读取SAR数据:一种新的通用阅读器和提出的新标准

L. Pierce
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引用次数: 0

摘要

所有最近的科学SAR数据的格式都或多或少地符合最近制定的ceo标准。如果产生SAR数据的每个组织都严格遵守这个标准,那么一个程序就可以读取所有的数据。然而,每个传感器的数据格式化方式存在微小但显著的差异,这导致需要不同的程序来读取每个传感器的数据,甚至是来自同一传感器的每种格式的数据。这使得大多数用户很难使用数据,因为第一步是将数据读入某种图像处理系统,如ERDAS、PCI、GRASS、KHOROS等。这个问题的解决方案是数据提供商和商业供应商为他们的客户编写磁带阅读器。不幸的是,许多读取器不能读取所有的辅助数据,也不能方便地移植到其他图像处理系统中使用。一种新的通用阅读器已经开发出来,可以解决所有这些问题。它使用简单的文本“格式化”文件来定义要读取的数据:变量名称和类型、文件中的位置和格式。阅读器以一种新的格式写入一个新文件,后面会讲到。一个标准的读取器现在从这个新文件读取,允许用户编写接口代码来将数据(辅助和图像)读取到用户的图像处理系统中。新提议的格式解决了以下问题:(1)每个图像一个文件,每个文件有一个记录长度;(2) ASCII辅助数据:KEYWORD=value;发表评论;(3)通过注释和严格的语法自文档化;(4)自读,使程序能够检查输入文件并生成能读取输入文件中所有数据的代码;(5)添加新参数简单,用户可以使用4中的程序生成新格式的阅读器。这段代码已经写好,现在可以工作了。
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Reading SAR data: a new general reader and a proposed new standard
All recent scientific SAR data is formatted in compliance, more or less, with the CEOS standard developed recently. If this standard were followed meticulously by each organization that produces SAR data, a single program could read all of the data. However, there are small but significant differences in how each sensor's data is formatted and this has led to the need for a different program to read the data for each sensor, and even for each format from the same sensor. This makes using the data difficult for most users, as the first step is to read it in to some kind of image processing system, such as ERDAS, PCI, GRASS, KHOROS, etc. The solution to this problem has been for data providers and commercial vendors to write tape readers for their customers. Unfortunately, many of these readers do not read all the ancillary data and do not allow easy porting for use with other image processing systems. A new general reader has been developed that solves all these problems. It uses simple text "format" files to define the data that is to be read in: variable name and type, location in file, and format. The reader writes a new file in a new format, as described later. A standard reader now reads from this new file, allowing the user to write interface code to read the data (ancillary and image) into the user's image processing system. The new proposed format addresses the following issues: (1) a single file per image, with a single record-length per file; (2) Ancillary data in ASCII: KEYWORD=value; comment; (3) Self-documenting via comments and strict syntax; (4) Self-reading, so that a program can inspect input file and generate code that can read in all data in input file; (5) Addition of new parameters is simple, and users can generate readers for the new format with the program in 4. This code is written and works now.
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期刊介绍: Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively. Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on. Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.
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