The Spatial Decision Support System (SDSS), as an emerging field of science and technology, is combined by Geographic Information System (GIS) and decision support system (DSS). Nowadays, more and more attentions have been paid to the technology of SDSS, and the construction of geographic database in SDSS has been a hot-spot for many years. One of the commonly used methods in geographical data management is directly entry spatial and attributes information into the relational database (generally used the Oracle relational database). Metadata plays an important role in process of building and in spatial data management. A case study is introduced. The Beijing Rural Resource Management Geographical Information System (BJRMGIS) is designed for the Beijing Agricultural Research Center,
aiming for rural spatial decision support to facilitate its analysis operations. The paper mainly contains two parts from the viewpoint of database, that is, the design of database metadata table and the function of database maintenance. (1) The frame of metadata. According to report of needs analysis, the data in BJRMGIS are classified into four categories: fundamental data, remotely sensed image data, statistical data and multimedia data. Moreover, the map is a special form of data. (2) The database maintenance functions include three modules, that is, user management, database import and
database management. This paper put forward the metadata-based database management decision support system model, and process from the practical problems to solve the applications. Also, the construction provides a reference for designing of other similar SDSS systems.
There are kinds of methods for ortho-rectification in application of remote sensing, including Collinearity Equation Model, Strict Geometric Model based on Affine Transformation, Improved Polynomial Model, Rational Function Model, Method based on Neural Network, and so on. But there is lack of system comparison between these methods. On the basis of detailing the algorithm of these methods above, advantages and drawbacks about these algorithms are summarized in this paper. Specific emphasis is the mathematical derivation and algorithm of RFM. Two kinds of algorithm based on neural network were taken in application of ortho-rectification. To compare accuracy and effective between the above methods, we also detailed the processing steps and make some experiments. The result shows that: in the condition of the same GCPs distribution, Rational Function Model that can reach sub pixel accuracy is the best of all from the viewpoint of precision, which can be used in practice in spite of its relatively slower speed.
In this paper, we first review the study of urban agriculture, including concept, connotation, characteristic, function and
the region of urban agriculture. Many researches found that urban agriculture is located in urban and peri-urban, but it is
difficult to distinguish urban and peri-urban. Some of these researches use criteria influencing the size and shape of the
peri-urban area, such as the urban influences, official city boundaries, travel time or distance to the centre, it is no clear.
So in our research we extract agricultural land and urban land from Beijing SPOT data by remote sensing technology,
calculate the model window the ratio of urban land use, according to the ratio of urban land to determine urban and
agricultural areas. We evaluated agricultural development level by using Statistical data, we compare the villages or
towns range of higher level of development with remote sensing technology, extract urban agriculture area, and draw the
This paper firstly summarizes the research progress of the spatialization about regional statistic data. It is concerned with
problems arising when a region is divided into different sets of zones for different purposes, and data available for one
set of zones are needed for a different set. The areal interpolation is usually used to solve this problem of statistic data. In
the study, we take Beijing Chao Yang District as study area (source zone), and we successfully apply three methods to
translate the industrial output value from the administrative zones of Chao Yang (source zones) to regular zones of 1km
grid lattice (target zones), including areal weighting; point-in-polygon and raster representation based on zone centroid
locations.It shows that the spatialization result can express the spatial characteristic of socioeconomic assets more
accurately and objectively.