Abstract
The development of aquaculture in many parts of the world has led to significant loss or conversion of wetlands. Both radar and optical remote sensing data have been used to map the extent and also development of aquaculture, which is particularly prevalent in tropical regions. Aquaculture systems are particularly distinct because of their distinct geometry. A number of studies have focused on assessing the impacts of aquaculture development on wetland ecosystems, including mangroves.
This is a preview of subscription content, log in via an institution to check access.
References
Biradar C, Xiao X. Quantifying the area and spatial distribution of double- and triple-cropping croplands in India with multi-temporal MODIS imagery in 2005. Int J Remote Sens. 2011;32:367–86.
Chen C, McNairn H. A neural network integrated approach for rice crop monitoring. Int J Remote Sens. 2006;27(7):1367–93.
Inoue Y, Kurosu T, Maeno H, Uratsuka S, Kozu T, Dabrowska Zielinska K, Qi J. Season-long daily measurements of multifrequency (Ka, Ku, X, C, and L) and full-polarizaiton backscatter signatures over paddy rice field and their relationship with biological variables. Remote Sens Environ. 2002;81:194–204.
Le Toan T, Ribbes F, Wang LF, Floury N, Ding KH, Kong JA, Fujita M. Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results. IEEE Geosci Remote Sens. 1997;35:41–56.
Li C, Frolking S, Xiao X, Moore B, Boles S, Qiu J, Huang Y, Salas W, Sass R. Modeling impacts of farming management alternatives on CO2, CH4, and N2O emissions: a case study for water management of rice agriculture in China. Global Biogeochem Cycles 2005;19(3). https://doi.org/10.1029/2004GB002341.
Ribbes F, Le Toan T. Rice parameter retrieval and yield prediction using Radarsat data. Towards digital earth – Proceedings of the International Symposium in Digital Earth, Toulouse, France; 1999.
Sakamoto T, Yokozawa M, Toritani H, Shibayama M, Ishitsuka N, Ohno H. Spatio–temporal distribution of rice phenology and cropping systems in the Mekong Delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Remote Sens Environ. 2008;100:1–16.
Salas W, Boles S, Li C, Yeluripati J, Xiao X, Frolking S, Green P. Mapping and modeling of greenhouse gas emissions from rice paddies with satellite radar observations and the DNDC biogeochemical model. Aquat Conserv Mar Freshwat Ecosyst. 2007;17:319–29.
Torbick N, Salas W, Xiao X, Ingraham P, Fearon M, Biradar C, Zhao D, Liu Y, Li P, Zhao Y. Integrating SAR and optical imagery for regional mapping of paddy rice attributes in the Poyang Lake Watershed, China. Can J Remote Sens. 2011;37:17–26.
Wassmann R, Neue HU, Lantin RS, Makarim K, Chareonsilp N, Buendia LV, Rennenberg H. Characterization of methane emissions from rice fields in Asia. II. Differences among irrigated, rainfed, and deepwater rice. Nutr Cycl Agroecosyst. 2000;58:13–22.
Xiao XM, Boles S, Liu JY, Zhuang DF, Frolking S, Li C, Salas W, Moore B. 2005. Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remot Sens Environ. 2005;95:480–92.
Xiao X, Boles S, Frokling S, Li C, Badu J, Salas W, Moore B. Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images. Remot Sens Environ. 2006;100:95–113.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media B.V., part of Springer Nature
About this entry
Cite this entry
Torbick, N., Salas, B., Xiao, X. (2018). Remote Sensing of Anthropogenic Activities: Agricultural Production. In: Finlayson, C.M., et al. The Wetland Book. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9659-3_309
Download citation
DOI: https://doi.org/10.1007/978-90-481-9659-3_309
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-3493-9
Online ISBN: 978-90-481-9659-3
eBook Packages: Biomedical and Life SciencesReference Module Biomedical and Life Sciences