Monitoring vegetation cover in Chongqing between 2001 and 2010 using remote sensing data

  • Qiang Xiao
  • Jianping TaoEmail author
  • Yang Xiao
  • Feng Qian


In this study, we applied asymmetric Gaussian function fitting to reconstruct a high-quality MODIS normalized difference vegetation index (NDVI) time series dataset. Following this, we retrieved vegetation cover data from the Chongqing area between 2001 and 2010 using this dataset, applying a dimidiate pixel method. We then used several analytical indices to analyze spatial and temporal changes and trends related to these changes. We determined that a reconstruction of the MODIS NDVI dataset using asymmetric Gaussian fitting in conjunction with a data quality weight coefficient improved data quality and created a foundation for accurate estimations of vegetation cover. We also determined that vegetation cover in the Chongqing area decreased gradually from east to west. During the 10-year study period, vegetation cover in the Chongqing area generally increased, changing from low to high coverage. This increase in vegetation cover was mainly the result of ecological protection policies and improving climate conditions. We also found that changes in vegetation cover were mainly the result of urban construction and afforestation initiatives, but vegetation cover improved overall.


TIMESAT Dimidiate pixel model Vegetation cover Dynamic change analysis 



This study was supported by the National Foundation of Natural Sciences of China (No. 31570612).We would like to thank Brian DOONAN for his help in writing this paper as well as to the journal editors and anonymous reviewers for their comments on an earlier version of this manuscript.


  1. Anderson, A. B., Wang, G., Fang, S., Gertner, G. Z., Güneralp, B., & Jones, D. (2005). Assessing and predicting changes in vegetation cover associated with military land use activities using field monitoring data at Fort Hood, Texas. Journal of Terramechanics, 42, 207–229.CrossRefGoogle Scholar
  2. Anupama, K., Prasad, S., & Reddy, C. S. (2014). Vegetation, land cover and land use changes of the last 200 years in the Eastern Ghats (southern India) inferred from pollen analysis of sediments from a rain-fed tank and remote sensing. Quaternary International, 325, 93–104.CrossRefGoogle Scholar
  3. Barati, S., Rayegani, B., Saati, M., Sharifi, A., & Nasri, M. (2011). Comparison the accuracies of different spectral indices for estimation of vegetation cover fraction in sparse vegetated areas. Egyptian Journal of Remote Sensing and Space Science, 14, 49–56.CrossRefGoogle Scholar
  4. Bargiel, D., Herrmann, S., & Jadczyszyn, J. (2013). Using high-resolution radar images to determine vegetation cover for soil erosion assessments. Journal of Environmental Management, 124, 82–90.CrossRefGoogle Scholar
  5. Bauer, T., & Strauss, P. (2014). A rule-based image analysis approach for calculating residues and vegetation cover under field conditions. Catena, 113, 363–369.CrossRefGoogle Scholar
  6. Cao, S. (2010). Socioeconomic road in ecological restoration in China. Environmental Science & Technology, 44, 5328–5329.CrossRefGoogle Scholar
  7. Cao, S. (2011). Impact of China’s large-scale ecological restoration program on the environment and society in arid and semiarid areas of China: achievements, problems, synthesis, and applications. Critical Reviews in Environmental Science and Technology, 41, 317–335.CrossRefGoogle Scholar
  8. Cao, S., Chen, L., Shankman, D., Wang, C., Wang, X., & Zhang, H. (2011). Excessive reliance on afforestation in China’s arid and semi-arid regions: lessons in ecological restoration. Earth-Science Reviews, 104, 240–245.CrossRefGoogle Scholar
  9. Cao, S., Zhang, J., Chen, L., & Zhao, T. (2016). Ecosystem water imbalances created during ecological restoration by afforestation in China, and lessons for other developing countries. Journal of Environmental Management, 183, 843–849.CrossRefGoogle Scholar
  10. Chauhan, S., & Ganguly, A. (2011). Standardizing rehabilitation protocol using vegetation cover for bauxite waste (red mud) in eastern India. Ecological Engineering, 37, 504–510.CrossRefGoogle Scholar
  11. Comiti, F., Da Canal, M., Surian, N., Mao, L., Picco, L., & Lenzi, M. A. (2011). Channel adjustments and vegetation cover dynamics in a large gravel bed river over the last 200 years. Geomorphology, 125, 147–159.CrossRefGoogle Scholar
  12. Dubovyk, O., Menz, G., Conrad, C., Thonfeld, F., & Khamzina, A. (2013). Object-based identification of vegetation cover decline in irrigated agro-ecosystems in Uzbekistan. Quaternary International, 311, 163–174.CrossRefGoogle Scholar
  13. Eckert, S., & Engesser, M. (2013). Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data. Applied Geography, 40, 179–190.CrossRefGoogle Scholar
  14. Gao, Y., Zhong, B., Yue, H., Wu, B., & Cao, S. (2011). A degradation threshold for irreversible loss of soil productivity: a long-term case study in China. Journal of Applied Ecology, 48(5), 1145–1154.CrossRefGoogle Scholar
  15. Goirán, S.B., Aranibar, J.N., & Gomez, M.L. (2012). Heterogeneous spatial distribution of traditional livestock settlements and their effects on vegetation cover in arid groundwater coupled ecosystems in the Monte Desert (Argentina). Journal of Arid Environments, 87, 188–197.Google Scholar
  16. Ivits, E., Cherlet, M., Mehl, W., & Sommer, S. (2009). Estimating the ecological status and change of riparian zones in Andalusia assessed by multi-temporal AVHHR datasets. Ecological Indicators, 9(3), 422–431.CrossRefGoogle Scholar
  17. Jiapaer, G., Chen, X., & Bao, A. (2011). A comparison of methods for estimating fractional vegetation cover in arid regions. Agricultural and Forest Meteorology, 151(12), 1698–1710.CrossRefGoogle Scholar
  18. Jing, X., Yao, W. Q., Wang, J. H., & Song, X. Y. (2011). A study on the relationship between dynamic change of vegetation coverage and precipitation in Beijing’s mountainous areas during the last 20 years. Mathematical and Computer Modelling, 54(34), 1079–1085.CrossRefGoogle Scholar
  19. Jönsson and Eklundh. (2002). Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Transactions on Geoscience and Remote Sensing, 40(8), 1824–1832.CrossRefGoogle Scholar
  20. Kong, D., Miao, C., Borthwick, A. G. L., Duan, Q., Liu, H., Sun, Q., et al. (2015). Evolution of the Yellow River Delta and its relationship with runoff and sediment load from 1983 to 2011. Journal of Hydrology, 520, 157–167.CrossRefGoogle Scholar
  21. Kyle, G., & Duncan, D.H. (2012). Arresting the rate of land clearing: change in woody native vegetation cover in a changing agricultural landscape. Landscape and Urban Planning, 106, 165–173.Google Scholar
  22. Lan, J. C., Sun, Y. C., Xiao, S. Z., & Yuan, D. X. (2016). Polycyclic aromatic hydrocarbon contamination in a highly vulnerable underground river system in Chongqing, Southwest China. Journal of Geochemical Exploration, 168, 65–71.Google Scholar
  23. Lanfredi, M., Simoniello, T., & Macchiato, M. (2004). Temporal persistence in vegetation cover changes observed from satellite: development of an estimation procedure in the test site of the Mediterranean Italy. Remote Sensing of Environment, 93, 565–576.CrossRefGoogle Scholar
  24. Li, X., Zhou, W., & Ouyang, Z. (2013). Forty years of urban expansion in Beijing: what is the relative importance of physical, socioeconomic, and neighborhood factors? Applied Geography, 38, 1–10.CrossRefGoogle Scholar
  25. Miao, C., Kong, D., Wu, J., & Duan, Q. (2016a). Functional degradation of the water-sediment regulation scheme in the lower Yellow River: spatial and temporal analyses. Science of the Total Environment, 551, 16–22.CrossRefGoogle Scholar
  26. Miao, C., Sun, Q., Borthwick, A. G. L., Duan, Q. (2016b). Linkage between hourly precipitation events and atmospheric temperature changes over China during the warm season. Scientific Reports 6 (art. 22543).Google Scholar
  27. Okin, G. S. (2007). Relative spectral mixture analysis—a multitemporal index of total vegetation cover. Remote Sensing of Environment, 106, 467–479.CrossRefGoogle Scholar
  28. Okin, G. S., Clarke, K. D., & Lewis, M. M. (2013). Comparison of methods for estimation of absolute vegetation and soil fractional cover using MODIS normalized BRDF-adjusted reflectance data. Remote Sensing of Environment, 130, 266–279.CrossRefGoogle Scholar
  29. Omuto, C. T., Vargas, R. R., Alim, M. S., & Paron, P. (2010). Mixed-effects modelling of time series NDVI-rainfall relationship for detecting human-induced loss of vegetation cover in drylands. Journal of Arid Environments, 74, 1552–1563.CrossRefGoogle Scholar
  30. Ouyang, W., Hao, F., Skidmore, A. K., & Toxopeus, A. G. (2010). Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River. Science of the Total Environment, 409(2), 396–403.CrossRefGoogle Scholar
  31. Pulido-Fernández, M., Schnabel, S., Lavado-Contador, J. F., Miralles Mellado, I., & Ortega Pérez, R. (2013). Soil organic matter of Iberian open woodland rangelands as influenced by vegetation cover and land management. Catena, 109, 13–24.CrossRefGoogle Scholar
  32. Qu, J., Cao, S., Li, G., Niu, Q., & Feng, Q. (2014). Conservation of natural and cultural heritage in Dunhuang, China. Gondwana Research, 26, 1216–1221.CrossRefGoogle Scholar
  33. Setiawan, Y., Yoshino, K., & Prasetyo, L. B. (2014). Characterizing the dynamics change of vegetation cover on tropical forestlands using multi-temporal MODIS EVI. International Journal of Applied Earth Observation and Geoinformation, 26, 132–144.CrossRefGoogle Scholar
  34. Soepboer, W., Sugita, S., & Lotter, A. F. (2010). Regional vegetation-cover changes on the Swiss Plateau during the past two millennia: a pollen-based reconstruction using the REVEALS model. Quaternary Science Reviews, 29, 472–483.CrossRefGoogle Scholar
  35. Turrion, M. B., Lopez, O., Lafuente, F., Mulas, R., Ruiperez, C., & Puyo, A. (2007). Soil phosphorus forms as quality indicators of soils under different vegetation covers. Science of the Total Environment, 378, 195–198.CrossRefGoogle Scholar
  36. Wilson, J. W., Sexton, J. O., Todd Jobe, R., & Haddad, N. M. (2013). The relative contribution of terrain, land cover, and vegetation structure indices to species distribution models. Biological Conservation, 164, 170–176.CrossRefGoogle Scholar
  37. Wing, B. M., Ritchie, M. W., Boston, K., Cohen, W. B., Gitelman, A., & Olsen, M. J. (2012). Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest. Remote Sensing of Environment, 124, 730–741.CrossRefGoogle Scholar
  38. Wu, C. J., Tuo, J. C., Zhang, M. F., Sun, L. N., Qian, Y., & Liu, Y. (2016). Sedimentary and residual gas geochemical characteristics of the Lower Cambrian organic-rich shales in Southeastern Chongqing, China. Marine and Petroleum Geology, 75, 140–150.CrossRefGoogle Scholar
  39. Xiao, Y., Xiao, Q., Ouyang, Z., Qin, M. (2015). Assessing changes in water flow regulation in Chongqing region, China. Environmental Monitoring and Assessment, 187 (art. 362).Google Scholar
  40. Zhang, J., Zhengjun, L., & Xiaoxia, S. (2009). Changing landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: land use/land cover, vegetation cover changes estimated using multi-source satellite data. International Journal of Applied Earth Observation and Geoinformation, 11(6), 403–412.CrossRefGoogle Scholar
  41. Zhang, J., Zhao, T., Jiang, C., & Cao, S. (2016). Opportunity cost of water allocation to afforestation rather than conservation of natural vegetation in China. Land Use Policy, 50, 67–73.CrossRefGoogle Scholar
  42. Zhou, H., Rompaey, A. V., & Wang, J. A. (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, 954–960.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Qiang Xiao
    • 1
    • 2
  • Jianping Tao
    • 1
    Email author
  • Yang Xiao
    • 3
  • Feng Qian
    • 1
  1. 1.Key Laboratory of Eco-environments in Three Gorges Reservoir Region (Ministry of Education), Chongqing Key Laboratory of Plant Ecology, and Resources Research in Three Gorges Reservoir Region, School of Life SciencesSouthwest UniversityChongqingChina
  2. 2.Chongqing College of Arts and SciencesChongqingChina
  3. 3.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina

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