Lake Baiyangdian, a largest wetland ecosystem in North China Plain, has dried up on seven occasions since the 1960s. In
recent years, more than one billion of cubic meters of water from upstream reservoirs and Yellow river have been
transported to the lake to rescue the shrinking wetlands. Since the Lake Baiyangdian was actually composed of 143 small
lakes and more than 70 villages with large or small area of cropland, dynamic distribution of aquatic plants in wetland
such as reed and associated growth condition of these allowed to monitor the changes of wetland landscape and water
quality to support the policy applications of water conveyance and wetland environmental treatment and control.
Assisted with ground survey analyses and Landsat TM image, the MODIS 250 m time series Normalized Difference
Vegetation Index (NDVI), given its combination of medium spatial and high temporal resolution, were applied to detect
the unique rapid growth stage of reed in the spring from adjacent crops such as winter wheat, cotton, and spring maize,
of which has a similar phenology in development of leaf area index, and dynamic reed areas were mapped in recent
decade. Landscape changes of the wetland were analyzed using maps of reed area and hydrological data.
KEYWORDS: Nitrogen, Soil science, Remote sensing, Magnetic resonance imaging, Data modeling, Agriculture, MODIS, Data acquisition, Geographic information systems, Statistical modeling
Overuse of chemical fertilizers raises the risk of nitrate pollution of groundwater in the North China Plain. To preserve
the groundwater and reduce the economic losses, an efficiently and quickly assessment of nitrate leaching risk on
regional farmland is crucial. In this research we developed a GIS-based model named 'Arc-NLEAP' based on NLEAP
model, combined the statistical and Remote Sensing data, to estimate applied fertilizer rates and crop yields, which are
two key variables indicating amount of input and output nitrogen in crop land, since crop greenness derived by MODIS
may reflect the content of chlorophyll of canopy which is closely related to nitrogen content, and NDVI values of crop
crucial growing periods determine crop production. The simulated results showed that the value for parameter NAL
(Nitrate Available for Leaching) was between 8 kg / ha and 474 kg / ha and the average was 117 kg / ha, for NL (amount
of Nitrate Leached) 18kg / ha (Low) , 59 kg / ha (Average) and 222 kg / ha(High).Percentages of parameter
MRI(Movement Risk Index) accounted for 8%,77% and 15% for low risk, medium risk and high risk respectively.
Taking water leaching index, nitrogen available for leaching, amount of Nitrate Leached, ammonia volatilization and
denitrification into consideration, we defined the N hazard class to evaluate the nitrogen leaching risk and the result
indicated that lager 74% of the study area was labeled as low N hazard class. Despite the spatial patterns for parameters
NAL and NL were similar, the values for MRI was determined by site-specific soil type and the capacity of water
movement principally, demonstrating that measures of controlling nitrate leaching should be based on the spatial pattern
of MRI, along with decreasing the amount of application rate simultaneity.
Mapping grain crop land productivity that associated soil quality and crop field management are needed over intensively
cropped regions such as the North China Plain to support science and policy application focused on understanding the
current and potential capacity of regional food support. In this study, the crop growth dynamic presenting by time series
field Greenness derived from MODIS 250 m data and soil moisture condition assessing by Normalized Difference Water
Index (NDWI) derived by MODIS 250 m and 500 m data were combined to detect the temporal and spatial variability
of productivity of winter wheat-summer maize field in the period 2000 to 2008 in Hebei and Shandong Province in
North China Plain. Annual average NDVI levels, average levels of nine years and coefficients of variation of levels in
the main growing season indicated corresponding crop growth condition and clearly presented spatial distribution of crop
growth. Both the levels of NDWI and the coefficients of variation of the levels have almost same pattern of spatial
distribution and correlations between two indexes levels were very high. The results of analysis of levels and coefficients
of variation of levels of NDVI and NDWI shows the combination analysis of two indexes can be used to assess the levels
of land productivity with a high spatial or temporal resolution .
Lower reaches of Tarim River, Western China is a very serious arid and desertification region. During 2000-2006, 2.36
billion cubic meters water has been transported to this area by nine terms to control regional desertification. We apply
grey correlation analysis for temporal and spatial variations of groundwater levels from nine monitoring sections and
corresponding MODIS vegetation indices (VI) in the third, fourth, and seventh terms of water conveyance to evaluate
the impacts of ecological water conveyances on basin hydrological processes and land cover. During the terms of water
conveyance, both groundwater level and VI along the canal are rising and a calculated grey incidence degree reaches
0.9. However, the increases of groundwater levels and VI gradually reduce from the source of water input in the
direction of the canal and calculated grey incidence degrees were below the level of significance for a single term of
water conveyance. At same time, the incidence degrees reduced significantly with increasing distances from the canal.
The analysis results shows that spatial variations of changes of hydrological processes and land cover conditions caused
by water input were very large, which may reduce the use efficiency of precious water resource in this region.
Tibet Plateau plays an important role in global changing and ecosystem studies because of its unique geographical
location and topography. Lhasa river basin which locates in the center of Tibet Plateau is a typical and important region
for agriculture and stockbreeding in Tibet. In this study a method of land cover mapping from 250m MODIS (Moderate
Resolution Imaging Spectroradiometer) product Normalized Difference Vegetation Index (NDVI) MOD13Q1 data is
presented. This knowledge-based method combines phenophase character of plants with time-series remote sensing data
and Geographic Information System spatial analysis. A quality assessment analysis is performed to time-series data by
temporal and spatial interpolation of invalid and missing data. The NDVI value is converted into a relative NVDI to
avoid the misclassification arising by data change of spatial and temporal. The preliminary results are compared with
both field observation points and classification mapped from Landsat TM imagery. The comparison indicates the result
of classification is promising.
Spatial variability of crop growth often needs to be evaluated due to different soil conditions, weather patterns and crop
information in a region. To simulate crop growth and productivity at a regional scale, a RS- and GIS-based crop growth
model named RS-CGM was developed. The model calculates crop distribution, leaf area index, soil water content using
remote sensing data that were integrated in crop growth module by inputting direct forcing variables, re-calibrating
specific parameters, and correcting yield prediction using simulation-observation difference of a variable. The main RS-CGM
components were intensively calibrated and verified against comprehensive field measurements of soil conditions,
irrigation, evapotranspiration (ET), crop leaf area index (LAI) and yields. .The RS-CGM was applied to a county in the
North China Plain to simulate winter-wheat yields in spatial and temporal dimensions. The model divides the simulating
area into a number of crop growth elements and calculates each element with a set of parameters, then achieves the
spatial crop yields and other concerned results aggregating to administrative regions. The simulated results show that the
model can effectively express the spatial variety of yields in a region. And suggest that it was feasible to develop a
spatial crop growth model combined with GIS, RS, and physiological process-oriented.
The evapotranspiration (ET) is one of the most important components of the water cycle in semi-arid Taihang Mountain region of North China. Due to significant changes in topography, the ET of this semi-arid region tends to vary dramatically both in time and space, which renders the accurate estimation of yearly or seasonal ET a difficult task. In current study, based on rGIS-ET v1.0, a regional ET model, by adding module of adjusting surface temperature in terrain, solar radiance terrain correction, and shaded relief, we improved the rGIS-ET a remote sensing model on ArcGIS platform for mapping ET distribution in such a semi-arid mountain area. With DEM of 30 meter and climate data, we run the model to estimate daily ET in mountain area using Landsat data. The ET distribution pattern estimated from Landsat data by rGIS-ET v2.0, was integrated into SWAT method to calculated daily ET at a high spatial resolution in the sub-watersheds. With input of the daily ET, SWAT simulated the annual flow of the component of water balance at sub-watersheds from 1995 to 2003. The variations of flows of annual ET were significant amount the sub-watersheds and the variations of ET flow may cause the variation of other components flow.
In this work, we integrate a popular remote sensing technique with ArcGIS to build a tool bar, named rGIS-ET, for
estimating regional evapotranspiration (ET) from Landsat data and MODIS data with improved resolution. The
development of rGIS-ET enables quick processing of large amount of remote sensing and other spatial data. It also
provides user-friendly interfaces for modelling, output display and result analyses. Both surface temperatures and albedo
were key parameters for calculating ET using Surface Energy Balance Algorithm. We adopted algorithms for estimating
surface temperatures and albedo of winter wheat and summer maize field from MODIS data at 250 m spatial resolution
to improve the resolutions of ET map of MODIS. We apply improved rGIS-ET to eight plain counties of Shijiazhuang
city, a typical agricultural region in North China Plain, to demonstrate its utility for calculating regional ET and
evaluating agriculture water resource usage. The improved ET map of MODIS could represent the spatial variation of
crop ET much better than that without improved.
The evapotranspiration (ET) is one of the most important components of the water cycle in semi-arid Taihang Mountain region of North China. The spatial distribution and seasonal variation of ET will directly impact the stream flow volume and the amount of lateral recharges to the aquifers of mountain front plain. Due to significant changes in topography, the ET of this semi-arid region tends to vary dramatically both in time and space, which renders the accurate estimation of yearly or seasonal ET a difficult task. In current study, based on rGIS-ET v1.0, a regional ET model, by adding module of adjusting surface temperature in terrain, solar radiance terrain correction, and shaded relief, we improved the rGIS-ET a remote sensing model on ArcGIS platform for mapping ET distribution in such a semi-arid mountain area. With DEM of 30 meter and climate data, we run the model to estimate daily ET in mountain area using Landsat data and MODIS data, respectively. The results of model application shows that model could correct the errors of ET value caused by elevation and terrain significantly while Landsat data was used. While MODIS data was used, the model could not do terrain correction accurately for MODIS has a low spatial resolution, but MODIS data with a high temporal resolution could be used to estimate the temporal variation of ET in a mountain area.
Moderate Resolution Imaging Spectroradiometer (MODIS) data are widely used to compute regional evapotranspiration (ET) at 1000-m spatial resolution. However, due to the fact that the village densities in most counties in North China Plain are higher than 0.5 per km2, the crop ET mapping at 1000-m resolution computed using MODIS data often fails to differentiate the crop field from the residential area, thus resulted in inaccurate ET estimation. In this study, we analyzed relationship between crop ET and MODIS-normalized difference vegetation index (NDVI) and deduced ET equations to calculating winter wheat and summer corn ET from NDVI. The equations were tested using measured data and proved that they are reliable. The equations were applied using MODIS 250 m spatial resolution NDVI and mapped crop ET at 250 m resolution. Compared with ET map from high resolution Landsat, the improved resolution ET map can described the spatial variations of regional crop ET in a similar pattern.
Temperature vegetation dryness index (TVDI) is a simple and effective methods for drought monitoring. In this study, the statistic characteristics of MODIS-EVI and MODI-NDVI at two different times were analyzed and compared. NDVI reaches saturation in well-vegetated areas while EVI has no such a shortcoming. In current study, we used MODIS-EVI as vegetation index for TVDI. The analysis of vegetation index and land surface temperature at different latitudes and different times showed that there was a zonal distribution of land surface parameters. It is therefore necessary to calculate the TVDI with a zonal distribution. Compared with TVDI calculated for the whole region, the zonal calculation of TVDI increases the accuracy of regression equations of wet and dry edge, improves the correlations of TVDI and measured soil moisture, and the effectiveness of the large scale drought monitoring using remote sensing data.
Sustainable management of water resources requires reliable information on regional evapotranspiration (ET) distribution, which is the largest output component of the hydrological cycle in North China Plain (NCP). In this work, we integrate a popular remote sensing technique with ArcGIS to build a ArcMap tool bar, named rGIS-ET, for estimating regional ET from Landsat TM/ETM+ data. The development of rGIS-ET enables quick processing of large amount of remote sensing and other spatial data. It also provides user-friendly interfaces for modeling, output display and result analyses. We use daily ET measurements from a weighting lysimeter in our experimental station to verify the performance of rGIS-ET. The verification confirms the reliability of ET calculation, whose errors during crop growing season are less than 10 %. We apply rGIS-ET to Luancheng County, a typical agricultural region in NCP, to demonstrate its utility for calculating regional ET and estimating agriculture water needs and ground water usage, both of which are critical to the design of an effective water resources management program for achieving sustainable development.
Accurate estimation of water consumption requires detailed information on vegetation types, including vegetable that is increasingly becoming one of the most important crops in China and many parts of the world. In current paper, a technique for rapid and accurate extraction of vegetable field (both greenhouse and open field) information from Landsat TM image is developed and tested. Through conducting field experiments and analyzing the Landsat TM images, we obtain the spectral characteristics of the film covered greenhouse vegetable and build a model to extract vegetable fields from the Landsat TM images. Applying this technique to Luancheng County of Hebei Province, China, we calculate the total area of the vegetable field being 208 ha. This number compares well with the result of our field survey. Based on the vegetable field area and the vegetable water consumption rate, we arrive at an estimation of the total vegetable water consumption in Luancheng County being 2.6*106 m3. The analyses also show that, in Luancheng County, the vegetable consumes about 4% of the total agricultural water use. The technique developed here provides an effective way for deriving vegetable field area from Landsat TM data and estimating the regional vegetable water consumption.
In this study, we demonstrate that the conventional temperature/vegetation drought index (TVDI) approach tends to overstate the degree of drought condition in areas with dense vegetation. This is because the TVDI approach may specify points with significant evapotranspiration (ET) activities (i.e. points with soil water content significantly above the wilting point) as the drought points in these areas. To overcome this shortcoming, we construct a new drought index, termed evapotranspiration/vegetation drought index (EVDI), using evapotranspiration distribution derived from the remote sensing data. We apply both TVDI and EVDI approaches to calculate drought indices for a dominantly crop farming region, Luancheng County, in Hebei Province of China at the season of high fractional vegetation cover. We use Landsat7 ETM+ data to derive the surface temperature, the fractional vegetation cover and evapotranspiration distribution, and compute both TVDI and EVDI maps for this region. Result comparison and analyses show that the TVDI map overstates the drought condition. The EVDI map is a more accurate representation of the real condition.
Hyperspectral remote sensing is not only an important technical method in observing global ecosystems and vegetation cover change, but also a main aspect of studies on precision agriculture. In order to monitor crop nutrient supply condition and to realize precision fertilization, spectral red edge parameter for winter wheat was studied. Experiments were carried out through 8 years since 1997 under four nitrogen support levels in Luancheng Station, Hebei province (e.g., 0, 100, 200 and 300 kg N ha-1). Canopy reflectance spectrum was measured by ASD HandHeld Spectroradiometer (325-1075 nm) during 2002 and 2004. The dynamics of red edge parameters for physiological stages of winter wheat canopy were calculated using first derivative curve. Analyses revealed that the red edge of the wheat canopy reflectance spectrum locates between 720-740 nm. All the different trial had distinct "red shift" trait, but higher N stress had shorter "red edge" wavelength. Position of red edge turned "blue shift" after pregnant period. Red edge swing is a first-order derivative spectrum when wavelength reached red edge position, red edge swing double peak shape showed that the pregnant period was the best stage to detect nitrogen deficiency. Red edge swing correlated with relative chlorophyll content and leaf N content. Area of red edge peak is the value of first-order derivative spectra accumulative total between 680 and 750 nm. These parameters can be used to estimate LAI and N accumulating quantities, and these results provide information needed for the development of variable-rate N application technology.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.