Research progress of remote sensing application in land resources

被引：0

作者：

Zhang Z. ^{[1
]}

Wang X. ^{[1
]}

Wen Q. ^{[1
]}

Zhao X. ^{[1
]}

Liu F. ^{[1
]}

Zuo L. ^{[1
]}

Hu S. ^{[1
]}

Xu J. ^{[1
]}

Yi L. ^{[1
]}

Liu B. ^{[1
]}

机构：

[1] Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing

来源：

| 1600年 / Science Press卷 / 20期

关键词：

Application research; Land cover; Land resources; Land use; Remote sensing;

D O I：

10.11834/jrs.20166149

中图分类号：

学科分类号：

摘要：

Remote sensing applied to land resource research has received increasing interest because of the excellent agreement of the temporal and spatial characteristics of remote sensing data and land resources. In the past decades, the development of remote sensing technology has greatly enriched the method and content of geography research. As one of most important directions of geography research, the research on land resources and the environment is carried out using remote sensing techniques. Remote sensing provides voluminous amounts of information and improves the depth of land resource research. With the support of the periodic acquisition of information via remote sensing, data information in land resource research is subjected to dynamic monitoring and updating. Extensive dynamic land resource information, such as quantity, distribution, composition, and type conversion, can be extracted from remote sensing data. Modern process analysis and change prediction for land resources have gradually become research hotpots because of the results of the monitoring of land resource changes. The research directions in relation to the remote sensing of land resources should focus on the following vectors in the future. First, research methods should be innovated to match the application requirements in China. Many research studies in China still focus on tracking, citing, consummating, and verifying the content and method of foreign models. Models suitable for the Chinese environment should be developed in the future. Second, remote sensing applications should be combined effectively with traditional disciplines. Maintaining consistency with traditional research in terms of concepts and connotations, clarifying the relationship of remote sensing parameters and their geoscience implications, and realizing the organic combination of land resource information and remote sensing parameters can improve the applicability and interpretability of research results. Third, the development of remote sensing applications for land resources should meet the requirements of global change research and consider large spatial regions, long time processes, and multiple observation angles. Given the different geographical elements of different regions, the consistency of temporal and spatial cognition should be emphasized against the background of global change research. Finally, applications should promote comprehensive analysis and evaluation to embody the relationship between human beings and land resources. The influence of this relationship on the sustainability and quality of the development process should also be studied. © 2016, Science Press. All right reserved.

引用

页码：1243 / 1258

页数：15

共 87 条

[1] Atkinson P.M., Tatnall A.R.L., Introduction neural networks in remote sensing, International Journal of Remote Sensing, 18, 4, pp. 699-709, (1997)
[2] Bartholome E., Belward A.S., GLC2000: a new approach to global land cover mapping from Earth observation data, International Journal of Remote Sensing, 26, 9, pp. 1959-1977, (2005)
[3] Bicheron P., Huc M., Henry C., Bontemps S., Lacaux J.P., Glob-Cover: Products Description Manual, (2008)
[4] Bischof H., Schneider W., Pinz A.J., Multispectral classification of landsat-images using neural networks, IEEE Transactions on Geoscience and Remote Sensing, 30, 3, pp. 482-490, (1992)
[5] Bontemps S., Defourny P., Bogaert E.V., Arino O., Kalogirou V., Perez J.R., Globcover 2009, Products Description and Validation Report, (2011)
[6] Buhe A., Tsuchiya K., Kaneko M., Ohtaishi N., Halik M., Land cover of oases and forest in XinJiang, China retrieved from ASTER data, Advances in Space Research, 39, 1, pp. 39-45, (2007)
[7] Chen L.D., Wang J., Fu B.J., Qiu Y., Land-use change in a small catchment of northern Loess Plateau, China, Agriculture, Ecosystems and Environment, 86, 2, pp. 163-172, (2001)
[8] Chen S.P., Dictionary of Remote Sensing, (1990)
[9] Chen Y.F., Liu Y.S., Wang J., Yan J.P., Guo X.D., Land use changes of an aeolian-loessial soil area in Northwest China: implications for ecological restoration, Pedosphere, 19, 3, pp. 356-361, (2009)
[10] Chen Z.Y., Remote Sensing Monitoring and Management of Fragile Ecosystems in Adjacent Area of Jin-Shan-Meng, (1994)

← 1 2 3 4 5 6 7 8 9 →