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

Land Degradation Assessment with Earth Observation

This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools

Scenario-based analysis of the impacts of lake drying on food production in the Lake Urmia Basin of Northern Iran

In many parts of the world, lake drying is caused by water management failures, while the phenomenon is exacerbated by climate change. Lake Urmia in Northern Iran is drying up at such an alarming rate that it is considered to be a dying lake, which has dire consequences for the whole region. While salinization caused by a dying lake is well understood and known to influence the local and regional food production, other potential impacts by dying lakes are as yet unknown. The food production in the Urmia region is predominantly regional and relies on local water sources. To explore the current and projected impacts of the dying lake on food production, we investigated changes in the climatic conditions, land use, and land degradation for the period 1990–2020. We examined the environmental impacts of lake drought on food production using an integrated scenario-based geoinformation framework. The results show that the lake drought has significantly affected and reduced food production over the past three decades. Based on a combination of cellular automaton and Markov modeling, we project the food production for the next 30 years and predict it will reduce further. The results of this study emphasize the critical environmental impacts of the Urmia Lake drought on food production in the region. We hope that the results will encourage authorities and environmental planners to counteract these issues and take steps to support food production. As our proposed integrated geoinformation approach considers both the extensive impacts of global climate change and the factors associated with dying lakes, we consider it to be suitable to investigate the relationships between environmental degradation and scenario-based food production in other regions with dying lakes around the world

Recent Shrinkage and Fragmentation of Bluegrass Landscape in Kentucky

The Bluegrass Region is an area in north-central Kentucky with unique natural and cultural significance, which possesses some of the most fertile soils in the world. Over recent decades, land use and land cover changes have threatened the protection of the unique natural, scenic, and historic resources in this region. In this study, we applied a fragmentation model and a set of landscape metrics together with the satellite-derived USDA Cropland Data Layer to examine the shrinkage and fragmentation of grassland in the Bluegrass Region, Kentucky during 2008–2018. Our results showed that recent land use change across the Bluegrass Region is characterized by grassland decline, cropland expansion, forest spread, and suburban sprawl. The grassland area decreased by 14.4%, with an interior (or intact) grassland shrinkage of 5%, during the study period. Land conversion from grassland to other land cover types has been widespread, with major grassland shrinkage occurring in the west and northeast of the Outer Bluegrass Region and relatively minor grassland conversion in the Inner Bluegrass Region. The number of patches increased from 108,338 to 126,874. The effective mesh size, which represents the degree of landscape fragmentation in a system, decreased from 6629.84 to 1816.58 for the entire Bluegrass Region. This study is the first attempt to quantify recent grassland shrinkage and fragmentation in the Bluegrass Region. Therefore, we call for more intensive monitoring and further conservation efforts to preserve the ecosystem services provided by the Bluegrass Region, which has both local and regional implications for climate mitigation, carbon sequestration, diversity conservation, and culture protection

Agricultural land systems : modelling past, present and future regional dynamics

This thesis arises from the understanding of how the integration of concepts, tools, techniques, and methods from geographic information science (GIS) can provide a formalised knowledge base for agricultural land systems in response to future agricultural and food system challenges. To that end, this thesis focuses on understanding the potential application of GIS-based approaches and available spatial data sources for modelling regional agricultural land-use and production dynamics in Portugal. The specific objectives of this thesis are addressed in seven chapters in Parts II through V, each corresponding to one scientific article that was either published or is being considered for publication in peer-reviewed international scientific journals. In Part II, Chapter 2 summarises the body of knowledge and provides the context for the contribution of this thesis within the scientific domain of agricultural land systems. In Part III, Chapters 3 and 4 explore remotely sensed and Volunteered Geographic Information (VGI) data, multitemporal and multisensory approaches, and a variety of statistical methods for mapping, quantifying, and assessing regional agricultural land dynamics in the Beja district. In Part IV, Chapters 5–7 explore the CA-Markov model, Markov chain model, machine learning, and model-agnostic approach, as well as a set of spatial metrics and statistical methods for modelling the factors and spatiotemporal changes of agricultural land use in the Beja district. In Part V, Chapter 8 explores an area-weighting GIS-based technique, a spatiotemporal data cube, and statistical methods to model the spatial distribution across time for regional agricultural production in Portugal. The case studies in the thesis contribute practical and theoretical knowledge by demonstrating the strengths and limitations of several GIS-based approaches. Together, the case studies demonstrate the underlying principles that underpin each approach in a way that allows us to infer their potentiality and appropriateness for modelling regional agricultural land-use and production dynamics, stimulating further research along this line. Generally, this thesis partly reflects the state-of-art of land-use modelling and contribute significantly to the introduction of advances in agricultural system modelling research and land-system science

Economics of Land Degradation and Improvement – A Global Assessment for Sustainable Development

environmental economics; biodiversity; sustainable developmen

Reducing risks by transforming landscapes: Cross-scale effects of land-use changes on ecosystem services

Globally, anthropogenic environmental change is exacerbating the already vulnerable conditions of many people and ecosystems. In order to obtain food, water, raw materials and shelter, rural people modify forests and other ecosystems, affecting the supply of ecosystem services that contribute to livelihoods and well-being. Despite widespread awareness of the nature and extent of multiple impacts of land-use changes, there remains limited understanding of how these impacts affect trade-offs among ecosystem services and their beneficiaries across spatial scales. We assessed how rural communities in two forested landscapes in Indonesia have changed land uses over the last 20 years to adapt their livelihoods that were at risk from multiple hazards. We estimated the impact of these adaptation strategies on the supply of ecosystem services by comparing different benefits provided to people from these land uses (products, water, carbon, and biodiversity), using forest inventories, remote sensing, and interviews. Local people converted forests to rubber plantations, reforested less productive croplands, protected forests on hillsides, and planted trees in gardens. Our results show that land-use decisions were propagated at the landscape scale due to reinforcing loops, whereby local actors perceived that such decisions contributed positively to livelihoods by reducing risks and generating co-benefits. When land-use changes become sufficiently widespread, they affect the supply of multiple ecosystem services, with impacts beyond the local scale. Thus, adaptation implemented at the local-scale may not address development and climate adaptation challenges at regional or national scale (e.g. as part of UN Sustainable Development Goals or actions taken under the UNFCCC Paris Agreement). A better understanding of the context and impacts of local ecosystem-based adaptation is fundamental to the scaling up of land management policies and practices designed to reduce risks and improve well-being for people at different scales