Examining changes in woody vegetation cover in a human-modified temperate savanna in Central Texas between 1996 and 2022 using remote sensing

Savanna ecosystems across the globe have experienced substantial changes in their vegetation composition. These changes can be attributed to three main processes: (1) encroachment, which refers to the expansion of woody plants into open areas, (2) thicketization, which is characterized by the growth of sub-canopy woody plants, and (3) disturbance, defined here as the removal of woodland cover due to both natural forces and human activities. In this study, we utilized Landsat surface reflectance data and Sentinel-1 SAR data to track the progression of these process from 1996 to 2022 in the significantly modified Post Oak Savannah ecoregion of Central Texas. Our methodology employs an ensemble classification algorithm, which combines the results of multiple models, to develop a more precise predictive model, along with the spectral–temporal segmentation algorithm LandTrendr in Google Engine (GEE). Our ensemble classification algorithms demonstrated high overall accuracies of 94.3 and 96.5% for 1996 and 2022, respectively, while our LandTrendr vegetation map exhibited an overall accuracy of 80.4%. The findings of our study reveal that 9.7% of the overall area experienced encroachment of woody plants into open area, while an additional 6.8% of the overall area has transitioned into a thicketized state due to the growth of sub-canopy woody plants. Furthermore, 5.7% of the overall area encountered woodland disturbance leading to open areas. Our findings suggest that these processes advanced unevenly throughout the region, resulting in the coexistence of three prominent plant communities that appear to have long-term stability: a dense deciduous shrubland in the southern region, as well as a thicketized oak woodland and open area mosaic in the central and northern regions. The successional divergence observed in these plant communities attests to the substantial influence of human modification on the landscape. This study demonstrates the potential of integrating passive optical multispectral data and active SAR data to accurately map large-scale ecological processes

Monitoring and modelling disturbances to the Niger Delta mangrove forests

The Niger River Delta provides numerous ecosystem services (ES) to local populations and holds a wealth of biodiversity. Nevertheless, they are under threat of degradation and loss mainly due to the population increase and oil and gas extraction activities. Monitoring mangrove vegetation change and understanding the dynamics related with these changes is crucial for the short and longer-term sustainability of the Niger Delta Region (NDR) and its mangrove forests. Over the last two decades, open access remote sensing data, together with technological and algorithmic advancements, have provided the ability to monitor land cover over large areas through space and time. However, the analysis of land cover dynamics over the NDR using freely available optical remote sensing data, such as Landsat, remains challenging due to the gaps in the archive associated with the West African region and the issue of cloud contamination over the wet tropics. This thesis applies state-art-of-the-art remote sensing techniques and integrated modelling approaches to provide reliable information relating to monitoring and modelling of land cover change in the NDR, focusing on its mangrove forests. Spectral-temporal metrics from all available Landsat images were used to accurately map land cover in three time points, using a Random Forests machine learning classification model. The performance of the classification was tested when L-band radar data are added to the Landsat-based metrics. Results showed that Landsat based metrics are sufficient in mapping land cover over the study region with high overall classification accuracies over the three time points (1988, 2000, and 2013) and degraded mangroves were accurately mapped for the first time. Two additional assessments: a change intensity analysis for the entire NDR and, fragmentation analysis focusing on mangrove land cover classes were carried out for the first time ever. The drivers of mangrove degradation were assessed using a Multi-layer Perceptron, Artificial Neutral Networks (MLP-ANN) algorithm. The results reveal that built-up infrastructure variables were the most important drivers of mangrove degradation between 1988 and 2000, whilst oil and gas infrastructure variables were the most important drivers between 2000 and 2013. Results also show that population density was the least important driver of mangrove degradation over the two study periods. Future land cover changes and mangrove degradation were predicted under two business-as-usual scenarios in the short (2026) and longer-term (2038) using a Multi-Layer Perceptron neutral network and Markov chain (MLP-ANN+MC) model. The model’s accuracy was assessed using the highly-accurate land cover classification of 2013. Results show that that mangrove forest and woodlands (lowland and freshwater forests) are demonstrating a net loss, whilst the built-up areas and agriculture are indicating a net increase in both the short and longer-term scenarios. However, degraded mangroves are demonstrating a net increase in the short-term scenario. Interestingly, in the longer-term scenario, more than double the net increase of mangroves degraded in the short-term scenario, are predicted to recover to their healthier state. The thesis results could provide useful information for planning conservation measures for sustainable mangrove forest management of the entire NDR

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

A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals associated with deforestation, gains and losses of carbon stocks in forests remaining forests, and forestation

A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals associated with deforestation, gains and losses of carbon stocks in forests remaining forests, and forestatio

The Impacts of Small-Scale Gold Mining on Food Security in Ghana

Small-scale gold mining has expanded in many countries in Sub-Saharan Africa and other parts of the world including Peru and the Philippines, over the last two decades. Numerous factors, including rising gold prices, agricultural poverty, and administrative difficulties, have been cited as explanations for the rapid growth. The rapid growth of small-scale gold mining has a plethora of implications for agriculture, particularly smallholder farming. This is because the primary resource (land) on which mining, and agriculture are based is scarce, and mineral deposits frequently coincide with land suitable for agriculture. Additionally, mining and agriculture both consume large amounts of water and are labour intensive. Thus, a direct link between the expansion of small-scale gold mining and its impact on smallholder agriculture has been established in various countries throughout Sub-Saharan Africa, though opinions vary on whether the relationship is complementary or competitive. Additionally, the impacts of these connections on food security have received relatively little attention, and they are heavily underrepresented in the literatures on small-scale mining and food security. This thesis closes this knowledge gap by shedding light on the impact of small-scale gold mining on food security and contributing to the debate over the relationship between small-scale gold mining and smallholder farming. I argue, using a mixed method case study in Ghana, that mining has a negative impact on food security and that women and children bear a disproportionate share of the burden. Additionally, I demonstrated how competitive and conflict-ridden the relationship between small-scale mining and smallholder farming is. This study was guided by a novel synthesis of the capability approach and a political ecology perspective. I begin by examining how structural and economic reforms have influenced mining and agricultural activities in Ghana over time, as well as the consequences of these reforms, with a particular emphasis on the often-overlooked ecological footprints. Second, I quantify and predict the pattern of land use and land cover change that would occur under various scenarios, as well as the factors that would cause these changes. Thirdly, I examine the factors affecting miners and smallholder farmers' access to critical resources (land, water, and labour), as well as the key actors in the mining and smallholder farming subsectors, as well as their power hierarchy and relationship. Finally, I examine the relationships between mining and smallholder farming and the state of individual food security (availability, access, utilisation, and stability). The key findings are as follows: first, that the promotion of export-oriented commodities such as gold and cash crops such as cocoa and oil palm at the expense of peasant farmers' food crops is associated with severe ecological impacts that remain shielded in the absence of required environmental legislation until they exacerbate. There are also flashpoints of conflict between mining and smallholder farming, which has been aggravated by recent reforms and lays the groundwork for future conflicts. Second, four distinct periods of land use and land cover dynamics for mining footprints were identified using a combination of social science and geospatial methods: periods of none to limited increase, gradual to accelerated increase, sharp increase, and gradual decrease in mining footprints. These land use and land cover dynamics were found to be associated with three major ecological impacts of mining: land degradation, deforestation, and water pollution. Over a 34-year period, a total of 27,333 ha (36% of forest cover) was lost, along with severe land degradation and water pollution. If mining activities continue at their current pace, the study predicts increased ecological impacts. Third, the previously coexisting mining and smallholder farming subsectors are now fiercely competing for access to critical resources (land, labour, and water), a situation shaped by unequal power relations between the two subsectors' key actors. Finally, small-scale gold mining significantly contributes to food insecurity and, as a result, to the poor health and well-being of many people, particularly women and children. Half of the study participants experienced moderate food insecurity, while 13% experienced severe food insecurity. Additionally, 79% of women of reproductive age (15 to 49) were unable to meet the Minimum Dietary Diversity (MDD) requirements, a measure of micronutrient adequacy and, thus, food quality. Furthermore, local challenges with food availability, as well as associated challenges with food access and utilisation, erode food stability over time, forcing more people to adopt alternative coping strategies. The findings of this study provide novel empirical evidence on the impacts of small-scale gold mining on food security and highlight the importance of integrating mixed and geospatial methods. Additionally, the findings demonstrate the value of combining political ecology and capability approaches in natural resource governance and food security research

Feature Papers of Drones - Volume II

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 24–41 are focused on drone applications, but emphasize two types: firstly, those related to agriculture and forestry (articles 24–35) where the number of applications of drones dominates all other possible applications. These articles review the latest research and future directions for precision agriculture, vegetation monitoring, change monitoring, forestry management, and forest fires. Secondly, articles 36–41 addresses the water and marine application of drones for ecological and conservation-related applications with emphasis on the monitoring of water resources and habitat monitoring. Finally, articles 42–54 looks at just a few of the huge variety of potential applications of civil drones from different points of view, including the following: the social acceptance of drone operations in urban areas or their influential factors; 3D reconstruction applications; sensor technologies to either improve the performance of existing applications or to open up new working areas; and machine and deep learning development

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity