The Normalized Difference Vegetation Index (NDVI) is an important vegetation greenness indicator. Compared to the AVHRR GIMMS NDVI data, the availability of two datasets with 1 km spatial resolution, i.e., Terra MODIS (MOD13A3) monthly composite and SPOT Vegetation (VGT) 10-day composite NDVI, extends the application dimensions at spatial and temporal scales. An overlapping period of 12 years between the datasets now makes it possible to investigate the consistency of the two datasets. Linear regression trend analysis was performed to compare the two datasets in this study. The results show greater consistency in regression slopes in the semi-arid regions of northern China. Alternatively, the results show only slight changes in the Terra MODIS NDVI regression slope in most areas of southern China whereas the SPOT VGT NDVI shows positive changes over a large area. The corresponding regression slope values between Terra MODIS and SPOT VGT NDVI datasets from the linear fit had a fair agreement in the spatial dimension. However, larger positive and negative differences were observed at the junction of the three regions (East China, Central China, and North China). These differences can be partially explained by the positive standard deviation differences distributed over a large area at the junction of these three regions. This study demonstrated that Terra MODIS and SPOT VGT NDVI have a relatively robust basis for characterizing vegetation changes in annual NDVI in most of the semi-arid and arid regions in northern China.
Eliminating poverty is the common mission of all mankind, and it is also an important task faced by many countries. Pro-poor tourism villages are an active attempt by China to use rural tourism to escape poverty. This paper aims to provide theoretical support for consolidating the results of poverty alleviation and achieving comprehensive poverty alleviation and to provide a scientific basis for policy formulation by using GIS spatial analysis to study the spatial distribution characteristics and influencing factors of 22,651 pro-poor tourism villages in China. The findings revealed that the spatial distribution of pro-poor tourism villages is roughly divided by the Hu line. Pro-poor tourism villages show an uneven agglomeration pattern and present a spatial pattern of dense southeast and sparse northwest with six high-density core areas, among which some cities in the southwest are H-H agglomeration areas. Specifically, topography, annual rainfall, endowment of tourism resources, location transportation, and policy orientation are important factors affecting the spatial distribution of pro-poor tourism villages.
For the last three decades, Northern China has been considered as one of the most sensitive areas regarding global environmental change. The integration of AVHRR GIMMS and MODIS NDVI data (1982-2011), of which for the overlapping period of 2000-2006 show good consistency, were used for characterizing land condition variability. The trends of standardized annually RNDVI, temperature, precipitation and PDSI were obtained using a linear regression model. The results showed that Northern China has a general increase in greenness for the period 1982-2011 (a = 0.05). Also, annually RNDVI is significantly correlated with temperature and precipitation data at the regional scale (p \ 0.05), implying that temperature and precipitation are the dominant limiting factors for vegetation growth. Since the greening is not uniform, factors other than temperature and precipitation may contribute to greening in some areas, while the grassland and cropland ecosystem are becoming increasingly vulnerable to drought. The results of trend analysis indicate that greenness seems to be evident in most of the study areas.
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