Paper
29 December 2008 Study on optimization of land use structure based on RS and ecological green equivalent
Jiqiang Niu, Yaolin Liu, Feng Xu, Lijun Wei
Author Affiliations +
Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72854P (2008) https://doi.org/10.1117/12.815976
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
Abstract
The optimization of land use structure is always considered as the quantitative optimization. Moreover, it's the optimization of spatial allocation and different scales. This paper obtains the spatial elements of land use by use the remote sensing technology. The optimization model and convolution algorithm of optimization is proposed based on remote sensing and ecological green equivalent. We can use these model and algorithm to optimize the data of land use structure from multi-scales for every region which do not rely on the administrative boundaries, and they are evaluated by the image data of Huangpi which obtain from landsat7 in 2005.The result indicates that the method can be applied to optimize the land use structure for actual land use planning. They can realize the multi-scales land use structure optimization for each region by dynamic control based on the RS and the ecological green equivalent. The reasonable and accuracy is improved in land use planning.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiqiang Niu, Yaolin Liu, Feng Xu, and Lijun Wei "Study on optimization of land use structure based on RS and ecological green equivalent", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854P (29 December 2008); https://doi.org/10.1117/12.815976
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Optimization (mathematics)

Remote sensing

Data modeling

Ecology

Vegetation

Convolution

Earth observing sensors

Back to Top