Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach
Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environment...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-04-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/7/1340 |
| _version_ | 1797539248940777472 |
|---|---|
| author | Shuailong Feng Shuguang Liu Lei Jing Yu Zhu Wende Yan Bingchun Jiang Maochou Liu Weizhi Lu Ying Ning Zhao Wang Qinyuan Li Jingni Jia |
| author_facet | Shuailong Feng Shuguang Liu Lei Jing Yu Zhu Wende Yan Bingchun Jiang Maochou Liu Weizhi Lu Ying Ning Zhao Wang Qinyuan Li Jingni Jia |
| author_sort | Shuailong Feng |
| collection | DOAJ |
| description | Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery. |
| first_indexed | 2024-03-10T12:42:19Z |
| format | Article |
| id | doaj.art-2b158e1c4f664d48aee25713f72cb456 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T12:42:19Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2b158e1c4f664d48aee25713f72cb4562023-11-21T13:44:44ZengMDPI AGRemote Sensing2072-42922021-04-01137134010.3390/rs13071340Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing ApproachShuailong Feng0Shuguang Liu1Lei Jing2Yu Zhu3Wende Yan4Bingchun Jiang5Maochou Liu6Weizhi Lu7Ying Ning8Zhao Wang9Qinyuan Li10Jingni Jia11National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaCollege of Mechanical and Electronic Engineering, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaNational Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology (CSUFT), Changsha 410004, ChinaHighways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.https://www.mdpi.com/2072-4292/13/7/1340highway constructionenvironmental impactsbufferroad-effect distance |
| spellingShingle | Shuailong Feng Shuguang Liu Lei Jing Yu Zhu Wende Yan Bingchun Jiang Maochou Liu Weizhi Lu Ying Ning Zhao Wang Qinyuan Li Jingni Jia Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach Remote Sensing highway construction environmental impacts buffer road-effect distance |
| title | Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach |
| title_full | Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach |
| title_fullStr | Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach |
| title_full_unstemmed | Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach |
| title_short | Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach |
| title_sort | quantification of the environmental impacts of highway construction using remote sensing approach |
| topic | highway construction environmental impacts buffer road-effect distance |
| url | https://www.mdpi.com/2072-4292/13/7/1340 |
| work_keys_str_mv | AT shuailongfeng quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT shuguangliu quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT leijing quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT yuzhu quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT wendeyan quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT bingchunjiang quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT maochouliu quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT weizhilu quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT yingning quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT zhaowang quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT qinyuanli quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach AT jingnijia quantificationoftheenvironmentalimpactsofhighwayconstructionusingremotesensingapproach |