[
Jiang, S., Chen, X., Smettem, K., Wang, T., 2021. Climate and land use influences on changing spatiotemporal patterns of mountain vegetation cover in southwest China. Ecol. Indic., 121, 107193. https://doi.org/10.1016/j.ecolind.2020.107193
]Search in Google Scholar
[
Jin, H., Chen, X., Wang, Y., Zhong, R., Zhao, T., Liu, Z., Tu, X., 2021. Spatio-temporal distribution of NDVI and its influencing factors in China. J. Hydrol., 603, 127129. https://doi.org/10.1016/j.jhydrol.2021.127129
]Search in Google Scholar
[
Julien, Y., Sobrino, J.A., Verhoef, W., 2006. Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999. Remote Sens. Environ., 103, 43–55. https://doi.org/10.1016/j.rse.2006.03.011
]Search in Google Scholar
[
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., 2015. The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteorol. Soc. Japan. Ser. II, 93, 5-48. https://doi.org/10.2151/jmsj.2015-001
]Search in Google Scholar
[
Li, D., Zhang, J., Wang, G., Wang, X., Wu, J., 2020. Impact of changes in water management on hydrology and environment: A case study in North China. J. Hydro-Environ. Res., 28, 75–84. https://doi.org/10.1016/j.jher.2019.04.001
]Search in Google Scholar
[
Li, M., Cao, S., Zhu, Z., Wang, Z., Myneni, R.B., Piao, S., 2023. Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022. Earth Syst. Sci. Data, 15, 4181-4203.
]Search in Google Scholar
[
Li, P., Wang, J., Liu, M., Xue, Z., Bagherzadeh, A., 2021. Spatiotemporal variation characteristics of NDVI and its response to climate on the Loess Plateau from 1985 to 2015. Catena, 203, 105331. https://doi.org/10.1016/j.catena.2021.105331
]Search in Google Scholar
[
Lin, M., Hou, L., Qi, Z., Wan, L., 2022. Impacts of climate change and human activities on vegetation NDVI in China’s Mu Us Sandy Land during 2000–2019. Ecol. Indic., 142, 109164. https://doi.org/10.1016/j.ecolind.2022.109164
]Search in Google Scholar
[
Liu, C., Yan, X., Jiang, F., 2021. Desert vegetation responses to the temporal distribution patterns of precipitation across the northern Xinjiang, China. Catena, 206, 105544. https://doi.org/10.1016/j.catena.2021.105544
]Search in Google Scholar
[
Liu, Q., Yang, Z., Han, F., Wang, Z., Wang, C., 2016. NDVIbased vegetation dynamics and their response to recent climate change: a case study in the Tianshan Mountains, China. Environ. Earth Sci., 75, 1–15. https://doi.org/10.1007/s12665-016-5987-5
]Search in Google Scholar
[
Liu, X., Zhu, X., Zhang, Q., Yang, T., Pan, Y., Sun, P., 2020. A remote sensing and artificial neural network-based integrated agricultural drought index: Index development and applications. Catena, 186, 104394. https://doi.org/10.1016/j.catena.2019.104394
]Search in Google Scholar
[
Liu, Y., Li, Y., Li, S., Motesharrei, S., 2015. Spatial and temporal patterns of global NDVI trends: correlations with climate and human factors. Remote Sens., 7, 13233–13250. https://doi.org/10.3390/rs71013233
]Search in Google Scholar
[
Luo, H., Dai, S., Li, M., Liu, E., Li, Y., Xie, Z., 2021. NDVIbased analysis of the influence of climate changes and human activities on vegetation variation on Hainan Island. J. Indian Soc. Remote Sens., 49, 1755–1767. https://doi.org/10.1007/s12524-021-01357-y
]Search in Google Scholar
[
Mao, D., Wang, Z., Luo, L., Ren, C., 2012. Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. Int. J. Appl. Earth Obs. Geoinf., 18, 528–536.
]Search in Google Scholar
[
Meddi, M.M., Assani, A.A., Meddi, H., 2010. Temporal variability of annual rainfall in the Macta and Tafna catchments, Northwestern Algeria. Water Resour. Manag., 24, 3817–3833. https://doi.org/10.3390/w13111477
]Search in Google Scholar
[
Milics, G., 2021. A coupled impact of different management and soil moisture on yield of winter wheat (Triticum aestivum L.) in dry conditions at locality Mezoföld, Hungary. J. Hydrol. Hydromech., 69, 76–86. https://doi.org/10.2478/johh-2020-0039
]Search in Google Scholar
[
Rhif, M., Abbes, A. Ben, Martínez, B., Farah, I.R., Gilabert, M.A., 2022. Optimal selection of wavelet transform parameters for spatio-temporal analysis based on nonstationary NDVI MODIS time series in Mediterranean region. ISPRS J. Photogramm. Remote Sens., 193, 216–233. https://doi.org/10.1016/j.isprsjprs.2022.09.007
]Search in Google Scholar
[
Shah, S.H., Rehman, A., Rashid, T., Karim, J., Shah, S., 2016. A comparative study of ordinary least squares regression and Theil-Sen regression through simulation in the presence of outliers. J Sci Technol, 137, 142.
]Search in Google Scholar
[
Shang, J., Zhang, Y., Peng, Y., Huang, Y., Zhu, L., Wu, Z., Wang, J., Cui, Y., 2022. Climate change drives NDVI variations at multiple spatiotemporal levels rather than human disturbance in Northwest China. Environ. Sci. Pollut. Res., 29, 13782-13796. https://doi.org/10.1007/s11356-021-16774-2
]Search in Google Scholar
[
Sohoulande, D.C., Singh, V.P., Frauenfeld, O.W., 2015. Vegetation response to precipitation across the aridity gradient of the southwestern United states. J. Arid Environ. 115, 35–43. https://doi.org/10.1016/j.jaridenv.2015.01.005
]Search in Google Scholar
[
Sun, J., Qin, X., 2016. Precipitation and temperature regulate the seasonal changes of NDVI across the Tibetan Plateau. Environ. Earth Sci., 75, 1–9. https://doi.org/10.1007/s12665-015-5177-x
]Search in Google Scholar
[
Tayeb, S.T., Kheloufi, B., 2019. Spatio-temporal dynamics of vegetation cover in North-West Algeria using remote sensing data. Polish Cartogr. Rev., 51, 117–127. https://doi.org/10.2478/pcr-2019-0009
]Search in Google Scholar
[
Wang, H., Li, Z., Niu, Y., Li, X., Cao, L., Feng, R., He, Q., Pan, Y., 2022. Evolution and climate drivers of NDVI of natural vegetation during the growing season in the arid region of Northwest China. Forests, 13, 1–21. https://doi.org/10.3390/f13071082
]Search in Google Scholar
[
Wang, J., Price, K.P., Rich, P.M., 2001. Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains. Int. J. Remote Sens., 22, 3827–3844. https://doi.org/10.1080/01431160010007033
]Search in Google Scholar
[
Wei, Y., Sun, S., Liang, D., Jia, Z., 2022. Spatial–temporal variations of NDVI and its response to climate in China from 2001 to 2020. Int. J. Digit. Earth, 15, 1463–1484. https://doi.org/10.1080/17538947.2022.2116118
]Search in Google Scholar
[
Wen, L., Yang, X., Saintilan, N., 2012. Local climate determines the NDVI-based primary productivity and flooding creates heterogeneity in semi-arid floodplain ecosystem. Ecol. Modell., 242, 116–126. https://doi.org/10.1016/j.ecolmodel.2012.05.018
]Search in Google Scholar
[
Wenxia, G., Huanfeng, S., Liangpei, Z., Wei, G., 2014. Normalization of NDVI from different sensor system using MODIS products as reference. IOP Conf. Ser. Earth Environ. Sci., 17. https://doi.org/10.1088/1755-1315/17/1/012225
]Search in Google Scholar
[
Xie, Y., Yue, T., Xin‐sheng, C., Feng, L., Zheng‐miao, D., 2015. The impact of Three Gorges Dam on the downstream ecohydrological environment and vegetation distribution of East Dongting Lake. Ecohydrology, 8, 738–746. https://doi.org/10.1002/eco.1543
]Search in Google Scholar
[
Xu, B., Qi, B., Ji, K., Liu, Z., Deng, L., Jiang, L., 2022. Emerging hot spot analysis and the spatial–temporal trends of NDVI in the Jing River Basin of China. Environ. Earth Sci., 81, 1–15. https://doi.org/10.1007/s12665-022-10175-5
]Search in Google Scholar
[
Yang, Y., Wang, S., Bai, X., Tan, Q., Li, Q., Wu, L., Tian, S., Hu, Z., Li, C., Deng, Y., 2019. Factors affecting long-term trends in global NDVI. Forests, 10, 1–17. https://doi.org/10.3390/f10050372
]Search in Google Scholar
[
Zaidi, S.M., Akbari, A., Abu Samah, A., Kong, N.S., Gisen, A., Isabella, J., 2017. Landsat-5 time series analysis for land use/land cover change detection using NDVI and semisupervised classification techniques. Polish J. Environ. Stud., 26, 2833–2840. https://doi.org/10.15244/pjoes/68878
]Search in Google Scholar
[
Zhang, Y., Gao, J., Liu, L., Wang, Z., Ding, M., Yang, X., 2013. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas. Glob. Planet. Change, 108, 139–148. https://doi.org/10.1016/j.gloplacha.2013.06.012
]Search in Google Scholar
[
Zhang, Y., Zhang, L., Wang, J., Dong, G., Wei, Y., 2023. Quantitative analysis of NDVI driving factors based on the geographical detector model in the Chengdu-Chongqing region, China. Ecol. Indic., 155, 110978. https://doi.org/10.1016/j.ecolind.2023.110978
]Search in Google Scholar
[
Zhao, M., Zhao, H.F., Li, R.Q., Zhang, L.Y., Zhao, F.X., Liu, L.X., Shen, R.C., Xu, M., 2017. Assessment on grassland ecosystem services in Qinghai Province during 1998–2012. Journal of Natural Resources, 32, 3, 418–433.
]Search in Google Scholar
[
Zhou, Z.-Y., Li, F.-R., Chen, S.-K., Zhang, H.-R., Li, G., 2011. Dynamics of vegetation and soil carbon and nitrogen accumulation over 26 years under controlled grazing in a desert shrubland. Plant Soil, 341, 257–268. https://doi.org/10.1007/s11104-010-0641-6
]Search in Google Scholar
[
Zoungrana, B.J.B., Conrad, C., Thiel, M., Amekudzi, L.K., Da, E.D., 2018. MODIS NDVI trends and fractional land cover change for improved assessments of vegetation degradation in Burkina Faso, West Africa. J. Arid Environ., 153, 66–75. https://doi.org/10.1016/j.jaridenv.2018.01.005
]Search in Google Scholar