Research on Acquisition Methods of High-Precision DEM for Distributed Hydrological Model

Compared with the traditional lumped hydrological models, distributed hydrological model, considering the effects of the uneven spatial distribution of watershed land surface on the hydrological cycle, has the characteristic of physical mechanism. Seeing from overall structure, there are two types of distributed hydrological model, which are runoff and convergence. The establishment of convergence network is on the basis of calculating reservoir routing convergence, at present, converged networks are constructed on the grounds of DEM, the resolution of DEM directly affects the result of convergence network construction, for now, due to confidentiality rules, it is very difficult to obtain highresolution DEM. With the development of GIS and RS, it is more convenient to acquire data from distributed hydrological model, which has been developing rapidly. SRTM is completed by the National Aeronautics and Space Administration (NASA), National Image Mapping Agency (NIMA) and the German and Italian space agencies. The current publicly available data resolution is 3 arc seconds (1 / 1200 of longitude and latitude), and its length is equivalent to 90 meters. The publication of this data set is an important breakthrough in geographical science and application, which has important application value. However, because of the limitations on using radar technology to obtain surface elevation data, there are many problems in the original SRTM DEM data, such as missing more regional data, existing many abnormal points, and so on. This article, which takes Xue Ye reservoir area as example, studies the methods of processing SRTM data and obtained highresolution DEM data of the region. 1. Problems Proposed Distributed hydrological model are applied widely because it can comprehensively consider variety of factors such as the vegetation of watershed, soil, terrain impact on hydrological processes, and spatial difference existing in these elements can more accurately reflect the factual hydrological movement. DEM (Digital Elevation Model) is the basis for establishing a distributed hydrological model, and we can extract some basic information required on modeling such as river network, slope, aspect and catchment area based on DEM. Extracting accuracy depends on the quality of data and extraction algorithms, in particular the quality of data impacts on the results greatly. If the quality of DEM data itself is not high, then no matter how perfect algorithm is, it is difficult to obtain satisfactory results. Therefore, it is the current problem to be solved acquiring DEM data of higher quality which makes it more practical. Despite of obtaining some higher results on investigating the topographic map, currently, it is still hard for the general user to obtain terrain map data of high precision for various reasons. Although we can obtain High-resolution DEM data in the specific region by using field measurements or other ways, the cost is very high by these ways. In addition, there are a lot of methods and means to access the DEM data for many researchers, however, DEM data sources which we can get are relatively scarce in the actual process of research. For these reasons, it is significant to promote study on distributed hydrological modeling technology and digital hydrology how to gain high-resolution DEM data in large areas relatively easily. In recent years, the development of spatial remote sensing technology provided a golden opportunity for the resolution to this issue, and SRTM (Shuttle Radar Topography Mission) mission generates high-resolution DEM data of most regions of the world by radar interference. The release of data is so important that the hydrological study can make the public acquire DEM data of a resolution of 3 arcseconds for free. 2. SRTM Data Sources and Problems 2.1. SRTM Data Sources SRTM is completed by the National Aeronautics and Space Administration (NASA), National Image Mapping Agency (NIMA) and the German and Italian space agencies, and it gets three dimensional radar data whose data amount is up to 12TB and which covers 80% area of the land surface from 60 ° north latitude to south latitude 56 ° on the surface of the Earth, through global operations of nearly 10 days by the imaging INSAR loaded in the "Endeavour" Space Shuttle, and then generates high-precision DEM of 30m resolution by dealing with received radar signal. SRTM is the world's first high-resolution elevation model, the current available data resolution in public is 3 arc seconds (1 / 1200 of longitude and latitude), and its length is equivalent to 90 meters. The publication of this data set is an important breakthrough in geographical science and application, which also has important application value. Fig.1 Schematic Diagram of SRTM Data Coverage The products of SRTM digital elevation includes DEM data of three different resolutions: The coverage area of SRTM1 only includes the continental United States, and the spatial resolution is 1 arc seconds; The date of SRTM3 covers the whole world, and the spatial solution is 3 arc seconds; The date of SRTM30 also covers the whole world, and the spatial solution is 30 arc seconds. The distribution of SRTM data goes by the agreement between NASA and NIMA, but the full resolution data (spatial resolution of 1 arc sec) outside the United States are controlled by the NIMA, and NASA can only provide the public with the date of a resolution of 3 arc seconds (equivalent to 90m). Obtained SRTM data now include two kinds of quality data, which is "Research" level and "Finished" data. Because of the limitations on using radar technology to obtain surface elevation data, there are many problems in the original SRTM DEM data, such as missing more regional data, existing many abnormal points, and so on, NGA does a certain amount of post processing on the SRTM data produced by JPL to be "Finished" version of the data. In the processing procedure, they have eliminated the data outliers different from the surrounding elevation up to 100m, set the sea level elevation to 0, set the lake elevation to a constant, and treated on the rivers and islands correspondingly, besides, they also have dealt with pixel of data elements on the edge to ensure the accuracy of the data mosaic, and filled non-data area less than 16 consecutive data points through interpolation methods. Compared with the original SRTM data, processed SRTM data has been greatly improved in the data quality, and studies show that the accuracy of terrain elevation fully meets or even exceeds regulatory requirements (vertical accuracy less than 16 m, horizontal accuracy less than 20 meters). Judging from the current study situation, SRTM data have attracted wide attention, and many researchers have successfully applied the SRTM-related research in the field related[1][2], while for the SRTM data they focused on the following two aspects in their research: Firstly, although there are data validation results showing that the SRTM data are of very high precision, for lack of time to acquire data, they still need to do further in-depth study on the SRTM data quality and the influence for analysis results on some practical problems in more of the region, which has been the key issue of study on SRTM data in recent years[3][4][5][6]; secondly, though non-data area less than 16 consecutive data points are filled with interpolation methods in the "Finished" version of the SRTM data, because there is no better processing way for some larger invalid data region, they still remains in data sets, which is undoubtedly a major obstacle in SRTM data applications. How to fill the no-data-area? It is an important research question of studying on the SRTM data, which has aroused the concern of many scholars at home and abroad [7][8][9]. 2.2. Major Problems of SRTM SRTM digital terrain data is the best current situation, highest resolution global digital terrain Data so far. However, there are also several deficiencies of SRTM [10]: (1) There are so many "invalid" area of SRTM. In the waters, high mountains and the gorge, the quality of SRTM-3 data is poor, there are vacant spots and blank areas often in small pieces of data in these areas. In addition, there are many lands of poor confidence level, where are mainly in the larger waters, or in the ups and downs, in the very narrow, deep valleys and marginal area of high mountain areas in the above-mentioned data area. These are mainly because of quality problems caused by the radar echo. According to research, data volume of these areas is 0.23% of total data SRTM-3. The study area of distributed hydrological model have a considerable number of this region, therefore, how to process "invalid" area, is the key issue that SRTM data should be applied in distributed hydrological model and the outcome directly affects the accuracy of hydrological simulation . (2) SRTM-3 data set is a digital surface elevation model (DSM), such as tree tops, roof, etc., instead of a digital elevation model of the ground. So the difference between SRTM-3 in some areas and the actual DTM is often not an accidental error, but a systematic bias related with the characters of ground features in the regions. Therefore, in the dense forest vegetation area and Residential area, DSM of SRTM-3 minus real DTM is positive; while in the snow-covered area, and radar beam of SRTM has a certain ability to penetrate, then DSM of SRTM-3 minus the actual DSM is presented as negative (the other explanation for negative: the real DTM relative to the DSM of SRTM-3, the former was much earlier for the time of getting the elevation data, as global is getting warming and the ice layer is getting melting, the snow height of the SRTM-3 shows as negative growth). In fact, at present, many scholars have carried out substantive research on the second aspect of the problem and have obtained a satisfactory conclusion. For the settlement in "invalid" area, although a number of ways processing these invalid data regions are made [11], the processing methods for the SRTM data applied in distributed hydrological model are relatively small. 3. Methods of Processing Data 3.1. Analysis of Invalid Regional Data To analyze the apply effects of SRTM in distributed hydrological model, the following takes Xue Ye reservoir area in Lai Wu City, Shandong Province and its surrounding areas for example as a test to verify the quality of the SRTM data. Xue Ye reservoir is a large reservoir, with control drainage area of 444 square km, total reservoir storage capacity of 221 million cubic meters, useful storage capacity of 112 million cubic meters, dead reservoir capacity of 2.8 million cubic meters. The position of Xue Ye reservoir is shown in Figure 2. SRTM data adopted as the data of the "Finished" version are downloaded from http://datamirror.csdb.cn/, and corresponding processing are done with the raw data after download by Arc / Info software, we obtain DEM data with a spatial resolution of the 90m, UTM projection of finally. In addition, the resolution of DEM purchased from the center of geographic information in Shandong Province is 25m. The whole study area is 14, and per one is of 742 lines site and 749 columns in total. Fig.2 Schematic Drawing of Xue Ye Reservoir Position Fig.3 The Location of Study Area and SRTM Data, White Areas Indicating Invalid Data Region Fig.4 DEM of 25m Resolution Figure 3 is a schematic diagram of the SRTM data in the study area, in which white patches show the invalid data regions. Statistics show that, because of the characteristics of using radar technology to produce DEM date, the distribution of invalid data area are closely related with terrain, which is mainly in the high mountains of complex terrain, valleys region and the flat region in the large lakes or water bodies [12]. For hydrology studies, there probably is more complex terrain condition in the upstream region of many basins, and thus there are more no-data-regions. The study area belongs to the above situation, with the study area of complex terrain. Seen from Figure 3, the distribution of the invalid region is relatively regular, most of the invalid regions are distributed on the regions of the large gradient, that is, river distribution along the valley leads to channel discontinuity. Obviously for the hydrology study, these no-data-regions cause great inconvenience for practical application of SRTM data, which needs to be processed. Ways to deal with Invalid region will later be introduced in detail, following in the first compares the SRTM data and 25mDEM. From the figures we can see the two kinds of data reflect the same characteristics of terrain, but large differences are still existed between the two on the level of detail for reflecting the terrain. In contrast, Figure 4 appears smoother than the SRTM data, while SRTM data can reflect more topographic details than the DEM data. From the above we can see, SRTM data has a high accuracy itself. Compared with adopted DEM data of 25m resolution, SRTM date can reflect more topographic details, but there are still some systematic errors in the SRTM data for needing more careful analysis and processing. In general, filling methods of the invalid regions of SRTM date is divided into three types: a. Filled with correspondent other high-resolution DEM data directly; b. Filled by spatial interpolation methods; c. filled under other supplementary data sources (such as the global digital elevation model GTOPO30). In contrast, the last two methods are applied in a wide range, however the data used to populate is not "real" elevation values, but calculated by interpolation, so the accuracy is somewhat limited; More accurate results are obtained in the first way, but in practice it is difficult to obtain the correspondent high-resolution data, and ASTER [13] data provides an golden opportunity to solve the problem. 3.2. Data Processed Based on ASTER ASTER (Advanced Space bone Thermal Emission and Reflection Radiometer) is a high-resolution satellite imaging device released cooperatively by NASA and METI, launched carrying EOSAM1 (Terra) platform of NASA in December 1999. Compared with other optical remote sensing system, ASTER has an important characteristic that it can also access images using subsystem of ASTER VNIR, accordingly it can get the three-dimensional relative data of 3N and 3B used to generate the DEM products. The absolute and relative DEM data whose spatial resolution is 30m can be produced by the ASTER stereo relative data, and the production of the absolute DEM data need GCP (Ground Control Point), while the production of the relative DEM data don’t need GCP. In practical application process, the users can produce their own DEM data using ASTER data and related software directly, and they can also present the production request of ASTER DEM or download archived DEM data through requested System of the NASA (http://edcimswww.cr.usgs.gov/pub/imswelcome). As the production of absolute DEM data needs users provide considerable numbers of ground control points data, while control data is relatively difficult to be available, ASTER DEM data available for download are is a relative DEM data in the majority so far. The following discusses the method of filling SRTM invalid region data with ASTER relative DEM data.