Abstract
The Mu Us Sandy Land (MUSL) has undergone climate changes and shifts in human activities driven by a series of ecological restoration projects in recent decades. We analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging and Spectroradiometer (MODIS) datasets during the past 33 years. The results show that (1) the vegetation in 53.46% of the MUSL exhibited an upward trend, and 34.45% of the area displayed a large increase, mainly in the eastern part of the MUSL region, including most of Shenmu County, Yuyang District, Hengshan County, and Jingbian County. (2) By the end of 2014, the rapid increase in vegetation encompassed 16.85% of the total area of the study region due to the construction of ecological engineering projects. (3) Based on the residual regression method, the area of positive effects accounted for 55.07% of the total area, and the vegetation in the study area was positively affected by human activities. Our study suggests that these multiple ecological restoration programs contributed to the accelerated greening trend in the MUSL region and highlights the importance of human intervention in regional vegetation growth under climate change conditions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Chen, T. F., & Wang, X. S. (2012). A correlation model on plant water consumption and vegetation index in Mu Us Desert, in China. Procedia Environmental Sciences, 13, 1517–1526. https://doi.org/10.1016/j.proenv.2012.01.144.
Chen, W., Sakai, T., & Moriya, K. (2013). Estimation of vegetation coverage in semi-arid sandy land based on multivariate statistical modeling using remote sensing data. Environmental Modeling & Assessment, 18, 547–558. https://doi.org/10.1007/s10666-013-9359-1.
Cheng, D. h., Li, Y., Chen, X., Wang, W. k., Hou, G. c., & Wang, C. l. (2013). Estimation of groundwater evaportranspiration using diurnal water table fluctuations in the Mu Us Desert, northern China. Journal of Hydrology, 490, 106–113. https://doi.org/10.1016/j.jhydrol.2013.03.027.
Du, L., & Li, G. (2008). Dynamic monitoring of eco-environment change over 1999-2006 in Yanchi County, Ningxia Hui Autonomous Region based on SPOT-VGT data. Journal of Beijing Forestry University, 30(5), 46–51.
Duan, H., Yan, C., Tsunekawa, A., Song, X., Li, S., & Xie, J. (2011). Assessing vegetation dynamics in the Three-North Shelter Forest region of China using AVHRR NDVI data. Environmental Earth Sciences, 64, 1011–1020. https://doi.org/10.1007/s12665-011-0919-x.
Evans, J., & Geerken, R. (2004). Discrimination between climate and human-induced dryland degradation. Journal of Arid Environments, 57, 535–554. https://doi.org/10.1016/S0140-1963(03)00121-6.
Fensholt, R., Rasmussen, K., Kaspersen, P., Huber, S., Horion, S., & Swinnen, E. (2013). Assessing land degradation/recovery in the African Sahel from long-term earth observation based primary productivity and precipitation relationships. Remote Sensing, 5(2), 664–686. https://doi.org/10.3390/rs5020664.
Ferrara, A., Salvati, L., Sateriano, A., & Nolè, A. (2012). Performance evaluation and cost assessment of a key indicator system to monitor desertification vulnerability. Ecological Indicators, 23, 123–129. https://doi.org/10.1016/j.ecolind.2012.03.015.
Guay, K. C., Beck, P., Berner, L. T., Goetz, S. J., Baccini, A., & Buermann, W. (2014). Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment. Global Change Biology, 20, 3147–3158. https://doi.org/10.1111/gcb.12647.
He, B., Chen, A., Wang, H., & Wang, Q. (2015). Dynamic response of satellite-derived vegetation growth to climate change in the three north shelter forest region in China. Remote Sensing, 7(8), 9998–10016. https://doi.org/10.3390/rs70809998.
Helldén, U., & Tottrup, C. (2008). Regional desertification: a global synthesis. Global and Planetary Change, 64(3–4), 169–176. https://doi.org/10.1016/j.gloplacha.2008.10.006.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965–1978. https://doi.org/10.1002/joc.1276.
Holben, B. N. (1986). Characteristics of maximum-value composite images from temporal AVHRR data. International Journal of Remote Sensing, 7(11), 1417–1434. https://doi.org/10.1080/01431168608948945.
Hutchinson, M. F. (1995). Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographical Information Systems, 9(4), 385–403.
Hutchinson, M. F., & Xu, T. (2013). ANUSPLIN. Canberra, Australia: Fenner School of Environment and Society, Australian National University. fennerschool.anu.edu.au.
Ibrahim, Y. Z., Balzter, H., Kaduk, J., & Tucker, C. J. (2015). Land degradation assessment using residual trend analysis of GIMMS NDVI3g, soil moisture and rainfall in Sub-Saharan West Africa from 1982 to 2012. Remote Sensing, 7(5), 5471–5494. https://doi.org/10.3390/rs70505471.
Jia, X., Fu, B., Feng, X., Hou, G., Liu, Y., & Wang, X. (2014). The tradeoff and synergy between ecosystem services in the Grain-for-Green areas in Northern Shaanxi, China. Ecological Indicators, 43, 103–111. https://doi.org/10.1016/j.ecolind.2014.02.028.
Jiang, L., Jiapaer, G., Bao, A., Guo, H., & Ndayisaba, F. (2017). Vegetation dynamics and responses to climate change and human activities in Central Asia. Science of the Total Environment, 599–600, 967–980. https://doi.org/10.1016/j.scitotenv.2017.05.012.
Jiang, X., Liu, X., Huang, F., Jiang, H., Cao, W., & Zhu, Y. (2010). Comparison of spatial interpolation methods for daily meteorological elements. Chinese Journal of Applied Ecology, 21(3), 624–630 http://www.ncbi.nlm.nih.gov/pubmed/20560317.
Karnieli, A., Qin, Z., Wu, B., Panov, N., & Yan, F. (2014). Spatio-temporal dynamics of land-use and land-cover in the Mu Us Sandy Land, China, using the change vector analysis technique. Remote Sensing, 6, 9316–9339. https://doi.org/10.3390/rs6109316.
Li, M. m., Liu, A. t., Zou, C. j., Xu, W. d., Shimizu, H., & Wang, K. y. (2012). An overview of the “Three-North” Shelterbelt project in China. Forestry Studies in China, 14(1), 70–79. https://doi.org/10.1007/s11632-012-0108-3.
Li, N., Yan, C. Z., & Xie, J. L. (2015). Remote sensing monitoring recent rapid increase of coal mining activity of an important energy base in northern China, a case study of Mu Us Sandy Land. Resources, Conservation and Recycling, 94, 129–135. https://doi.org/10.1016/j.resconrec.2014.11.010.
Li, S., Chen, S., & Zhang, J. (2009). Environmental changes analysis of Hongjiannao Lake during recent fifty years. Resources and Environment, 10(6), 178–183.
Li, Y., Cao, Z., Long, H., Liu, Y., & Li, W. (2017). Dynamic analysis of ecological environment combined with land cover and NDVI changes and implications for sustainable urban–rural development: The case of Mu Us Sandy Land, China. Journal of Cleaner Production, 142, 697–715.
Liu, D., Chen, Y., Cai, W., Dong, W., Xiao, J., Chen, J., Zhang, H., Xia, J., & Yuan, W. (2014). The contribution of China’s Grain to Green Program to carbon sequestration. Landscape Ecology, 29, 1675–1688. https://doi.org/10.1007/s10980-014-0081-4.
Liu, S., Kang, W., & Wang, T. (2016). Drought variability in Inner Mongolia of northern China during 1960–2013 based on standardized precipitation evapotranspiration index. Environmental Earth Sciences, 75(2), 1–14. https://doi.org/10.1007/s12665-015-4996-0.
Liu, Y., & Yue, H. (2016). Analysis of Hongjiannao Lake area based on SMMI. Science Technology and Engineering, 16(16), 122–127.
Luk, S. (1983). Recent trends of desertification in the Maowusu desert. Environmental Conservation, 10(3), 213–224.
Luo, L., & Wang, H. (2015). Research on the resource utilization of soft sandstone in the Mu Us Sand Land Region during the land consolidation project. In Proceedings of the Ninth International Conference (pp. 1009–1022). doi:https://doi.org/10.1007/978-3-662-47241-5.
Mandal, S., Srivastav, R. K., & Simonovic, S. P. (2016). Use of beta regression for statistical downscaling of precipitation in the Campbell River basin, British Columbia, Canada. Journal of Hydrology, 538, 49–62. https://doi.org/10.1016/j.jhydrol.2016.04.009.
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. International Journal of Applied Earth Observations and Geoinformation, 18, 528–536. https://doi.org/10.1016/j.jag.2011.10.007.
Powell, S. J., Jakeman, A., & Croke, B. (2014). Can NDVI response indicate the effective flood extent in macrophyte dominated floodplain wetlands? Ecological Indicators, 45, 486–493. https://doi.org/10.1016/j.ecolind.2014.05.009.
Prince, S. D., Becker-Reshef, I., & Rishmawi, K. (2009). Detection and mapping of long-term land degradation using local net production scaling: application to Zimbabwe. Remote Sensing of Environment, 113(5), 1046–1057. https://doi.org/10.1016/j.rse.2009.01.016.
Runnstrom, M. C. (2003). Rangeland development of the Mu Us Sandy Land in semiarid China: an analysis using Landsat and NOAA remote sensing data. Land Degradation & Development, 14, 189–202.
Stow, D., Daeschner, S., Hope, A., Douglas, D., Petersen, A., Myneni, R., & Oechel, W. (2003). Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s. International Journal of Remote Sensing, 24(5), 1111–1117. https://doi.org/10.1080/0143116021000020144.
Wang, F., Hessel, R., Mu, X., Maroulis, J., Zhao, G., Geissen, V., & Ritsema, C. (2015a). Distinguishing the impacts of human activities and climate variability on runoff and sediment load change based on paired periods with similar weather conditions: a case in the Yan River, China. Journal of Hydrology, 527, 884–893. https://doi.org/10.1016/j.jhydrol.2015.05.037.
Wang, J., Wang, K., Zhang, M., & Zhang, C. (2015b). Impacts of climate change and human activities on vegetation cover in hilly southern China. Ecological Engineering, 81, 451–461. https://doi.org/10.1016/j.ecoleng.2015.04.022.
Wang, L., Mu, Y., Zhang, Q., & Zhang, X. (2013). Groundwater use by plants in a semi-arid coal-mining area at the Mu Us Desert frontier. Environmental Earth Sciences, 69, 1015–1024. https://doi.org/10.1007/s12665-012-2023-2.
Wang, N., Xie, J., Han, J., & Luo, L. (2014a). A comprehensive framework on land-water resources development in Mu Us Sandy Land. Land Use Policy, 40, 69–73. https://doi.org/10.1016/j.landusepol.2013.09.022.
Wang, Q., Zhang, B., Zhang, Z., Zhang, X., & Dai, S. (2014b). The Three-North Shelterbelt program and dynamic changes in vegetation cover. Journal of Resources and Ecology, 5(1), 53–59. https://doi.org/10.5814/j.issn.1674-764x.2014.01.006.
Wang, T., Yan, C., Song, X., & Xie, J. (2012). Monitoring recent trends in the area of aeolian desertified land using Landsat images in China’s Xinjiang region. ISPRS Journal of Photogrammetry and Remote Sensing, 68, 184–190. https://doi.org/10.1016/j.isprsjprs.2012.01.001.
Wessels, K. J., Prince, S. D., Malherbe, J., Small, J., Frost, P. E., & VanZyl, D. (2007). Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa. Journal of Arid Environments, 68(2), 271–297. https://doi.org/10.1016/j.jaridenv.2006.05.015.
Wessels, K. J., Prince, S. D., Zambatis, N., MacFadyen, S., Frost, P. E., & Van Zyl, D. (2006). Relationship between herbaceous biomass and 1km 2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa. International Journal of Remote Sensing, 27(5), 951–973. https://doi.org/10.1080/01431160500169098.
Wu, S., Li, J., Zhou, W., Joseph, B., Yu, D., Zhou, L., et al. (2017). A statistical analysis of spatiotemporal variations and determinant factors of forest carbon storage under China’s Natural Forest Protection Program. Journal of Forestry Research., 29, 415–424. https://doi.org/10.1007/s11676-017-0462-z.
Wu, Z., Wu, J., Liu, J., He, B., Lei, T., & Wang, Q. (2013). Increasing terrestrial vegetation activity of ecological restoration program in the Beijing-Tianjin Sand Source Region of China. Ecological Engineering, 52, 37–50. https://doi.org/10.1016/j.ecoleng.2012.12.040.
Xin, Z., Xu, J., & Zheng, W. (2008). Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau(1981-2006): impacts of climate changes and human activities. Science in China Series D:Earth Sciences, 51(1), 67–78. https://doi.org/10.1007/s11430-007-0137-2.
Xu, Y., Yang, J., & Chen, Y. (2016). NDVI-based vegetation responses to climate change in an arid area of China. Theoretical and Applied Climatology, 126, 213–222. https://doi.org/10.1007/s00704-015-1572-1.
Yan, F., Wu, B., & Wang, Y. (2013). Estimating aboveground biomass in Mu Us Sandy Land using Landsat spectral derived vegetation indices over the past 30 years. Journal of Arid Land, 5(4), 521–530. https://doi.org/10.1007/s40333-013-0180-0.
Yan, G., Lou, H., Liang, K., & Zhang, Z. (2016). Dynamics and driving forces of Bojiang Lake area in Erdos Larus Relictus National Nature Reserve, China. Quaternary International, 475, 1–12. https://doi.org/10.1016/j.quaint.2016.12.034.
Yan, Q. L., Zhu, J. J., Hu, Z. B., & Sun, O. J. (1991). Environmental impacts of the shelter forests in Horqin Sandy land, northeast china. Journal of Environmental Quality, 40(3), 815–824. https://doi.org/10.2134/jeq2010.0137.
Yin, R., & Yin, G. (2010). China’s primary programs of terrestrial ecosystem restoration: initiation, implementation, and challenges. Environmental Management, 45, 429–441. https://doi.org/10.1007/s00267-009-9373-x.
Zhang, G., Zhang, Y., Dong, J., & Xiao, X. (2013). Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011. Proceedings of the National Academy of Sciences, 110(11), 4309–4314. https://doi.org/10.1073/pnas.1210423110.
Zheng, X., & Zhu, J. (2014). Temperature-based approaches for estimating monthly reference evapotranspiration based on MODIS data over North China. Theoretical and Applied Climatology, 121(3), 695–711. https://doi.org/10.1007/s00704-014-1269-x.
Zheng, X., & Zhu, J. (2017). A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data. Theoretical and Applied Climatology, 127(1–2), 465–480. https://doi.org/10.1007/s00704-015-1646-0.
Zhou, H., Van Rompaey, A., & Wang, J. (2009). Detecting the impact of the “Grain for Green” program on the mean annual vegetation cover in the Shaanxi province, China using SPOT-VGT NDVI data. Land Use Policy, 26(4), 954–960. https://doi.org/10.1016/j.landusepol.2008.11.006.
Zhou, S., Huang, Y., Yu, B., & Wang, G. (2015). Effects of human activities on the eco-environment in the middle Heihe River Basin based on an extended environmental Kuznets curve model. Ecological Engineering, 76, 14–26. https://doi.org/10.1016/j.ecoleng.2014.04.020.
Zhu, H. (2013). Underlying motivation for land use change: a case study on the variation of agricultural factor productivity in Xinjiang, China. Journal of Geographical Sciences, 23(6), 1041–1051. https://doi.org/10.1007/s11442-013-1061-3.
Funding
This research was funded by the National Key Research and Development Program of China (grant number 2016YFC0500806), the China National Key Basic Research Program (grant number 2013CB429901), and the National Natural Science Foundation of China (grant number 41171400).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xiu, L., Yan, C., Li, X. et al. Monitoring the response of vegetation dynamics to ecological engineering in the Mu Us Sandy Land of China from 1982 to 2014. Environ Monit Assess 190, 543 (2018). https://doi.org/10.1007/s10661-018-6931-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10661-018-6931-9