nasa-gesdisc/es-publications-researchareas huggingface dataset:
Sea-level rise from land subsidence in major coastal cities (2022)

Coastal land can be lost at rapid rates due to relative sea-level rise (RSLR) resulting from local land subsidence. However, the comparative severity of local land subsidence is unknown due to high spatial variabilities and difficulties reconciling observations across localities. Here we provide self-consistent, high spatial resolution relative local land subsidence (RLLS) velocities derived from Interferometric Synthetic Aperture Radar for the 48 largest coastal cities, which represent 20% of the global urban population. We show that cities experiencing the fastest RLLS are concentrated in Asia. RLLS is also more variable across the 48 cities (16.2 to 1.1 mm per year) than the Intergovernmental Panel on Climate Change estimations of vertical land motion (5.2 to 4.9 mm per year). With our standardized method, the identification of relative vulnerabilities to RLLS and comparisons of RSLR effects accounting for RLLS are now possible across cities worldwide. These will better inform sustainable urban planning and future adaptation strategies in coastal cities.

Research areas: Land Surface/Agriculture Indicators
Natural City Growth in the People's Republic of China (2017)

This paper analyzes the growth of Metropolitan Statistical Areas in the PRC between 1992 and 2013 by focusing on the night-light radiancea measure of economic activityof connected subcity places that we refer to as a natural city. This paper documents the rapid growth of natural cities in the PRC between 1992 and 2009 that was followed by a slight reduction in the size of some natural cities between 2010 and 2013 in the aftermath of the recent global financial crisis. Institutional factorssuch as the location of places near Special Economic Zones, the ramifications of legal migration from rural to urban areas following reforms to the hukou (household registration) system, and infrastructure accessibilityare found to be important drivers of the integration of peripheral places into natural cities.

Research areas: Habitat Conversion/Fragmentation
Effects of conservation policy on China's forest recovery (2016)

Chinas forest cover exhibited a positive trend that was significantly related with the implementation of a national conservation policy.
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            Forest loss is one of the most pervasive land surface transformations on Earth, with drastic effects on global climate, ecosystems, and human well-being. As part of biodiversity conservation and climate change mitigation efforts, many countries, including China, have been implementing large-scale policies to conserve and restore forests. However, little is known about the effectiveness of these policies, and information on Chinas forest dynamics at the national level has mainly relied on official statistics. In response to international calls for improved reliability and transparency of information on biodiversity conservation and climate change mitigation efforts, it is crucial to independently verify government statistics. Furthermore, if forest recovery is verified, it is essential to assess the degree to which this recovery is attributable to policy, within the context of other relevant factors. We assess the dynamics of forest cover in China between 2000 and 2010 and evaluate the effectiveness of one of the largest forest conservation programs in the worldthe Natural Forest Conservation Program (NFCP). Results indicate that forest cover has significantly increased in around 1.6% of Chinas territory and that the areas exhibiting forest gain experienced a combined increase in net primary productivity (ca. 0.9 Tg of carbon). Among the variables evaluated at county level, the NFCP exhibited a significantly positive relation with forest gain, whereas reduction in rural labor showed a negative relationship with both forest loss and gain. Findings such as these have global implications for forest conservation and climate change mitigation efforts.

Research areas: Land Surface/Agriculture Indicators
Status of road ecology research in Africa: do we understand the impacts of roads, and how to successfully mitigate them? (2019)

Across Africa, transport infrastructure, including roads, is being built in over 30 planned development corridors that are likely to have major impacts on remaining natural habitats and associated biodiversity. Linked to this is the projected increase in human population size, which is predicted to grow by 1.3 billion people by 2050. Road ecology is the study of the ecological effects (both positive and negative) of roads and traffic but is perceived to be under-researched in Africa. In this context, we undertook a systematic review of road ecology research in Africa to understand the geographic and taxonomic scope of work undertaken to date, as well as recommendations for reducing the impacts of roads. We discovered 210 road ecology publications from Africa (published between 1954 and 2016), with most publications from the more affluent and politically stable regions (e.g., southern and East Africa). We found more publications than expected, with relevant research concealed within studies whose primary focus was on other topics. Most publications (1) focused on single species, and in particular on mammals (where chimpanzees and forest elephants were most studied); (2) were from southern Africa; and 3) were conducted in the grassland and savannah biome and the tropical and subtropical forest biome. Most publications examined the direct impacts of roads, in particular wildlife-vehicle collisions. Only one-third of the publications provided some form of recommendation for intervention to reduce or mitigate the impacts of roads, based on evidence from the publication. Most recommended interventions related to ecosystem or natural process recreation, as well as site and area stewardship. Gaps and future directions for research include rigorous testing of measures to mitigate the impacts of roads, inclusion of traffic monitoring in studies, understanding the impacts of upgrading roads, and exploring livelihood, economic and moral incentives and education and training as potential interventions for reducing the impacts of roads. Our review has highlighted the need for accelerating the study of the impacts of roads on natural habitats and biodiversity, in light of planned large-scale infrastructure development, and especially the study of appropriate mitigation measures that can be rigorously assessed and implemented before and during construction and upgrading of roads in Africa.

Research areas: Ecosystems
Decades of urban growth and development on the Asian megadeltas (2018)

The current and ongoing expansion of urban areas worldwide represents the largest mass migration in human history. It is well known that the world's coastal zones are associated with large and growing concentrations of population, urban development and economic activity. Among coastal environments, deltas have long been recognized for both benefits and hazards. This is particularly true on the Asian megadeltas, where the majority of the world's deltaic populations reside. Current trends in urban migration, combined with demographic momentum suggest that the already large populations on the Asian megadeltas will continue to grow. In this study, we combine recently released gridded population density (circa 2010) with a newly developed night light change product (1992 to 2012) and a digital elevation model to quantify the spatial distribution of population and development on the nine Asian megadeltas. Bivariate distributions of population as functions of elevation and coastal proximity quantify potential exposure of deltaic populations to flood and coastal hazards. Comparison of these distributions for the Asian megadeltas show very different patterns of habitation with peak population elevations ranging from 2 to 11 m above sea level over a wide range of coastal proximities. Over all nine megadeltas, over 174 million people reside below a peak population elevation of 7 m. Changes in the spatial extent of anthropogenic night light from 1992 to 2012 show widely varying extents and changes of lighted urban development. All of the deltas except the Indus show the greatest increases in night light brightness occurring at elevations &lt;10 m. At global and continental scales, growth of settlements of all sizes takes the form of evolving spatial networks of development. Spatial networks of lighted urban development in Asia show power law scaling properties consistent with other continents, but much higher rates of growth. The three largest networks of development in China all occur on deltas and adjacent lowlands, and are growing faster than the rest of the urban network in China. Since 2000, the Huanghe Delta + North China Plain urban network has surpassed the Japanese urban network in size and may soon connect with the Changjiang Delta + Yangtze River urban network to form the largest conurbation in Asia.

Research areas: Habitat Conversion/Fragmentation
Assessing the sustainability of urbanization at the sub-national level: The Ecological Footprint and Biocapacity accounts of the Budapest Metropolitan Region, Hungary (2022)

The growing concentration of people and wealth often results in imbalances of resource consumption and carrying capacity, therefore, the sustainability assessment of urbanization can offer an important basis for global sustainable transition. This paper aims to provide an analysis of the environmental sustainability of urbanization in Hungary focusing on the long-term changes of ecological footprint and biocapacity at the sub-national level, with a special attention to the Budapest Metropolitan Region (BMR). During the research a hybrid method considering an input-output model and household consumption data was used for the calculation of regional ecological footprint, whereas biocapacity was measured on the basis of land use data. Findings suggest, that even though the ecological deficit of the country has been gradually decreasing since the early 2000s, due to a shrinking population and increasing biocapacity, the ecological overshoot is still significant in the case of Budapest and its agglomeration (30 fold and 2.4 fold respectively). The unsustainability of the BMR is caused partly by demographic factors (7.6% population growth as opposed to the the 7.7% decrease in the countryside) and partly by rising per capita ecological footprint values (especially in the agglomeration from 2.73 to 2.92 gha/capita), which are not balanced by biocapacity on the supply side. This research concluded that policy makers in ageing societies with a highly centralized urban system like Hungary should launch programmes targeted specifically to primary metropolitan areas to improve environmental efficiency and encourage people to change their consumption behaviour.

Research areas: Habitat Conversion/Fragmentation
Assessing the ecological footprint and biocapacity of Portuguese cities: Critical results for environmental awareness and local management (2020)

The unsustainable use of our planet's resources needs to be tackled from different angles and multiple levels of governance. As the human population urbanizes, having access to reliable, cross-cutting, quantitative city-level sustainability metrics is key to understanding the environmental impacts of urban dwellers and the role cities can play in the 21st century sustainability challenge. Framing the environmental pillar of urban sustainability with an overarching metric like the Ecological Footprint informs stakeholders and citizens about a city's overall pressure on the biosphere. In Portugal, six cities established a pioneering collaborative project to guide their transition to sustainability and support city governance; this paper presents the results of the first phase of the project. We tracked annual demand for natural resources and ecological services by the city residents and compared it against the carrying capacity of the cities' ecological assets. We then assessed the ability of this new data to increase local environmental awareness and support local public policies in Portugal and elsewhere. Lessons from this study inform the ongoing debate on the Ecological Footprint's usefulness as sustainability metric for cities, and point to specific policy insights for managing key consumption sectors and reaching key targets such as the UN SDGs.

Research areas: Habitat Conversion/Fragmentation
Forest thinning in ponderosa pines increases carbon use efficiency and energy flow from primary producers to primary consumers (2021)

A better understanding of carbon use efficiency (CUE) and carbon allocation during disturbance is critical to improve simulations of the global carbon cycle and understanding future climate impacts. Forest thinning of high stem density, high elevation dry western US forests is becoming more common to reduce severe fire danger but there are uncertainties about how forest thinning may impact forest CUE, carbon allocation and energy flow through the food chain. In three, quarter ha stands with similar soils, elevation and climate along a forest thinning gradient near Flagstaff (AZ), we measured total net primary production (NPP of wood, fine root, and leaves), total autotrophic respiration (R<SUB>a</SUB> of wood, rhizosphere, and canopy respiration), gross primary production (GPP = NPP + R<SUB>a</SUB>) and large mammal herbivory (with camera traps and dung counts) over a ∼2 year period. We found strong seasonality in all carbon cycling variables and herbivory, peaking during the warm, wet monsoon period. Carbon was produced more efficiently in the thinned stands, with carbon use efficiency (CUE = NPP/GPP) of ∼0.63, versus the unthinned stand with CUE of 0.38. GPP was similar in the two thinned stands (∼3.5 Mg C ha<SUP>−1</SUP> yr<SUP>−1</SUP>) but was about 30% greater in the unthinned stands (5.0 Mg C ha<SUP>−1</SUP> yr<SUP>−1</SUP>). Finally, the thinned stand had higher understory NPP, large herbivore consumption and had triple the total energy going into primary consumers. Overall, the thinning, and the return to a more natural prefire suppression forest structure, increased the CUE and energy flow from primary producers to primary consumers.

Research areas: Habitat Conversion/Fragmentation, Wildfires
Downscaling SSP-consistent global spatial urban land projections from 1/8-degree to 1-km resolution 20002100 (2021)

Long-term, spatial urban land projections that simultaneously offer global coverage and local-scale empirical accuracy are rare. Recently a set of such projections was produced using data-science-based simulations and the Shared Socioeconomic Pathways (SSPs). These projections update at decadal time intervals from 2000 to 2100 with a spatial resolution of 1/8 degree, while many socio-environmental studies customarily run their analysis and modelling at finer spatial resolutions, e.g. 1-km. Here we develop and validate an algorithm to downscale the 1/8-degree spatial urban land projections to the 1-km resolution. The algorithm uses an iterative process to allocate the decadal amount of urban land expansion originally projected for each 1/8-degree grid to its constituent 1-km grids. The results are a set of global maps showing urban land fractions at the 1-km resolution, updated at decadal intervals from 2000 to 2100, under five different urban land expansion scenarios consistent with the SSPs. The data can support studies of potential interactions between future urbanization and environmental changes across spatial and temporal scales.

Research areas: Habitat Conversion/Fragmentation
Engineered bioclimatic responses in ancient settlements: a case study (2021)

The Mandya district of Karnataka, India, houses a unique Jain settlement constructed about 1000 years ago. Recent excavations by the Archaeological Survey of India (ASI) indicate a high degree of engineering skills among the builders of this settlement. Adapting to heat-stresses in a region where the Monsoons often failed was and is still a matter of concern. Ingenious methods were adopted to modulate bioclimatic responses to maintain thermal comfort indices. The Aretippurians used composite building fabrics which modulated heat transfer to the interiors. Indeed, the thermal transmittances for these composite fabrics were low to moderate for both the temple complexes as well as the dormitories; these were 0.27 Wm1K1 and 0.23 Wm1K1, respectively. A site visit revealed that a unique and engineered micro-climate was also made to prevail on this hilltop settlement housing several hundred Jain settlers. A granite skirted reservoir was indeed the piece-de-resistance promoting hydraulic air-conditioning for eight months of the year around the premises with copious winds blowing over a large and exposed rain-fed reservoir. This fanned chilled air across the open plan temples, courtyards, and lived-in areas. This paper explores bioclimatic responses for around 120 residents to the prevailing indoor settings modulated by an engineered microclimate. This was possible because of the staggered layout, unique building forms, use of mixed building fabric, and carefully chosen glazing ratios which yielded salubrious settings. Clearly, this entailed a complex interplay between the intercepted solar insolation, structure-driven turbulence, and the transfer of heat across the original composite walls within and around the complex, requiring a systematic experimental as well as modelling study. The experimental part of the project involved the calculation of the thermal transmittivity across the walls made up of fired bricks, granite, and limestone, and the theoretical part involved the use of appropriate software to reconstruct air flow and heat distribution across floors, walls, and ceilings to proxy the original flow pattern yielding the comfortable PMV (predicted mean vote) and PET (physiological equivalent temperature) values within these premises. This exercise may well lead to further explorations on indoor comfort adaptations in tropical settings with the use of many edifying vernacular idioms in ancient settlements which prevail even in modern layouts.

Research areas: Heat
US national maps attributing forest change: 1986–2010 (2020)

National monitoring of forestlands and the processes causing canopy cover loss, be they abrupt or gradual, partial or stand clearing, temporary (disturbance) or persisting (deforestation), are necessary at fine scales to inform management, science and policy. This study utilizes the Landsat archive and an ensemble of disturbance algorithms to produce maps attributing event type and timing to >258 million ha of contiguous Unites States forested ecosystems (19862010). Nationally, 75.95 million forest ha (759,531 km2) experienced change, with 80.6% attributed to removals, 12.4% to wildfire, 4.7% to stress and 2.2% to conversion. Between regions, the relative amounts and rates of removals, wildfire, stress and conversion varied substantially. The removal class had 82.3% (0.01 S.E.) users and 72.2% (0.02 S.E.) producers accuracy. A survey of available national attribution datasets, from the data users perspective, of scale, relevant processes and ecological depth suggests knowledge gaps remain.

Research areas: Habitat Conversion/Fragmentation
Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda (2022)

Trees sustain livelihoods and mitigate climate change but a predominance of trees outside forests and limited resources make it difficult for many tropical countries to conduct automated nation-wide inventories. Here, we propose an approach to map the carbon stock of each individual overstory tree at the national scale of Rwanda using aerial imagery from 2008 and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas and 17% in plantations, accounting for 48.6% of the national aboveground carbon stocks. Natural forests cover 11% of the total tree count and 51.4% of the national carbon stocks, with an overall carbon stock uncertainty of 16.9%. The mapping of all trees allows partitioning to any landscapes classification and is urgently needed for effective planning and monitoring of restoration activities as well as for optimization of carbon sequestration, biodiversity and economic benefits of trees.

Research areas: Land Surface/Agriculture Indicators
A framework for large-scale mapping of human settlement extent from Sentinel-2 images via fully convolutional neural networks (2020)

Human settlement extent (HSE) information is a valuable indicator of world-wide urbanization as well as the resulting human pressure on the natural environment. Therefore, mapping HSE is critical for various environmental issues at local, regional, and even global scales. This paper presents a deep-learning-based framework to automatically map HSE from multi-spectral Sentinel-2 data using regionally available geo-products as training labels. A straightforward, simple, yet effective fully convolutional network-based architecture, Sen2HSE, is implemented as an example for semantic segmentation within the framework. The framework is validated against both manually labelled checking points distributed evenly over the test areas, and the OpenStreetMap building layer. The HSE mapping results were extensively compared to several baseline products in order to thoroughly evaluate the effectiveness of the proposed HSE mapping framework. The HSE mapping power is consistently demonstrated over 10 representative areas across the world. We also present one regional-scale and one country-wide HSE mapping example from our framework to show the potential for upscaling. The results of this study contribute to the generalization of the applicability of CNN-based approaches for large-scale urban mapping to cases where no up-to-date and accurate ground truth is available, as well as the subsequent monitor of global urbanization.

Research areas: Habitat Conversion/Fragmentation
Monitoring tropical forest degradation using spectral unmixing and Landsat time series analysis (2020)

Tropical forest loss currently contributes 5 to 15% of anthropogenic carbon emissions to the atmosphere. The large uncertainty in emissions estimates is a consequence of many factors, including differences in definitions of forests and degradation, as well as estimation methodologies. However, a primary factor driving uncertainty is an inability to properly account for forest degradation. While remote sensing offers the only practical way of monitoring forest disturbances over large areas, and despite recent improvements in data quality and quantity and processing techniques, remote sensing approaches are still limited in their ability to detect forest degradation. In this paper, a system is presented that uses time series of Landsat data and spectral mixture analysis to detect both degradation and deforestation in forested landscapes. The Landsat data are transformed into spectral endmember fractions and are used to calculate the Normalized Degradation Fraction Index (NDFI; Souza et al., 2005). The spectrally unmixed data are used for disturbance monitoring and land cover classification via time series analysis. To assess the performance of the system, maps of deforestation and degradation were used to stratify the study area for collection of sample data to which unbiased estimators were applied to produce accuracy and area estimates of degradation and deforestation from 1990 to 2013. The approach extends previous research in spectral mixture analysis for identifying forest degradation to the temporal domain. The method was applied using the Google Earth Engine and tested in the Brazilian State of Rondonia. Degradation and deforestation were mapped with 88.0% and 93.3% User's Accuracy, and 68.1% and 85.3% Producer's Accuracy. Area estimates of degradation and deforestation were produced with margins of error of 13.9% and 5.3%, respectively, over the 24 year time period. These results indicate that for Rondonia a decreasing trend in deforestation after 2004 corresponds to an increase in degradation during the same time period.

Research areas: Habitat Conversion/Fragmentation