Assessing intensive urban land use based on remote sensing images and industry survey data

WANG Haiwen; JIA Junqing; LI Beichen; DONG Yongping; HA Sier

doi:10.6046/zrzyyg.2022099

2023 Vol. 35, No. 2

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WANG Haiwen, JIA Junqing, LI Beichen, DONG Yongping, HA Sier. 2023. Assessing intensive urban land use based on remote sensing images and industry survey data. Remote Sensing for Natural Resources, 35(2): 149-156. doi: 10.6046/zrzyyg.2022099

Citation:

WANG Haiwen, JIA Junqing, LI Beichen, DONG Yongping, HA Sier. 2023. Assessing intensive urban land use based on remote sensing images and industry survey data. Remote Sensing for Natural Resources, 35(2): 149-156. doi: 10.6046/zrzyyg.2022099

Assessing intensive urban land use based on remote sensing images and industry survey data

1. School of Geography Science, Inner Mongolia Normal University, Hohhot 010010, China
;2. Inner Mongolia Land and Space Planning Institute, Hohhot 010010, China
;3. Inner Mongolia Autonomous Region Land Use and Renovation Engineering Technology Research Center, Hohhot 010010, China
;4. Xi’an Changlin Fengcao Ecological Technology Co., Ltd., Xi’an 710000, China

Received Date: 21 March 2022

Revised Date: 26 May 2022

Publish Date: 07 July 2023

Abstract

Abstract

To scientifically evaluate the land suitability of urban functional areas and to accurately assess the intensive urban land use (IULU) in Hohhot City, this study built an indicator system by integrating the industry survey data and the features extracted from remote sensing images. Then, it assessed the urban function zoning and the IULU in Hohhot through quantification and integration based on land. The results show that 93.0% of the functional areas share common multivariate quantitative characteristics, indicating suitable functional orientation and land use. Moreover, this study built a high-precision multivariate regression model using remote sensing factors (i.e., the principal components of images and the proportions of the shadow and vegetation areas) and survey data (i.e., carbon stock, building density, and the land prices of residential and commercial functional areas). Then, the floor area ratio was calculated based on the model, thus achieving the quantitative assessment of the IULU. The results of this study show that the assessment of IULU based on remote sensing images and industry survey data is feasible and has value in popularization and applications.
- land resources /
- intensive urban land use /
- remote sensing /
- floor area ratio