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A Study Based on NOAA NDVI and Weather Station Data Land Use Policy 43 (2015) 42–47 Contents lists available at ScienceDirect Land Use Policy jo urnal homepage: www.elsevier.com/locate/landusepol Does the Green Great Wall effectively decrease dust storm intensity in China? A study based on NOAA NDVI and weather station data ∗ Minghong Tan , Xiubin Li Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing 100101, PR China a r a t i b s c t l e i n f o r a c t Article history: China launched its “Green Great Wall” (GGW) program in 1978. However, the effects of this program Received 7 July 2014 are subject to intense debate. This study compares changes in the vegetation index in regions where Received in revised form the GGW program has been implemented with those where it has not. Subsequently, a definition to 15 September 2014 measure dust storm intensity (DSI) was proposed that better calculates the intensity of dust events; it Accepted 22 October 2014 considers the frequency, visibility, and duration of dust events. The results show that in the GGW region, vegetation has greatly improved, while it varied dramatically outside the GGW region. In the mid-1980s, Keywords: DSI decreased significantly, different from the changes in dust storm frequency in the study region. By Green Great Wall NDVI discounting the effects of climatic change and human pressures, the results show that the GGW program greatly improved the vegetation index and effectively reduced DSI in northern China. Dust storm intensity © 2014 Elsevier Ltd. All rights reserved. Introduction with many observers concluding that they have been ineffective as desertification controls worldwide (Glenna et al., 1998). Dust has a considerable impact on aerosol radioactive forcing, China’s desert areas, which occupy approximately 13% of the biogeochemical cycling, and agricultural production. This impact country’s total surface area, are a major source of Asian dust (Song, often affects vast areas (Prospero, 1999; Prospero and Lamb, 2003; 2004). In a bid to improve broader environmental factors as well Schepanski et al., 2012). For instance, sand and dust from east and as to combat desertification, the Chinese Government has imple- central Asia are not only carried to Japan, North Korea, and South mented several ecological restoration projects including the Grain Korea across the sea, but can also influence the Pacific Ocean and for Green (GFG) program (Feng et al., 2003; Wang et al., 2007), even be transported to North America and Greenland (McKendry the Green Great Wall (GGW) program (Fang et al., 2001), and the et al., 2001; Huang et al., 2007; Uno et al., 2009; Wang et al., Natural Forest Conservation program (Zhang et al., 2000). Among 2013). Thus, many countries have instituted anti-desertification them, the GGW program is arguably one of the most aggres- programs at a national level, such as Iran’s National Action Program sive meteorological-modification programs of the 20th century to Combat Desertification (Amiraslani and Dragovich, 2011), the (Parungo et al., 1994). It was designed to curtail the expansion of the 2 Country Pilot Partnership for Integrated Sustainable Land Manage- Gobi Desert and will, ultimately, cover 4.1 million km . Also called ment in Namibia (Akhtar-schuster et al., 2011), the 22nd Country the Three-North Shelterbelt Forest Program, it will represent the Master Plan in Israel (Portnov and Safriel, 2004), and the Great dominant ecological engineering program in China and account for Plains Shelterbelt project in the United States. Of these, perhaps an important portion of the world’s total ecological construction the most famous is the Great Plains Shelterbelt, which stretches (Wang et al., 2010). The GGW program was launched in 1978 and over 29,000 km in a 160 km-wide zone from Canada to the Brazos is to be completed by 2050. River in the eastern Great Plains (Cook and Cable, 1995). However, In light of this information, has the implementation of the the outcomes following the implementation of these programs GGW program brought about the desired effect of dampening have spurred intense international debate (McTainsh et al., 2011), dust storms in China? Some authors consider the project to have been successful, pointing to the fact that the forest cover rate has increased from 5.1% in 1978 to 9.0% in 2001 (Zhu et al., 2004), and that vegetation conditions have improved (Duan et al., 2011). Both ∗ of these factors control desertification and may decrease dust storm Corresponding author. Tel.: +86 10 64889431; fax: +86 10 64854230. frequency (DSF), especially in the MuUs and Horqin sand lands E-mail address: [email protected] (M. Tan). http://dx.doi.org/10.1016/j.landusepol.2014.10.017 0264-8377/© 2014 Elsevier Ltd. All rights reserved. M. Tan, X. Li / Land Use Policy 43 (2015) 42–47 43 Table 1 of China. Conversely, other studies conclude that the program’s The visibility range denoted for every level (pre-1979 criterion). effectiveness at controlling dust storms should be questioned (Wang et al., 2010) because decreases in DSF are caused mainly by Grade Visibility (m) Mid-value of a visibility (m) climatic factors. Therefore, before a more rigorous evaluation of the effects of the implemented GGW program on dust storm intensity 0 <50 25 ≥ (DSI) can be carried out, we must resolve two fundamental issues. 1 50 to <200 125 2 ≥200 to <500 350 First, can we prove that the changes in vegetation resulted from 3 ≥500 to <1000 750 the implementation of the program rather than from natural con- 4 ≥1000 to <2000 1500 ditions such as precipitation? Second, a more accurate definition 5 ≥2000 to <4000 3000 ≥ with which to measure dust storm activities is required because 6 4000 to <10,000 7000 7 ≥10,000 to <20,000 15000 DSF cannot fully reflect DSI, which has a close relationship with the 8 ≥20,000 to <50,000 35000 frequency, visibility, and duration of dust events (McTainsh et al., 9 ≥50,000 50000 2005; Speer, 2013; O’Loingsigh et al., 2014). a Note: Visibility is used in the calculation of DSI. In this study, we compare changes in the vegetation indices for the regions where the GGW program has been implemented (“GGW region”) with those for where it has not (“Outside GGW National Oceanic and Atmospheric Administration (NOAA). The region”; Fig. 1). Moreover, the effects of precipitation on the vege- NDVI value consists of bi-weekly composite images with 8-km res- tation indices are also taken into account. Next, we calculate DSI olutions. This data has been widely applied in semi-arid and arid with reference to duration, visibility, and frequency. Finally, we areas (Anyamba and Tucker, 2005; Fensholt et al., 2012; Funk and evaluate the effects of the implementation of the GGW program Brown, 2006; Holm et al., 2003) because the data are in good agree- on DSI. ment with ground-based observations (Holm et al., 2003; Fensholt et al., 2009). Therefore, the AVHRR NDVI data set is well suited for vegetation studies, especially in regions with an annual rainfall less Study area than 1000 mm, such as the Sahel–Sudanian area (Fensholt et al., 2 2009). The study area covers 6.9 million km and ranges from approx- ◦ ◦ ◦ ◦ imately 23 52 to 53 31 N and from 73 29 to 134 58 E (Fig. 1). In Definition of DSI this area, the main vegetation types include farmland, grass, for- est, desert, and no vegetation. The main soil types include aeolian, We calculated the summed DSIs (SDSIj) of all dust events calcic, desert, meadow, cinnamon, and brown earth soils. recorded by a station in year j using Eq. (1) (Tan et al., 2014): The study area includes two parts: the GGW region and the Out- side GGW region (Fig. 1). The GGW region includes 551 counties in n j 1 13 provinces, municipalities and autonomous regions in northern = × SDSIj DURAi j (1) China; it stretches from far-western Xinjiang to Heilongjiang in the VISIB i=1 i northeast, representing approximately 42% of the total land area of j the country. In this region, mean annual precipitation varies from where DURAi is the duration of dust event i at the station in year approximately 450 mm in the southeastern part to 20 mm in the j calculated according to the start and end times of the dust event, j northwestern part (Zheng and Zhu, 2013). and VISIBi is the visibility (in meters) of dust event i at the station in year j. We then further calculated the total value (T SDSI) of SDSIj for Data and methods all years at a station using the following Eq. (2): Dust storm data (from 1971 to 1998) were sourced from the k China Meteorological Administration and included the start and T SDSI = SDSIj (2) end times of the dust storm, visibility details, and the geographic j=1 location of each observation station (longitude and latitude). In China, before 1979, storm events were rated on a scale of ‘0’ to ‘9’ by In 1999, another afforestation initiative—the GFG program—was meteorological observation stations, mainly according to visibility launched in China; it is difficult to distinguish the effects of the range; however, the visibility was not recorded. Since 1980, visibil- GGW program from those of the GFG initiative. Thus, our study ity data has been recorded at all stations. Following the pre-1979 encompasses the period from 1971 to 1998 to discuss the effects criterion, this study first classified the dust events after 1979 into of the GGW program on DSI. Furthermore, in north China, the ten grades.
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