Mapping and assessment of wetland conditions by using remote sensing images and POI data
Wetlands are one of the most valuable natural resources on earth and play an important role in preserving biodiversity. However, due to economic development and human disturbances, many wetlands across the world have deteriorated and disappeared over the past several decades. By using remote sensing...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-08-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X21001503 |
| _version_ | 1818742723056762880 |
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| author | Zhaohui Yang Junwu Bai Weiwei Zhang |
| author_facet | Zhaohui Yang Junwu Bai Weiwei Zhang |
| author_sort | Zhaohui Yang |
| collection | DOAJ |
| description | Wetlands are one of the most valuable natural resources on earth and play an important role in preserving biodiversity. However, due to economic development and human disturbances, many wetlands across the world have deteriorated and disappeared over the past several decades. By using remote sensing images and point of interest (POI) data, we proposed a knowledge-based raster mapping (KBRM)-based framework and implemented it in the assessment of wetland ecological conditions in Suzhou, China. Density maps of waterbodies, vegetation covers, imperviousness, roads, and POI values were derived and used as five ecological indicators that can represent the ecological conditions of wetlands. The KBRM approach was used to integrate these indicators into an overall rating and map wetland ecological conditions efficiently. Thus, spatial variations in wetland ecological conditions can be distinguished and represented in detail. Cross validation was conducted with water quality data at 15 field sampling sites. The validation results demonstrated that the overall wetland condition scores generated by our approach and the water quality index (WQI) values calculated from water quality data were strongly correlated. These findings confirm that our framework could be used to effectively map and evaluate spatial variations in wetland ecological conditions and provide more support for policy-making in wetland protection and management |
| first_indexed | 2024-12-18T02:17:03Z |
| format | Article |
| id | doaj.art-6ebac1bfe4394e008973d6f5a6b5ce36 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-12-18T02:17:03Z |
| publishDate | 2021-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-6ebac1bfe4394e008973d6f5a6b5ce362022-12-21T21:24:20ZengElsevierEcological Indicators1470-160X2021-08-01127107485Mapping and assessment of wetland conditions by using remote sensing images and POI dataZhaohui Yang0Junwu Bai1Weiwei Zhang2Corresponding author.; School of Environmental Science & Engineering, Suzhou University of Science and Technology, 99 Xuefu Road, Suzhou 215009, Jiangsu, ChinaSchool of Environmental Science & Engineering, Suzhou University of Science and Technology, 99 Xuefu Road, Suzhou 215009, Jiangsu, ChinaSchool of Environmental Science & Engineering, Suzhou University of Science and Technology, 99 Xuefu Road, Suzhou 215009, Jiangsu, ChinaWetlands are one of the most valuable natural resources on earth and play an important role in preserving biodiversity. However, due to economic development and human disturbances, many wetlands across the world have deteriorated and disappeared over the past several decades. By using remote sensing images and point of interest (POI) data, we proposed a knowledge-based raster mapping (KBRM)-based framework and implemented it in the assessment of wetland ecological conditions in Suzhou, China. Density maps of waterbodies, vegetation covers, imperviousness, roads, and POI values were derived and used as five ecological indicators that can represent the ecological conditions of wetlands. The KBRM approach was used to integrate these indicators into an overall rating and map wetland ecological conditions efficiently. Thus, spatial variations in wetland ecological conditions can be distinguished and represented in detail. Cross validation was conducted with water quality data at 15 field sampling sites. The validation results demonstrated that the overall wetland condition scores generated by our approach and the water quality index (WQI) values calculated from water quality data were strongly correlated. These findings confirm that our framework could be used to effectively map and evaluate spatial variations in wetland ecological conditions and provide more support for policy-making in wetland protection and managementhttp://www.sciencedirect.com/science/article/pii/S1470160X21001503WetlandRemote sensingKnowledge-based raster mapping (KBRM)Point of interest (POI)Mapping and assessment |
| spellingShingle | Zhaohui Yang Junwu Bai Weiwei Zhang Mapping and assessment of wetland conditions by using remote sensing images and POI data Ecological Indicators Wetland Remote sensing Knowledge-based raster mapping (KBRM) Point of interest (POI) Mapping and assessment |
| title | Mapping and assessment of wetland conditions by using remote sensing images and POI data |
| title_full | Mapping and assessment of wetland conditions by using remote sensing images and POI data |
| title_fullStr | Mapping and assessment of wetland conditions by using remote sensing images and POI data |
| title_full_unstemmed | Mapping and assessment of wetland conditions by using remote sensing images and POI data |
| title_short | Mapping and assessment of wetland conditions by using remote sensing images and POI data |
| title_sort | mapping and assessment of wetland conditions by using remote sensing images and poi data |
| topic | Wetland Remote sensing Knowledge-based raster mapping (KBRM) Point of interest (POI) Mapping and assessment |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X21001503 |
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