This paper presents a new drought assessment method by modifying the NDVI-Ts space, which named NDVI-Ts general space. Based on this method, the general dry side and wet side equation were established for the period of 1981 and 2010 in the Mongolian Plateau. The results showed that: 1) the NDVI-Ts general space was more stable for monitoring drought than that for the single time Remote Sensing data; 2) TVDI was lower in the areas with high latitude, high vegetation cover, well-growing vegetation, which indicated higher soil moisture.3) The dry level area was the largest one, and the normal area was the second largest, the wet level area was the third, the extremely dry and extremely wet area was the least.4)The results showed that the fluctuated area mainly occurred in the normal level and the dry level, the extremely wet level, the wet level and extremely dry level basically remained unchanged. It may be explored that, the aridification became more serious in the 1981 – 2012, the area transformation mainly occurred between the normal level and dry level.
This paper presents a new drought assessment method by modifying the NDVI-Ts space, which named NDVI-Ts general space. Based on this method, the general dry side and wet side equation were established for the period of 2000 and 2010 in the Mongolian Plateau. The results showed that: 1) the NDVI-Ts general space was more stable for monitoring drought than that for the single time Remote Sensing data; 2) Drought mainly distributed in the Mongolian Plateau, In Mongolian Plateau, there was about 75% area of drought; 3) Drought changed in the period of 2000 and 2010. In the year of 2003, the area of severe drought is the smallest. In 2001, the drought is the most serious. The results showed that, the distribution of drought was different in different year. There may be close correlation between the occurrence of drought and precipitation.
Fractional Vegetation Cover (FVC) is one of the most important variables in monitoring the changes of terrestrial ecosystems. Based on the Two-endmember model, FVC from 2000 to 2012 in Xinjiang was derived from MODIS Normalized Difference Vegetation Index (MODIS NDVI)) (16-Day). The spatio-temporal vegetation changes were analyzed, and the results showed that: Vegetation cover in Inner-Mongolia was higher than that in Mongolia. In the year of 2000, the FVC in Inner-Mongolia is 0.557, and 0.516 in Mongolia; while in the year of 2012, the FVC in Inner-Mongolia is 0.663, and 0.593 in Mongolia.
Transpiration, an essential component of surface evapotranspiration, is particularly important in the research of surface evapotranspiration in arid areas. The paper explores the spectral information of the arid vegetal evapotranspiration from a semi-empirical perspective by the measured data and the up-scaling method. The paper inverted the transpiration of Haloxylon ammodendronat at the canopy, pixel and regional scales in the southern edge of the Gurbantunggut desert in Xinjiang, China. The results are as follows: At the canopy scale, the optimal exponential model of the sap flow based on the hyperspectrum is Y = 3.65× SR(1580,1600) + 0.76, R2 = 0.72. At the pixel scale, there was a good linear relationship between the sap flow and the SR index, with a linear relationship of Y = 0.0787 X - 0.0724, R2 = 0.604. At the regional scale, based on the optimal exponential model and the EO-1 Hyperion remote sensing data, the transpiration of the study area was inverted. Comparing the results of the SEBAL and SEBS models, the errors of the simulation results were 12.66% and 11.68%. The paper made full use of the knowledge flow at different scales, bridging the scale difference in canopy and remote sensing images to avoid the information bottleneck in the up-scaling. However, there is much limit in the data acquirement, the endmembers determine, the temporal-spatial up-scaling, and the accuracy assessment to be improved in the future studies.
The stem sap flow exhibited a bi-peaked or multi-peaked curve, with lower values at night than
during the day. The ambiguous noon-depression phenomenon usually occurs during 14:00~16:00
from mid-May to the early September. Under the same environmental conditions, the larger the
stem diameter, the larger the stem sap flow, and the more obvious the ambiguous noon-depression
phenomenon. The daily changes of the sap flow were highest in June and lowest in September.
There were differences in the monthly mean value in different plants, which may result from the
differences in the crown and the number of assimilation organ. The daily accumulation showed a
“S” trend between May and the end of August, and showed a straight line with the same slope in
September and October. The larger the stem diameter, the larger the daily water use and the
accumulative rate were. The sap flow was influenced by meterological factors, it was positively
correlated with solar radiation, air temperature and wind speed, and negatively correlated with the
air relative humidity, in which the solar radiation had the greatest impact on the sap flow. Under
the same environmental condition, the larger the stem diameter, the better the correlation was. The
correlation was the largest water use in July, and least in May and October. The larger the stem
diameter, the more the water consumption was.
According to the requirements of China National Scientific Data Sharing Program (NSDSP), the research and development of web oriented RS Image Publication System (RSIPS) is based on Java Servlet technique. The designing of RSIPS framework is composed of 3 tiers, which is Presentation Tier, Application Service Tier and Data Resource Tier. Presentation Tier provides user interface for data query, review and download. For the convenience of users, visual spatial query interface is included. Served as a middle tier, Application Service Tier controls all actions between users and databases. Data Resources Tier stores RS images in file and relationship databases. RSIPS is developed with cross platform programming based on Java Servlet tools, which is one of advanced techniques in J2EE architecture. RSIPS's prototype has been developed and applied in the geosciences clearinghouse practice which is among the experiment units of NSDSP in China.
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