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To reveal the key factors influencing vegetation productivity in sandy lands, we conducted a comprehensive analysis of vegetation productivity on regional scale, pixel scale, and plot scale of the sandy lands in northwes-tern Liaoning Province, based on soil physicochemical data, topographical data, climate data, and the intrinsic characteristics of vegetation. On the regional scale, we established a random forest model to explore the impact of topographical factors, climate factors, and vegetation characteristics on vegetation productivity. On the pixel scale, we performed a correlation analysis between vegetation cover and climate factors. On the plot scale, we combined the physicochemical properties of 234 soil samples with topographical factors and vegetation characteristics, and utilized the random forest model to calculate the importance values of each factor. The results showed that soil nutrients could explain 24.8% of the spatial variation in net primary productivity when other factors were excluded. When introducing topographical factors into the model, the model could explain 40% variation of net primary productivity. When further incorporating fractional vegetation coverage and leaf area index into the model, the model could explain 72.8% variation of net primary productivity. Our findings suggested that fractional vegetation coverage and leaf area index were the most influential factors affecting vegetation productivity in this area. Topographical factors ranked second, followed by climate factors, which had a relatively small impact.

Precise estimation of gross primary productivity (GPP), the key parameter in carbon cycle analysis, plays an important role in the research of carbon cycle and global climate change. Vegetation GPP was simulated by VPM model based on MOD09A1 and climate data in Changbai Mountain Natural Reserve from 2000 to 2015. The results showed that mean GPP was 1203 g C·m -2 ·a -1 . The annual vegetation GPP significantly increased from 2000 to 2015. There was no significant difference in the temporal trends of forest GPP at different vertical vegetation zones. However, GPP of the alpine tundra decreased remarkably. The correlation between GPP and precipitation was not significant. The positive correlation of GPP and temperature was mainly distributed in broad-leaved Korean pine forests and alpine tundra. Spring temperature had the strongest influence on GPP, with 80% pixels had a positive correlation with temperature. The GPP had a stronger correlation with temperature compared with precipitation.

Based on the 1:10000 aerial photo in 1997 and the three QuickBird images in 2002, 2005, and 2008, and by using Barista software and GIS and RS techniques, the three-dimensional information of the residential community in Tiexi District of Shenyang was extracted, and the variation pattern of the three-dimensional landscape in the district during its reconstruction in 1997-2008 and related affecting factors were analyzed with the indices, ie. road density, greening rate, average building height, building height standard deviation, building coverage rate, floor area rate, building shape coefficient, population density, and per capita GDP. The results showed that in 1997-2008, the building area for industry decreased, that for commerce and other public affairs increased, and the area for residents, education, and medical cares basically remained stable. The building number, building coverage rate, and building shape coefficient decreased, while the floor area rate, average building height, height standard deviation, road density, and greening rate increased. Within the limited space of residential community, the containing capacity of population and economic activity increased, and the environment quality also improved to some extent. The variation degree of average building height increased, but the building energy consumption decreased. Population growth and economic development had positive correlations with floor area rate, road density, and greening rate, but negative correlation with building coverage rate.

In this paper, three-dimensional building information was extracted from high resolution satellite image based on Barista software. Combined with ArcGIS software, the dynamic changes of the building landscape in Tiexi District of Shenyang City during urban renewal process were analyzed from the conversion contribution rate, building density, average building height, and built-up area rate. It was found that during this urban renewal process, four dominant landscape types (vacant lot, residential building, industrial building, and road) were the main parts of the landscape changes. The areas of vacant lot, residential building, commercial building, and road increased, while that of industrial building decreased. The building density decreased, while the average building height increased. There was an obvious regional variation in building landscape. The building density in industrial district was higher than that in residential district, while the average building height was in adverse. The further from the city center, the lower the building density and building average height.