遥感

定量遥感尺度效应刍议

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  • 1. 遥感科学国家重点实验室, 北京师范大学, 北京 100875;
    2. 国家海洋信息中心, 天津 300171
李小文,中国科学院院士,中国地理学会会员(S110001110M)。E-mail: lix@bnu.edu.cn

收稿日期: 2013-04-16

  修回日期: 2013-05-30

  网络出版日期: 2013-09-05

基金资助

国家973 项目(2013CB733401)

Prospects on future developments of quantitative remote sensing

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  • 1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of CAS, Beijing 100875, China;
    2. National Marine Data and Information Service, Tianjin 300171, China

Received date: 2013-04-16

  Revised date: 2013-05-30

  Online published: 2013-09-05

Supported by

Foundation National "973" Program, No.2013CB733401

摘要

目前定量遥感在面向国家需求、面向基础研究方面,存在海量遥感数据无法有效利用、定量遥感研究缺乏普适性和系统性、遥感应用难以再上新台阶等主要问题。因此,目前的遥感科学研究需要整合,需要向前迈出一大步。由于地表的异质性,我们如果只停留在演绎普适的机理模型在特定地点作个性化的处理,是不能适合地学的应用和研究的。必须在已有的反演和实验数据的基础上,用归纳的方法,总结出一些规律性的东西。走我国自然地理学"自上而下的演绎方法和自下而上归纳方法的结合"研究"尺度综合"的路子,在解决遥感科学核心问题"尺度效应"方面先搭建一个方法框架,同时建立几个开放的相关平台(如数据,反演,计算机模拟,等等),与有关学科的专家共享。

本文引用格式

李小文, 王祎婷 . 定量遥感尺度效应刍议[J]. 地理学报, 2013 , 68(9) : 1163 -1169 . DOI: 10.11821/dlxb201309001

Abstract

With regard to the national needs and basic research, several critical issues should be addressed in quantitative remote sensing: inefficient use of mass remote sensing data, inadequate universality and systematicness of quantitative remote sensing research, and limits in remote sensing applications. Therefore, Remote Sensing Science (RSS) research subjects need to be integrated with other disciplines in order to advance our understanding of RSS. In the authors' opinion, due to the heterogeneity of the geo-surface, generalization and modeling on the basis of experimental data, as opposed to individual interpretation of a specific location, could be the key for the future research. Combining "a top-down deduction method" with "a bottom-up induction method" in integrative physical geography in China, we want to build a methodological framework to resolve the central issues of RSS, for instance, the "scale effect", and to create several open platforms (such as data, inversion and computer simulation), and to bring together experts from different disciplines.

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