The Qinghai-Tibetan Plateau holds over 1000 lakes and accounts for roughly 50 % of the total lake area in China. Lakes on the Tibetan Plateau play critical roles in the water cycle and ecological and environment systems of the Plateau. A better understanding of lake variations on the Tibetan is important for evaluating climate change on Tibetan Plateau under global warming. The remote sensing technique is an efficient tool to analyze the status and variatios of lakes. This study use topographic maps, aerial photographs, Landsat TM images, and compilations of other relevant data to set up one synthesis method using remote sensing, and uses the method to analyze the changes of the Yamzho and Chencuo lakes on the Plateau from 1970 to 2000. The results show using the method to study the lakes variation from 1970 to 2000 is feasible and all the Yamzho and Chencuo lakes shrunk with 6. 78% and 2. 6% from 1970 to 2000,but all the Yamzho and Chencuo lakes expanded with 2. 92% and 0. 78% in the period of 1990～2000.
Forest cover will be changed by natural disaster, deforest and other activities. Remote sensing has the ability to monitor the change of forest cover in large area. However, in order to get the change information of forest cover, the method for getting the change information from remote sensing images is needed. Based on the Algorithm of Global Land Cover Change (LCC) of National Aeronautics and Space Administration (NASA ) by using MODIS data, this paper has studied the method of forest cover change by using MODIS data. Three kinds of monitoring methods (Red-NIR method, Co-occurrence method and Similitude method) have been tested in northeast forest of China in this time. At the same time, their validation has been compared by using the large area forest fires which have taken place in Heilongjiang province in recent year.
High-resolution remote sensing image could provide much detailed information of the surface of the ground. It becomes a hotpot of RS research to use the image analysis methods to fulfill object extraction and update the geography information database. Traditional pixel-level approaches merely utilize the spectral characteristic ignoring the abundant patial information. An object-oriented method is proposed in this paper: firstly the image is processed by segmentation to attain the image objects, then the knowledge is established according to the analysis of the spectral character, geometry character and the spatial relation of the roads in the image, finally the roads could be extracted by making use of the rules
defined in the knowledgebase. We choose the IKONOS image of Nanjing city as experiment data to verify the validity of the proposed method, the experiment result shows that it could obtain better effect compared with the traditional method.
Alteration remote sensing anomaly is a new independent parameter for overall evaluation and location predication for mineral resource. With the ETM+ data in the area with the bare base rock, the technique extract ing alteration remote sensing anomaly composing of minerals containing water grown up;but in the area of cover with vegetation the extracting effect is in explore. In this paper , by principal component analysis of ETM+ data from Xiangshan U field covering with vegetation, the author avoid the influence of vegetation, obtained good alteration RS anomaly containing water minerals, which both in rhyolitic porphyroclastic lava of northwest field and in metamorphic rock of west part of northern field are all the products of the hydrothermal hydronuscoviting and possess important exploring significance.
Adopting technology in remote sensing and landscape ecology , the article took advantage of remote sensing data in different years to access the ecological security in Boao region. Based on the concept of making fully use of image information, the paper compared the classification result of different classification methods in different band combinations and used the better result in landscape analysis.Through computation of landscape indices of six counties, conclusion can be drawn that unused area in the region has decreased corruptly during the period of 1988 to 2000, which indicates the good effects of land use exploitation. The cultivated land area has also shrunk because there has distinct phenomenon of farmland occupied by building . On the other hand, the woodland has increased evidently . As far as the analysis on the landscape level, the landscape fragmentation of the region has been improved while the landscape diversity and the landscape equilibrium has been impaired.
Urbanization process is a major factor of change in Beijing city, and urbanization caused land cover change, which not only brings the prosperity of econom ics, but also leads to pollution and crowd transportation. Based on the long time-series of TM and ETM+ data of Beijing city and a Self Organized Feature Map of Neural network (SOFM ) classification method are developed for processing the TM and ETM+ data. The classification maps present the changes of five kinds of objectives, showing the urban expand dynamic track, in Beijing city from the year 1994 to 2003 on this paper. The urban expand process
of Beijing city in passed decade shows that it centered the old city and surrounded the ring roads. On the support of analyzing of the trend of city expansion, a potential model is adopted that provides a general trend of urban expansion has approached the urban growth evolution. And then the potential index images are shown in the paper, from which we can see that the city expansion potential of Beijing city is increased by degrees from the inner fourth ring road to the sixth ring road, and also show that the transformation from farmlands to built- up areas is themain resource of urbanization. The phenomenon of urbanization in Beijing we has found has been tested on the airspaces of north Beijing. And then we applied the potential
model to predict the urban growth potential from 2003 to 2012. In order to maintain the balance of landuse and referring to the actual situation of spatial structure of Beijing, we propose that the solid city will be suitable for the developmen t of Beijing city.
It has been attached importance to monitoring forest fire based on EOS-MODIS data in the world. How far is the universality of the arithmetic to identify forest fire based on MODIS Data. There still exist smuch demand for validate the arithmetic. Nine forest fires occurred in China is used to validate arithmetic of identifying fire based on MODIS data in this paper. The result shows that the arithmetic is universal mostly. Eight out of nine fires can be detected through the arithmetic based on MODIS data for identifying forest fire . Just low temperature hot spot could be missed sometimes when zone or season changes. Threshold value should be defined through relation among light temperature of fire and mean and standard variance of fire neighborhood,which could avoid missing fire spot. There are two important rules when identifying forest fire by MODIS data as follow. ① Light temperature of forest fire is three times standard deviation above themean from fire pixels and its neighborhood; ②Light temperature of forest fire is near on the band 21 and band 22 ,which is usually characteristic of CH21- CH22< 20 K instead of noise that. Therefore, the rule CH21- CH22< 20 K can be used for distinguish fire from noise. Additional, it is effective to distinguish forest fire from other fires spot by using forest bound data which extracted from MODIS data without cloud before fire date. Finally suggest for improving arithmetic of identifying forest fire based on MODIS data is presented according knowledge acquired.
As to technology and economic cost synthetically, extracting urban vegetation features by vegetation indices from Thematic Mapper (TM ) images is a comparatively good way. Because of the particularity of the urban vegetation and varieties of vegetation indeices (VIs) , Which vegetation index is suitable to discriminate urban vegetation features still remains a p roblem to be solved urgently. This study area is located in Shanghai. We utilize a combination of one-way ANOVA and multiple comparisons approaches to demonstrate the differences and similarities in sensitivity to vegetation conditions of the nine
indices including NDVI, DVI, EVI, GEMI, GNDVI, RDVI, RVI, TGDVI and TNDVI. The analysis results indicate: ①After TM images being managed by VIs, the vegetation information in TM images has really been enhanced. But their potential for discriminating vegetation of different VIs is not the same.Our result shows the performance and validity of discriminating vegetation of VIs is evaluated as follows:GEMI, RDVI, NDVI, GNDVI, RVI, TNDVI, DVI, EVI and TGDVI from excellent to bad. ②VIs can extract vegetation features from TM images basically, however, can’t do well in discriminate the vegetation in detail. In all, VIs can identify grass and farmland except EVI and TGDVI. EVI does better in discriminating grass and woods while GEMI is more suitable to distinguish grass and farmland. On discriminating woods and farmland TNDVI is a better choice. ③VIs can identify neither vegetation nor non-vegetation further. On the whole, it is very difficult for all the vegetation indices to discriminate buildings and roads, specially for TGDVI, DVI and EVI. NDVI, GNDVI, TNDVI and GEMI can extract the water information from TM images well, while other vegetation indices can only separate vegetation from non-vegetation and are not suited to discriminate non-vegetation further.
Cloud microphysical property has great impact on their optical character and the radiation budget of the earth-atmo sphere system. In this paper, the spectrum characteristics of MODIS VIS and NIR/SIR channels are simulated with SBDART radiat ive transfer model, the simulated result shows MODIS VIS channel is sensitive to the optical thickness while NIR/SIR channels are sensitive to the effective radius of cloud. An algorithm is presented for retrieving the optical thickness and effective radius, the database of such channels’ reflectivity is created and used to retrieve. In addition, an instance is presented to approved the rationality of themethod. The theoretical sensitivity study, which is about the distribution of retrieved effective radius changing with the height, demonstrates that retrieving effective radius using different channels represent different particle scale characteristic in different height of the cloud, respectively. For in stance, channel 20 (3. 75 Lm) is sensitive to the particles at the top of cloud and, channel 6 (1. 64 Lm )mainly represent the middle particles’ scale characteristic, and channel 7 (2. 13 Lm ) is sensitive to the particles between channel 20 and channel 6.
Spectral features of various materials are different from each other, so the target can be detected among a group of ones with different materials based on the principle. Usually, the targets with the same features, such as color and shape, can not be detected in the panchromatic images; or the traditional methods cannot give approving results because of the large scale of data and low precision of detection.So, this paper presents a new target detection method for multispectral images and hyperspectral images based on the Principal component analysis ( PCA) and Independent component analysis ( ICA) . The data of multispectral images is firstly processed by PCA method in order to reduce the dimension of original multispectral images and take the redundancies out for getting the main components of images. The disposed data will be processed using the independent component analysis ( ICA ) algorithm, and then the target can be detected from the abstracted spectral features. This paper takes the advantages of PCA method and ICA method, and makes the target detection in multispectral and hyperspectral images quickly. At last , the validity of this method is verified by a test which detects two kinds of leaves ( artificial and real) , using the new method by combining the ICA and PCA.
Physico-geographic regionalization need synthetically analyze multi-aspect factors such as hydrology, meteorology, geology , physiognomy and natural disasters. In the age of digital earth, the traditionally qualitative method on physico-geographic regionalization cannot meet the requirement of informatization with high degree, which need the quantitative analysis based on mass spatial data . So the powerful tools are required to integratedly manage, storage, display , analyze, and simulate the geographical and spatial data. Geographical Information System ( GIS) is the best solution means, which is fully used in the study of the physico-geographic Regionalization of Gansu Provincial Highway. The applications mainly include spatial data acquisition and management and as a result a spatial database is constructed. Kinds of environmental parameters are calculated based on the spatial analysis functions,which is the key of quantitative analysis. The at lasis compiled based GIS and computer technologies. It is an explicit platform to exposit the research result s. A thematic GIS with independent copyright is developed based on object-oriented visual program technology of VB and ComGIS technology of MapObjects. Spatial database, atlas and thematic GIS would promote the application of the research results of the highway' s physico-geographic regionalization in Gansu Province.
Status of giant panda’s habitat relates to its long-term exist ing and breeding. Assessment on Giant panda’s habitat on a large scale will benefit the protection of habitat and planning of nature reserves.In this paper, using GIS and remote sensing (RS) techniques, selecting several factors including elevation,slope, vegetation and bamboo distribution, habitats of giant pandas in Qinling mountain range were evaluated based on exten sive field survey and previous researches. Spatial patterns and protection condition of pandas’ habitat were analyzed and some counter measures on habitat s’ protection were brought forw rd.Results show that: ①giant pandas’ habitats in Qinling mountain range cover an area of about 440 000 ha,80% of which distribute between 1500 and 2400 m. ②The whole habitat are separated in to several parts due to the transportation, rivers and other surrounding developments. ③The current nature reserves and proposed reserves and corridors were connected with each other, forming a protection network for giant pandas in Qinling mountain range. More than 70% of habitats were protected in this network. This research will contribute to the protection of giant pandas’ habitat in this mountain range.
Information extraction from remote sensing data encountered a new challenge while the spatial resolution is increasing quickly. People suppose that the higher the spatial resolution is, the better the result of objects classification is. To prove this guess we use two approaches: pixel-based classification and object-oriented analysis. The former site test shows one class has different precision from various resolution images. Some classes improve their precision with the high resolution but others don’t. Without various resolution image data, how can we acquire the best information with only one image? Object qriented approach offers a good solution with its key technology: multi-scale image segmentation. Object-orien ted image analysis does no t classify single p ixel bu t rather image ob ject s. No t on ly spectral information but also spatial, physical and contextual characteristics of image objects are used for classification. The site resu lt show s that ob ject s have their best scale image levels to class. The precision of object-oriented approach is much higher than those of based-pixel approach. It makes us believe that this process is the best selection for high-resolution image analysis. Two test results have proved that all objects cou ldn’t be extracted well from the same resolution or scale. They need the corresponding resolution images or scale image levels. Multi-scale image analysis is the perfect method.
In order to realize the automatic or semi-automatic registration of SAR images with high resolution and optics images, in this paper, a novel and robust algorithm is proposed. The algorithm contains three main steps. Firstly, speckle filtering is employed on SAR image, and a coarse matching between SAR and optics images is implemented, which simplifies the complication of the whole process. In the second step , image edges are extracted from SAR and optics images, respectively, which treat as the input data for the sub sequent process. Finally, a bridging-mode constraint method based on the edge
texture is used to achieve a fine match. Due to the constraint and correlation between the processing local image region and its neighbor regions, the multi-value problem can be well resolved, which results to the algorithm’s robustness and applicat ion. Domestic Airborne high-resolution SAR data and SPOT 25 PAN data are used for experiments, and the results show the methods proposed in this paper work well in automatic or semi-automatic registration of high-resolution SAR images and optics images, with pixels accuracy.
Strip noise is one of the important factors affecting the quality of the imaginary acquired from space and the further processing on information retrieving from MODIS 1B image. Aiming at the characteristics of strip noise in Band 5 of MODIS 1B image, the cause of strip noise formation was described, and the commonly used methodo logies and principles for destriping imaginaries from several different sensors were systematically compared with discussions focusing mainly on their constraints in operations. In this study, the Fourier Transform Algorithm , the most frequently used methodology for destriping, was experimentally utilized for strip noise removal in MODIS 1B image, and in the light of self-correlation characteristic of MODIS data, a new approach by means of self-correlation in terpolation algorithm for effective removal of strip noise in Band 5 of MODIS image was proposed. Comparison of mean values and standard deviations as well as edge affection obtained from the strip noise removed image by these two methodo logies suggested that self-correlation in terpolat ion algorithm is evidently superior to the traditional Fourier transform algorithm in destriping MODIS 1B products.
In this paper a brief comment on the basic principle, algorithm and advantage/ draw back of monitoring sea ice concentration using remote sensing technique in visible-infrared, passive and active microwave is made. Especially , the NASA team algorithm and its weather filter for monitoring total,first-year and multi-year sea ice concentration in each mixed pixel, which are shown on the remote sensing image by using passive microwave sensors SMMR or SSM/ I, are introduced and discussed in detailed.
The advantage of creating the map and image database all over the world is that it can avoid the long cycle, low efficiency of application and re-use. The foundation of map and image database is the base of rectifying with high efficient and accuracy . It introduces the processing of building the Multi-level and Multi-resolution data base of image and map all over our country in this paper . Some technical including the standard of data source selecting and control points selecting , the model of database creating and managing , the method of database application and sharing , and the foreground of its application is also be talked about .
