Adopting Land Cover Standards for Sustainable Development in Ghana: Challenges and Opportunities

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F25%3A103137" target="_blank" >RIV/60460709:41320/25:103137 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2073-445X/14/3/550" target="_blank" >https://www.mdpi.com/2073-445X/14/3/550</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/land14030550" target="_blank" >10.3390/land14030550</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Adopting Land Cover Standards for Sustainable Development in Ghana: Challenges and Opportunities

Popis výsledku v původním jazyce

The adoption of land cover standards is essential for resolving inconsistencies in global, regional, and national land cover datasets. This study examines the challenges associated with integrating existing datasets, including variations in land cover class definitions, classification methodologies, limited interoperability, and reduced comparability across scales. Focusing on Ghana as a case study, this research aims to develop a land cover legend and land cover map aligned with International Organization for Standardization (ISO) 19144-2 standards, evaluate the effectiveness of improving land cover classification and accuracy of data, and finally, assess the challenges and opportunities for the adoption of land cover standards. This study uses a multi-sensor remote sensing approach, integrating Sentinel-1 and Sentinel-2 optical imagery with ancillary data (elevation, slope, and aspect), to produce a national land cover dataset for 2023. Using the random forest (RF) algorithm, the land cover map was developed based on a land cover legend derived from the West African land cover reference system (WALCRS). The study also collaborates with national and international organizations to ensure the dataset meets global reporting standards for Sustainable Development Goals (SDGs), including those for land degradation neutrality. Using a survey form, stakeholders in the land cover domain were engaged globally (world), regionally (Africa), and nationally (Ghana), to assess the challenges to and opportunities for the adoption of land cover standards. The key findings reveal a diverse range of land cover types across Ghana, with cultivated rainfed areas (28.3%), closed/open forest areas (19.6%), and savanna areas (15.9%) being the most dominant classes. The classification achieved an overall accuracy of 90%, showing the robustness of the RF model for land cover mapping in a heterogeneous landscape such as Ghana. This study identified a limited familiarity with land cover standards, lack of documentation, cost implication, and complexity of standards as challenges to the adoption of land cover standards. Despite the challenges, this study highlights opportunities for adopting land cover standards, including improved data accuracy, support for decision-making, and enhanced capacity for monitoring sustainable land cover changes. The findings highlight the importance of integrating land cover standards to meet international reporting requirements and contribute to effective environmental monitoring and sustainable development initiatives

Název v anglickém jazyce

Adopting Land Cover Standards for Sustainable Development in Ghana: Challenges and Opportunities

Popis výsledku anglicky

The adoption of land cover standards is essential for resolving inconsistencies in global, regional, and national land cover datasets. This study examines the challenges associated with integrating existing datasets, including variations in land cover class definitions, classification methodologies, limited interoperability, and reduced comparability across scales. Focusing on Ghana as a case study, this research aims to develop a land cover legend and land cover map aligned with International Organization for Standardization (ISO) 19144-2 standards, evaluate the effectiveness of improving land cover classification and accuracy of data, and finally, assess the challenges and opportunities for the adoption of land cover standards. This study uses a multi-sensor remote sensing approach, integrating Sentinel-1 and Sentinel-2 optical imagery with ancillary data (elevation, slope, and aspect), to produce a national land cover dataset for 2023. Using the random forest (RF) algorithm, the land cover map was developed based on a land cover legend derived from the West African land cover reference system (WALCRS). The study also collaborates with national and international organizations to ensure the dataset meets global reporting standards for Sustainable Development Goals (SDGs), including those for land degradation neutrality. Using a survey form, stakeholders in the land cover domain were engaged globally (world), regionally (Africa), and nationally (Ghana), to assess the challenges to and opportunities for the adoption of land cover standards. The key findings reveal a diverse range of land cover types across Ghana, with cultivated rainfed areas (28.3%), closed/open forest areas (19.6%), and savanna areas (15.9%) being the most dominant classes. The classification achieved an overall accuracy of 90%, showing the robustness of the RF model for land cover mapping in a heterogeneous landscape such as Ghana. This study identified a limited familiarity with land cover standards, lack of documentation, cost implication, and complexity of standards as challenges to the adoption of land cover standards. Despite the challenges, this study highlights opportunities for adopting land cover standards, including improved data accuracy, support for decision-making, and enhanced capacity for monitoring sustainable land cover changes. The findings highlight the importance of integrating land cover standards to meet international reporting requirements and contribute to effective environmental monitoring and sustainable development initiatives

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20705 - Remote sensing

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Land

ISSN

2073-445X

e-ISSN

2073-445X

Svazek periodika

14

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

38

Strana od-do

1-38

Kód UT WoS článku

001453192100001

EID výsledku v databázi Scopus

—