Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea

North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed...
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Autor*in:	Yong Piao [verfasserIn] Seunggyu Jeong [verfasserIn] Sangjin Park [verfasserIn] Dongkun Lee [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	forest change trend terrace field North Korea random forest (RF) Google Earth Engine (GEE)

Übergeordnetes Werk:	In: Remote Sensing - MDPI AG, 2009, 13(2021), 17, p 3501
Übergeordnetes Werk:	volume:13 ; year:2021 ; number:17, p 3501

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/rs13173501

Katalog-ID:	DOAJ018540651

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author	Yong Piao
spellingShingle	Yong Piao misc forest change trend misc terrace field misc North Korea misc random forest (RF) misc Google Earth Engine (GEE) misc Science misc Q Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea
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topic_title	Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea forest change trend terrace field North Korea random forest (RF) Google Earth Engine (GEE)
topic	misc forest change trend misc terrace field misc North Korea misc random forest (RF) misc Google Earth Engine (GEE) misc Science misc Q
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title	Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea
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title_sort	analysis of land use and land cover change using time-series data and random forest in north korea
title_auth	Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea
abstract	North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed and analyzed a time-series land use land cover (LULC) map to identify the LULC changes (LULCCs) over extensive periods across North Korea and understand the forest change trends. The analysis of LULC used Landsat multi-temporal image and Random Forest algorithm on Google Earth Engine(GEE) from 2001 to 2018 in North Korea. Through the LULCC detection technique and consideration of the cropland change relation with elevation, the forest change in North Korea for 2001–2018 was evaluated. We extended the existing sampling methodology and obtained a higher overall accuracy (98.2% ± 1.6%), with corresponding kappa coefficients (0.959 ± 0.037), and improved the classification accuracy in cropland and forest cover. Through the change detection and spatial analysis, our research shows that the forests in the southern and central regions of North Korea are undergoing restoration. The sampling method we extended in this study can effectively and reliably monitoring the change trend of North Korea forests. It also provides an important reference for the regional environmental management and ecological security in North Korea.
abstractGer	North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed and analyzed a time-series land use land cover (LULC) map to identify the LULC changes (LULCCs) over extensive periods across North Korea and understand the forest change trends. The analysis of LULC used Landsat multi-temporal image and Random Forest algorithm on Google Earth Engine(GEE) from 2001 to 2018 in North Korea. Through the LULCC detection technique and consideration of the cropland change relation with elevation, the forest change in North Korea for 2001–2018 was evaluated. We extended the existing sampling methodology and obtained a higher overall accuracy (98.2% ± 1.6%), with corresponding kappa coefficients (0.959 ± 0.037), and improved the classification accuracy in cropland and forest cover. Through the change detection and spatial analysis, our research shows that the forests in the southern and central regions of North Korea are undergoing restoration. The sampling method we extended in this study can effectively and reliably monitoring the change trend of North Korea forests. It also provides an important reference for the regional environmental management and ecological security in North Korea.
abstract_unstemmed	North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed and analyzed a time-series land use land cover (LULC) map to identify the LULC changes (LULCCs) over extensive periods across North Korea and understand the forest change trends. The analysis of LULC used Landsat multi-temporal image and Random Forest algorithm on Google Earth Engine(GEE) from 2001 to 2018 in North Korea. Through the LULCC detection technique and consideration of the cropland change relation with elevation, the forest change in North Korea for 2001–2018 was evaluated. We extended the existing sampling methodology and obtained a higher overall accuracy (98.2% ± 1.6%), with corresponding kappa coefficients (0.959 ± 0.037), and improved the classification accuracy in cropland and forest cover. Through the change detection and spatial analysis, our research shows that the forests in the southern and central regions of North Korea are undergoing restoration. The sampling method we extended in this study can effectively and reliably monitoring the change trend of North Korea forests. It also provides an important reference for the regional environmental management and ecological security in North Korea.
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title_short	Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea
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Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea

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