Assessing the effect between green space and net primary productivity of urban forms using remote sensing and structural equation modeling

Chi Chuan Cheng, Su Fen Wang, Jen Wei Hung

Research output: Contribution to conferencePaper

Abstract

This study focuses on applying remote sensing and structural equation modeling (SEM) to assess the effect between green space and net primary productivity (NPP) of urban forms. The study area is Greater Taipei area in Taiwan, which includes two urban forms. One is Taipei City and the other is Taipei metropolitan area (i.e., Taipei City, New Taipei, and Keelung). The research processes include the calculation and selection of landscape indices, the NPP estimation using remote sensing, and the assessment of green space on the NPP between urban forms using the SEM. The results indicate as follows. (1) The green space of Taipei City is 65.44% in 2006 and the annual NPP is 2.09 ton/ha/yr. The effect of green space on the NPP is 0.86 according to the SEM established by six landscape indices, that is, percentage of landscape (PLAND), patch density (PD), largest patch index (LPI), mean Euclidean nearest neighbor distance (ENN_MN), area-weighted mean shape index (SHAPE_AM), mean patch size (AREA_MN). (2) The green space of Taipei metropolitan area is 86.32% in 2006 and the annual NPP is 3.20 ton/ha/yr. The effect of green space on the NPP is 0.93 under the established SEM by six landscape indices [PLAND, PD, LPI, ENN_MN, SHAPE_MN (mean shape index), CONTIG_AM (area-weighted mean contiguity index)]. (3) Assessing the effect between green space and NPP of two urban forms, Taipei metropolitan area is higher than Taipei City although two selected indices are different. From the above result, obviously remote sensing is a timely, economic, effective, and large-scale approach for the NPP estimation. Meanwhile, structural equation modeling is feasible to assess the effect of green space on the NPP between urban forms. The result obtained from this study can be a reference for the sustainable urban planning of Greater Taipei area in Taiwan.

Original languageEnglish
Publication statusPublished - 2017 Jan 1
Event38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017 - New Delhi, India
Duration: 2017 Oct 232017 Oct 27

Other

Other38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017
CountryIndia
CityNew Delhi
Period17-10-2317-10-27

Fingerprint

Remote sensing
Productivity
Urban planning
Economics

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Cheng, C. C., Wang, S. F., & Hung, J. W. (2017). Assessing the effect between green space and net primary productivity of urban forms using remote sensing and structural equation modeling. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.
Cheng, Chi Chuan ; Wang, Su Fen ; Hung, Jen Wei. / Assessing the effect between green space and net primary productivity of urban forms using remote sensing and structural equation modeling. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.
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abstract = "This study focuses on applying remote sensing and structural equation modeling (SEM) to assess the effect between green space and net primary productivity (NPP) of urban forms. The study area is Greater Taipei area in Taiwan, which includes two urban forms. One is Taipei City and the other is Taipei metropolitan area (i.e., Taipei City, New Taipei, and Keelung). The research processes include the calculation and selection of landscape indices, the NPP estimation using remote sensing, and the assessment of green space on the NPP between urban forms using the SEM. The results indicate as follows. (1) The green space of Taipei City is 65.44{\%} in 2006 and the annual NPP is 2.09 ton/ha/yr. The effect of green space on the NPP is 0.86 according to the SEM established by six landscape indices, that is, percentage of landscape (PLAND), patch density (PD), largest patch index (LPI), mean Euclidean nearest neighbor distance (ENN_MN), area-weighted mean shape index (SHAPE_AM), mean patch size (AREA_MN). (2) The green space of Taipei metropolitan area is 86.32{\%} in 2006 and the annual NPP is 3.20 ton/ha/yr. The effect of green space on the NPP is 0.93 under the established SEM by six landscape indices [PLAND, PD, LPI, ENN_MN, SHAPE_MN (mean shape index), CONTIG_AM (area-weighted mean contiguity index)]. (3) Assessing the effect between green space and NPP of two urban forms, Taipei metropolitan area is higher than Taipei City although two selected indices are different. From the above result, obviously remote sensing is a timely, economic, effective, and large-scale approach for the NPP estimation. Meanwhile, structural equation modeling is feasible to assess the effect of green space on the NPP between urban forms. The result obtained from this study can be a reference for the sustainable urban planning of Greater Taipei area in Taiwan.",
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Cheng, CC, Wang, SF & Hung, JW 2017, 'Assessing the effect between green space and net primary productivity of urban forms using remote sensing and structural equation modeling', Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India, 17-10-23 - 17-10-27.

Assessing the effect between green space and net primary productivity of urban forms using remote sensing and structural equation modeling. / Cheng, Chi Chuan; Wang, Su Fen; Hung, Jen Wei.

2017. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.

Research output: Contribution to conferencePaper

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AU - Wang, Su Fen

AU - Hung, Jen Wei

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N2 - This study focuses on applying remote sensing and structural equation modeling (SEM) to assess the effect between green space and net primary productivity (NPP) of urban forms. The study area is Greater Taipei area in Taiwan, which includes two urban forms. One is Taipei City and the other is Taipei metropolitan area (i.e., Taipei City, New Taipei, and Keelung). The research processes include the calculation and selection of landscape indices, the NPP estimation using remote sensing, and the assessment of green space on the NPP between urban forms using the SEM. The results indicate as follows. (1) The green space of Taipei City is 65.44% in 2006 and the annual NPP is 2.09 ton/ha/yr. The effect of green space on the NPP is 0.86 according to the SEM established by six landscape indices, that is, percentage of landscape (PLAND), patch density (PD), largest patch index (LPI), mean Euclidean nearest neighbor distance (ENN_MN), area-weighted mean shape index (SHAPE_AM), mean patch size (AREA_MN). (2) The green space of Taipei metropolitan area is 86.32% in 2006 and the annual NPP is 3.20 ton/ha/yr. The effect of green space on the NPP is 0.93 under the established SEM by six landscape indices [PLAND, PD, LPI, ENN_MN, SHAPE_MN (mean shape index), CONTIG_AM (area-weighted mean contiguity index)]. (3) Assessing the effect between green space and NPP of two urban forms, Taipei metropolitan area is higher than Taipei City although two selected indices are different. From the above result, obviously remote sensing is a timely, economic, effective, and large-scale approach for the NPP estimation. Meanwhile, structural equation modeling is feasible to assess the effect of green space on the NPP between urban forms. The result obtained from this study can be a reference for the sustainable urban planning of Greater Taipei area in Taiwan.

AB - This study focuses on applying remote sensing and structural equation modeling (SEM) to assess the effect between green space and net primary productivity (NPP) of urban forms. The study area is Greater Taipei area in Taiwan, which includes two urban forms. One is Taipei City and the other is Taipei metropolitan area (i.e., Taipei City, New Taipei, and Keelung). The research processes include the calculation and selection of landscape indices, the NPP estimation using remote sensing, and the assessment of green space on the NPP between urban forms using the SEM. The results indicate as follows. (1) The green space of Taipei City is 65.44% in 2006 and the annual NPP is 2.09 ton/ha/yr. The effect of green space on the NPP is 0.86 according to the SEM established by six landscape indices, that is, percentage of landscape (PLAND), patch density (PD), largest patch index (LPI), mean Euclidean nearest neighbor distance (ENN_MN), area-weighted mean shape index (SHAPE_AM), mean patch size (AREA_MN). (2) The green space of Taipei metropolitan area is 86.32% in 2006 and the annual NPP is 3.20 ton/ha/yr. The effect of green space on the NPP is 0.93 under the established SEM by six landscape indices [PLAND, PD, LPI, ENN_MN, SHAPE_MN (mean shape index), CONTIG_AM (area-weighted mean contiguity index)]. (3) Assessing the effect between green space and NPP of two urban forms, Taipei metropolitan area is higher than Taipei City although two selected indices are different. From the above result, obviously remote sensing is a timely, economic, effective, and large-scale approach for the NPP estimation. Meanwhile, structural equation modeling is feasible to assess the effect of green space on the NPP between urban forms. The result obtained from this study can be a reference for the sustainable urban planning of Greater Taipei area in Taiwan.

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Cheng CC, Wang SF, Hung JW. Assessing the effect between green space and net primary productivity of urban forms using remote sensing and structural equation modeling. 2017. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.