A 33-year NPP monitoring study in southwest China by the fusion of multi-source remote sensing and station data

Knowledge of regional net primary productivity (NPP) is important for the systematic understanding of the global carbon cycle. In this study, multi-source data were employed to conduct a 33-year regional NPP study in southwest China, at a 1-km scale. A multi-sensor fusion framework was applied to obtain a new normalized difference vegetation index (NDVI) time series from 1982 to 2014, combining the respective advantages of the different remote sensing datasets. As another key parameter for NPP modeling, the total solar radiation was calculated by the improved Yang hybrid model (YHM), using meteorological station data. The verification described in this paper proved the feasibility of all the applied data processes, and a greatly improved accuracy was obtained for the NPP calculated with the final processed NDVI. The spatio-temporal analysis results indicated that 68.07% of the study area showed an increasing NPP trend over the past three decades. Significant heterogeneity was found in the correlation between NPP and precipitation at a monthly scale, specifically, the negative correlation in the growing season and the positive correlation in the dry season. The lagged positive correlation in the growing season and no lag in the dry season indicated the important impact of precipitation on NPP.Comment: 20 pages, 11 figure

Climate Change and Environmental Sustainability-Volume 4

Anthropogenic activities are significant drivers of climate change and environmental degradation. Such activities are particularly influential in the context of the land system that is an important medium connecting earth surface, atmospheric dynamics, ecological systems, and human activities. Assessment of land use land cover changes and associated environmental, economic, and social consequences is essential to provide references for enhancing climate resilience and improving environmental sustainability. On the one hand, this book touches on various environmental topics, including soil erosion, crop yield, bioclimatic variation, carbon emission, natural vegetation dynamics, ecosystem and biodiversity degradation, and habitat quality caused by both climate change and earth surface modifications. On the other hand, it explores a series of socioeconomic facts, such as education equity, population migration, economic growth, sustainable development, and urban structure transformation, along with urbanization. The results of this book are of significance in terms of revealing the impact of land use land cover changes and generating policy recommendations for land management. More broadly, this book is important for understanding the interrelationships among life on land, good health and wellbeing, quality education, climate actions, economic growth, sustainable cities and communities, and responsible consumption and production according to the United Nations Sustainable Development Goals. We expect the book to benefit decision makers, practitioners, and researchers in different fields, such as climate governance, crop science and agricultural engineering, forest ecosystem, land management, urban planning and design, urban governance, and institutional operation.Prof. Bao-Jie He acknowledges the Project NO. 2021CDJQY-004 supported by the Fundamental Research Funds for the Central Universities and the Project NO. 2022ZA01 supported by the State Key Laboratory of Subtropical Building Science, South China University of Technology, China. We appreciate the assistance of Mr. Lifeng Xiong, Mr. Wei Wang, Ms. Xueke Chen, and Ms. Anxian Chen at School of Architecture and Urban Planning, Chongqing University, China

Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data

Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development. Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals (SDGs). Urban sprawl has resulted in unsustainable urban development patterns from social, environmental, and economic perspectives. This study is among the first examples of research in Africa to combine remote sensing data with social media data to determine urban sprawl from 2011 to 2017 in Morogoro urban municipality, Tanzania. Random Forest (RF) method was applied to accomplish imagery classification and location-based social media (Twitter usage) data were obtained through a Twitter Application Programming Interface (API). Morogoro urban municipality was classified into built-up, vegetation, agriculture, and water land cover classes while the classification results were validated by the generation of 480 random points. Using the Kernel function, the study measured the location of Twitter users within a 1 km buffer from the center of the city. The results indicate that, expansion of the city (built-up land use), which is primarily driven by population expansion, has negative impacts on ecosystem services because pristine grasslands and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover. In addition, social media usage data suggest that there is the concentration of Twitter usage within the city center while Twitter usage declines away from the city center with significant spatial and numerical increase in Twitter usage in the study area. The outcome of the study suggests that the combination of remote sensing, social sensing, and population data were useful as a proxy/inference for interpreting urban sprawl and status of access to urban services and infrastructure in Morogoro, and Africa city where data for urban planning is often unavailable, inaccurate, or stale

Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate

This book focuses on some significant progress in vegetation dynamics and their response to climate change revealed by remote sensing data. The development of satellite remote sensing and its derived products offer fantastic opportunities to investigate vegetation changes and their feedback to regional and global climate systems. Special attention is given in the book to vegetation changes and their drivers, the effects of extreme climate events on vegetation, land surface albedo associated with vegetation changes, plant fingerprints, and vegetation dynamics in climate modeling

Hydro-Ecological Modeling

Water is not only an interesting object to be studied on its own, it also is an important component driving almost all ecological processes occurring in our landscapes. Plant growth depends on soil water content, as well is nutrient turnover by microbes. Water shapes the environment by erosion and sedimentation. Species occur or are lost depending on hydrological conditions, and many infectious diseases are water-borne. Modeling the complex interactions of water and ecosystem processes requires the prediction of hydrological fluxes and stages on the one side and the coupling of the ecosystem process model on the other. While much effort has been given to the development of the hydrological model theory in recent decades, we have just begun to explore the difficulties that occur when coupled model applications are being set up

Land Use Change from Non-urban to Urban Areas

This reprint is related to land-use change and non-urban and urban relationships at all spatiotemporal scales and also focuses on land-use planning and regulatory strategies for a sustainable future. Spatiotemporal dynamics, socioeconomic implication, water supply problems and deforestation land degradation (e.g., increase of imperviousness surfaces) produced by urban expansion and their resource requirements are of particular interest. The Guest Editors expect that this reprint will contribute to sustainable development in non-urban and urban areas

Quantifying ecosystem services within a reforested urban landscape using remote sensing in eThekwini region of KwaZulu-Natal, South Africa.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in PDF

Effects of urban expansion on coastal vegetation ecosystems conservation and functioning in Buffalo City Metropolitan Municipality, South Africa

Coastal urban expansion is on an upward trajectory, which poses serious threats to ecosystem functioning, human wellbeing and the general environment across the globe. It is on this premise that this study brings to the fore the growing complexity of environmental sustainability problems in a former apartheid space, as characterized by coastal urbanization and the intricacies of vegetation conservation. Consequently, literature utilized for this study reveals that urban expansion has led to an uncontrolled threat to the coastal ecosystem, culminating in soil erosion, environmental pollution through illegal dumping of solid waste, loss of coastal vegetation to other land use types, among others. Therefore, constant monitoring of these spaces is needed due to their fragility, as they are pivotal in the earth-atmosphere processes to the benefit of the entire humanity. To this end, the current study offers critical analysis and insights about the South African coastal ecological space. The essence of using BCMM in its consideration as an ecological space and former apartheid territory brings to the fore a scientific explanation of the spatial configuration and changes in the CVEs of the study area during the post-colonial era. In the course of investigating this study, the Urban Green Sustainability (UGS) theory was adopted in the course of selecting the review of literature, methodological approach and analysis of results. A mixed methodological approach (qualitative, quantitative and geospatial techniques) was explored in data collection and analysis. 254 copies of the questionnaire were returned and analysed for this research. Results generated revealed by the BCMM respondents confirms the occurrence of uncontrolled urbanization, deforestation and crop cultivation as major causes of coastal vegetation loss. In the same vein, the LULC classification results revealed that about 466 km2 of forest vegetation has been lost in BCMM from 1998-2018. Also, LULC classification results were validated by performing the Normalized Difference Built-Up Index (NDBI), Normalized Difference Vegetative Index (NDVI), Kappa’s coefficient (k), coefficient of determination (R2) and Pearson’s Product Moment Correlation (P) tests. The results also revealed that the built-up area had increased from 194 km2 in 1998 to 814 km2 in 2008. Further, all statistical tests revealed very good and highly correlated overall classification accuracies (of R2=0.89 and P=0.86) during the study period (1998 – 2018). This study makes a clarion call towards the rehabilitation of degraded coastal environments and proffers solutions towards the actualization of environmentally sustainable CVEs which offers optimal ecosystem services.Thesis (PhD) -- Faculty of Science and Agriculture, 202