Photogrammetry and Remote Sensing Development Trend of Photogrammetry and Remote Sensing

As an image-based spatial information science, photogrammetry and remote sensing are the core of geospatial information [1, 2]. Geospatial informatics is a comprehensive science and technology of spatial data collection, measurement, analysis, storage, management, display and application (see figure), which belongs to the category of modern spatial information science and technology. In 2004, the US Department of Labor listed geospatial information technology, nanotechnology and biotechnology as the three most promising technologies, and their development trends are as follows. The development trend of geospatial information acquisition has obvious characteristics of multi-platform, multi-sensor, multi-scale and hyperspectral, high space, high time resolution and integration of space, sky and earth.

With the rapid development of space technology, communication technology and information technology, people will be able to use various sensors such as ultraviolet, visible light, infrared, microwave, synthetic aperture radar, lidar and terahertz to obtain multi-scale target images from various space, adjacent space, aviation and ground platforms, greatly improving their spatial resolution, spectral resolution and time resolution, forming an integrated data acquisition method of photogrammetry and remote sensing, and providing people with more and more image and non-image data.

With the development of the new global satellite navigation and positioning system (GNSS), the positioning system will automatically measure the spatial position and attitude of various sensors with higher accuracy, thus realizing high-precision real-time photogrammetry and remote sensing without ground control. The development trend of geospatial information processing and information extraction is towards quantification, automation and real-time [3]. At present, a prominent problem in the field of photogrammetry and remote sensing is the huge amount of data, insufficient information and difficult to find knowledge. Grid computing and grid technology have brought new opportunities to solve this problem. Therefore, the following problems need to be solved in the grid computing environment [4]: ① Under the unified space-time reference, the spatial positions and postures of various sensors are automatically determined in real time; ② Using the data obtained by various contact and non-contact sensors, the mathematical model and integral of the physical and geometric characteristics of the target are solved.

Solution; ③ Automatic and intelligent methods for grid calculation and information extraction of multi-platform and multi-sensor remote sensing images; ④ Integration and fusion methods of multi-source massive spatial information; ⑤ Automatic change detection and real-time update of spatial information; ⑥ Spatial data cognitive model, data mining from massive spatial database, and finding the knowledge that users need.

To solve the above six problems, it is necessary to make breakthroughs in many aspects, such as time-space benchmark, remote sensing imaging mechanism, pattern recognition, computer vision, data mining, etc., to realize the overall inverse solution of geometric and physical equations, and to realize the quantification, automation and real-time of spatial information processing and information extraction. The development trend of geospatial information management and analysis is information sharing, interoperability and gridding.

From the perspective of grid computing resource sharing and collaborative computing, the current geographic information system has developed from a stand-alone GIS system to a network and mobile geographic information system (Web2GIS and Mobile2GIS), and the next step will be the grid geographic information system (Grid2GIS). Therefore, it is necessary to solve the problems of inconsistent time datum, inconsistent spatial datum, inconsistent data format and semantic inconsistency in geospatial data. Caused by inconsistent spatial datum.

The problem can be solved by global geocentric coordinate system or coordinate transformation; Inconsistent data formats can be solved by interoperable software; It is difficult to solve the problems caused by the inconsistency between tense and semantics. The former needs to solve the real-time updating of spatial data or the establishment of spatio-temporal geographic information system, while the latter needs a semantic grid of spatial information based on ontology to deal with these semantic differences, so as to realize the * * * sharing and interoperability of spatial information under grid technology. With the concept of global information grid put forward, it is imperative to establish a global unified spatial information grid. Therefore, under the framework of global unified geographical coordinates, the world should be divided into grids with different thicknesses according to the unbalanced development of nature and society. The center of the grid is the latitude and longitude coordinates and the global geocentric coordinate system, and each ground object and its attribute characteristics are stored in the grid. This storage method is especially suitable for the spatial statistics and analysis of national social and economic data, which makes the analysis, spatial data mining and decision-making based on spatial data reach a new level. The development trend of the application of geospatial information achievements is the diversification of achievements and the popularization and universality of applications. Future geospatial information products can be vectors or gratings, graphics or images, two-dimensional or three-dimensional, static images or continuous animated video images.

It can be multimedia or streaming media, virtual reality or measurable real-life images, or the integration and integration of the above products.

For a long time, photogrammetry and remote sensing have been mainly used in earth science and environmental science. As an image-based spatial information science, it will continue to be applied to image cities, virtual digital earth and geographical environment, and has great potential in industrial manufacturing, medical diagnosis and cultural heritage protection. If the original image or processed image is released as a product together with their orientation elements and measurement tool software, users can realize their own on-demand measurement and on-demand interpretation under Web2. So as to realize the popularization and popularization of the application of geospatial information achievements.

Geospatial information is widely used in economic construction, national defense construction and government decision-making, and will further create efficient and high-quality service modes, including car navigation, blind navigation, mobile phone graphic image service, smart community service, mobile location service and other location-based public information services. Geospatial information socialization services include real-time services of national resources, environment, disaster investigation and the temporal and spatial distribution and changes of various economic activities, providing temporal and spatial information services for digital cities, digital ports, digital warehouses, digital logistics and distribution, etc. The whole social service of space-time information is pulling.

Geospatial informatics and the fundamental driving force for the industrialization of 3S technology have a market prospect of tens of billions. With the appearance of Google Eart h H, MSN Virt ual Eart h H, the next generation Internet and Web2. 0, a new geographic information era has quietly arrived. The service objects in the new geographic information era include not only professional users, but also ordinary users. In the new geographic information era, professionals and mass users can interact and participate in on-demand services. The service environment is graphics, images and multimedia, and the provision and implementation of services are dynamic. In the new geographic information era, with the fifth product beyond 4D, DMI can be measured [527]. From map to real-life image, it refers to the general name of aerial/aerospace/ground stereo images with absolute orientation elements in the comprehensive integrated management time-space sequence. It is not only intuitive and vivid, but also allows users to browse and measure relative (height, slope, etc.) directly. ), through the corresponding application software, plug-ins and API, in its professional application system, according to the demand analysis, absolute positioning and mining attribute tagging information, while the measurable real-life image with time dimension can form historical search and exploration mining with the support of spatial information grid technology. In the new geographic information era, users of spatial information have the function of active participation. The spatial information system in the new era can be combined with sensor networks to provide updated data in real time, so as to realize real-time and quasi-real-time data update and make geospatial information more vivid.