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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Autores principales:	Zhaohui Yang, Junwu Bai, Weiwei Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Wetland Remote sensing Knowledge-based raster mapping (KBRM) Point of interest (POI) Mapping and assessment Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/6ebac1bfe4394e008973d6f5a6b5ce36
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id	oai:doaj.org-article:6ebac1bfe4394e008973d6f5a6b5ce36
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spelling	oai:doaj.org-article:6ebac1bfe4394e008973d6f5a6b5ce362021-12-01T04:47:13ZMapping and assessment of wetland conditions by using remote sensing images and POI data1470-160X10.1016/j.ecolind.2021.107485https://doaj.org/article/6ebac1bfe4394e008973d6f5a6b5ce362021-08-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21001503https://doaj.org/toc/1470-160XWetlands 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 managementZhaohui YangJunwu BaiWeiwei ZhangElsevierarticleWetlandRemote sensingKnowledge-based raster mapping (KBRM)Point of interest (POI)Mapping and assessmentEcologyQH540-549.5ENEcological Indicators, Vol 127, Iss , Pp 107485- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Wetland Remote sensing Knowledge-based raster mapping (KBRM) Point of interest (POI) Mapping and assessment Ecology QH540-549.5
spellingShingle	Wetland Remote sensing Knowledge-based raster mapping (KBRM) Point of interest (POI) Mapping and assessment Ecology QH540-549.5 Zhaohui Yang Junwu Bai Weiwei Zhang Mapping and assessment of wetland conditions by using remote sensing images and POI data
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
format	article
author	Zhaohui Yang Junwu Bai Weiwei Zhang
author_facet	Zhaohui Yang Junwu Bai Weiwei Zhang
author_sort	Zhaohui Yang
title	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_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_sort	mapping and assessment of wetland conditions by using remote sensing images and poi data
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6ebac1bfe4394e008973d6f5a6b5ce36
work_keys_str_mv	AT zhaohuiyang mappingandassessmentofwetlandconditionsbyusingremotesensingimagesandpoidata AT junwubai mappingandassessmentofwetlandconditionsbyusingremotesensingimagesandpoidata AT weiweizhang mappingandassessmentofwetlandconditionsbyusingremotesensingimagesandpoidata
_version_	1718405779042598912

Mapping and assessment of wetland conditions by using remote sensing images and POI data

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