A new regionalization scheme for effective ecological restoration on the loess plateau in China
Citation
Chen, P., Shang, J., Qian, B., Jing, Q., Liu, J. (2017). A new regionalization scheme for effective ecological restoration on the loess plateau in China. Remote Sensing, [online] 9(12), http://dx.doi.org/10.3390/rs9121323
Plain language summary
The Loess Plateau, located in the arid and semi-arid region of northwestern China, suffered severe ecosystem degradation due to impacts from long-term intensive human activities. The Chinese government has launched the Grain for Green Programs for ecological restoration over the past few decades (the 1980s and 2001–2013). To prevent potentially unsuitable activities during vegetation restoration, it is important to examine the impact of historical restoration activities on the target ecological system to inform future restoration policies. In this study, a regionalization method and a corresponding scheme were proposed to evaluate restoration effects in the region. First, land cover maps were used to identify distribution of native and restored vegetation, and the net primary productivity (NPP) for 2001–2013 were calculated from long term satellite data using the Carnegie-Ames-Stanford Approach model. NPP in the restored areas was considered as an indicator for restoration suitability, through comparison with NPP in the native vegetation areas. Using weather, soil, and topographic data, a scheme was designed to regionalize restoration suitability, and the results were compared with an existing Chinese eco-geographical regionalization scheme. The results showed that our regionalization scheme performed well, with an average potential classification accuracy of 81%. Compared with the eco-geographical regionalization scheme, the new scheme showed an improved consistency of vegetation dynamics, indicating a better potential to guiding vegetation restoration in the region.
Abstract
To prevent potentially unsuitable activities during vegetation restoration, it is important to examine the impact of historical restoration activities on the target ecological system to inform future restoration policies. Taking the Loess Plateau of China as an example, a regionalization method and corresponding scheme were proposed to select suitable vegetation types (forested lands, woody grasslands/bushlands, grasslands, or xerophytic shrublands and semi-shrublands) for a given location using remote sensing technology in order to analyze the vegetation growth status before and after the largest ecological conservation project in the country: The Grain for Green Program (GTGP). To design the scheme, remote sensing data covering the periods before and after the implementation of the GTGP (the 1980s and 2001-2013) were collected, along with soil, meteorological, and topographic data. The net primary production (NPP) values for 2001-2013 were calculated using the Carnegie-Ames-Stanford Approach (CASA) model. Locations representing the native vegetation and the restored vegetation were first recognized using maps of vegetation cover. Then, for the restored vegetation area, the places suitable for planting the covered vegetation type were selected by comparing the NPP value of the corresponding vegetation type in the native vegetation area to the NPP value in the site under consideration. Third, half of these sites were uniformly selected based on their NPP value, and these areas and the native vegetation area were used as training regions. Based on weather, soil, and topographic data, a new regionalization scheme was designed using standardized Euclidean distances. Finally, data from the remainder of the Loess Plateau were used to validate the new regionalization scheme, which was also compared to an existing Chinese eco-geographical regionalization scheme. The results showed that the new regionalization scheme performed well, with an average potential classification accuracy of 81.81%. Compared with the eco-geographical regionalization scheme, the new scheme exhibited improved the consistency of vegetation dynamics, reflecting the potential to better guide vegetation restoration activities on the Loess Plateau.