Earth Observations for Addressing Global Challenges

"Earth Observations for Addressing Global Challenges" presents the results of cutting-edge research related to innovative techniques and approaches based on satellite remote sensing data, the acquisition of earth observations, and their applications in the contemporary practice of sustainable development. Addressing the urgent tasks of adaptation to climate change is one of the biggest global challenges for humanity. As His Excellency António Guterres, Secretary-General of the United Nations, said, "Climate change is the defining issue of our time—and we are at a defining moment. We face a direct existential threat." For many years, scientists from around the world have been conducting research on earth observations collecting vital data about the state of the earth environment. Evidence of the rapidly changing climate is alarming: according to the World Meteorological Organization, the past two decades included 18 of the warmest years since 1850, when records began. Thus, Group on Earth Observations (GEO) has launched initiatives across multiple societal benefit areas (agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather), such as the Global Forest Observations Initiative, the GEO Carbon and GHG Initiative, the GEO Biodiversity Observation Network, and the GEO Blue Planet, among others. The results of research that addressed strategic priorities of these important initiatives are presented in the monograph

Remotely sensed and modelled pasture biomass, land condition and the potential to improve grazing-management decision tools across the Australian rangelands

This report assesses the potential for expanding on current capacity to monitor land condition using remotely sensed fractional cover products to improve biomass estimation, animal productivity, pasture growth models and grazing decision tools (e.g. safe carrying capacity) across the Australian rangelands. We focus on northern Australia and include relevant research and implementation from southern Australia where appropriate

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

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

The remote sensing of papyrus vegetation (Cyperus papyrus L.) in swamp wetlands of South Africa.

Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.Papyrus (Cyperus papyrus .L) swamp is the most species rich habitat that play vital hydrological, ecological, and economic roles in central tropical and western African wetlands. However, the existence of papyrus vegetation is endangered due to intensification of agricultural use and human encroachment. Techniques for modelling the distribution of papyrus swamps, quantity and quality are therefore critical for the rapid assessment and proactive management of papyrus vegetation. In this regard, remote sensing techniques provide rapid, potentially cheap, and relatively accurate strategies to accomplish this task. This study advocates the development of techniques based on hyperspectral remote sensing technology to accurately map and predict biomass of papyrus vegetation in a high mixed species environment of St Lucia- South Africa which has been overlooked in scientific research. Our approach was to investigate the potential of hyperspectral remote sensing at two levels of investigation: field level and airborne platform level. First, the study provides an overview of the current use of both multispectral and hyperspectral remote sensing techniques in mapping the quantity and the quality of wetland vegetation as well as the challenges and the need for further research. Second, the study explores whether papyrus can be discriminated from each one of its coexistence species (binary class). Our results showed that, at full canopy cover, papyrus vegetation can be accurately discriminated from its entire co-existing species using a new hierarchical method based on three integrated analysis levels and field spectrometry under natural field conditions. These positive results prompted the need to test the use of canopy hyperspectral data resampled to HYMAP resolution and two machine learning algorithms in identifying key spectral bands that allowed for better discrimination among papyrus and other co-existing species (n = 3) (multi-class classification). Results showed that the random forest algorithm (RF) simplified the process by identifying the minimum number of spectral bands that provided the best overall accuracies. Narrow band NDVI and SR-based vegetation indices calculated from hyperspectral data as well as some vegetation indices published in literature were investigated to test their potential in improving the classification accuracy of wetland plant species. The study also evaluated the robustness and reliability of RF as a variables selection method and as a classification algorithm in identifying key spectral bands that allowed for the successful classification of wetland species. Third, the focus was to upscale the results of field spectroscopy analysis to airborne hyperspectral sensor (AISA eagle) to discriminate papyrus and it co-existing species. The results indicated that specific wavelengths located in the visible, red-edge, and near-infrared region of the electromagnetic spectrum have the highest potential of discriminating papyrus from the other species. Finally, the study explored the ability of narrow NDVI-based vegetation indices calculated from hyperspectral data in predicting the green above ground biomass of papyrus. The results demonstrated that papyrus biomass can be modelled with relatively low error of estimates using a non-linear RF regression algorithm. This provided a basis for the algorithm to be used in mapping wetland biomass in highly complex environments. Overall, the study has demonstrated the potential of remote sensing techniques in discriminating papyrus swamps and its co-existing species as well as in predicting biomass. Compared to previous studies, the RF model applied in this study has proved to be a robust, accurate, and simple new method for variables selection, classification, and modelling of hyperspectral data. The results are important for establishing a baseline of the species distributions in South African swamp wetlands for future monitoring and control efforts

Conservation science for common ground: developing the necessary tools to manage livestock grazing pressure in Bale Mountains National Park, Ethiopia

One of the greatest proximate threats facing biodiversity is habitat change as a result of the combined effects of agricultural development and livestock grazing. Extensive livestock systems are increasingly competing with wildlife for access to land and natural resources in African rangelands. Ethiopia has the highest numbers of livestock in Africa with most livestock production taking place in highland systems. The Bale Mountains contain the largest extent of afroalpine habitat in Africa and are the most important conservation area in Ethiopia as one of thirty-four Conservation International Biodiversity Hotspots. The Bale Mountains National Park was established forty years ago to protect the endemic, and rodent-specialist Ethiopian wolf (Canis simensis) and the afroalpine habitats upon which they depend. I use a 21 year time-series of livestock counts in the park to detect changes in the Oromo traditional livestock production system or godantu. I show that a seasonal transhumant livestock production regime, akin to godantu, only appears to persist in the Web valley today and I also find some evidence that the type of livestock is changing with smaller stock, such as sheep and goats, being more frequently kept. Despite reportedly growing numbers of households in the Web valley, I do not detect an overall increase in livestock numbers, suggesting that the area may have reached its carrying capacity in terms of livestock. In contrast, the number of livestock on the Sanetti Plateau increased over the monitoring period, including the remote and inhospitable western section of the plateau. Furthermore, I detect an increase in the risk of contact and disease transmission between Ethiopian wolves and free-roaming dogs in wolf optimal habitats. I subsequently estimate, through the use of transects, the densities of livestock in the Web valley, Morebawa and Sanetti and calculate the ratio of observed to maximum sustainable livestock density (based on rainfall and vegetation productivity). The conservative results suggest that the Web valley and Morebawa are overstocked given the rangeland predicted productivity for those areas, and that the problem of overstocking is at its worst during the dry season. I then establish critical relationships between vegetation conditions, livestock grazing pressure and rodent populations (Tachyoryctes macrocephalus, Lophuromys melanonyx and Arvicanthis blicki) in the afroalpine, under both natural and controlled experimental conditions. Rodent biomass declines as the livestock index increases along a natural grazing gradient, but rodents‟ body condition, use of the habitat or breeding ecology and most vegetation variables measured do not significantly vary across the livestock grazing gradient. Rodent populations do respond to the experimental removal of livestock inside exclosures, although this response is site and species-specific, and I find some evidence that these responses are concurrent with changes in the vegetation. Grazed plots have higher plant species richness and diversity compared to the exclosure sites which harbour reduced bareground cover and taller vegetation. Differences among rodent species in their responses to grazing may be mediated by interaction between the direct effects of grazing on habitat quality and species-specific habitat requirements, although the specific mechanism of this interaction could not be tested. Livestock may negatively affect rodents by increasing their predation risk (through removing vegetation cover), by reducing the soil suitability for maintaining burrow systems (through trampling) or, less likely, by competing for food resources. A series of simple dynamic food chain models are developed to explore the interactions between Ethiopian wolves, rodents and vegetation and how they may be affected by increasing levels of livestock grazing. I also explore how predictions made about these trophic dynamics are affected by the type of functional response linking the different levels. The models suggest that the pastures of the Web valley and Morebawa are likely to be incapable of maintaining wolves at current livestock densities, while the Sanetti plateau may be able to sustain only slight increases in livestock density before tipping into a trophic configuration unable to sustain wolves. This model is a first step in assessing the seriousness of conflict between pastoralists and wildlife in BMNP. Resource selection functions are developed and validated for cattle and sheep/goats grazing in the Bale afroalpine in an attempt to understand some of the drivers behind the heterogeneous use of the landscape by livestock. Habitat use by livestock is focused on lower-lying pastures in the vicinity of water sources (rivers or mineral springs). Only cattle strongly select for/against particular vegetation types. The probability of habitat use is also linked to the distance from the nearest villages. The models developed highlight a strong association between livestock use and rodent biomass in Morebawa and Eastern Sanetti, suggesting that livestock grazing poses a threat to Ethiopian wolves‟ persistence in marginal habitats in which rodent availability is already limited. Furthermore, the concentration of livestock around water sources has serious implications for the degradation of the park‟s hydrological system and the livelihoods and food security of the millions of people living in the dependent lowlands. Integrating research and practice is a fundamental challenge for conservation. I discuss how the methodological tools developed and the insights gained into the dynamics of the afroalpine system can contribute to the management of livestock grazing pressure in Bale Mountains National Park and highlight gaps in the knowledge of the afroalpine ecosystem where more research is needed

The Hindu Kush Himalaya Assessment

This open access volume is the first comprehensive assessment of the Hindu Kush Himalaya (HKH) region. It comprises important scientific research on the social, economic, and environmental pillars of sustainable mountain development and will serve as a basis for evidence-based decision-making to safeguard the environment and advance people’s well-being. The compiled content is based on the collective knowledge of over 300 leading researchers, experts and policymakers, brought together by the Hindu Kush Himalayan Monitoring and Assessment Programme (HIMAP) under the coordination of the International Centre for Integrated Mountain Development (ICIMOD). This assessment was conducted between 2013 and 2017 as the first of a series of monitoring and assessment reports, under the guidance of the HIMAP Steering Committee: Eklabya Sharma (ICIMOD), Atiq Raman (Bangladesh), Yuba Raj Khatiwada (Nepal), Linxiu Zhang (China), Surendra Pratap Singh (India), Tandong Yao (China) and David Molden (ICIMOD and Chair of the HIMAP SC). This First HKH Assessment Report consists of 16 chapters, which comprehensively assess the current state of knowledge of the HKH region, increase the understanding of various drivers of change and their impacts, address critical data gaps and develop a set of evidence-based and actionable policy solutions and recommendations. These are linked to nine mountain priorities for the mountains and people of the HKH consistent with the Sustainable Development Goals. This book is a must-read for policy makers, academics and students interested in this important region and an essentially important resource for contributors to global assessments such as the IPCC reports. ; Constitutes the first comprehensive assessment of the Hindu Kush Himalaya region, providing an authoritative overview of the region Assembles the collective knowledge of over 300 leading researchers, practitioners, experts, and policymakers Combines the current state of knowledge of the Hindu Kush Himalaya region in one volume Offers Open Access to a set of practically oriented policy recommendation

Meeting Future Energy Needs in the Hindu Kush Himalaya

As mentioned in earlier chapters, the HKH regions form the entirety of some countries, a major part of other countries, and a small percentage of yet others. Because of this, when we speak about meeting the energy needs of the HKH region we need to be clear that we are not necessarily talking about the countries that host the HKH, but the clearly delineated mountainous regions that form the HKH within these countries. It then immediately becomes clear that energy provisioning has to be done in a mountain context characterized by low densities of population, low incomes, dispersed populations, grossly underdeveloped markets, low capabilities, and poor economies of scale. In other words, the energy policies and strategies for the HKH region have to be specific to these mountain contexts