Study of coastal water zone ecosystem health in Zhejiang Province based on remote sensing data and GIS

The coastal ecosystem health assessment is a field of increasing importance.In this paper,a preliminary assessment of ecosystem health in Zhejiang coastal water zone was made,mainly based on remote sensing data and GIS technique.Its spatial and quantitative evaluation was facilitated by the progress of remote sensing and GIS technique development.Firstly,human activities,hydrology and ecosystem problems in the study area were discussed and analyzed.Secondly,from 4 aspects of human stress,physical,chemical and biological responses to anthropogenic activities and natural stress,several indicators such as water transparency（Secchi Disk Depth,SDD）,suspended substance concentration,dissolved inorganic nitrogen,active phosphate,chlorophyll,harmful algae bloom,as well as distribution of sewage,sea lanes and port were employed.Thirdly,the Analytic Hierarchical Process was used for indicator weight calculation,and the ecosystem health criteria were established according to the integrative analysis of national water quality criteria,similar coastal ecosystem health research in other places or data inherent properties.The results indicated that from 2005 to 2007 the coastal water ecosystem health value in Zhejiang Province was unhealthy and needs ecological restoration by human intervention.

Remote Sensing Monitoring of Tobacco Field Based on Phenological Characteristics and Time Series Image―A Case Study of Chengjiang County, Yunnan Province, China

Using three-phase remote sensing images of China-Brazil Earth Resources Satellite 02B (CBERS02B) and Landsat-5 TM, tobacco field was extracted by the analysis of time series image based on the different phenological characteristics between tobacco and other crops. The spectral characteristics of tobacco and corn in luxuriant growth stage are very similar, which makes them difficult to be distinguished using a single-phase remote sensing image. Field film after tobacco seedlings transplanting can be used as significant sign to identify tobacco. Remote sensing interpre- tation map based on the fusion image of TM and CBERS02B's High-Resolution (HR) camera image was used as stan- dard reference material to evaluate the classification accuracy of Spectral Angle Mapper (SAM) and Maximum Like- lihood Classifier (MLC) for time series image based on full samples test method. SAM has higher classification accu- racy and stability than MLC in dealing with time series image. The accuracy and Kappa of tobacco coverage extracted by SAM are 83.4% and 0.692 respectively, which can achieve the accuracy required by tobacco coverage measurement in a large area.

The application of hyperspectral remote sensing to coast environment investigation

Requirements for monitoring the coastal zone environment are first summarized. Then the appli- cation of hyperspectral remote sensing to coast environment investigation is introduced, such as the classification of coast beaches and bottom matter, target recognition, mine detection, oil spill identification and ocean color remote sensing. Finally, what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

RESEARCH ON THE LOCAL CORRECTION MODEL OF ATMOSPHERIC DRY DELAY IN GPS REMOTE SENSING WATER VAPOR

The precision of atmospheric dry delay model is closely correlated with the accuracy of GPS water vapor in the process of GPS (Global Position System) remote sensing. Radiosonde data (from 1996 to 2001) at Qingyuan are used to calculate the exact values of the atmospheric dry delay. Base on these calculations and the surface meteorological parameters, the local year and month correction models of dry delay at the zenith angle of 0° are established by statistical methods. The analysis result shows that the local model works better and is slight more sensitive to altitude angle than universal models and that it is not necessary to build models for each month due to the slight difference between year model and month model. Furthermore, when the altitude angle is less than 75°, the difference between curve path and straight path increases rapidly with altitude angle’s decrease.

Retrieval of canopy biophysical variables from remote sensing data using contextual information

In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data, a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensing images. The developed algorithm was used for inversion of leaf area index (LAI) from Enhanced Thematic Mapper Plus (ETM+) data by combining with optimization method to minimize cost functions. The results show that the distribution of LAI is spatially consistent with the false composition imagery from ETM+ and the accuracy of LAI is significantly improved over the results retrieved by the conventional pixelwise retrieval methods, demonstrating that this method can be reliably used to integrate spatial contextual information for inverting LAI from high-resolution remote sensing images.

Geometric calibration of high-resolution remote sensing sensors

This paper introduces the applications of high-resolution remote sensing imagery and the necessity of geometric calibration for remote sensing sensors considering assurance of the geometric accuracy of remote sensing imagery. Then the paper analyzes the general methodology of geometric calibration. Taking the DMC sensor geometric calibration as an example, the paper discusses the whole calibration procedure. Finally, it gave some concluding remarks on geometric calibration of high-resolution remote sensing sensors.

Atmospheric radiative transfer simulation for at mospheric correction of remote sensing data

The radiance leaving the earth-atmosphere system which can be sensed by a satellite borne radiometer is the sum of radiation emission from the earth surface and each atmospheric level that are transmitted to the top of the atmosphere. The radiation emission from the earth surface and the radiance of each atmospheric level can be separated from the radiance at the top the atmospheric level measured by a satellite borne radiometer. However, it is very difficult to measure the atmospheric radiance, especially the synchronous measurement with the satellite. Thus some atmospheric radiative transfer models have been developed to provide many options for modeling atmospheric radiation transport, such as LOWTRAN, MODTRAN, 6S, FASCODE, LBLRTM, SHARC, and SAMM. Meanwhile, these models can support the detailed detector system design, the optimization and evaluation of satellite mission parameters, and the data processing procedures. As an example, the newly atmospheric radiative transfer models, MODTRAN will be compared with other models after the atmospheric radiative transfer is described. And the atmospheric radiative transfer simulation procedures and their applications to atmospheric transmittance, retrieval of atmospheric elements, and surface parameters, will also be presented.

Some essential questions in remote sensing science and technology

In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas,there are critical research questions.In particular,I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing,removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration,integrating knowledge and remotely sensed data into effective information extraction,and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion,image classification,regression analysis,three dimensional information extraction,shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation? Finally,4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate,hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return,the quality of remotely sensed parameters can be improved.

Human Settlement Evaluation in Mountain Areas Based on Remote Sensing,GIS and Ecological Niche Modeling

The Qinghai-Tibet Plateau is the word＇s highest and largest plateau. Due to increasing demands for environment exploration and tourism, a large transitional area is required for altitude adaptation. Hehuang valley, which locates in the transition zone between the Loess Plateau and the Qinghai-Tibet Plateau, has convenient transportation and relatively low elevation. Our question is whether the geographic conditions here are appropriate for adapted stay before going into the Qinghai-Tibet Plateau. Therefore, in this study, we examined the potential use of ecological niche modeling （ENM） for mapping current and potential distribution patterns of human settlements. We chose the Maximum Entropy Method （Maxent）, an ENM which integrates climate, remote sensing and geographical data, to model distributions and assess land suitability for transition areas. After preprocessing and selection, the correlation between variables and spatial auto- correlation input data were removed and 106 occurrence points and 9 environmental layers were determined as the model inputs. The threshold- independent model performance was reasonable according to lO times model running, with the area under the curve （AUC） values being 0.917± 0.01, and 0.923±0.002 for test data. Cohen＇s kappa coefficient of model performance was 0.848. Results showed that 82.22% of the study extent was not suitable for human settlement. Of the remaining areas, highly suitable areas aceounted for 1.19%, moderately for 5.3% and marginally for 11.28%. These suitable areas totaled 418.79 km2, and 86.25% of the sample data was identified in the different gradient of suitable area.The decisive environmental factors were slope and two climate variables： mean diurnal temperature range and temperature seasonality. Our model showed a good performance in mapping and assessing human settlements. This study provides the first predicted potential habitat distribution map for human settlement in Ledu County, which could also help in land use management.

Remote Sensing Image Deblurring Based on Grid Computation

In general, there is a demand for real-time processing of mass quantity remote sensing images. However, the task is not only data-intensive but also computating-intensive. Distributed processing is a hot topic in remote sensing processing and image deblurring is also one of the most important needs. In order to satisfy the demand for quick proc- essing and deblurring of mass quantity satellite images, we developed a distributed, grid computation-based platform as well as a corresponding middleware for grid computation. Both a constrained power spectrum equalization algorithm and effective block processing measures, which can avoid boundary effect, were applied during the processing. The re- sult is satisfactory since computation efficiency and visual effect were greatly improved. It can be concluded that the technology of spatial information grids is effective for mass quantity remote sensing image processing.

Edge Enhancement for Remote Sensing Image Using Norm Algorithm in L_2 Vector Space

The Householder transformation-norm structure function in L2 vector space of linear algebra is introduced, and the edge enhancement for remote sensing images is realized. The experiment result is compared with traditional Laplacian and Sobel edge enhancements and it shows that the effect of the new method is better than that of the traditional algorithms.

Land Degradation Evaluation in North Hebei Province Based on Remote Sensing and GIS

Land degradation is one of the serious environmental problems that can lead to poverty, and is especially prominent in eco-fragile areas in developing countries and increases the risk of environmental safety. North Hebei Province belongs to an ecologically fragile region in North China, which has great impact on the eco-safety of Beijing and Tianjin. Using Landsat TM data and GIS, this paper evaluates land degradation in North Hebei province of China from the the 1960′s to 1987 and 2000. Land use/cover change pattern from 1987 to 2000, its regional difference and forest change characteristics will also be analyzed; soil erosion intensity and arable land suitability were also evaluated. Results revealed that land use/cover pattern in this study area did not change greatly from 1987 to 2000. The structure and function of regional land ecosystem was at a level of local improvement and integral deterioration. Land above medium soil erosion intensity reached 21 percent, which was also the area with a serious soil erosion and land degradation problem. Soil erosion and land degradation intensity of grassland was the biggest. For the present arable land, the proportion of high suitability was 13 percent.

Remote Sensing Archeology in China

China is a country noted for its vast territory and time-honored civilization.Cultural sites can be found across the country,including the famous Silk Road,which was started in the 2nd century BC and served as terrestrial and maritime outlets for the cultural exchanges between China and the rest of the world.

Spatial patterns and driving forces of land use change in China during the early 21st century

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science （LCS） in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km × 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21 st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the ＂Grain for Green＂ policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of ＂Western Development＂, ＂Revitalization of Northeast＂, coupled with rapidly economic development during this period.

Spatial-temporal changes of Tianjin urban spatial morphology from 1978 to 2004

Taken fractal dimension, compact ratio, urban centroid and urban principal axis as the urban spatial characteristic indices, Tianjin city＇s urban area is investigated in the last 26 years in a quantitative perspective, and its traits and changes during different periods are also analyzed. It is clear that these indices can not only scientifically and explicitly assess the urban morphology, urban direction and its changes and trends, but also uncover long-term effects of economy and urban planning on urban morphology.

Assessing Reclamation Levels of Coastal Saline Lands with Integrated Stepwise Discriminant Analysis and Laboratory Hyperspectral Data

At different times over the past 30 years in Zhejiang Province, China, the coastal tidelands have been successively enclosed and reclaimed for agricultural land use. The purpose of this work was to evaluate whether laboratory hyperspectral data might be used to estimate the physicochemical characteristics of these reclaimed saline soils. A coastal region of Shangyu City (Zhejiang Province), which was grouped into four subzones according to reclamation history, was used as the study area, and soil samples were collected in each subzone. Physicochemical analyses showed that the soils were characterized by high electrical conductivity and sand content with low organic matter; the longer the saline lands had been reclaimed, the lower were the electrical conductivity and sand content and the higher the organic matter content. These changing trends of soil chemical and physical properties were found in laboratory reflectance spectra of soil samples and their first-order derivative curves. Stepwise discriminant analysis (SDA) identified six salient spectral bands at 488, 530, 670, 880, 1400, and 1900 nm. Using derived discriminant functions for saline lands with different historical years of reclamation, classification revealed an overall accuracy from a self-test of 86.6% and from cross-validation of 89.3%. Therefore, as opposed to time-consuming field investigations, this study suggested that remotely sensed hyperspectral data could serve as a promising measure to assess the reclamation levels of coastal saline lands.

Monitoring Glacier and Supra-glacier Lakes from Space in Mt. Qomolangma Region of the Himalayas on the Tibetan Plateau in China

Because of the large number and remoteness, satellite data, including microwave data and optical imagery, have commonly been used in alpine glaciers surveys. Using remote sensing and Geographical Information System （GIS） techniques, the paper presents the results of a multitemporal satellite glacier extent mapping and glacier changes by glacier sizes in the Mt. Qomolangma region at the northern slopes of the middle Himalayas over the Tibetan Plateau. Glaciers in this region have both retreated and advanced in the past 35 years, with retreat dominating. The glacier retreat area was 3.23 km2 （or o.75 km^2 yr^-1 during 1974 and 1976, 8.68 km^2 （or 0.36 km^2 yr^-1 during 1976 and 1992, 1.44 km^2 （or 0.12 km^2 yr^-1） during 1992-2ooo. 1.14 km^2 （or 0.22 km^2 yr^-1 during 2000-2003, and 0.52 km^2 （or 0.07 km^2 yr^-1 during 2003-2008, respectively. While supra-glacier lakes on the debris-terminus of the Rongbuk Glacier were enlarged dramatically at the same time, from 0.05 km^2 in 1974 increased to 0.71 km^2 in 2008, which was more than 13 times larger in the last 35 years. In addition, glacier changes also showed spatial differences, for example, glacier retreat rate was the fastest at glacier termini between 5400 and 5700 m a.s.l than at other elevations. The result also shows that glaciers in the middle Himalayas retreat almost at a same pace with those in the western Himalayas.

A Spectral Index for Estimating Soil Salinity in the Yellow River Delta Region of China Using EO-1 Hyperion Data

Soil salinization is one of the most common land degradation processes. In this study, spectral measurements of saline soil samples collected from the Yellow River Delta region of China were conducted in laboratory and hyperspectral data were acquired from an EO-1 Hyperion sensor to quantitatively map soil salinity in the region. A soil salinity spectral index (SSI) was constructed from continuum-removed reflectance (CR-reflectance) at 2052 and 2203 nm, to analyze the spectral absorption features of the salt-affected soils. There existed a strong correlation (r = 0.91) between the SSI and soil salt content (SSC). Then, a model for estimation of SSC with SSI was established using univariate regression and validation of the model yielded a root mean square error (RMSE) of 0.986 and an R2 of 0.873. The model was applied to a Hyperion reflectance image on a pixel-by-pixel basis and the resulting quantitative salinity map was validated successfully with RMSE = 1.921 and R2 = 0.627. These suggested that the satellite hyperspectral data had the potential for predicting SSC in a large area.

Vegetation NPP Distribution Based on MODIS Data and CASA Model——A Case Study of Northern Hebei Province

Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.

Improvement of Mono-window Algorithm for Retrieving Land Surface Temperature from HJ-1B Satellite Data

The thermal infrared channel (IRS4) of HJ-1B satellite obtains view zenith angles (VZA) up to ±33°. The view angle should be taken into account when retrieving land surface temperature (LST) from IRS4 data. This study aims at improving the mono-window algorithm for retrieving LST from IRS4 data. Based on atmospheric radiative transfer simulations,a model for correcting the VZA effects on atmospheric transmittance is proposed. In addition,a generalized model for calculating the effective mean atmospheric temperature is developed. Validation with the simulated dataset based on standard atmospheric profiles reveals that the improved mono-window algorithm for IRS4 obtains high accuracy for LST retrieval,with the mean absolute error (MAE) and root mean square error (RMSE) being 1.0 K and 1.1 K,respectively. Numerical experiment with the radiosonde profile acquired in Beijing in winter demonstrates that the improved mono-window algorithm exhibits excellent ability for LST retrieval,with MAE and RMSE being 0.6 K and 0.6 K,respectively. Further application in Qinghai Lake and comparison with the Moderate-Resolution Imaging Spectroradiometer (MODIS) LST product suggest that the improved mono-window algorithm is applicable and feasible in actual conditions.