Permafrost

oth time and space.
We next categorize the TP according to land cover type based on the global International
Geosphere-Biosphere Programme (IGBP) 30 arc-second (approximately 1 km × 1 km)
latitude-longitude vegetation/land-cover classification data consisting of 16 land types, and
quantify temporal changes in vegetation based on the 8 km × 8 km Global Inventory Modeling
and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI). The TP is
also classified according to the distribution of permafrost using the Circum-Arctic Map of
Permafrost and Ground-Ice Conditions and the Maps of Geocryological Regions and
Classifications in China. We assess in situ and reanalysis temperature trends according to land
cover type, disturbed versus undisturbed regions, and permafrost distribution, and quantify the
corresponding warming trends related to land cover types and changes.
Preliminary results suggest that statistically significant vegetation decreases have occurred
over the last 20 years in the central and eastern TP. Based on this geographic distribution of
vegetation changes as well as the land cover type classification, we indeed find different
temperature trends based on disturbed versus undisturbed regions. The seasonality of these
changes plays an important role; however, vegetation changes alone do not account for
observed temperature increases. Surface temperature trends are likely also affected by the
reported general warming of the atmosphere in recent decades. However, the distribution of
permafrost also accounts for differences in observed temperature variability on the TP. We
hypothesize that as permafrost affects soil moisture and hence vegetation and heat fluxes,
reported surface temperature changes and analogous changes in land cover are partly driven by
the distribution of permafrost.
Key words: Tibetan Plateau, climate change, land-use change, permafrost
190
Volume Rendering of Qinghai-Tibet Railway Borehole Data
Qing-Sheng Shang, Jian-Wen Guo
(Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy
Sciences, Lanzhou 730000, China)
Abstract: Qinghai-Tibet railway geographical information system and digital roadbed is a
platform for sharing data, running models and displaying research result. Three dimension (3D)
visualization techniques were applied in the system. In this paper a method of borehole data
volume rendering was discussed.
Borehole is a main way to know circumstance under ground. Borehole data include
lithology data and normal property data such as temperature, pressure etc. Through the
lithology data the stratigraphic unit can be constructed. Through normal property data the
physical field under ground can be constructed.
Voxel modeling is used to build 3D model. The regular voxel data are created from
discrete borehole data with kriging algorithm.
A geology space is separated into different stratigraphic units. An approach called horizons
method was used to build contact surface of different stratigraphic units. Borehole data are