Light use efficiency (LUE ) is an important parameter for GPP and and NPP estimation model, cause by the existing
model method to estimate the actual LUE is always simple and rough, which may lead to serious bias by GPP and NPP.
The photochemical reflectance index ( PRI ) has great potential for direct estimation the actual LUE. In this paper, wheat
in different nitrogen treatments was designed in field trial during Wheat growing period, for obtain photosynthesis and
reflective hyperspectral data, and then LUE and PRI was calculated in critical period of wheat growth. The results show
that, at different growth stages under three different nitrogen conditions, LUE and PRI value were significantly increased
with increasing nitrogen absorption; Last longer, more capable of absorbing nitrogen amount, the correlation between
LUE and PRI was better,for example, the correlation coefficient is obviously larger in heading stage than elongation
stage for same nitrogen treatment.
Remote sensing monitoring the macroscopic vegetation situation and reflecting environmental factors influence the
results and the process of crops; Crop growth simulation model using environmental factors simulate the process of crop
growth, revealing the cause and essence of the process, both of them have advantages and disadvantages. Thus
developing the study of combine remote sensing yield estimation and dynamic crop growth model is essential, it is a
significant scientific issue studying the approach and method which can combine these two advanced technologies. In
this paper, using multi-temporal remote sensing information and crop model ORYZA2000 combined method realizing
the rice growth simulation in pixel scale, after the comparison between simulated result and the actual statistic value,
accuracy is high and result is good. The combination of remote sensing information and crop simulation model is a
complex issue, its result will be affected by many factors, combined with the field test in this study is a simplification of
the actual situation, this will certainly affect the result’s accuracy.. This method has great practical significance and at the
same time has positive application prospect. It can be used to monitor and evaluate crop growth condition, forecast crop
yield and so on, thus can be used in decision support service on different regional scales and guiding agricultural
production.
Evapotranspiration is the important process of plant physiological and ecological, estimating and monitoring
evapotranspiration are very useful for evaluation of the influence on the crop growth situation. Determination
evapotranspiration over natural surface, the utilization of satellite remote sensing is indispensable. In this paper, a new
method is established based on high resolution remote sensing data(TM/ETM) combination Penman-Monteith regional
daily evapotranspiration calculation model. The key of the algorithm is used to calculate the Temperature-Vegetation
Coverage Index (TVCI) based on an empirical parameterisation of the relationship between surface temperature (Ts) and
vegetation index (NDVI), Ts and NDVI in combination can provide information on vegetation and moisture conditions
at the surface. Two methods used to calculate the TVCI. The “Universal triangle” method was used to estimate TVCI
according to Carlson et al. (1995). Using a trapezoid (triangle) correlation between surface temperature and fractional
vegetation cover, we constructed an improved ‘Actual triangle’ method to estimate TVCI, then coupling the Penman-
Monteith equation (1998) to estimate daily ET. Daily ET based on the ‘Actual triangle’ methods was compared well with
methods by the ‘soil water lost method’, while daily ET based on the ‘Universal triangle’ methods was underestimated.
So, it is suitable to use ‘Actual triangle’ method to estimate TVCI instead of ‘Universal triangle’ method in the North
China Plain even if the method was applied under different climate conditions. These results indicate that the method is
feasible, and VTCI is a close real-time drought monitoring approach. It is based on satellite derived information and
combination with the meteorology data, and the potential for operational application of the method is therefore large.
Crop model is a powerful tool in crop growth monitoring and yield forecasting, however crop model is developed based
on single point scale, due to regional differentiation、field variation and other reasons lead to input parameters and initial
conditions which required by crop model simulation are hard to obtain, the application of crop model has been greatly
limited in the regional scale, the introduction of remote sensing will solve this problem, remote sensing is combined with
the crop model WOFOST, using the state variable retrieved by remote sensing to optimize crop model simulation,
revaluing the sensitive parameters and initial conditions which needed in crop model on the region scale, in order to take
the advantage of crop model in the area.This study is on the basis of adaptive adjustment and amendment of crop model
WOFOST, build a winter wheat growth simulation model which is suitable for Yucheng, Shandong; Using the field
experiment data calibration and validation the WOFOST model, discussed the method which combined crop simulation
model and remote sensing under water stress level, using remote sensing calibrated some key processes of crop
simulation or reinitialize、parameterize the crop simulation model in order to achieve the optimization model; Explored
some reasonable and practical method of remote sensing information application in crop simulation at regional scale,
with more research, make it possible to monitor regional crop growth and forecast the output.
Remote sensing data combined with crop model is an important application and development trend of current
agricultural information technology, it can solve the problem that remote sensing or crop model cannot solve alone. In
order to simulate crop growth and yield prediction in large scale, this paper using field test data to calibrate and
validation the model parameters before apply to the winter wheat WOFOST model, than according to the actual
environment of Xinxiang, simulate the growth in 3 different condition in the 2002-2003 growing season. Contrast the
simulation value WOFOST model, using the Landsat-7 ETM retrieving leaf area index, define winter wheat’s growth
condition in each pixel, the remote sensing information combined with crop model is accomplished at pixel scale. Based
on the actual production of Xinxiang winter wheat in 2003,compare the simulate results with the corresponding
parameter, results shows that the method of this study method is feasible.
Based on medification of crop model WOFOST, a winter wheat growth model was applied in Yucheng region of Shandong Province in the North China Plain. Combination method of remote sensing information with crop model in water stress production level was studied. Through coupling remote sensing information, crop model was optimized by reestimating its parameters and initial conditions. A new method of regional remote sensing combining crop model was established and its application was studied. This method has highly potential application in crop growth monitoring and yield forecasting.
The land surface temperature (LST) plays an important role in the process of interaction between surface and atmosphere.
It is widely need in meteorology, geology, hydrology, ecological and many other fields. This article uses the ETM+ data
of February 16th, 2002 and August 27th, 2002, using the single window algorithm to retrieve the LST in the southern area
of Gansu province. First step is removing cloud for image. Secondly, classifies the type of surface by dividing into three
types of water surface, snow surfaces (winter) and natural surface. Then, estimate the emissivity according to the
classification in order to calculate surface temperature. Through the analysis of spatial distribution of land surface
temperature in the study area, the result shows QinZhiHao's single window algorithm is consistent with the reality.
Every year there are ice disasters in the Bohai Sea, which bring serious effect on the human’s life and production. So
how to monitor the ice disaster becomes an important issue. The remote sensing technology has a good advantage of
monitoring ice disaster over others. In this paper, NOAA/AVHRR data is used to retrieval each parameter of sea surface.
Firstly, according to the worked brightness temperature difference can separate sea from land. Then taking advantage of
the difference of the albedo of visible light and near infrared band to get rid of clouds and seawater, however, due to the
thin ice albedo there exists some errors, thus we can use the multi channel split window method (MCSST) further
extraction of sea ice in accordance with sea surface temperature, then we can get the sea ice area on the basis of number
of pixels and satellite spatial resolution. Secondly, after getting the region of sea ice, sea ice thickness can be obtained
through the empirical formula between ice thickness and near infrared band albedo. Lastly, after solving the extraction of
the ice information within mixed pixels, ice concentration also can be calculated.
The land surface temperature is an important parameter to hydrology and meteorology, it affects the exchange of
sensible and latent heats between atmosphere, sea and land, and it can not be lack in many research fields. To retrieve
land surface temperature exactly and quantificationally will promote the development of research areas such as drought
forecasting crop yield estimating numerical weather forecast, global climate change and carbon balance. Therefore,
retrieval of land surface temperature using thermal infrared remote sensing becomes one of the most important tasks in
quantificational remote sensing study. The TM images are used in this article, which were recorded in June 11, 2001
over Nakchu area in Tibetan Plateau, to calculate the land surface temperature. The natural surface is classified based
on information of remote sensing (snow, water and other land surface) and relevant information of geography, then the
emissivity can be dealt with by each surface type in different way. Last, the land surface temperature is inversed by
mono-window algorithm. The result show that the derived regional distributions of the the land surface temperature for
the whole mesoscale area is agreed with the land surface status very well.
Estimation evapotranspiration(ET) over large area of inhomogeneous landscape is very important and not an easy
problem. Determination evapotranspiration over natural surface, the utilization of satellite remote sensing is
indispensable. Using remote sensing data and weather stations data, a parameterization method is described for
estimation evapotranspiration over the Tibetan Plateau area. In this paper, the natural surface is classified based on
information of remote sensing and relevant information of geography, then the ET can be dealt with by each surface type
in different way. Further more, distribution figure of the evapotranspiration is given out. The results indicate: (1) The
regional distribution is characteristic by its terrain nature and the regional distribution is obvious and regular. It is seen
that the derived regional distributions of the evapotranspiration for the whole mesoscale area is agreed with the land
surface status very well. (2) The maximum evapotranspiration is over forest, rivers edge and other area can be irrigated
(many flourish grass or crops growing there) are high too, the value of the evapotranspiration over nudation area is low.
The derived regional evapotranspiration is contrasted with the value calculated by FAO-PM, and the result can be
accepted.
Tibetan Plateau has a crucial impact on the atmospheric circulation changes of Asia and even the northern hemisphere
and southern hemisphere, directly affecting the formation and evolution of weather and climate of China, and therefore
the studying on weather, climate and their evolving mechanism over Qinghai-Tibet Plateau is of great significance, and
this studying is helpful for improving accuracy of forecast disaster weather. Tibetan Plateau is the magnifying glass of
global climate change too. The system of ecology and the environment in Tibetan Plateau is very fragile and very
sensitive to global climate change, so Tibetan Plateau is a window of studying global climate change. Due to the special
geographical conditions of the Tibetan Plateau, the weather stations are scarce over the plateau region, especially in its
western region. The introduction and application of satellite remote sensing data on studying on the Tibetan Plateau, in
particular, is very important and very necessary. Using satellite remote sensing data, some areas of the Tibetan Plateau is
classified into several surface types, regional distributions of the Surface parameters are calculated and discussed
according to each type. Further more, each distribution map and straight-bar figure of the Surface parameters is given
out. The results indicate: All the regional distributions are characteristic by their terrain nature and the regional
distributions are obvious and regular. It is seen that the derived regional distributions of land surface parameters for the
whole mesoscale area are in good accordance with the land surface status.
Accurate crop growth monitoring and yield predicting is very important to food security and agricultural sustainable
development. Crop models can be forceful tools for monitoring crop growth status and predicting yield over
homogeneous areas, however, their application to a larger spatial domains is hampered by lack of sufficient spatial
information about model inputs, such as the value of some of their parameters and initial conditions, which may have
great difference between regions even fields. The use of remote sensing data helps to overcome this problem. By
incorporating remote sensing data into the WOFOST crop model (through LAI), it is possible to incorporate remote
sensing variables (vegetation index) for each point of the spatial domain, and it is possible for this point to re-estimate
new values of the parameters or initial conditions, to which the model is particularly sensitive. This paper describes the
use of such a method on a local scale, for winter wheat, focusing on the parameters describing emergence and early crop
growth. These processes vary greatly depending on the soil, climate and seedbed preparation, and affect yield
significantly. The WOFOST crop model is calibrated under standard conditions and then evaluated under test conditions
to which the emergence and early growth parameters of the WOFOST model are adjusted by incorporating remote
sensing data. The inversion of the combined model allows us to accurately monitoring crop growth status and predicting yield on a regional scale.
Determination the regional land surface parameters and components of surface radiation balance over heterogeneous landscape is very important and not an easy problem, in such researches, the utilization of satellite remote sensing is indispensable. In this study, a parameterization method based on Landsat-7 ETM+ data and 22 weather stations data is described for deriving the regional distributions of land surface parameters and components of surface radiation balance over the South Ningxia area. The distribution figs and straight-bar charts of the parameters and components are given out. Further more, the South Ningxia area is classified into five surface types, regional distributions are discussed according to each type. The main results indicate: All the regional distributions are characteristic by their terrain nature and the regional distributions are obvious and regular. The figures of the mountains and rivers are very clear, cause there is a great deal vegetation growing over the mountains and rivers edge. It is seen that the derived regional distributions of land surface parameters and components of surface radiation balance for the whole mesoscale area are in good accordance with the land surface status.
Northwestern China is a semi-arid or arid area in China. Ningnan (or South Ningxia) district is located south of Ningxia Province belong to Northwestern part of China. Climate in this region is more dry and lack of precipitation. Because global climate have been changing, temperature has been increasing and rainfall has been decreasing in South Ningxia. The ecology has been deteriorating, such as vegetation cover destroying, water losing and soil erosion. Therefore, the people who live in South Ningxia have been poor. Recently, Chinese government put into effect on strategy of "great development of Chinese northwest", aiming to improve environmental and ecological conditions and rise people's living standard. South Ningxia district was defined as area of emigration where the measurements of returning land for farming to forestry were taken into account . How to evaluate the plans and measurements is very important to continue to improving local environmental and ecological conditions further. The basic index of evaluation is soil water profit and loss statement while evapotranspiration (ET) is an important component in statement income and outcome of soil water. It is a very complicated problem to estimate evapotranspiration (ET) over large area of natural surface. In this paper, the natural surface was classified as 5 categories based on information from remote sensing, each categories being dealt with special way. Using data of remote sensing and weather stations, the result of regional evapotranspiration over Ningnan(South Ningxia) was given out, and verified and discussing are also made out. The work helps to assess whether or not improve environmental and ecological conditions.
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