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 provides a coherent pattern identification analysis of coastal land use and land cover (LULC) under the impact of seawater intrusion. This study analysis applied the 4-, 3-, and 2-band false color composite Landsat satellite data to characterize the LULC in the study area. The evapotranspiration (ET) and heat fluxes were estimated by using the SEBAL model with two-time phase thermal infrared band images and regional surface parameters. Our findings are as follows: 1) Due to its distance from the sea, the vegetation index gradually increases as the level of land use gradually increased. 2) The different influences of seawater intrusion in the study area resulted in significantly different influences of land surface parameters (LST, Gn, MSAVI, and Uindex) on ET. There are a variety of types of relational patterns between parameters (LST, Gn, MSAVI and Uindex) and ET (positive, negative, and no relationship). 3) Seawater intrusion significantly affected the spatial pattern of LUCC, which evidently affected the spatial distribution of ET. The spatial distribution pattern and change characteristics of ET were formed by double driving forces of seawater intrusion and LUCC under the background effects of regional climate.
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.
GEOLUE model was designed with Light Use Efficiency (LUE) mechanism and was validated with
observed data and models comparison (GLOPEM, CASA, and CEVSA). We found that: GEOLUE model
correctly simulates monthly, quarterly and annual variation of Net Primary Product (NPP) in different
vegetation communities under monsoon climate. The spatial distribution of NPP simulated by GEOLUE
matched up to 96.67% with that of forest and shrub land. The GEOLUE model perfectly simulated the
seasonal characteristics and spatial pattern of biomass in different types of vegetation. The total amount
NPP of China simulated by GEOLUE is 0.667GtC in spring, 1.365GtC in summer, 0.587GtC in autumn
and 0.221GtC in winter. The average total NPP of China for 5 years is 2.84GtC / year.
In this paper, 10-day (ten-day) spatio-temporal response of vegetation to the change of temperature and
precipitation was analyzed in spring, summer, autumn and whole year in Xinjiang, China during the
period of 1998-2009 based on the SPOT VEGETATION-NDVI data and 10-day average temperature
or precipitation data observed by 54 meteorological stations in Xinjiang through correlation analysis.
The results show that the response of 10-day NDVI to temperature was more significant than that to
precipitation, and the maximal response of vegetation to temperature and precipitation lagged for two
10-day periods. Seasonally, the effect of temperature and precipitation on vegetation NDVI was the
highest in autumn, then in spring, and it was the lowest in summer. The response of vegetation to
10-day change of meteorological factors was positive in spring, the affecting duration was long, and it
was relatively short in autumn and summer. Spatially, the 10-day maximal response of NDVI to
temperature in northern Xinjiang was higher than that in southern Xinjiang. The results indicated that
interannual change of temperature was not the dominant factor affecting the change of vegetation
NDVI in Xinjiang, but the decrease of annual precipitation was the main factor resulting in the
fluctuation of vegetation coverage. 10-day average temperature was an important factor to promote
vegetation growth in Xinjiang within a year, but the effect of precipitation on vegetation growth within
a year was not strong.
Under the influence of the global change and human activity, the land use/land cover change (LUCC) is remarkable.
The evapotranspiration is one of the key taches of the water cycle. And it's the component of both water balance and
energy balance, which embodiments the balance of the substance, energy and the information system. The
evapotranspiration is closely related to the land use and land cover change. In this paper, we first gives the dynamic
characteristics of the land use and land cover change; and then, the distribution of the land surface water and heat flux
and evapotranspiration, by means of the SEBAL equation, based on the radiation balance equation and energy balance
equation; and finally, based on the tempo-spatial characteristics of evapotranspiration, we discusses the influence of
land use/cover change to the land surface evapotranspiration from two aspects: land use/land cover type and fresh/salt
water.
Two images of Landsat TM/ETM+ which belong to 1990 and 1999 respectively, were used to get the information of Land
Use/Cover Change (LUCC) of Sangong River basin. Land surface temperature (LST) of corresponding periods was
calculated by using the mono-windows algorithm, Bihong Fu's algorithm and Hongbo Su's algorithm. Based on accuracy
assessment, the response of LST to LUCC of this region and the relationship between LST and NDVI were analyzed by
combining the LUCC and LST. The results showed that, in this decade (1990-1999), urban development and increasing of
land use for agriculture caused significant changes of land use/cover in this region, which led to the land surface temperature
rising by 10 in average. As the study area is oasis which is located in the edge of desert, the vegetation had an obvious
influence on the LST which showed a negative correlation with vegetation index.
The theory of fractal is a new tool for studying spatial pattern of land use, and the techniques of remote sensing and GIS
offer a technical support. Firstly, under the support of RS and GIS, the classification information of land use is extracted
from the Lands ant TM imageries of the Baiyang River of two periods (2000 and 2005),and a spatial database of land use
is built. Secondly, in order to improve the understanding about the land use change about the Baiyang River, we use the
fractal model to calculate fractal indices of different landscape patterns, Combining some landscape indices including the
indices of the landscape diversity, the landscape fragmentation, the landscape shape and landscape separation, we
analyze the characteristics of land use change quantificationally and provide sustainable development of land use with
several pieces of advice in the end.
KEYWORDS: Data modeling, Vegetation, Statistical modeling, Remote sensing, Biological research, Near infrared, Geography, Inspection, Global Positioning System, Analytical research
Using the CBERS data in August,2005 and the corresponding measured grass yield data from 15 samples in the
region of Bayinbuluke grassland, we established the monadic linear regression models the non-linear regression models
and the logarithm models to express the relationship between grassland aboveground biomass and the Vegetation
Index(VI). The results showed that: 1)there were close relation between the VI and grassland aboveground biomass: 2)
the comparison of different forms showed that the logarithm equation was the best one in terms of the suitability of use
in study area: 3) the results from the non-linear regression analysis showed that the order was MSAVI NDVI LAI and
SAVI in terms of the fitting accuracy between these VI and grassland aboveground biomass data: 4) the non-linear
regression Y=-1242.2MSAVI3+6254.1MSAVI2-10044MSAVI+5267 was the best model which could be used in monitoring
grassland biomass based on the VI Bayinbuluke grassland.5) the calculated results were as follows: the total
aboveground biomass of Bayinbuluke in 2005 was 1.23x104t; the total biomass of high grass was 8.82×103t and the
density was 116.14g/m2;the total biomass of low grass was 2.04x103t and the density was 70.33g/m2 the total biomass of
swampland was 1.30x103t and the density was 122.36g/m2
Keywords Remote Sensing, vegetation index(VI), grassland, aboveground biomass, Bayinbuluke
Spatial and temporal distribution of vegetation net primary production (NPP) in China was studied using three light-use
efficiency models (CASA, GLOPEM and GEOLUE) and two mechanistic ecological process models (CEVSA GEOPRO).
Based on spatial and temporal analysis (e.g. monthly, seasonally and annually) of simulated results from ecological process
mechanism models of CASA, GLOPEM, and CEVSA, the following conclusions could be made: (1) during the last 20 years,
NPP change in China is followed closely by the seasonal change of climate affected by the monsoon with an overall trend of
increasing. (2) Average annual NPP in China was 2.864±1GtC. All five models were able to simulate spatial features of
biomass for different ecological types in China. This paper provides a baseline for China's total biomass production. It also
offers a means of estimating the NPP change due to afforestation, reforestation, conservation and other human activities and
could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases.
The autumn of 2007 has seen the most serious drought of last 30 years in the Poyang Lake Watershed (PLW, for short), which resulted in the sharp shrinkage of Poyang Lake from 3000 km2 of normal water coverage sharply to about only 50 km2 at drought peak. This paper adopted the data products of Moderate Resolution Imaging Spectroradiometer (MODIS, boarding on NASA satellites of Terra and Aqua) to analyze temporal process and spatial extension of this Drought in PLW. MODIS-derived Normalized Difference Water Deviation Index (NDWDI, for short) was calculated to examine the water balance of soil against background level, which was expressed with the NDWI average during 2000~2007. Though the Poyang Lake experienced sharp shrinkage in water area, the region near the Lake didn't show corresponsive serious water stress in NDWDI image series. This fact lies in that though the river runoff into the Lake decreased obviously, the soil of lake basin was exposed to less l water stress as the low terrain can easily supply water balance via ground flux.
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