This study assesses surface urban heat island (UHI) and its associated surface physical characteristics using remote sensing approaches.TERRA/MODIS images acquired in 2005 in three different seasons were selected to generate land surface temperature and surface characteristics for the Changsha\|Zhuzhou\|Xiangtan metropolitan area in China.The intensity of urban heat island effects and its seasonal variations were examined.The result showed that UHI effects were significant both in the summer and the spring.Land surface temperatures in the city were 8℃ to 10℃ warmer than those in surrounding rural areas in the spring and the summer seasons.Although UHI effects existed in the winter,they are not as significant.Land surface temperature in the city was 4℃ warmer than that in surrounding rural areas in winter.This study uses normalized difference vegetation index (NDVI) and normalized difference built\|up index (NDBI) as indicators of surface physical characteristics and investigates the relationship between land surface temperature (LST),NDVI,and NDBI.Results from this study indicate that,while the relationship between LST and NDVI changes in different seasons,there is a strong positive linear relationship between NDBI and LST for all seasons.The amount of slope and intercept of linear relationship between NDBI and LST can indicate the magnitude of UHI for different seasons.This finding suggests that NDBI provides an alternative physical indicator for analyzing LST quantitatively over different seasons,and therefore providing a useful way to study UHI effects using remote sensing.
Recently,along with the fast\|developing urban construction,the urban heat effect (UHI) has caught great attention.Using the Landsat TM images which were obtained on 1999,2005 and 2009,the evolution of the urban heat island distribution in Dongying city are analyzed and future tendency of urban heat island are predicted,following the Markov Model in this paper.The result showed that the UHI in Dongying city was obvious and existed steadily,the centers of UHI present to the Xicheng district,Dongcheng district,which are all the densely inhabited district and industrial park gathering,vegetation and water have reduced the role of heat island effect with the developing of urban expanding,the distributing of heat island become wide ,besides the distributing show a small and wide.With the urban pay more attention to environmental governace and urban greening,the trend of Dongying heat island effect has weakened in the next decade,but the speed is slow.
Taking Xuzhou city as the case study area,Land Surface Temperature (LST) was calculated using Landsat TM data,single\|window algorithm and the parameters was obtained through various channels．The decomposition of mixed\|pixel and the relationship between LST and land cover was studied．Based on the Vegetation\|Impervious Surface Area\|Soil (V-I-S) model and spectral unmixing,land cover types were categorized into three components:vegetation,soil and ISA,which have a major impact on urban heat environment.The spatial distribution characteristic of UHI(Urban Heat Island) in the study area and the relationship between Land cover types and various affecting factors were studied quantitatively by using LST and the types of V\|I\|S and direct classification．The research results could be effectively applied for urban residency environmment research and the ecological environment process analysis.
“Beijing-1” is a new type of earth observation satellite which is lunched by China.An Artificial Neural Network (ANN) method for vegetation cover retrieval with “Beijing-1” in Miyun Reservoir basin has been developed in this paper,and then the result was compared with the traditional regression analysis method and the NDVI method for dimidiate pixel model.It demonstrates that for vegetation cover retrieval in mountainous areas,ANN has the advantage of precise simulation of non-linear transmission over traditional methods,especially for case mountainous vegetation information which traditional methods usually fail.
This paper applied the eigenvector\|based decompositions method,and studied the fine classification problem of the polarimetric SAR imagery.Under the analysis of H-Alpha plane,we introduced another characteristic parameter named the mean target power (span) which was presented with all of eigenvalues and pseudo\|probabilities.And a simple method of selecting thresholds to segment the mean target power of the targets was given,and the Radarsat-2 data of Poyang Lake area was used to test the method.After the analysis of classification results,we found that the method firstly considering the mean power information cound provide much more detailed classification than H-Alpha plane classification with only scattering entropy and angle information.
The land cover characteristic is the important parameter of land surface information,which is the essential factor to understand the change temporal-spatial information of land surface.In this paper,the method of classification based on multi\|parameters of land surface was proposed.The data of the experimenter was Landsat ETM+ image of Wuhan.The Vegetation Index of Universal Pattern Decomposition (VIUPD),land surface temperature and the character of texture were carried.According to the method of Decision Tree,the image was classified in the consideration of the spectral and spatial information.The results demonstrated that the method of classification based on multi\|parameters of land surface was superior to traditional Decision tree based on the spectral reflectance and Supported Vector Machine (SVM).The accuracy of classification based on multi\|parameters of land surface was higher than that of the other algorithms.
The paper applied comprehensive classification method to remote sensing image,the methods have tasseled cap transformation,unsupervised classification,supervised classification,post classification processing ,and so on.After processing,land use type of Yellow River Delta were divided into nine types,and saline land were divided into four grades: mild saline land,moderate saline land,severe saline land and barren land.Precision evaluation has proved that the precision of this comprehensive classification method has a great enhancement.
Based on the water reflectance spectra and chlorophyll concentration measured in July,2008,this study was conducted in order to discuss and analyze the correlation between reflectance spectra and chlorophyll concentration of Songhua lake.The results showed that the correlation between the reflectance spectra of each band and the chlorophyll concentration was good and a single\|band model was established with the reflectance of 700 nm.The ratio of reflectance and first derivative reflectance were found to be significantly correlated with the chlorophyll concentration.The geometric characteristics of reflectance spectra at the ridge of 700 nm were also well correlated with the chlorophyll concentration.The estimation model of chlorophyll concentration of Songhua lake was established.
This paper revolves around the internalization of the behavior of protecting or destructing the eco\|environmental,which is the core problem of the mineral resources eco-compensation.Firstly,it illustrates the problem of parameters valuation at the current ecological compensation system.And then it analyses the necessity of database construction of valuation parameters about diggings’ land destruction eco-compensation based on spatial information technology.Finally,technical processes,methods and key technologies of the database construction are reported by practice research.Conclusion of the study shows the solution to the construction of valuation parameters about diggings’ land destruction eco\|compensation based on spatial information technology is feasible and convenient in practice.The implementation of the program will promote the scientific and reasonable pricing,and will play significant role of information supporting for fine management of the diggings’eco-environmental rehabilitation.
In order to present the difference between VSWIes (Vegetation Supply Water Index) retrieved from different remote sensing data,VSWIes abstracted from Landsat TM and EOS MODIS data of Hebei province in North China are calculated and compared.At first,NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) are calculated from the two remote sensing sources respectively.And then VSWIes are retrieved and compared.Finally,the following conclusions are be drawn:① On September 8,2004 in the study region,the difference between TM VSWI and MODIS VSWI is changing from \|0.51 to 0.20,and the negative values are mainly happened in towns,bare fields and water bodies; ② In vegetation cover areas,TM VSWI is often bigger than MODIS VSWI,but the difference is little; ③ The minimum,maximum and average values of the difference between TM VSWI and MODIS VSWI present the same trend: the values are increasing with the increase of vegetation coverage.The conclusions of this paper are helpful for recognizing VSWIes difference between TM and MODIS and can provide important information for fusion of the drought indices extracted from the two different sources.
In this paper GIMMS/NDVI data was utilized to analyze the vegetation cover characteristcs of spatio\|temporal variation and its response to temperature and precipitation change in Northwest China during 1982 to 2006.The results show that: the annual average NDVI has been increased with an rate of 0.5%/10a in Northwestern China,the vegetation cover was significant increased in July,August and October.The vegetation cover was significant increased in Xinjiang Tianshan,Artai Mountains,Gansu Qilian Mountains and the eastern part of Qinghai; and it was declined from Germu to Yushu in Qinghai,most parts of Shaanxi and Talimu Basin,Tulufan,Tahe,Tuoli in Xinjiang.It was positive correlation between vegetation cover and temperature and precipitation inter\|annual changes.However,it was a significant linear relationship between the vegetation cover and the monthly average temperature and precipitation during the years.The relation with high positive correlation between the vegetation cover and the monthly average temperature,but when the average monthly temperature was exceed 20℃ and the NDVI decreased; when the average monthly precipitation was in the 0~100 mm,the NDVI was increased with linear,however,when the average monthly precipitation was more than 100mm,a clear growth trend was no longer exist.
Some alteration mineral information occurs in subpixel for imagery spatial resolution.Detection to this kind geological altered target has low probability.It's better to obtain the target pixels by comparing the spectrums of pixels.Because target detection algorithms are good at exploiting military objectives,these detectors have potential advantage in exploiting geological altered information.This article evaluates the performance of these algorithms applying in exploiting sericite in the test Zone.
Vegetation change is a hot spot of global change research.Using the SPOT VGT NDVI time series data sets,comprehensive utilization of RS and GIS technology,based on trend analysis,HURST index analysis and other methods,the temporal and spatial vegetation cover changes from 1999 to 2007 in Xinjiang were analyzed and the spatial distribution of HURST index and HURST index differences in land\|use types were explored in this paper.The results show that:an increasing trend of vegetation which is not significant in the past decade is detected in Xinjiang.And changes in vegetation cover in most parts of Xinjiang would maintain the current trend.And the time series in local area is anti\|sustainability.While the mean of HURST indices of NDVI time series in various land\|use types is above 0.65,and the HURST indices in desert,Gobi,and bare land are significantly higher than other land cover types,the HURST indices of NDVI time series in the land\|use types affected by human activities are generally low,which sustainability were lower than that of natural or semi\|natural vegetation cover types.
Mangrove forest is an important vegatation type on biodiversity conservation and wetland ecological protection.Acquisition changes on mangrove area timely is an urgent need for protection.In this paper,taking Fujian Zhangjiang Estuary National Nature Reserve as study area,multi-temporal ALOS PALSAR data acquired in 2007 are processed.The temporal change characteristics and depolarization characteristics on L band HH、HV channel are analyzed.On L band HH、HV channel,backscatter information does not change significantly over time,which is similar to local forests,but depolarization ability between mangrove forests and local forests is obviously different.Compared to temporal information,polarization information is more important for mangrove forests extraction.Based on object\|oriented approach classification,we proposed a method for mangrove forests extraction by using HV,HH polarization and their ratio from a mono temporal data.The results show that mangrove can be extracted with high accuracy.
The oil spills can be effectively discriminated through SAR images.This paper is taking use of the characteristic parameters extracted from the ASAR images of south sea and other sea areas of China using the software of marine oil spill radar image monitoring systems,which include the backscatter coefficient of oil film (AVR),the homogeneous level (PMR),gradient value (GRD),the area(A),the complicated level(C),and so on.Based on the statistical regularity of these parameters and other knowledge,this paper will tell readers a method of discriminating oil spills and look\|alikes.And an example is also attached.
Land reclamation evaluation is becoming more and more important with this work carried out widely.In this paper Yiyang Zhongzhou land reclaimed region as an example,selected multi-source multitemporal RS data,extracted vegetation coverage by building model with ERDAS IMAGINE software,the results images have been statistic analysised.The result indicated that vegetation coverage after reclaimed is higher than before.It is concluded that evaluation results in line with the actual situation,the veracious result shows the feasibility of this mean.
Total suspended matter is an important water quality parameter,and it has a bright future for remote sensing to monitor the concentration of TSM.The way to inverse the water quality parameters mainly contains three methods,and the semi\|empirical algorithm is applied in this paper.Based on the in situ spectral and TSM concentration in Shitoukoumen reservoir in June 13th,2008,the back\|scattering coefficient of TSM is calculated.Also,it needs to select some empirical parameters and optimum wavelength (675 nm).And then,regression algorithm is built between the in situ TSM concentration and back\|scattering coefficient with the determination coefficient 0.8327.It is clear that semi-empirical algorithm has more advantages in the inversion precision than empirical one which is based on the remote sensing reflectance,because of the inherent optic parameters involved.Furthermore,it will lead better results in the area which is rich in suspended sediment.
The object-oriented classification method was used to extract land use/land cover information from high spatial resolution remote sensing images,and the results are compared with the traditional information extraction method.It showed that the accuracy was greatly improved,and the method can avoid salt and pepper noise effectively.The classification results are easier to understand and interpretative.Overall precision,Kappa,producer precision,user precision,Hellden precision and Short precision of object-oriented classification are better than that of traditional classification method.The extraction effect of each ground object increased significantly.overall precision increased 21.76% and Kappa coefficient increased 0.2756.These experiments show that the object-oriented method is superior to traditional method in high resolution remote sensing information extraction.
Some noises still exist in standard MODIS NDVI product and need to be screened before further applications.An ideal filter should only remove noisy data,and keep the good data as much as possible.Most previous studies only concerned about the filter's performance in terms of handling noisy data,and neglected filter's capacity to retain the original high\|quality data (fidelity).The present study analyzed three filters included in Timesat 2.3 tools,examined the effect of data quality on the performance of three filter algorithms,both qualitatively and quantitatively.Through comparative analysis,we concluded that Asymmetric Gaussians has the highest fidelity performance of all,followed by Double Logistic algorithm,and Savizky\|Glolay algorithm performance worst.
Spaceborne polarimetric microwave radiometer WindSat can provide the effective measurement for the ocean surface wind vector.The brightness temperatures measured by WindSat need geolocation process.Geolocation is an important part of WindSat data calibration and validation.In this paper,a modified geolocation algorithm of Patt94 is used for WindSat.The evaluation process is presented and the errors are analyzed.By simulating WindSat orbit,possible error sources and their influences are described.Finally,a method for radiometer attitude correction is discussed.
The main method of current forest resources sub-compartment division is adopted drawing division boundary according to the condition of opposite hillside in the field,which existence of human subjectivity and lacks of scientific objectivity in this approach.This paper brings forward the strategy of object--oriented multi-scale segmentation,which takes different segmentation scales according to the feature information of diferent scales.Based on this,the multi-scale segmentation network is established and the layered extraction of the feature information is realized.And then in sub-compartment division of forest resources,experimental results show that the method can greatly improve the accuracy of the sub-compartment division in image-based automatic interpretation.
China’s current series of satellites,such as FY satellites,resources satellites and oceanographic satellites can all achieve a variety of earth observation performance; they had played a very important role in disaster and environmental monitoring.However,in the face of complex and diverse natural disasters and environmental issues,these satellites are difficult to fully meet the requirements of the spatial resolution,temporal resolution and spectral resolution in the disaster and environmental monitoring and prediction,so does the all\|weather requirement.For the small satellites A,B (HJ-1A/B),which work on environment and disaster monitoring and forecasting,the paper makes assessment on data quality of the multi-spectral remote sensing data,then extracts the data features,and is aimed to provide a reference on its use and extension.
Remote sensing image fusion technology is concerned as the ways to obtain the RS data are growing.Aiming at the characteristics of multi-spectral imaging with more spectral information,Low-resolution and Resource-2 panchromatic images with high-resolution,rich texture information,this article,taking the ASTER multi-spectral image and Resources-2 panchromatic image of Dangtu County in Maanshan,Anhui Province as a case,discusses the fusion methods and effects of two kinds of images using three fusion methods based on principal component transformation,wavelet transform as well as principal component transformation combination with wavelet transform respectively,and comparing three fused images.The results show that the method based on principal component transformation combination with wavelet transform owns the best integration effect.It greatly overcomes the shortcoming of the fusion methods based on single transformation,and improves the visual effects and spectral information of the original image to provide more precise data for regional research.
ALOS image data was used to carry out a multi-levels segmentation with a method called FNEA in Definiens Developer 7 solftware and image objects were got.Spectral and spatial values of image objects,as well as relationship of objects among different levels were considered to extract land use and land cover information in the test area located in Honghu City,Hubei Province.Then an object-oriented classification based on single level segmentation and a pixel-based Maximum Likelihood classification were used to compare with it.Results showed that the object-oriented classification based on multi-levels segmentation not only overcame “Pepper and Salt Phenomenon” appeared in the pixel-based Maximum Likelihood classification but also obtained a significant improvement on classification accuracy compared with the other two classification methods.
The principles and methods of remote sensing spectral characteristic parameters including derivative spectrum,red edge parameter,spectrum absorption characteristics and spectrum reflectance characteristics,national and international development of hyperspectral remote sensing and its application in extracting biophysical and biochemical information of vegetation,and the feasibility of vegetation indices application are reviewed.The potentiality of further application of remote sensing technology in extracting vegetation information in order to promote remote sensing was put forward.Remote sensing spectral parameter provides a powerful tool for extracting vegetation biophysical and biochemical information.
The global environmental change research community requires accurate and up-to-date land cover dataset to support ecosystem assessment,biodiversity conservation,climate change and environmental modeling.It is important to establish a scientific standard classification system when we develop land cover datasets,because it can influence the integration and share of data products,as well as the application areas of the products.This paper expounds the progress of land cover classification system made in regional and global scales,as well as FAO land cover classification system.It also pointed out:① There is no unified standard classification system so far,which effects the application of data products and the detection of land cover change;② Mosaic feature is the inherent characteristic of earth surface,we should make great effort to express effectively and quantify feature of mosaic types;③ It's urgent to develop a standard land cover classification system in China which cant only be consistent with global land cover products ,but also reflect the natural environmental condition of China.
