접근불가지역인 북한의 시계열 토지피복도 매핑 및 산림 변화 동향 분석

학위논문(석사) -- 서울대학교대학원 : 농업생명과학대학 생태조경·지역시스템공학부(생태조경학), 2021.8. 이동근.North Korea, as an inaccessible area, has little research on land cover change, but it is very important to understand the changing trend of LULCC and provide information previously unknown to North Korea. This study therefore aimed to construct and analyze a 30-m resolution modern time-series land use land cover (LULC) map to identify the LULCCs over long time periods across North Korea and understand the forest change trends. A land use and land cover (LULC) map of North Korea from 2001 to 2018 was constructed herein using semi-permanent point classification and machine learning techniques on satellite image time-series data. The resultant relationship between cropland and forest cover, and the LULC changes were examined. The classification results show the effectiveness of the methods used in classifying the time series of Landsat images for LULC, wherein the overall accuracy of the LULC classification results was 97.5% ± 0.9%, and the Kappa coefficient was 0.94 ± 0.02. Using LULC change detection, our research effectively explains the change trajectory of North Korea’s current LULC, providing new insights into the change characteristics of North Korea’s croplands and forests. Further, our results show that North Korea’s urban area has increased significantly, its forest cover has increased slightly, and its cropland cover has decreased. We determined that North Korea’s Forest protection policies have led to the forest restoration. Thus, as agriculture is one of North Korea’s main economic contributors, croplands have been forced to relocate, expanding to other regions to compensate for the land loss caused by forest restoration.북한은 세계에서 가장 심각하게 황폐화된 산림 중 하나를 포함하고 있지만 최근에는 산림 복원을 강조하고 있다. 산림 복원이 일어나는 정도를 이해하기 위해서는 토지 이용과 토지 피복 변화 경향 (LULCC)을 이해해야 한다. 따라서 본 연구는 30m 해상도의 현대 시계열 토지 이용 토지 피복 (LULC)지도를 구성 및 분석하여 북한 전역의 장기 LULCC를 식별하고 산림 변화 추세를 이해하는 것을 목표로 한다. 2001 - 2018 년 기간 동안 국가의 LULC지도는 30m 해상도 위성 이미지 시계열 데이터를 기반으로 반영구적 포인트 분류 및 기계 학습을 사용하여 구성되었으며, 이는 GEE (Google Earth Engine)에서 수집 한 현상 학적 정보와 함께 사용되고 있다. 또한 LULCC 탐지기 법과 경작지 변화와 고도의 관계를 고려하여 2001 - 2018 년 북한의 산림 변화를 평가하였다. LULC 맵 결과의 전체 분류 정확도는 97.5 % ± 0.9 %이고, Kappa 계수는 0.94 ± 0.02 이다. LULCC 탐지는 또한 2001 - 2018 년에 북한의 산림 면적이 약간 증가한 것으로 나타났다. 일반적으로 산림 피복 면적은 크게 변하지 않았으나 남부와 중부 지역의 산림 복원과 북부와 서부의 경작지 상대적 증가 측면에서 뚜렷한 공간적 변화가 관찰되었다. 북한의 특성과 산림 정책 문서를 검토 한 결과 북한 근대 산림의 일부 지역이 복원되고 있음을 확인하였다.Chapter 1. Introduction 1 Chapter 2. Study Area 7 Chapter 3. Materials and Methods 8 3.1. Study overview 8 3.2. Data Collection 9 3.3. Data Processing 11 3.4. Classification Process 12 3.5. LULCC Analysis 14 3.6. Reference Data Collection and Classification Accuracy Validation 15 Chapter 4. Results 17 4.1. LULC Classification Accuracy Assessment 17 4.2. LULC Classification Results 20 4.3. LULC Change Detection 22 4.4. Relation with mountainous cropland and elevation 26 Chapter 5. Discussion 28 5.1. Interpretation and explanation of the forest change in North Korea 28 5.2. Importance of spatial analysis and future research directions 30 5.3. Limits and Advantages 32 Chapter 6. Conclusion 34 Bibliography 36 Appendix 44 Abstract in Korean 51석

Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite

Acquiring accurate and timely information on the spatial distribution of paddy rice fields and the corresponding yield is an important first step in meeting the regional and global food security needs. In this study, using dense vegetation index profiles and meteorological parameters from the Communication, Ocean, and Meteorological Satellite (COMS) geostationary satellite, we estimated paddy areas and applied a novel approach based on a remote sensing-integrated crop model (RSCM) to simulate spatiotemporal variations in rice yield in Northeastern Asia. Estimated seasonal vegetation profiles of plant canopy from the Geostationary Ocean Color Imager (GOCI) were constructed to classify paddy fields as well as their productivity based on a bidirectional reflectance distribution function model (BRDF) and adjusted normalized difference vegetation indices (VIs). In the case of classification, the overall accuracy for detected paddy fields was 78.8% and the spatial distribution of the paddy area was well represented for each selected county based on synthetic applications of dense-time GOCI vegetation index and MODIS water index. For most of the Northeast Asian administrative districts investigated between 2011 and 2017, simulated rice mean yields for each study site agreed with the measured rice yields, with a root-mean-square error of 0.674 t ha−1, a coefficient of determination of 0.823, a Nash-Sutcliffe efficiency of 0.524, and without significant differences (p-value = 0.235) according to a sample t-test (α = 0.05) for the entire study period. A well-calibrated RSCM, driven by GOCI images, can facilitate the development of novel approaches for the monitoring and management of crop productivity over classified paddy areas, thereby enhancing agricultural decision support systems

Forest Biodiversity, Conservation and Sustainability

One of the highest priorities for human societies in the 21st century, under the challenges of predicted great environmental changes, is to conserve all kinds of biodiversity across the planet. Among all the biota that exist on Earth, forest ecosystems demonstrate a high degree of biodiversity, being thought to comprise the most diverse ecosystems, as most of the terrestrial species in the world dwell in these ecosystems. Forest biodiversity is interlinked to a web of socio-economic factors, providing an array of goods and services that range from timber and non-timber forest resources to mitigating climate change and conservation of genetic resources; therefore, it is innately linked to ecosystems and human well-being. However, in recent decades, the decrease in forest biodiversity has been a crucial and ongoing environmental issue that needs special attention and adapted ecosystem management. This Special Issue book on forest biodiversity (FB) includes a selected number of research works from all over the world dealing with emerging issues, for understanding FB and its needs for conservation, ecological processes, disturbances, climate change and ecosystems resilience, structural complexity and ecosystem functions, ecological theories and silvicultural practices, and ecosystems stability. More specifically, it includes papers focused on the indicators and methods for assessing and monitoring forest biodiversity, evaluation of practices, planting and silvicultural treatments, and management and monitoring methods, with an overall goal to provide new insights on forest biodiversity conservation, conservation of forest biodiversity in protected areas, treatments of endangered or threatened forest habitats, and sustainable management of forest resources

Doctor of Philosophy

dissertationChina’s retail sector has undertaken tremendous transformation since its opening to foreign investment in 1992. Retail transnational corporations have expanded rapidly in this emerging market. Yet relatively little is known about how they have embedded in the Chinese market and expanded spatially and temporally. China has experienced unprecedented urbanization since the onset of economic reform in 1978. Dramatic land use and land cover (LULC) change and urban expansion have taken place in the past three decades. Detailed time-series analysis of LULC change and urban growth in Chinese cities is still scant. This dissertation focuses on the expansion of foreign hypermarket retailers in China and the urban growth in one Chinese city, Suzhou. This research analyzes the penetration strategy and local embeddedness of foreign hypermarket retailers, examines their spatial inequality and dynamics at different geographical levels, and identifies their location determinants through binary logistic regression models. This study applies random forest classification to multitemporal Landsat Thematic Mapper (TM) images of Suzhou for LULC change analysis, employs landscape metrics and Geographic Information System (GIS) analysis to investigate urban growth patterns, and develops global and local logistic regression models to identify determinants of urban growth. The results indicate that spatiotemporal expansion of foreign hypermarket retailers has been largely dictated by the gradual liberalization policy of the Chinese government. Their local embeddedness has been impacted by both home and host economies. Relative gaps in foreign hypermarkets among three macro regions are narrowing while absolute gaps are widening. Provincial foreign hypermarket distribution has shown significant clustering in the Yangtze River Delta since 2005. Their distribution in Shanghai has changed from dispersion to intensified clustering and shown a clear trend of suburbanization. This study confirms that the random forest algorithm can effectively classify the heterogeneous landscape in Suzhou and LULC change has accelerated from 1986 to 2008. Three urban growth types, edge-expansion, infilling, and leapfrog are identified. Compared with the global model, the geographically weighted logistic regression model has overall better goodness-of-fit and provides more insights to spatial variations of the influence of underlying factors on urban growth

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

Remote Sensing Applications in Coastal Environment

Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments

Operationalization of Remote Sensing Solutions for Sustainable Forest Management

The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry

Urban Forests and Landscape Ecology

Urbanization is a dominant driver of landscape transformation across the world, with cities representing centers of economic and socio-cultural development. Today, more than 4.2 billion people live in urban areas, which represent ~3% of the Earth’s land area. By 2050, it is predicted this number will increase to 6.6 billion people (~70% of the predicted global population). As the human population grows, cities around the globe will continue to expand, increasing the demand for food and services. Within cities, urban forests provide multiple nature-based solutions, as well as other environmental services and socio-economic benefits, such as heat mitigation and social integration. Urban forests are also important for coping with psychological stress during events, such as the COVID-19 pandemic. Therefore, urban forests are a priority for basic and applied forest research because they are intimately connected with people’s physical, cultural, and economic well-being in the urban environment, and can also be important reservoirs of biodiversity. To promote a better understanding of urban forests and landscape ecology, this book in “Urban Forests and Landscape Ecology” compiled research set in urban forests and focused on some spatially explicit processes. Studies presented in this book are highly interdisciplinary and use a wide range of research approaches. This book present nine scientific publications from global urban forests demonstrating that these forests, as a nature-based solution, provide multiple environmental services and are crucial to improve urban livability and thereby the wellbeing of city dwellers

Land Use and Land Cover Mapping in a Changing World

It is increasingly being recognized that land use and land cover changes driven by anthropogenic pressures are impacting terrestrial and aquatic ecosystems and their services, human society, and human livelihoods and well-being. This Special Issue contains 12 original papers covering various issues related to land use and land use changes in various parts of the world (see references), with the purpose of providing a forum to exchange ideas and progress in related areas. Research topics include land use targets, dynamic modelling and mapping using satellite images, pressures from energy production, deforestation, impacts on ecosystem services, aboveground biomass evaluation, and investigations on libraries of legends and classification systems

Land Use and Land Cover Mapping in a Changing World

It is increasingly being recognized that land use and land cover changes driven by anthropogenic pressures are impacting terrestrial and aquatic ecosystems and their services, human society, and human livelihoods and well-being. This Special Issue contains 12 original papers covering various issues related to land use and land use changes in various parts of the world (see references), with the purpose of providing a forum to exchange ideas and progress in related areas. Research topics include land use targets, dynamic modelling and mapping using satellite images, pressures from energy production, deforestation, impacts on ecosystem services, aboveground biomass evaluation, and investigations on libraries of legends and classification systems