nasa-gesdisc/es-publications-researchareas huggingface dataset:
Physics-based simulations of multiple natural hazards for risk-sensitive planning and decision making in expanding urban regions (2023)

Rapid urban expansion in many parts of the world is leading to increased exposure to natural hazards, exacerbated by climate change. The use of physics-based models of natural hazards in risk-informed planning and decision-making frameworks may provide an improved understanding of site-specific hazard scenarios, allowing various decision makers to more accurately consider the consequences of their decisions on risks in future development. We present results of physics-based simulations of flood, earthquake, and debris flow scenarios in a virtual urban testbed. The effect of climate change, in terms of increasing rainfall intensity, is also incorporated into some of the considered hazard scenarios. We use our results to highlight the importance of using physics-based models applied to high-resolution urban plans to provide dynamic hazard information at the building level for different development options. Furthermore, our results demonstrate that including building elevations into digital elevation models is crucial for predicting the routing of hazardous flows through future urban landscapes. We show that simulations of multiple, independent hazards can assist with the identification of developing urban regions that are vulnerable to potential multi-hazard events. This information can direct further modelling to provide decision-makers with insights into potential multi-hazard events. Finally, we reflect on how information derived from physics-based hazard models can be effectively used in risk-sensitive planning and decision-making.

Research areas: Habitat Conversion/Fragmentation
Spatial distribution and opportunity mapping: Applicability of evidence-based policy implications in Punjab using remote sensing and global products (2019)

Evidence-based policy-making generally applies scientifically rigorous methods to arrive at location-based decisions for public service facilities. The provision of equal opportunities is becoming increasingly difficult due to urbanization. Most studies examined the inequality in context with social indicators and few empirical studies focused on the distribution of opportunities in the form of opportunity indices. This study aims to examine the spatial distribution of public facilities in 36 districts of Punjab province, Pakistan. We develop a composite opportunity index from various social indicators retrieved from household surveys. Using global and local Moran's indices, we analyzed the social indicators along three lines, i.e., health, education, and civic facilities. We investigated inequalities in opportunities through its various factors derived from NOAA nighttime light data and other global data sets. Results reveal that the allocation of facilities is clustered in north and north-eastern regions of Punjab while southern areas are having large inequality of opportunities in accessing basic services. The inequalities are driven particularly in terms of poverty, road accessibility, and urban infrastructure depicted through nighttime data, while it is not driven by population. The evidence-based method in this research will help implicate policies through prioritizing resource allocation in terms of space and equal opportunities.

Research areas: Habitat Conversion/Fragmentation
Identification of Priority Areas for Improving Urban Ecological Carrying Capacity: Based on SupplyDemand Matching of Ecosystem Services (2022)

As the most concentrated area of human activities, cities consume many natural resources and discharge a large amount of waste into the natural environment, which has a huge environmental impact. Most of the ecological and environmental problems, such as environmental pollution, global climate change, and loss of biodiversity, are related to urban systems. How to coordinate urban development with the urban ecological carrying capacity is related to the destiny of the city itself, and also to whether its surrounding areas can successfully achieve the goal of high environmental quality and sustainable development. At present, the theory and methods of urban ecological carrying capacity research are relatively new, which has caused problems for policy makers in practical applications. This paper proposes a theoretical framework for urban ecological carrying capacity assessment based on the analysis of ecosystem services supply and demand. Combined with multi-source spatial data and spatial model methods, the supply and demand of ecosystem services were spatially quantified. The capital city of China, Beijing, was the case study area for this research. The spatial differentiation of the supplydemand relationship of ecosystem services is formed. The priority areas for ecological carrying capacity improvement at pixel scale and at the administrative level are obtained, respectively. The results show that the first priority area is concentrated in the center of the urban area, accounting for 31.11% of the total area of Beijing. According to the secondary zone and the specific ecosystem service type, the ecological carrying capacity improvement strategy of different zones is proposed. This study provides a new perspective for investigating urban ecological carrying capacity and for identifying the priority areas for ecological carrying capacity improvement, and helps the policy-makers to design tailored policy actions.

Research areas: Habitat Conversion/Fragmentation
Multi-criteria modeling for land suitability evaluation of the urban greenbelts in Iran (2021)

In this study, a multi-criteria model was considered for land suitability evaluation (LSE) of the urban greenbelt (UGB) in 25 major cities of Iran. On this basis, the greenbelt suitability index (SI) and the environmental change index (Y) of the urban sprawl were estimated for the present and future periods. The research modeling was constructed based on some global datasets and factors (i.e., elevation, slope, soil, land use, land cover, agriculture, precipitation, river and road networks, and settlement sprawl) to evaluate greenbelt suitability. Spatial modeling revealed the highest greenbelt suitability (with SI values above 0.8) for the hinterlands of eight cities, including Hamadan, Zanjan, Sanandaj, Rasht, Sari, Gorgan, Qazvin, and Kermanshah. Results also revealed the estimated Y values of the urban sprawl between 0.07 and 2.32 for all case studies, relating to a mean sprawl disturbance (X) of 0.27 in the status quo (2018). In the probable future time (2030), the Y values were estimated between 0.68 and 5.89 with a mean sprawl disturbance (X) of 0.73 for all case studies, revealing a large increase in the thresholds of the environmental change index. The increase of the Y values in the future time indicates the necessity of new suitable UGB plans with new regulation and optimum to curb the urban land use degradation during future developments.

Research areas: Habitat Conversion/Fragmentation
Relationships between urban development level and urban vegetation states: A global perspective (2019)

Urban development exerts both benign and malignant impacts on urban vegetation. Mixed results have been reported regarding the responses of urban vegetation to urbanization. However, these results are limited by both sample size and location. It is essential to conduct global-scale research in urban areas with various development levels in order to acquire a more comprehensive understanding of the relationship between urban development and vegetation states. Thus, we firstly created an urban development score to quantify the development intensity of 68,651 urban areas across 14 biomes through using nighttime light and population density data. We then classified each urban area into a relative development level according to the score and biome. Based on the urban development scores and levels, we determined the relationship between urban development and vegetation states, as represented by the remote-sensed vegetation index. Findings suggested that four distinct types of relationships exist across biomes, namely positive, convex (positive then negative), non-significant, and negative. The positive corrections were commonly found between urban development and vegetation states especially in less-productive biomes such as deserts and open shrublands. However, the positive correlations diminished and eventually turned negative as urban areas became more developed and/or were located in more productive biomes. Turning points of the relationship between urban development and vegetation states were detected in four biomes that have moderate productivity. Completely negative relationships were only found in highly productive tropical and temperate biomes. The results of this study call for a closer examination of the altered urban vegetation states as the result of human engineering.

Research areas: Habitat Conversion/Fragmentation
Total carbon accumulation in a tropical forest landscape (2012)

Regrowing tropical forests worldwide sequester important amounts of carbon and restore part of the C emissions emitted by deforestation. However, there are large uncertainties concerning the rates of carbon accumulation after the abandonment of agricultural and pasture land. We report here accumulation of total carbon stocks (TCS) in a chronosequence of secondary forests at a mid-elevation landscape (900-1200 m asl) in the Andean mountains of Colombia.

Research areas: Habitat Conversion/Fragmentation
An Improved Forest Structure Data Set for Europe (2022)

Today, European forests face many challenges but also offer opportunities, such as climate change mitigation, provision of renewable resources, energy and other ecosystem services. Large-scale analyses to assess these opportunities are hindered by the lack of a consistent, spatial and accessible forest structure data. This study presents a freely available pan-European forest structure data set. Building on our previous work, we used data from six additional countries and consider now ten key forest stand variables. Harmonized inventory data from 16 European countries were used in combination with remote sensing data and a gap-filling algorithm to produce this consistent and comparable forest structure data set across European forests. We showed how land cover data can be used to scale inventory data to a higher resolution which in turn ensures a consistent data structure across sub-regional, country and European forest assessments. Cross validation and comparison with published country statistics of the Food and Agriculture Organization (FAO) indicate that the chosen methodology is able to produce robust and accurate forest structure data across Europe, even for areas where no inventory data were available.

Research areas: Land Surface/Agriculture Indicators
Superfund cleanup time and community characteristics: A survival analysis (2022)

This paper investigates the correlation of socioeconomic characteristics of communities close to Superfund sites with the duration of cleanup using spatial survival analysis with frailty effects. Census-tract-level data is used to achieve a more accurate representation of affected areas. We find evidence of slower cleanup in areas with higher minority population, particularly when controlling for EPA Region. Additionally, sites that are more costly, have high assessed hazards, and have a Community Action Group are associated with longer cleanup times, while sites which are federally owned and have low assessed hazards are associated with shorter cleanup times.

Research areas: Environmental Impacts
Review of the sub-Saharan African small hydropower situation (2018)

The significance of renewable energy sources, such as generation of viable output from small hydropower (SHP), has been of great concern with several measures being taken to alleviate the serious shortfall of electricity supply in rural areas of sub-Saharan Africa. SHP can play very important roles in the electrification of rural areas. The potential for SHP is typically found away from the more populous areas and is a very suitable energy source for the purpose of rural electrification. It can be used either as standalone power source or as a hybrid system with other energy sources. Depletion of fossil fuels and inability to meet the rising demand for electricity are among the hindrances to the economic development of sub-Saharan Africa. This paper focuses on SHP situation in sub-Saharan Africa, especially off-the-grid areas where the central grid is inaccessible. There is a need to establish widespread SHP turbines to overcome this situation. This paper draws conclusions on the importance of designing and implementing SHP turbines for sub-Saharan Africa. It also highlights small-scale hydropower as one of the most cost-effective energy technologies to be considered for electrification, and proposes guidelines to help future implementation of this technology in a better way.

Research areas: Energy Production/Use
Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways (2016)

The projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatially explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.

Research areas: Habitat Conversion/Fragmentation
Nitrogen‐fixing trees have no net effect on forest growth in the coterminous United States (2021)

Nitrogen (N)‑fixing trees fulfil a unique and important biogeochemical role in forests through their ability to convert atmospheric N2 gas to plant‑available N. Due to their high N fixation rates, it is often assumed that N‑fixing trees facilitate neighbouring trees and enhance forest growth. This assumption is supported by some local studies but contradicted by others, leaving the overall effect of N‑fixing trees on forest growth unresolved. Here we use the US Forest Service's Forest Inventory and Analysis database to evaluate the effects of N‑fixing trees on plot‑scale basal area change and individual‑scale neighbouring tree demography across the coterminous US. First we discuss the average trends. At the plot and individual scales, N‑fixing trees do not affect the relative growth rates of neighbouring trees, but they facilitate recruitment and inhibit survival rates, suggesting that they are drivers of tree turnover in the coterminous US. At the plot scale, N‑fixing trees facilitate the basal area change of non‑fixing neighbours. In addition to the average trends, there is wide variation in the effect of N‑fixing trees on forest growth, ranging from strong facilitation to strong inhibition. This variation does not show a clear geographical pattern, though it does vary with certain local factors. N‑fixing trees facilitate forest growth when they are likely to be less competitive: under high N deposition and high soil moisture or when neighbouring trees occupy different niches (e.g. high foliar C:N trees and non‑fixing trees). Synthesis. N‑fixing trees have highly variable effects on forest growth and neighbour demographics across the coterminous US. This suggests that the effect of N‑fixing trees on forest development and carbon storage depends on local factors, which may help reconcile the conflicting results found in previous localized studies on the effect of N‑fixing trees on forest growth.

Research areas: Land Surface/Agriculture Indicators
Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon (2019)

Brazilian Amazon forests contain a large stock of carbon that could be released into the atmosphere as a result of land use and cover change. To quantify the carbon stocks, Brazil has forest inventory plots from different sources, but they are unstandardized and not always available to the scientific community. Considering the Brazilian Amazon extension, the use of remote sensing, combined with forest inventory plots, is one of the best options to estimate forest aboveground biomass (AGB). Nevertheless, the combination of limited forest inventory data and different remote sensing products has resulted in significant differences in the spatial distribution of AGB estimates. This study evaluates the spatial coverage of AGB data (forest inventory plots, AGB maps and remote sensing products) in undisturbed forests in the Brazilian Amazon. Additionally, we analyze the interconnection between these data and AGB stakeholders producing the information. Specifically, we provide the first benchmark of the existing field plots in terms of their size, frequency, and spatial distribution.

Research areas: Land Surface/Agriculture Indicators
Forest expansion dominates China's land carbon sink since 1980 (2022)

Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased Chinas reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9  0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting.

Research areas: Land Surface/Agriculture Indicators, Habitat Conversion/Fragmentation
High-Resolution Global Maps of 21st-Century Forest Cover Change (2013)

Forests in Flux
            
              Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others.
              
                Hansen
                et al.
              
              (p.
              850
              ) examined global Landsat data at a 30-meter spatial resolution to characterize forest extent, loss, and gain from 2000 to 2012. Globally, 2.3 million square kilometers of forest were lost during the 12-year study period and 0.8 million square kilometers of new forest were gained. The tropics exhibited both the greatest losses and the greatest gains (through regrowth and plantation), with losses outstripping gains.
            
          , 
            Landsat data reveals details of forest losses and gains across the globe on an annual basis from 2000 to 2012.
          , 
            Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazils well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

Research areas: Land Surface/Agriculture Indicators, Habitat Conversion/Fragmentation