Changes in NDVI and human population in protected areas on the Tibetan Plateau

Abstract

Understanding the Tibetan Plateau's role in environmental change has gained increasing scientific attention in light of warming and changes in land management. We examine changes in greenness over the Tibetan Plateau using the Normalized Difference Vegetation Index (NDVI) from the Global Inventory Monitoring and Modeling Study (GIMMS 3 g) to identify significant changes over the entire plateau, six ecoregions, and protected areas based on a multiyear time series of July imagery from 1982 to 2015. We also test whether there have been changes in human populations in protected areas. There has been relatively little change in mean NDVI over the Tibetan Plateau or ecoregions, however, there were significant changes at the pixel level. There are sixty-nine protected areas on the Tibetan Plateau; sixtytwo protected areas had no significant change in mean NDVI and seven protected areas experienced a significant increase in NDVI. There has been an increase in population within protected areas from 2000 to 2015; however, mean populations significantly increased in two protected areas and significantly decreased in four protected areas. Results suggest a slow greening of the Tibetan Plateau, ecoregions, and protected areas, with a more rapid greening in northern Tibet at the pixel level. Most protected areas are experiencing minor changes in NDVI independent of human population. ARTICLE HISTORY

NDVI-Based Greening of Alpine Steppe and Its Relationships with Climatic Change and Grazing Intensity in the Southwestern Tibetan Plateau

“…The NDVI decreased significantly from 2000 to 2010 and increased substantially from 2011 to 2020. These results are consistent with Gillespie et al (2019) [36] and Li et al (2020) [9], who found that the southwest of the Tibetan Plateau became browning from 2000 to 2010. This result may be related to the implementation of ecological projects such as the Grassland Ecological Protection Program (2011-2020).…”

“…The TP is an ideal place to study the change of vegetation cover and its response to climate change because it is relatively concentrated and less disturbed by human activities [26,27]. The applications of NDVI in the TP are mainly focusing on the vegetation change [28,29], the relationship between vegetation and climatic change [30], elevation gradient [31,32], vegetation types [33,34], and human activities [35,36]. Some research showed that the vegetation of the TP changed with a trend of "overall increase and local decrease".…”

Grassland Conservation Effectiveness of National Nature Reserves in Northern China

“…For example, Mu et al proposed the Area-Pattern Quadrant Analysis (APQA) system specialized for wetland NNR effectiveness assessment [75], and Huang et al devised three indices, i.e., the Landscape Transfer Index (LTI), the Protected Landscape Integrity Index (PLII), and the Interfered Landscape Sprawl Index (ILSI), based on the landscape transfer matrix [72]. According to Gillespie et al, the NDVI mean aggregated at the reserve-based level and the NDVI changes at the pixel level have both been conducted to assess the effectiveness of protected areas [34]. For this study, we also used the NDVI mean at the reserve-based level and the NDVI changes at the pixel level, together with a t test, to construct the effectiveness score metric, which presents a possible pattern for evaluating the effectiveness of NNRs on grassland protection.…”

“…As the most widely used single indicator for characterizing vegetation conditions, the NDVI can be used to represent vegetated regions and differentiate non-vegetated areas, as computed by the normalized interpretation of the near-infrared to red ratio [31]. With regard to the effectiveness of vegetation restoration as well as the ecological monitoring within PAs, studies have increasingly used the NDVI as a proxy to analyze the ecosystem dynamics within PAs [32][33][34][35].…”

Remote Sensing Applications in Monitoring of Protected Areas

“…Time-series remote sensing data have allowed for the reconstruction of the histories of disturbances induced by anthropogenic and natural impacts. Typical examples have included: the inventory and monitoring studies in NPs and PAs in a landscape context, such as in the Acadia NP and other northeastern U.S. NPs [12,35], the Yellowstone NP [36] and the Olympic NP of the Pacific Northwest of the U.S. [37]; for monitoring the interannual variability in snowpack and lake ice in southwest Alaska [38]; in the assessment of national forests of eastern U.S. [39]; in monitoring the land cover change and ecological integrity of Canada's national parks [40], such as the wildlife habitat changes in Kejimkujik NP and the national historic site in southern Nova Scotia of the Canadian Atlantic Coastal Uplands Natural Region [41]; in operational active fire mapping and burnt area identification to Mexican nature PAs [42]; in Tibetan Plateau [43] and Changbai Mountain National Nature Reserve [44,45] of China.…”