Many indices based on MODIS data are used to monitor the process of agricultural drought, such as apparent thermal inertia (ATI) and temperature vegetation dryness index (TVDI). Notable differences in performance and geographic predictions exist among these indices. We statistically evaluated the performance of different drought indices for a known drought process in 2014 in the typical rainfed maize region of Songliao Plain, China, using a linear regression model based on the relationships between indices and soil moisture data. Our results show that during the growth season of May to September, the indices performed independently with changing curves, particularly in different phenological periods. By contrast, correlations tended to be higher for ATI than for other indices in the early vegetative growth stage, whereas small differences were detected among the other indices in the late vegetative to late reproductive growth stages. Our results confirm that the TVDI can be the best choice to detect agricultural drought in the study area.
This paper was to assess the reliability of RADARSAT-2 quad-polarization SAR data in rice mapping and yield estimation. Five scenes of RADARSAT-2 images were acquired in the rice season of 2011 in Jiangsu Province, China. Ground experiments were conducted in accordance with the acquisition dates. For rice mapping, optimal dual-polarization combination was obtained by ratio change detection. The accuracy of rice mapping by HV/HH reaches 79.2% and by VV/HH reaches 84.9%. For rice yield estimation, an improved scheme based on assimilation method has been put forward. ORYZA2000 model was coupled with an empirical rice backscattering model to simulate the dual-polarization ratios. SCE-UA optimization algorithm is employed to determine the optimal set of input parameters during the re-initialization process. As a result, an improved accuracy has been confirmed.
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.
Soil Moisture and Vegetation Growth are the most important and direct index in drought monitoring, and the
spectral interpretation of vegetation and soil are serious factors in the judgment of drought degree. Based on
the spectral character of water, recently, a new model of Surface Water Capacity Index (SWCI) has been put
forward, and the index is more sensitive to the surface water content, and suit for regional drought
monitoring. The comparative analysis showed: SWCI is more sensitive than NDVI to monitoring surface soil
water content; this is available in real-time soil drought monitoring.
The method of Normalized Multi-Band Drought Index (NMDI) is constructed by fully considered the
channel 2 (860nm) sensitive to leaf water content changes and the difference between two liquid water
absorption bands (1640 nm and 2130 nm) as the soil and vegetation water sensitive band. The potential
have been confirmed with the application in different time-series MODIS data. The results show: there is a
significant correlation between Normalized Multi-Band Drought Index (NMDI) and soil moisture, the
index adopted passed the significant F-tests with α = 0. 01. So the method of Normalized Multi-Band
Drought Index (NMDI) could be used in Henan drought monitoring. We found that the index of NMDI
application to areas with moderate vegetation coverage, however, needs further investigation.
Soil Moisture and Vegetation Growth are the most important and direct index in drought monitoring, and the
spectrum interpretation of vegetation and soil are serious factors in the judgment of drought degree. To find a
more real-time monitoring index of cropland soil moisture by remote sensing, a Cropland Soil Moisture Index
(CSMI) was established in this paper based on the effective reflections of Normalized Difference Vegetation
Index (NDVI) on deeper soil moisture and well expressions of Surface Water Content Index (SWCI) on
surface soil moisture. By validation with different time-series MODIS data, the Cropland Soil Moisture Index
(CSMI) not only overcome the limitation of hysteretic nature and saturated quickly of Normalized Difference
Vegetation Index (NDVI), but also take the advantage of the Surface Water Content Index (SWCI) which
effectively reduce the atmosphere disturbance and retrieval surface soil water content better. The index passed
the significant F-tests with α = 0. 01, and is a true real-time drought monitoring index.
Soil Moisture and Vegetation Growth are the most important and direct index in drought monitoring, and the
spectrum interpretation of vegetation and soil are serious factors in the judgment of drought degree. To find a
more real-time monitoring index of cropland soil moisture by remote sensing, a Cropland Soil Moisture Index
(CSMI) was established in this paper based on the effective reflections of Normalized Difference Vegetation
Index (NDVI) on deeper soil moisture and well expressions of Surface Water Content Index (SWCI) on
surface soil moisture. By validation with different time-series MODIS data, the Cropland Soil Moisture Index
(CSMI) not only overcome the limitation of hysteretic nature and saturated quickly of Normalized Difference
Vegetation Index (NDVI), but also take the advantage of the Surface Water Content Index (SWCI) which
effectively reduce the atmosphere disturbance and retrieval surface soil water content better. The index passed
the significant F-tests with α = 0. 01, and is a true real-time drought monitoring index.
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.
In this study, three scenes of Landsat TM/ETM+ images covering Beijing area were used to examine the relationship
between the UHI and land use and land cover (LULC) changes, as well as between the UHI and vegetation greenness.
The brightness temperatures, LULC, and NDVI were retrieved from the calibrated images. The results showed that the
urban or built-up area in Beijing has increased by 4.07% from 1988 to 2005, with nearly 5.7% of vegetated land lost
during the same period. The barren area was also increased in this period as large number of land was taken over for
urban construction. Seasonal pattern of UHI was obvious with highest UHI intensity observed in summer and lowest in
winter. Moreover, with the rapid urbanization, the extent of UHI expanded with newly hot spots emerged surrounding the
central urban area. In addition, higher NDVI or vegetation coverage leads to higher land surface temperature (LST) in
winter and lower LST in summer. This was due to the different thermal characteristic between vegetated area and
non-vegetated area. Therefore, increasing vegetation coverage can be beneficial to the mitigation of UHI effect in urban
area in hot season while to keep the land warmer in cold season.
In this paper, a practical scheme for assimilation of multi-temporal and multi-polarization ENVISAT ASAR data in rice
crop model to map rice yield has been presented. To achieve this, rice distribution information should be obtained first by
rice mapping method to retrieve rice fields from ASAR images, and then an assimilation method is applied to use the
temporal single-polarized rice backscattering coefficients which are grouped for each rice pixel to re-initialize
ORYZA2000. The assimilation method consists in re-initializing the model with optimal input parameters allowing a
better temporal agreement between the rice backscattering coefficients retrieved from ASAR data and the rice
backscattering coefficients simulated by a coupled model, i.e. the combination of ORYZA2000 and a semi-empirical rice
backscatter model through LAI. The SCE-UA optimization algorithm is employed to determine the optimal set of input
parameters. After the re-initialization, rice yield for each rice pixel is calculated, and the yield map over the area of
interest is produced finally. The scheme was applied over Xinghua study area located in the middle of Jiangsu Province
of China by using the data set of an experimental campaign carried out during the 2006 rice season. The result shows that
the obtained rice yield map generally overestimates the actual rice production situation, with an accuracy of 1133 kg/ha
on validation sites, but the tendency of rice growth status and spatial variation of the rice yield are well predicted and
highly consistent with the actual production variation.
Soil moisture and vegetation growth are the most important and direct index for drought. The interpreting to vegetation and
spectrum analysis of soil are two important elements in the judgment of drought. Recently, Abduwasit Ghulam and other
researchers, on the basis of the spatial distribution characters of soil moisture in near infrared spectrum, adopt the expansion
analysis method and establish PDI. Later, vegetation index is introduced by establishing a new drought monitoring method MPDI
after comprehensively considering about the soil moisture and vegetation growth characters. The article, directing against the
drought in different periods of Henan Province, adopts the MODIS image data to undertake PDI and MPDI calculations and
compares with the soil moisture data with that of the same period, concluding that: PDI and MPDI are closely related with the
original data from land observation, among which the relations between MPDI and 0-20cm calculation is the closest; PDI and
MPDI are all close to the drought situation concluded from the calculation of bared land and the early growth period of
vegetations; MPDI is more suitable for the areas with vegetations.
Soil moisture and vegetation growth are the most important and direct index for drought. The interpreting to vegetation and
spectrum analysis of soil are two important elements in the judgment of drought. Recently, Abduwasit Ghulam and other
researchers, on the basis of the spatial distribution characters of soil moisture in near infrared spectrum, adopt the expansion
analysis method and establish PDI. Later, vegetation index is introduced by establishing a new drought monitoring method MPDI
after comprehensively considering about the soil moisture and vegetation growth characters. The article, directing against the
drought in different periods of Henan Province, adopts the MODIS image data to undertake PDI and MPDI calculations and
compares with the soil moisture data with that of the same period, concluding that: PDI and MPDI are closely related with the
original data from land observation, among which the relations between MPDI and 0-20cm calculation is the closest; PDI and
MPDI are all close to the drought situation concluded from the calculation of bared land and the early growth period of
vegetations; MPDI is more suitable for the areas with vegetations.
Paddy rice is a staple food in China and it's growth monitoring, acreage extraction and yield estimate are of far
reaching importance. It is difficult to apply conventional remote sensing technique for obtaining precise information on
paddy planting and growth, for rice bowls are mostly distributed over rainy regions in China. The radar image is
unlimited by cloud, rain and fog, and could proceed all weather operation and obtain more stable data, therefore it could
be used for paddy monitoring. Making use of Envisat's ASAR data and NOAA data in 2004, paddy's
backward-scattering characteristics with different polarizations were studied in this paper. To combine multi-temporal
radar data with one view ETM image, paddyfield of experimental area in Hongze of Jiangsu Province was classified.
Results show that 1) characteristics of paddy's hh and vv polarizations vary from stage to stage and vv polarization is
more sensitive. The polarization ratio hh / vv of paddy during metaphase is apparently higher than other objects'. 2)
paddy's polarization ratio hh / vv and growth vigor closely relate to each other , thereof two empirical time-domain
models of backward- scattering were established, wherewith to estimate number of days after transplanting and growing
season. 3) hh and ratio hh / vv are both well correlated with NDVI. 4) hh polarization data could be used for information
extraction of towns and water bodies, and the hh / vv image in metaphase for partition of paddy from other objects. The
recognition accuracy being ninety percent over, multi-temporal and -polarization radarsat data are of predominance and
potential for paddy growth and/or acreage monitoring.
Drought is the serious agrometeorological disaster influences the growth of winter wheat in Henan Province, China.
The main causes of drought formation in the province was preliminarily described based on factors such as
geographical, monsoon circulation and the global climate background and then drought patterns that happened during
last more than 40 years were analyzed in terms of negative departure percentage from averaged precipitation as
indicators. Results show that heavy droughts are centralized in northeast part of the province and light droughts
centralized in southwest part. The light ones took place every 3 years, medium ones did every 7 years and heavy ones
every 10 years. This study is beneficial to winter wheat cropping planning and drought-prevention in Henan Province.
The characteristic of climate in North China is short of precipitation in winter and spring. Insufficient supply of water is a major factor affecting yield of winter wheat. The variation of yield caused by irrigation or drought at different stages is not alike. The relationship between them can be represented with water-yield reaction coefficient. Based on the experiment conducted in 2001 through 2004, yield of winter wheat has a marked positive correlation with precipitation at different stages after winter. The water-yield reaction coefficients increase with crop development, especially in turning green stage. The maximum occurs at head sprouting stage. Then it decreases slightly at milking stage. In order to raise water use efficiency of winter wheat, it is necessary to practice irrigation at elongating and head sprouting stages first and milking stage next.
KEYWORDS: Meteorology, Climatology, Atmospheric modeling, Data processing, Sun, Lithium, Statistical analysis, Information science, Information technology, Information security
As a major agrometeorological disaster of winter wheat in Henan, drought is a big contributing factor to the steady rise of the yield. To make risk assessment of the drought-caused yield decline is of much significance to rational choice of culvars and putting forth measures against drought loss. Based on interannual meteorological and yield records, analysis is undertaken of yearly drought probability, percentage yield decline and yield coefficient of variation, whereupon is constructed a model for comprehensive risk assessment of wheat yield and regionalized is the risk happening. Evidence suggests that the indices of the risk assessment range over 1.23 ~ 4.88, with the high-value zones making up 12.5%, distributed mainly in eastern, and northeastern Henan, the middle-value zones accounting for 36.5% in southwest, southeast, eastern, northeast and northwest Henan and the low-value zones (51.0%) in the extensive region, with Lushi - Xiangcheng (Beijing to Guangzhou railway in Henan) as the axis line in the east - west (south - north) Henan province.
Drought is one of the major meteorological disasters to agriculture in north China so that the development of methods for effectively monitoring droughts is of great significance to dry land crops. This paper makes analysis of products of energy and water balances retrieved from LAS (Large Aperture Scintillometer) measurements, indicating that the structural parameter of LAS refractive index shows regular difference in daily variation between different weather backgrounds and remarkable difference in sensible heat flux on a seasonal basis, with higher negative correlation between such flux and soil humidity at 0 ~ 50 cm depth.
Drought is a principal agrometeorological disaster to winter wheat zones in North China. From the correlation of wheat yield to rainfall the drought indices are determined that correspond to varying levels of severities on an agricultural basis. In wheat growing season, when rainfall displays its negative anomalies of <15, 15-35, 36-55 and <55%, there occurs a slight, moderate, heavy and extreme drought, leading to yield drop by <10, 10-20, 21-30 and <30%, respectively. The economic loss consists of yield reduction and drought-fighting input like irrigation. A drought-caused loss model is presented from historical meteorological and wheat yield datasets, with which to make the distribution of economic losses in the last 30 years over the province of Henan. Evidence suggests that in years of heavy droughts the loss was between 450 to 675 (<250) RMB yuans per hectare in the NE (west − SW) segment of the province.
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