This paper deals with the application of the 3S technique to the management of crop residue burning,
which includes the general principle and method of data processing as well as the results of the monitoring of crop
residue burning. The RS technique is used to monitor the hot spot caused by crop residue burning and determine the
harvest period. The GIS technique is employed to determine the nature of the hot spot and analyze the condition of
crop residue burning, whereas the GPS technique is adopted to find the exact location of the hot spot caused by crop
residue burning detected by the RS technique. The general situation of the application of this technique to this
field in recent years is also recounted in this paper.
Retrieving atmospheric water vapor from remote sensing data is very important in such aspects as weather
forecast, atmosphere correction and the study of climatic change and water circulation. At present, there are the
two-band ratio method and the three-band ratio method for retrieving atmospheric water vapor from near infrared
data. Based on the near infrared radiative transfer theory, this paper has proposed an improved three-band ratio
method under the simulation of the radiative transfer model, MODTRAN. Applying this method to three water absorbing
bands of MODIS, the authors obtained three kinds of water vapor values. Then the method for retrieving water vapor
for MODIS data was worked out on the basis of different sensitivities of the three bands to the absorbing of water
vapor. The authors retrieved the water vapor of eastern China and the results show that the method is feasible and
practical.
Influenced jointly by such factors as ocean, land and atmosphere, the coastal zone is characterized by
the mixing of various land types with high extent of variation. Therefore, traditional spectrum-based classification
cannot meet the demand of precision. The coastal zone is close to ocean water which can be recognized easily by its
significant spectral difference from land objects in the remotely sensed images. Taking advantage of this feature,
this paper proposes a new classification method for coastal zone remotely sensed images by adding space information.
Ocean water is recognized first, and then the distance from every non-ocean-water pixel to its nearest sea water is
calculated. Different objects on the coastal zone have their respective characteristic distances to ocean water. So
helped with the space information, we can improve the precision of classification, especially for the objects with
similar spectral features but different distances to sea water. Using this method, the authors studied the multi-
band QuickBird image of Huangdao island in Qingdao, and the result proves the validity of this method in coastal
areas relative to the pure spectrum method.
As an important parameter governing energy balance over land, Land Surface Temperature (LST) plays an
important role in meteorology, hydrology, ecology and some other disciplines. In this paper, the authors have
analyzed the probable sources of errors in retrieving land surface temperature using MODIS data and dealt in detail
with the validation method for simultaneous retrieval using relatively high resolution remote sensing data. A
comparison between ASTER land surface temperature and MODIS LST products was conducted in Taihu area on August 1,
2003. Linear regression of three typical areas in water surface, city ground, and outskirts of Wuxi respectively
shows that the result is satisfactory for validation, with R2 being 0.9666.
Cloud detection is absolutely necessary in the processing of satellite remote sensing data. Through
analyzing meteoric characteristics of cloud in different spectra and integrating the spectral characteristics of
MODIS (Moderate Resolution Imaging Spectroradiometer), the authors put forward a new cloud detection method based on
multi-spectrum synthesis. Taking into account such factors as visible reflectance, infrared brightness temperature
and window brightness temperature difference, the algorithm can gradually build a cloud detection mask and finally
obtain an entire cloud processing result which can discriminate cloud from clear sky. The algorithm was applied in
different periods and different scenes to make validation and analysis. The results show that the cloud detection is
ideal, especially for thin cirrus which is invisible in the visible band. This technique can promote the use of
MODIS data and improve the accuracy of retrieving.
Detection and removal of cloud and haze are arduous problems in optical remote sensing imagery
processing. Thick cloud and haze have the character of high reflection, so we can set the threshold to detect and
remove the areas having extremely high reflection and even mosaic the images with near dates’ ones to create clear
and cloudless images. Relatively, areas covered by thin cloud and haze have the spectral characteristics of both
surface features and cloud and haze, thus making it difficult to separate them. Consequently, the authors first
processed the images with relative radiometric normalization and then transformed the images from the RGB to the HIS
color model. The assumption was that the interference of thin cloud and haze, similar to mixing a color pigment with
white, would increase the color intensity and decrease the saturation of an image but would not change its hue
value. Guided by this assumption, the authors processed the multi-temporal images and isolated areas contaminated by
thin cloud and haze. The results suggest that it is possible for an automatic method based on the HIS color model to
detect thin cloud and haze on satellite images.
In this paper, Beijing was chosen as a representative study area, and the method of pixel information decomposition was taken on the land part. The land cover percentage was extracted. LAI was calculated according to the research on the cover of plant. Based on characteristics of multi-reflecting light, the authors obtained the reflectance of the soil by using the Bi-directional Reflectance Model of Canopy and Soil and taking only one reflectance into account. According to the roughness factor, the soil water content could be calculated based on the relationship between soil reflaction and LAI.
Based on performing various sorts of image processing on the original 9 bands of ASTER sensors, the authors objectively adopted the quantitative indicator of average separability to determine the optimal combinations of features most suitable for classification. In conjunction with the signature or prototype data for each class, the maximum likelihood classifier, BP neural network classifier and decision tree classifier based on data mining software of See 5.0 were respectively implemented to characterize the spatial distribution patterns of major land cover types over the entire study area. The final classification results based on field validation with 379 actual observations show that the decision tree algorithm possesses the best performance of extraction, with an overall accuracy of 84.4% and a kappa coefficient of 0.822, followed by the BP network algorithm, and that the maximum likelihood classifier has the worst performance of classification. In comparison with the traditional establishment and classification procedures which have been embedded into ENVI 4.1 and ERDAS 8.7, the automated decision tree algorithm used in this study is based on See 5.0 and Cart module (Classification and Regression tree). Due to its objectivity, high efficiency, reliability and high accuracy, the automated decision tree deserves more attention in future practice of classification.
It is difficult for remote sensing change detection based only on spectral information to obtain satisfactory results. In this paper, multiscale texture information combined with spectral information was adopted to evaluate the urban expansion detection by using the post-classification comparison technique. The results show that, if the scale for texture extraction and the data combination are appropriately selected, the addition of texture features in change detection can significantly improve the overall accuracy and Kappa coefficient in comparison with the method based only on spectral data. Moreover, the combination of multiscale texture and spectral data in change detection can produce the highest accuracy. However, it is shown that false alarm may appear on the edges of some land cover types when the texture information is incorporated in urban area change detection.
The bleach of red beds above the oil and gas reservoirs caused by the hydrocarbon microseepage is one of the usual indicators in indirect search for oil and gas by remote sensing technology. Therefore, the mapping of ferriferous minerals and the information extraction of iron anomalies play an important role in oil and gas remote sensing exploration. As a new generation of the multispectral image, the spectral resolution of ALI (Advanced Land Imager) has a great improvement compared with the ETM+ imagery. ALI has six bands in the 0.4~1.0μm wavelength region and can represent special spectral characteristics of ferriferous minerals in the 0.4~1.0μm region, so it can be used for the mapping of ferriferous minerals and the information extraction of iron anomalies. In this paper, the three-lake region of Qaidam basin was chosen as the study area, in which gas reservoirs are developed. An ALI image and the spectral angle mapping (SAM) method were used to map the distribution of ferriferous minerals, with a good result obtained. Based on the mapping result, the paper has discussed the spatial relationship of the ferriferous minerals to gas anomaly and gas distribution.
The measurement of GIS Exploratory Spatial Data Analysis in the land price distribution information extraction was study in this paper. As it is very difficult to satisfy the two premises in the traditional statistics for land price samples, other methods should be sought for. The Exploratory Spatial Data Analysis (ESDA) has been set up on the mathematic basis, which has some spatial methods for land price distribution. Besides, a few samples should be needed and the spatial relationship has been considered. It can therefore be used to study the land price distribution. The actuality research of ESDA was expounded in a case of urban commercial land price by GIS Arc / Info 8.0 in this paper. First, its mathematic basis was described. Then the measurements of GIS Exploratory spatial Data Analysis were studied, which included the data structure research, full trend analysis, searching direction and so on. In the end, the GIS Exploratory Spatial Data Analysis measurement was investigated with the Kriging Analysis as an example. The error analysis indicates that, if the frequency distribution of the samples assumes Normal Q-Q Plots and the measurements are used properly, the result is acceptable.
Xishuangbanna is one of the largest tropical forest vegetation and highest biodiversity regions and also an important rubber-producing area in China. This paper has studied the impacts of rubber plantation on the fragmentation of tropical forests and its substitution for natural forests. It is concluded that the rubber plantation in Xishuangbanna shows significant geophysical patterns and high spatial and temporal dynamics. Rubber plantation has had no significant impacts on soil erosion but has evidently accelerated fragmentation, resulting in the homogeneity of landscape. Although rubber plantation has social and economic benefit in a certain degree, it has obviously threatened the biodiversity and stability of the tropical forest ecosystem.
Soil erosion is one of the important environment problems,and land use classification is an important process in this aspect. The normal automatic classification (supervised classification and unsupervised classification) based on spectral characteristics cannot meet the accuracy needed. Therefore, the slope (produced by DEM) which affects the land use type location and the NDVI (produced by TM images) which reflects the vegetation coverage sensitivity should be taken into account. With Yanhe basin as the study area, the authors carried out the research on methods for extracting the land use information in complicated areas on the loess plateau. The result indicates that the division of the image into several parts according to the TM image characteristics and the extraction of the land use type one by one assisted by the slope are suitable for the complicated terrain area. The result obtained serves as an important reference to the remote sensing classification technical system.
Orchard is an important agricultural industry in Jiaodong peninsular. The prompt and effective
extraction of the orchard information is of great significance in guiding fruit production and local planning. In
this paper, the authors investigated the orchard information extraction model from the SPOT-5 image based on sub-
region and hierarchical theory by using texture information, spectral information and spatial information.
Experiments show that the model formulated by the authors can work efficiently.
Based on collecting and analyzing geographic, geologic and hydrologic data and supported by
corresponding digital image process software, the authors used multi-time satellite data and aerial photographs to
analyze and investigate the Caowei River. The cause of Dieshui in Caowei River channel was studied in the light of
geology and water dynamics. The development trend of the Caowei River is predicted, which can be used as the
reference data for the dredging of the channel of the Caowei River.
In the past thirty years, the coastwise change has been very obvious in the lower reaches of the
Beijiang River. With the development of economy, the riverway environment has changed tempestuously, but the mastery
of the change regularity is very difficult on the basis of traditional measures. With the advantages of macroscopic,
dynamic and systematic researches, the RS technology can be used to study the characteristics of riverway evolution
form the view of spanning a historical period of time. Using MSS and TM as the data source including 7 periods in
the past thirty years and the 1︰50000 topographic map, the authors studied the flux of the riverside, the evolution
of the bottomland and riverway by using 3S and on the basis of RS recognition symbols and characteristics of the
image. According to the 3S analysis of the data available between 1975 and 2002, the riverway experienced an obvious
evolutionary process, the bank and bottomland changed distinctly, and part of the area was filled up. According to
the characteristics of the transverse evolution of the riverway relative to the longitudinal evolution in this
period,it is concluded that the longitudinal distortion of the riverway affected the transverse distortion, i.e.,
there exists an inverse variation relationship between the transverse distortion and the longitudinal distortion.
The development trend of the riverway seems to become increasingly steady.
Remote sensing of water pollution has constituted an important research field in recent years. This
paper intends to analyze water pollution of the Aksu-Tarim River section using TM data. A model has been established
between the DN values of TM images and the ground water pollution data obtained from the local water monitoring
agency along four cross sections of the river. The results indicate that there exists a good correlation between the
DN values and the ground data, suggesting that the model is applicable for the estimation of water quality in the
river. Using the model, the authors tried to re-build the water quality variation curves of the river from the
available TM images. This study provides another example for the argument that remote sensing is a powerful
technique for water pollution monitoring. It is highly possible for remote sensing to assess water quality in a
river system when high-quality spatial and temporal remote sensing data required are available.
The remote sensing images are usually imported directly into the professional relational database.
Nevertheless, for the large data size of images, the time consuming on reading and transmission would be
unendurable, which adversely affects the user-friendly function. Starting with a different angle, the authors
transform the remote sensing image into the user-defined file which can be handled by the operation system. Metadata
information of images can be extracted and stored into the relational database, with each metadata item
corresponding to a user-defined file. In this way, the importing and exporting of mass remote sensing data can be
greatly speeded up, and the metadata information can be consulted quickly and conveniently.