Are you Lingmei Huang?

Claim your profile

Publications (3)0 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: Relationship between vegetation and climate has been a hot spot in climate change researches since vegetation is a key component of land ecosystem that represents climate change. In this study, GIMMS NDVI data and meteorology data (precipitation and temperature) from 1982 to 2006 are used to do time lag analysis between NDVI and precipitation/temperature. First, whole time series NDVI and precipitation/temperature time lag analysis were done in two spatial scale- pixel and vegetation type districts. While in pixel scale, results show that NDVI has at least one month time lag with precipitation and temperature when they have significantly correlation. Different vegetation types response distinctly with climate conditions and Northern Temperate Meadow Steppe and Southern Cool Temperate Deciduous Needle-leaf Forest change immediately with climate, where maximum correlation coefficients appears between NDVI and climate factors at the same month. Comparatively, there are time lags in other regions. Second, we studied inter-annual time lag effects in growing season (from April to September) and accumulation effects of precipitation and temperature.
    IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2010, July 25-30, 2010, Honolulu, Hawaii, USA, Proceedings; 01/2010
  • [show abstract] [hide abstract]
    ABSTRACT: The study of land use/cover change helps to explain the inner mechanism of interaction of human-earth system. Based on the classification of the remote sensing data in 1978, 1987, 2000 and 2005, using indices representing spatial pattern characteristics of land use/cover such as gravity center migration, diversity index, dominance index, evenness index and fragmentation index, spatial pattern dynamics characteristics of land use in Yongding River basin from 1978 to 2005 is studied. Results show that the amount of patches trended to increase gradually and fragmentation degree of Yongding River basin rose obviously.
    IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2010, July 25-30, 2010, Honolulu, Hawaii, USA, Proceedings; 01/2010
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: Vegetation production is the main support of foods, materials and fuels in human life. Plants carbonize and transform solar radiation to their own biomass through photosynthesis. Vegetation productivity research is now an important issue in global change research and in recent years, modeling net primary productivity (NPP) defined as the difference between accumulated photosynthesis and accumulated autotrophic respiration by green plants per unit time and space and biomass of terrestrial ecosystems has been a subject of increasing interest because of the essentiality of terrestrial carbon cycle in global carbon budget and climate change. Light use efficiency (LUE) algorithms are a potentially effective approach to monitoring global NPP using satellite-borne sensors such as NOAA, MODIS and SPOT. In this paper, we took monthly NDVI and vegetation type in 2005 derived from SPOT vegetation data of 1km×1km spatial resolution, monthly meteorological data such as air and soil temperature ( ), precipitation (mm) and solar radiation (MJ/m �� 2) in the same year which are interpolated into raster images using kriging method and resampled to the same resolution as NDVI as input of the LUE model to estimated absorbed photosynthetically active radiation and LUE (�0 ) and then simulated both annual and monthly NPP in China's Inner Mongolia region. Additionally, an aboveground biomass estimation model was constructed through the relationship between NPP and field survey data of aboveground biomass to calculate aboveground biomass in the study area. This model was later validated by field survey data and showed good estimation accuracy. According to all the works done above, we analyze temporal and spatial distribution of NPP and biomass. The result shows that net primary productivity of Inner Mongolia in 2005 is 405.22 MtC/a with 176.70 MtC/a of the biomass, presenting an obvious increase compared with 390.8 MtC/a NPP in 2002 referred to the research of Zhu(1) mainly caused by well precipitation condition and graze restriction. There is a similar spatial distribution between NPP and biomass that both show a decline current from the northeast to southwest. The reason lies in the vegetation type diversity raised by hydrothermal condition. Referring to the vegetation type here, the highest value of NPP and biomass both appear in Greater Xing'an Mountains in the northeast most of which exceed 750 gC/m2a-1 and 260