Torna ai risultati
Scheda bibliografica · Consultazione e accesso
Artículo de revista

A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series

Chao Chen et al · Elsevier · 2026

Materiale supplementare disponibile
Lettura rapida. Controlla i dati essenziali della risorsa e accedi al contenuto con il pulsante principale. La scheda mostra solo le informazioni necessarie per identificare, citare e aprire l’opera.
Pubblicazione seriale

A beyond GDP approach in times of economic recession. The case of Genuine Progress Indicator (GPI) for Greece during 1995 to 2022

Questa pubblicazione seriale contiene 148 contenuti correlati.

Accesso alla risorsa

Apri il contenuto dall’opzione principale o scegli un’altra fonte disponibile.

DOAJ DOAJ Articles
Entrar por DOAJ
Accesso principale

Materiale supplementare disponibile

El enlace apunta a material asociado, anexos, tablas, datos o página complementaria. No se marca como libro/texto completo.
Apri materiale

Riepilogo

Descripción general del contenido del recurso.

Shoreline resources constitute one of the most critical terrestrial elements, as they play a pivotal role in fluvial-lacustrine monitoring and the sustainable utilization of spatial resources. As the longest and most economically significant river in China, the Yangtze River exhibits several unique geographical attributes, and as such, research on the spatiotemporal evolution and precise spatial delineation of its shoreline is important. Taking into account the complexity of the geographical environment, the study proposed a multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series data. Longitudinal variations, spatial displacement, and interbank disparities between the northern and southern shores of the Yangtze River, China have been quantitatively assessed, supported by a shoreline change rate model was developed using the Digital Shoreline Analysis System. The results demonstrated a high level of accuracy in shoreline spatial positioning, with clearly demarcated land–water boundaries. From 1990 to 2020, the total shoreline length exhibited a net increase from 12,645.02 km to 13,637.42 km. Both the northern and southern shores displayed synchronous elongation trends, peaking in 2010 before subsequent retreat. Linear regression rate and end point rate analyses revealed overall stability in these migration trends but pronounced interbank heterogeneity. The southern shore exhibited significantly greater linear regression and end point rate variability than the northern shore (P < 0.05), indicative of the stronger synergistic impacts from anthropogenic and natural drivers in that area. This study establishes a framework for high-resolution dynamic monitoring of shorelines along large river systems and elucidates the spatial differentiation mechanisms governing the fluvial evolution of shorelines. The findings provide empirical support for optimizing shoreline resource allocation, delineating environmental conservation boundaries, and implementing the “Yangtze River Conservation Strategy,” thereby advancing the capacity of regional sustainable development and spatial governance.

Come citare

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

al, C. C. E. (2026). A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series. https://doi.org/10.1016/j.indic.2026.101153

MLA

al, Chao Chen et. "A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series." 2026. https://doi.org/10.1016/j.indic.2026.101153.

Chicago

al, Chao Chen et. 2026. "A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series.". https://doi.org/10.1016/j.indic.2026.101153.

Harvard

al, C. C. E. 2026, A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series, Elsevier, available at: https://doi.org/10.1016/j.indic.2026.101153 [Accessed 8 Aug. 2026].

Condividi e stampa

Salva la scheda, copia il link permanente o stampala in PDF.

Esporta riferimento

Esporta il record nei formati più comuni per usarlo con un gestore bibliografico.

Dettagli della risorsa

Informazioni bibliografiche utili per verificare che sia il materiale corretto.

Titolo
A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series
Autore / collaboratori
Chao Chen et al
Editore
Elsevier
Anno di pubblicazione
2026
ISSN
2665-9727
ISSN
2665-9727
Lingua
Inglés

Soggetti

Esplora risorse correlate a partire da questi soggetti.

Copiato