Mapping regional land cover and land use change using MODIS time series

Coarse resolution satellite observations of the Earth provide critical data in support of land cover and land use monitoring at regional to global scales. This dissertation focuses on methodology and dataset development that exploit multi-temporal data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve current information related to regional forest cover change and urban extent. In the first element of this dissertation, I develop a novel distance metric-based change detection method to map annual forest cover change at 500m spatial resolution. Evaluations based on a global network of test sites and two regional case studies in Brazil and the United States demonstrate the efficiency and effectiveness of this methodology, where estimated changes in forest cover are comparable to reference data derived from higher spatial resolution data sources. In the second element of this dissertation, I develop methods to estimate fractional urban cover for temperate and tropical regions of China at 250m spatial resolution by fusing MODIS data with nighttime lights using the Random Forest regression algorithm. Assessment of results for 9 cities in Eastern, Central, and Southern China show good agreement between the estimated urban percentages from MODIS and reference urban percentages derived from higher resolution Landsat data. In the final element of this dissertation, I assess the capability of a new nighttime lights dataset from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) for urban mapping applications. This dataset provides higher spatial resolution and improved radiometric quality in nighttime lights observations relative to previous datasets. Analyses for a study area in the Yangtze River Delta in China show that this new source of data significantly improves representation of urban areas, and that fractional urban estimation based on DNB can be further improved by fusion with MODIS data. Overall, the research in this dissertation contributes new methods and understanding for remote sensing-based change detection methodologies. The results suggest that land cover change products from coarse spatial resolution sensors such as MODIS and VIIRS can benefit from regional optimization, and that urban extent mapping from nighttime lights should exploit complementary information from conventional visible and near infrared observations

Remote sensing of night lights: a review and an outlook for the future

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordRemote sensing of night light emissions in the visible band offers a unique opportunity to directly observe human activity from space. This has allowed a host of applications including mapping urban areas, estimating population and GDP, monitoring disasters and conflicts. More recently, remotely sensed night lights data have found use in understanding the environmental impacts of light emissions (light pollution), including their impacts on human health. In this review, we outline the historical development of night-time optical sensors up to the current state of the art sensors, highlight various applications of night light data, discuss the special challenges associated with remote sensing of night lights with a focus on the limitations of current sensors, and provide an outlook for the future of remote sensing of night lights. While the paper mainly focuses on space borne remote sensing, ground based sensing of night-time brightness for studies on astronomical and ecological light pollution, as well as for calibration and validation of space borne data, are also discussed. Although the development of night light sensors lags behind day-time sensors, we demonstrate that the field is in a stage of rapid development. The worldwide transition to LED lights poses a particular challenge for remote sensing of night lights, and strongly highlights the need for a new generation of space borne night lights instruments. This work shows that future sensors are needed to monitor temporal changes during the night (for example from a geostationary platform or constellation of satellites), and to better understand the angular patterns of light emission (roughly analogous to the BRDF in daylight sensing). Perhaps most importantly, we make the case that higher spatial resolution and multispectral sensors covering the range from blue to NIR are needed to more effectively identify lighting technologies, map urban functions, and monitor energy use.European Union Horizon 2020Helmholtz AssociationNatural Environment Research Council (NERC)Chinese Academy of ScienceLeibniz AssociationIGB Leibniz Institut

Humans on Earth: Global extents of anthropogenic land cover from remote sensing

This review provides a perspective of the current state of the art in remote sensing of anthropogenic land cover and human-modified landscapes at global scales. The fact that humans have adapted to almost all of Earth’s environments, yet remain strongly clustered within each of these environments influences both the nature of anthropogenic impact on Earth’s landscapes and the challenges of mapping it. Remote sensing provides a consistent synoptic view of these environments by mapping the land cover associated with the anthropogenic land uses of settlement and food production, as well as their complement in forest cover. We give brief descriptions and illustrative comparisons of several current land cover products representing the global extents of settlements, agriculture and forests derived from remote sensing. To accommodate the challenges inherent to mapping any land cover at widely varying scales, we compare size distributions of spatially contiguous land cover (rather than total area) for several global land cover products. Despite the use of different sensors and different mapping criteria, there is remarkable consistency in the size distributions of these products – both within and across land cover class. Rank-size distributions of settlements, agricultural areas and forests are all well-described by power laws spanning more than four orders of magnitude in both area and number. This consistency in the form of the distributions suggests fundamental similarities among different types of land cover. The observed similarities can be explained by depicting land cover mosaics as co-evolving spatial networks sharing common processes of nucleation, growth and connection

Monitoring the spatial-temporal dynamics of urban green space in Shanghai from 2000 to 2020 with remote sensing data

MBArch - Màster Universitari en Estudis Avançats en Arquitectura-Barcelona: Gestió i Valoració Urbana i ArquitectònicaUrbanization is an important process of human development and change, and is the result of economic, cultural and social development. Along with the rapid development of the global economy there has been a rapid deterioration of the ecological environment. The harmonious and sustainable development of population, resources and the environment is an important research topic in the world today, and the creation of eco-cities with resource conservation, green space and good environment is the main trend and the main goal of urban development in various countries at present. Since the introduction of the policy of reform and opening up, Shanghai has entered a period of rapid urbanization, which has only slowed down in recent years. However, the building of an international metropolis in Shanghai has given rise to "urban diseases" such as high population density, limited land resources, deteriorating air quality, heat island effect. At the same time, the Shanghai government has adopted many policies and measures to improve environmental quality and build an eco-city. Based on this background, the aim of the article is to analyzing the temporal and spatial changes in Shanghai's urban green spaces and the differences between current situations and planning which can help to better build an ecological city. The data for this study were obtained from major satellite data and open platforms for land cover data. An NDVI analysis was carried out based on the data obtained and compared with the official land cover data. Fragstats has also been used to analyze an overall landscape pattern index for Shanghai. The results from the analysis show that: 1. The area of green space in Shanghai continued to decrease from 2000 to 2015 and increased from 2015 to 2020. The artificial surface area increased continuously from 2000 to 2010, especially between 2005 and 2010 when the city grew rapidly, and decreased from 2010 to 2020 when the urban growth rate tended to level off. Green space in the city centre decreases rapidly between 2000 and 2005, improves a little between 2005 and 2010, deteriorates again between 2010 and 2015, and improves considerably until 2020. 2. The comparison between the 2020 green space area calculated by GIS and the 2020 Shanghai land cover type map obtained by Copernicus Data Open Center shows that the overlap degree is 89.44%, which indicates that the protection and development of urban green space in Shanghai in the recent five years is good, and basically conforms to the planning goal. 5 3. Analysis of the landscape type transfer matrix reveals that a disproportionate amount of agricultural land has been transferred to built-up land, and the second largest area of water bodies transferred to built-up areas. 4. it is worth noting that the area of agricultural land, grassland and woodland used for construction has increased in recent years. 5. The analysis of the landscape pattern index reveals that there are many minor problems in Shanghai's urban development, with excessive density of urban buildings, excessive fragmentation of farmland and grassland, low landscape connectivity and irregular trends in patch shapes

Nighttime Lights as a Proxy for Economic Performance of Regions

Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions

洪水と地震脆弱性を考慮したミャンマーヤンゴンの都市成長予測モデル

学位の種別: 課程博士審査委員会委員 : （主査）東京大学准教授 竹内 渉, 東京大学准教授 沖 一雄, 東京大学准教授 川崎 昭如, 東京大学准教授 関本 義秀, 東京大学准教授 本間 裕大University of Tokyo(東京大学