Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China

Landscape character assessment (LCA) can outline the distinctions between landscapes and aid in identifying and preserving a sense of place, with the core result being landscape character (LC) mapping. Despite LCA being popular, challenges, such as a single LC factor structure and its inherent and s...

Full description

Saved in:
Bibliographic Details
Main Authors: Yunong Wu, Yulian Pan, Mengke Li, Yiyuan Sun
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Ecological Indicators
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X25006909
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850082612814544896
author Yunong Wu
Yulian Pan
Mengke Li
Yiyuan Sun
author_facet Yunong Wu
Yulian Pan
Mengke Li
Yiyuan Sun
author_sort Yunong Wu
collection DOAJ
description Landscape character assessment (LCA) can outline the distinctions between landscapes and aid in identifying and preserving a sense of place, with the core result being landscape character (LC) mapping. Despite LCA being popular, challenges, such as a single LC factor structure and its inherent and subjective selection, remain. LC identification methods are constantly being updated; however, limitations by sample size, data type, and lack of object-specificity remain to be addressed. In this study, the traditional LC factor was defined as the part of the factor component based on which the configuration and coordinate factors were introduced to construct the 3C structure of the LC composition. Considering the area along the middle reaches of the Yangtze River, the bottom-up induction method was used to screen the five composition factors and their weight with a greater influence on the rural landscape through CATREG, and obtained 329 types of landscape description units and 382,279 characterized patches through fuzzy superposition. K-prototype clustering with improved weighting and elbow method coding was introduced to determine the optimal K-value for the 106 LC types. Boundary identification and unique segmentation using eCognition yielded 456 LC areas. Using a top-down deductive approach combined with an overall landscape view, the three types and seven LC zones were obtained using large-scale geohydrological name types and categorized by the LC area as a boundary. Three aspects of the LCA identification stage were improved: composition of LC factors, assignment of LC factor weights, and improvement of identification techniques and methods to construct a more comprehensive, accurate, and geographically specific LC identification system.
format Article
id doaj-art-f18597b52d3f48e8a9e28b0f1b5f79f6
institution DOAJ
issn 1470-160X
language English
publishDate 2025-08-01
publisher Elsevier
record_format Article
series Ecological Indicators
spelling doaj-art-f18597b52d3f48e8a9e28b0f1b5f79f62025-08-20T02:44:29ZengElsevierEcological Indicators1470-160X2025-08-0117711376010.1016/j.ecolind.2025.113760Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, ChinaYunong Wu0Yulian Pan1Mengke Li2Yiyuan Sun3Department of Landscape Architecture, College of Horticulture and Landscape Architecture, Southwest University, Chongqing 400715, ChinaDepartment of Landscape Architecture, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, ChinaWuhan Aesthetic Ecological Landscape Planning Research Institute, Wuhan 430056, ChinaDepartment of Landscape Architecture, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, China; Corresponding author at: Huazhong Agricultural University, No.1 Shizishan Street, Hongshan District, Wuhan City, Hubei Province 430070, China.Landscape character assessment (LCA) can outline the distinctions between landscapes and aid in identifying and preserving a sense of place, with the core result being landscape character (LC) mapping. Despite LCA being popular, challenges, such as a single LC factor structure and its inherent and subjective selection, remain. LC identification methods are constantly being updated; however, limitations by sample size, data type, and lack of object-specificity remain to be addressed. In this study, the traditional LC factor was defined as the part of the factor component based on which the configuration and coordinate factors were introduced to construct the 3C structure of the LC composition. Considering the area along the middle reaches of the Yangtze River, the bottom-up induction method was used to screen the five composition factors and their weight with a greater influence on the rural landscape through CATREG, and obtained 329 types of landscape description units and 382,279 characterized patches through fuzzy superposition. K-prototype clustering with improved weighting and elbow method coding was introduced to determine the optimal K-value for the 106 LC types. Boundary identification and unique segmentation using eCognition yielded 456 LC areas. Using a top-down deductive approach combined with an overall landscape view, the three types and seven LC zones were obtained using large-scale geohydrological name types and categorized by the LC area as a boundary. Three aspects of the LCA identification stage were improved: composition of LC factors, assignment of LC factor weights, and improvement of identification techniques and methods to construct a more comprehensive, accurate, and geographically specific LC identification system.http://www.sciencedirect.com/science/article/pii/S1470160X25006909Landscape character factor3C structure of compositionRegional scaleRural landscapeImproved K-prototype
spellingShingle Yunong Wu
Yulian Pan
Mengke Li
Yiyuan Sun
Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China
Ecological Indicators
Landscape character factor
3C structure of composition
Regional scale
Rural landscape
Improved K-prototype
title Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China
title_full Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China
title_fullStr Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China
title_full_unstemmed Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China
title_short Construction of regional rural landscape character identification system: A case of a riverine area along the middle reaches of the Yangtze River, China
title_sort construction of regional rural landscape character identification system a case of a riverine area along the middle reaches of the yangtze river china
topic Landscape character factor
3C structure of composition
Regional scale
Rural landscape
Improved K-prototype
url http://www.sciencedirect.com/science/article/pii/S1470160X25006909
work_keys_str_mv AT yunongwu constructionofregionalrurallandscapecharacteridentificationsystemacaseofariverineareaalongthemiddlereachesoftheyangtzeriverchina
AT yulianpan constructionofregionalrurallandscapecharacteridentificationsystemacaseofariverineareaalongthemiddlereachesoftheyangtzeriverchina
AT mengkeli constructionofregionalrurallandscapecharacteridentificationsystemacaseofariverineareaalongthemiddlereachesoftheyangtzeriverchina
AT yiyuansun constructionofregionalrurallandscapecharacteridentificationsystemacaseofariverineareaalongthemiddlereachesoftheyangtzeriverchina