From Beauty to Management: Assessment of Coastal Scenery on Nova Scotian Beaches as a Guide for Better Decision Making

Botero, C.M.; Sheehan, L., and Cordero, R., 2024. From beauty to management: Assessment of coastal scenery on Nova Scotian beaches as a guide for a better decision making. In: Phillips, M.R.; Al-Naemi, S., and Duarte, C.M. (eds.), Coastlines under Global Change: Proceedings from the International Coastal Symposium (ICS) 2024 (Doha, Qatar). Journal of Coastal Research, Special Issue No. 113, pp. 21-27. Charlotte (North Carolina), ISSN 0749-0208. Coastal management is an integrated form of decision-making that considers a wide variety of social uses and economic activities on the maremtory. The ecosystems of coastal areas may be classified into three groups: sandy, rocky, and flooded. The Coastal Scenery Evaluation System (CSES) measures the beauty of a defined coastal area based on an assessment of 18 natural and 8 human parameters, which are integrated in a fuzzy logic model to obtain an overall value that represents the level of scenic appeal which then falls into one of five rank-ordered classes. During the summer of 2023, 149 beaches in the province of Nova Scotia, Canada, were assessed using the CSES technique. Sampling occurred over 25 days and involved 6997 kilometers of field trips. The results reveal a coastline dominated by rural (51%; n=76) and village beaches (24%; n=36), with very few urban (1%; n=2) and resort (1%; n=2) beaches. Almost half of the beaches were located within recreational (40%; n=60) and natural (5%; n=7) parks. Access to some beaches in Canada is challenging because they border private lands (beginning above the high-water mark) where the owners can restrict access to the shoreline. In terms of coastal scenery values, almost one-third of beaches were categorized as “high natural” and “natural” (11% Class I and 19% Class II, respectively), 42% were categorized as light and intensive development beaches (32% Class IV and 11% Class V, respectively), and 28% were categorized as medium landscape value (Class III). Based on these results, an additional classification was conducted to identify those beaches that require an ecosystem management approach, those with recreational management requirements, and those with tourism potential. Special attention was devoted to Class III beaches, as they have equal possibilities to be either better preserved and be upgraded to Class II, or to be further developed and be downgraded to Class IV. The research demonstrates the utility of the CSES technique, not only to classify beaches based on their beauty, but also as a coastal management tool to provide insightful information that improves the decision-making process in multiple coastal areas.

Authors

Institutions

Publication Details

Journal
Journal of Coastal Research
Published
2024-12-20
DOI
https://doi.org/10.2112/jcr-si113-005.1
Citations
1
Primary Topic
Coastal and Marine Management
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Beauty to Management: Assessment of Coastal Scenery on Nova Scotian Beaches as a Guide for Better Decision Making

Lorn Sheehan, Camilo M. Botero, Raúl R. Cordero
1 citations
Journal of Coastal Research
Coastal and Marine Management
0.71
article

From Beauty to Management: Assessment of Coastal Scenery on Nova Scotian Beaches as a Guide for Better Decision Making

Lorn Sheehan, Camilo M. Botero, Raúl R. Cordero
article en
1 citations

Abstract

Botero, C.M.; Sheehan, L., and Cordero, R., 2024. From beauty to management: Assessment of coastal scenery on Nova Scotian beaches as a guide for a better decision making. In: Phillips, M.R.; Al-Naemi, S., and Duarte, C.M. (eds.), Coastlines under Global Change: Proceedings from the International Coastal Symposium (ICS) 2024 (Doha, Qatar). Journal of Coastal Research, Special Issue No. 113, pp. 21-27. Charlotte (North Carolina), ISSN 0749-0208. Coastal management is an integrated form of decision-making that considers a wide variety of social uses and economic activities on the maremtory. The ecosystems of coastal areas may be classified into three groups: sandy, rocky, and flooded. The Coastal Scenery Evaluation System (CSES) measures the beauty of a defined coastal area based on an assessment of 18 natural and 8 human parameters, which are integrated in a fuzzy logic model to obtain an overall value that represents the level of scenic appeal which then falls into one of five rank-ordered classes. During the summer of 2023, 149 beaches in the province of Nova Scotia, Canada, were assessed using the CSES technique. Sampling occurred over 25 days and involved 6997 kilometers of field trips. The results reveal a coastline dominated by rural (51%; n=76) and village beaches (24%; n=36), with very few urban (1%; n=2) and resort (1%; n=2) beaches. Almost half of the beaches were located within recreational (40%; n=60) and natural (5%; n=7) parks. Access to some beaches in Canada is challenging because they border private lands (beginning above the high-water mark) where the owners can restrict access to the shoreline. In terms of coastal scenery values, almost one-third of beaches were categorized as “high natural” and “natural” (11% Class I and 19% Class II, respectively), 42% were categorized as light and intensive development beaches (32% Class IV and 11% Class V, respectively), and 28% were categorized as medium landscape value (Class III). Based on these results, an additional classification was conducted to identify those beaches that require an ecosystem management approach, those with recreational management requirements, and those with tourism potential. Special attention was devoted to Class III beaches, as they have equal possibilities to be either better preserved and be upgraded to Class II, or to be further developed and be downgraded to Class IV. The research demonstrates the utility of the CSES technique, not only to classify beaches based on their beauty, but also as a coastal management tool to provide insightful information that improves the decision-making process in multiple coastal areas.

Journal of Coastal ResearchVol. 113(sp1)
Dalhousie University (CA), Sergio Arboleda University (CO)
Life below water
Openalex Percentile: Top 19%
Coastal and Marine Management
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.