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The USDA’s definition of food deserts, which is based on the distance to store and a neighborhood’s income, seems to be inadequate to explain the food security status of a neighborhood. Thus, an exploratory factor analysis (EFA) was conducted to explore the underlying structures behind the 11 measures of a neighborhood's characteristics, which, in turn, describes a neighborhood's food insecurity. The studied neighborhoods were the census tracts in the lower 48 states of the U.S. The EFA systematically grouped the 11 characteristics into two factors (i.e., socioeconomic and demographic) determining neighborhood vulnerability. Both factors suggest that the neighborhoods in the South have a high vulnerability that could influence the number and type of food stores or prospects of new food stores in those neighborhoods. Based on the factor structure revealed by the EFA, the Neighborhood Food Insecurity Index (NFII) was created. The NFII measures the relative food vulnerability of every U.S. census tract affecting its residents' ability to access a healthy food provider. The index indicates that about 43 million (13.14%) people in the U.S. live in neighborhoods with high food vulnerability. The index also shows that regionally, the South had the greatest percentage of populations living in high food-vulnerable neighborhoods followed by the West, Midwest, and Northeast regions.

The United Nation's sustainable development goal is to achieve zero hunger by 2030 and achieve food security throughout the world. In this context, we analyze the anthropogenic factors such as land use and land cover change, waterlogging, and soil salinity which combinedly affecting the agricultural sustainability and threatening the food security in the southwestern region of Bangladesh. Landsat satellite images from 1991 to 2021 were used to detect the changes and identify how anthropogenic activities have altered the land cover and land use and impede the sustainability of agriculture. Terra MODIS vegetation indices from 2000 to 2020 were used to detect waterlogging. Soil salinity was measured from the soil samples and vegetation soil salinity index (VSSI) from Landsat images. Findings of the study revealed that agricultural lands have decreased because of an increase in shrimp farming. Waterlogging and soil salinity are increasing due to increased shrimp farms also for poor drainage infrastructure and human modification. The area of agricultural land in 2011 was 19,657.12 acres,12,750.14 acres, and 38,774.70 acres in Keshabpur, Abhaynagar, and Manirampur, which changed to 12,668.70 acres (-36%), 7151.27 acres (-44%), and 32,809.30 acres (-16%) in 2021. Our hotspot analysis reveals that very high vulnerability to waterlogging due to floods was highest in Manirampur (15,464.09 acres). Finally, we proposed a new framework called IDCEM designed for monitoring land-use change, salinity, and waterlogging in the interior coast, which will indirectly help to promote food security and help in achieving sustainable development goal.

This study aims to analyze the pattern of bank erosion and simulate the physical aspects of vulnerability in the lower Meghna River, Bangladesh using remote sensing (RS) and geographic information systems (GIS). The physical factors of vulnerability were analyzed using GIS-based Structured Query Language (SQL). A questionnaire survey, GPS survey and field observation survey were conducted for collecting the primary data in the study area. The secondary data were mainly satellite image collected from the United States Geological Survey (USGS) website. Using time series Landsat images (MSS, TM and OLI-TIRS), this study analyzed 36 years of erosion and accretion process in the Mehendiganj Upazila region from 1980 to 2016. The result indicates that an enormous amount of land (4470.47 ha) was submerged by the river and average land loss rate was 124.18 ha/year. The study quantifies the number of vulnerable households beneath the present condition and how much it will be altered after a positive/negative change with the factors of vulnerability related to the households. Simulation data reveals that under the present physical condition, 43.88% of households were identified as severely vulnerable. The output of this study can be used in the classification of vulnerable households and for the improvement of the physical infrastructure development process near the erosion prone areas, also helps to mitigate environmental disaster in the developing countries.

In addition to recognizing a commemorative space and geography that serve to legitimize a particular racial identity, streetscapes in the U.S. named after Dr. Martin Luther King, Jr., (MLK) are also a stereotyped space that is presupposed as marginalized. The main objective of this paper is to investigate whether stereotyped MLK neighborhoods differ from the lived spaces. To achieve this objective, the paper relies on two indexes of segregation: namely dissimilarity and interaction indices, the racial composition, and the socioeconomic characteristics of MLK neighborhoods in the 48 contiguous states. Both dissimilarity and interaction indices implied higher segregation in the South and Midwest. The higher proportion of the African American population relative to Whites and other races in the MLK neighborhoods, except in California, confirms that the MLK streetscapes are racially concentrated spaces. Further, analysis of socioeconomic variables does resonate with the stereotype of MLK neighborhoods as marginalized spaces. To demystify the stereotype and to reconstruct the identity of African Americans and their lived and experienced spaces, this paper draws upon studies of the broader process of racialization, critical toponymy, and stereotype theories. Based on this exploratory approach, the paper concludes that though the characteristics of MLK neighborhoods reflect their marginalized status, this status is itself the result of a broader process of racialization. This process has distributed resources unequally among racial groups, forming and buttressing negative stereotypes about African Americans while also stigmatizing their living spaces, which are all too often susceptible to a policy of benign (or not-so-benign) neglect, property devaluation, and industrial pollution.

This study investigates Land Use Land Cover changes in the Chattogram metropolitan area, the second-largest city in Bangladesh. Using a questionnaire survey of 150 local inhabitants, the study explores perceived human-induced causes of landslides. Using time series Landsat images, this study also analyzes Land Use Land Cover changes from 1990 to 2020. The analysis reveals built-up area extended rapidly during 1990–2020. In 1990, total built-up area was 82.13 km2, which in 30 years, stood at 451.34 km2. Conversely, total vegetative area decreased rapidly. In 1990, total vegetation area was 364.31 km2, which reduced to 130.44 km2 in 2020. The survey results show that most of the respondents faced landslide therefore; it is nothing new among them. Respondents were identified several reasons for landslide like extensive rainfall, hill cutting, steep hill, weak soil texture, etc. A large number of local people opined that diverse human activities are causes of landslide in their local area and it has impacted on their livelihood. Chi-square test suggests that there are statistically significant differences between local and non-local inhabitants regarding their opinion on whether excessive hill cutting is alone responsible for landslide and whether deforestation is the sole reason for landslide. This study also used four multinomial logistic regression (MLR) to examine the effects of independent variables like gender, age, level of education, income, housing pattern and experience of facing landslide on their perception of human-induced causes of landslide. Findings show that age and experience of facing landslide are two significant predictors for the first model, explaining excessive hill cutting was alone responsible for landslide. Level of education and experience of facing landslide are found statistically significant for explaining our second model that is building infrastructures solely causes landslide. Moreover, our third model claims only deforestation can be blamed for landslide which is significantly explained by three predictors, namely gender, age and income. Finally, we found our fourth model that is landslide occurs only due to excessive sand collection is significantly explained by participant's gender, level of education, and income.

Purpose The elevated level of nitrate in groundwater is a serious problem in Texas aquifers. To control and manage groundwater quality, the characterization of groundwater contamination and identification of the factors affecting the nitrate concentration of groundwater are significant. The purpose of this paper is to determine factors which have significant impacts on the elevated groundwater nitrate concentrations of the Southern High-Plains and the Edwards-Trinity aquifers. Design/methodology/approach The characterization of groundwater nitrate contamination was undertaken by analyzing the hydrochemical data of groundwater within a statistical framework. The multivariate statistical analysis (ordinary least square) and geographically weighted regression (GWR) models were used to study the relationship between groundwater nitrate contamination and land use of the study areas. Findings Results show groundwater nitrate contamination is typically due to an overapplication of N fertilizers to cotton in the Southern High-Plains aquifer and to grassland in the Edwards-Trinity aquifer. Adjusted R2 (0.45) explains variations of nitrate concentration by well-depth, cotton production, shrubland and grassland in the Edwards-Trinity aquifer. The results of an analysis of variations in N concentration with well depth for all 192 wells indicate that nitrate concentrations in water from wells in the Southern High-Plains and Edwards-Trinity aquifers tend to decrease with increasing well-depth. Originality/value In this study, the GWR model was built to identify nitrate concentration within a geographic framework to ensure sustainable use of groundwater, which is important for local management purposes. The analysis should include local spatial variations of elements such as hydrologic characteristics and the land use activities if groundwater nitrate contamination causes adverse effects on human and ecosystem health.

Throughout much of Europe, new waves of immigration have raised concerns about cultural fragmentation and disunity, interethnic conflict, and growing antipathy toward immigrants. Our goal is to provide evidence of uneven patterns of immigrant population distribution and residential integration, both within and between countries of the European Union. Our analyses focus on the spatial concentration of the foreign-born population in 27 countries and 1396 sub-regional areal units (called NUTS3), which in turn are nested within larger economic and cultural regions (i.e., NUTS2). Estimates of new forms of multiscale segregation (i.e., using the index of dissimilarity) are calculated from data drawn from Eurostat and a variety of other sources. Descriptive multivariate models of population concentration or macro-segregation center on key economic (i.e., GDP per capita), social (i.e., education), and ecological (i.e., urbanization) predictors of segregation within and between European countries. New forms of spatial segregation are expressed demographically in substantial regional heterogeneity among immigrants throughout Europe. Multivariate analyses indicate that immigrant-native patterns of population concentration and distribution vary widely between and within European countries with very different economies, demographic conditions, and histories of immigration. In almost all European countries, immigrants from outside of Europe are less spatially integrated with the native population than are immigrants from other countries within Europe. Differences in immigrant-native spatial integration are clearly reflected in the large numbers of immigrant regional “hot spots,” which are driven by public policy and idiosyncratic political considerations at the national and regional levels. Our comparative approach provides an overview of country-to-country differences in European immigrant settlement patterns and multiscale patterns of integration and segregation.

This article evaluates the impact of upstream water withdrawal on downstream land use and livelihood changes in the Teesta River basin, using a combination of geospatial and social data. Results show that water bodies gradually decreased, indicating a low volume of water discharge from upstream of the Teesta River basin due to the construction of several barrages. During the study period, a significant change in the area of water bodies was observed between 2012 and 2016, from 881 to 1123 Ha, respectively. The cropland area increased because farmers changed their cropping practice due to water scarcity and floods. Trend analyses of riverbank erosion and accretion patterns suggest an increase in accretion rates compared to the rate of riverbank erosion. A household survey was conducted using a self-administered questionnaire where 450 respondents have participated (farmers: 200 and fishermen: 250). Survey results show that most of the farmers (65.5%) and fishermen (76.8%) think that the construction of upstream barrages caused harm to them. The majority of farmers and fishermen feel water scarcity, mainly in the dry season. We found that a large number of participants in the study area are willing to change their occupations. Furthermore, participants observed that many local people are migrating or willing to migrate to other places nowadays. Our study also found that farmers who face water scarcity in their area are more likely to change their location than their counterparts, while those who face problems in their cultivation are less likely to move. On the other hand, upstream barrages, fishing effects, and getting support in crisis significantly predict fishermen's occupation changes. We believe our results provide essential information on the significance of transboundary water-sharing treaties, sustainable water resource management, and planning.

The average global sea level has been predicted to rise anywhere between 0.53–2.5 m by 2100 with some local and regional variations in various climate change scenarios. Relative sea level change along most of the European coastline is similar to the global average. The objective of this paper is to estimate the extent of impact regarding three sea level rise (SLR) scenarios on European coastal regions. First, three inundation models estimate the area affected by the base sea level, 1 m SLR, and 2 m SLR. Then, based on the population and land cover classes in the coastal regions, land cover types and the estimated future population affected by the SLR scenarios are analyzed. This study used an inundation model (EU-DEM v1.1 digital elevation model). Land cover data from CLC2018 and monthly averaged sea level anomalies (SLA) files from 2013 to 2015 were used in the model. In the SLR0 scenario, about 8.7 million people are estimated to be affected at 2100. An estimated 11.6 million people will be affected in the SLR1 scenario; and an estimated 14.8 million people will be affected by the SLR2 scenarios. Arable lands and pastures are the two top land cover classes that will be affected by SLR. However, land under urban fabric and transportation are also two important land cover types affected by SLR which can induce major economic costs to coastal countries. A significant area of underwater bodies and wetlands will come in contact with sea water due to the extreme events caused by SLR.

The objective of this study is to analyze groundwater types and the extent of seawater intrusion in terms of ion concentrations in groundwater sample using USGS monitoring wells. Groundwater quality indices [fsea, GQI (dom), GQI (mix), GQI (swi)] were used to estimate the spatial distributions of groundwater types in the US coastal aquifers. Results showed that the dominating groundwater chemistry in the study area was Na+ and Cl−. Results also indicated that seawater intrusion of groundwater occurred in the US coastal aquifers. Based on the results of GQI (mix) and GQI (dom), most of the wells fell under domain II in the Piper diagram, indicating that they were of the Na–Cl water type. Na–Cl and mixed Ca–Mg–Cl were determined to be the two dominant groundwater types in the coastal aquifers of the US seawater intrusion evident in the Palm Beach and Miami-Dade counties of Florida, the San Diego and Santa Barbara areas of California, and within Virginia and New Jersey on the east coast. As the sea level continues to rise further inland, Na–Cl concentration in groundwater will increase, particularly in aquifers along low-lying coasts.

The City of Atlanta has seen phenomenal urban expansion, racial re-composition, and migration patterns over decades. In this paper, we try to answer overarching question: Has the economic development and urban sprawl in Atlanta been accompanied by racially diverse neighborhoods? Or has the economic development in Atlanta led to a racially integrated landscape? We use demographic data from the U.S. Census Bureau, the Internal Revenue Service, and the Panel Study for Income Dynamics. First, we use hotspot analysis to study temporal changes in spatial patterns of concentration of the black population in Atlanta. Second, using the index of dissimilarity (D) and interaction index (I), we estimate the extent of segregation between whites and blacks. Third, we calculate the migration effectiveness in three sub-regions of Atlanta. The results show that hotspots of the black population are located in the central and south-central parts of Atlanta, and have expanded predominantly in the eastern and southern directions during the last four decades. Racial diversity has increased generally in the counties immediately north of the city proper, but the southern and peripheral counties had less racial diversity. Remarkably, southern Atlanta did not witness the economic development in the same way as northern Atlanta. The migration effectiveness index shows that, in recent years, Atlanta suburbs attracted more migrants, both from within the Atlanta region and from the rest of the United States, as compared to the Atlanta city proper. In recent decades, neighborhoods in the Suburb-I becoming racially more diverse, and one would expect this trend will extend in other regions too in the future.

The aim of this paper is to analyze the spatial patterns of wastage trends of ice masses in the Southern Andes. The study compared digital elevation models from Shuttle Radar Topographic Mission (SRTM) (Year 2000) with the elevation footprints from the Geoscience Laser Altimeter System (GLAS) campaign for the years 2004 through 2008 in the Dry Central, North Wet, South Patagonia, and Cordillera Darwin regions. Overall, the mean elevation differences on clean ice were negative in all four regions. However, the higher mass balance trends were observed in the Cordillera Darwin (-0.126 ± 0.05 m w.e.a- 1) and the North Wet (− 0.122 ± 0.12 m w.e.a- 1) regions. In contrast, no major change in mass balance trends was observed in Dry Central (-0.037 ± 0.13 m w.e.a- 1) and South Patagonian Icefield (-0.037 ± 0.05 m w.e.a- 1).

The accessibility of hospital facilities is of great importance not only for maintaining social stability, but also for protecting the basic human right to health care. Traditional accessibility research often lacks consideration of the dynamic changes in transport costs and does not reflect the actual travel time of urban residents, which is critical to time-sensitive hospital services. To avoid these defects, this study considered the city of Kaifeng, China, as an empirical case, and directly acquired travel time data for two travel modes to the hospital in different time periods through web mapping API (Application Program Interface). Further, based on travel time calculations, we compared five baseline indicators. For the last indicator, we used the optimal weighted accessibility model to measure hospital accessibility for each residential area. The study discovered significant differences in the frequency and spatial distribution of hospital accessibility using public transit and self-driving modes of transportation. In addition, there is an imbalance between accessibility travel times in the study area and the number of arrivals at hospitals. In particular, different modes of transportation and different travel periods also have a certain impact on accessibility of medical treatment. The research results shed new light on the accessibility of urban public facilities and provide a scientific basis with which local governments can optimize the spatial structure of hospital resources.

The dynamic nature of internal migration flows has altered population redistribution and changed composition in the United States for more than a century. Socioeconomic push and pull factors have influenced people’s migration decisions during various internal migration waves in the United States. The main objective of this paper is to identify how effective internal migration flows have been in transforming the population distribution of the United States since the mid-1990s. We also examine the characteristics of the counties that gained or lost population during the last two decades. We analyze migration data from the Internal Revenue Service (IRS) from 1994–95 to 2006–07 to achieve these objectives. The results show that migration was very effective in redistributing population from rural to urban areas. Although suburbanization was a major characteristic of urban growth, our study indicates that suburbanization was not as effective as rural-to-urban migration. The South continued to be the major population magnet in the United States. Counties with large black and Hispanic populations had a negative migration effect. During the last two decades, increase in the Hispanic population and economic inequality in American neighborhoods have also influenced migration patterns in the United States.

An accurate estimation of mass balance of mountain glaciers is important to understand global climate change process. The glaciers in the Pamir region are remote, difficult to access, and are often impossible to evaluate using in-situ methods. The objectives of this study are to estimate the extent of glacial retreat of the Fedchenko glacier from 1933 to 2014, and to estimate the mass balance of the Fedchenko in the Pamir region of Tajikistan. ASTER and Landsat satellite images were used in the study. Glacier terminus of the Fedchenko glacier retreated about 1.7 km over the last 81 years. However, in the recent years, the rate of retreat has slowed down. The lower part of the ablation zone, which is mostly debris covered has exhibited higher surface lowering trend compared to the area between the altitude of 3800m to the equilibrium line altitude (ELA).

The Patagonian Icefield has the largest temperate ice mass in the southern hemisphere. Using remote sensing techniques, this study analyzed multi-decadal glacial retreat and expansion of glacier lakes in Northern Patagonia. Glacial boundaries and glacier lake boundaries for 1979, 1985, 2000, and 2013 were delineated from Chilean topographic maps and Landsat satellite images. Aster stereo images were used to measure mass balance from 2007 to 2012. The highest retreat was observed in San Quintin glacier. The area of glacier lakes increased from 13.49 km2 in 1979 to 65.06 km2 in 2013. Four new glacier lakes formed between 1979 and 2013. Between 2007 and 2012, significant glacial thinning was observed in major glaciers, including HPN1, Pared Norte, Strindberg, Acodado, Nef, San Quintin, Colonia, HPN4, and Benito glaciers. Generally, ablation zones lost more mass than accumulation zones.

Mississippi River affects the carbon dynamics in the northern Gulf of Mexico (N-GoM) significantly. Hence, total alkalinity (TA) algorithms developed for major ocean basins produce inaccurate estimations for this region. A TA algorithm was developed, which addresses the local effects of coastal processes and complex spatial influences. In-situ data collected during numerous previous research cruises in the N-GoM were compiled and used to calculate the efficiency of an existing TA algorithm that uses Sea-Surface-Temperature (SST) and Sea-Surface-Salinity (SSS) as explanatory variables. To improve this algorithm, statistical analyses were performed to improve the coefficients and functional form of this algorithm. Then, chlorophyll-a (Chla) was included as an additional explanatory variable. Chla worked as a proxy for addressing the organic carbon pumps pronounced effects on coastal waters. Finally, a Geographically Weighted Regression (GWR) algorithm was developed to address spatial non-stationarity, which apparently could not be addressed in the previously developed global algorithm.

Globally, water bodies are increasingly affected by undesirable harmful algal blooms. This dissertation contributes to research methodology pertaining to quantification of the algal blooms in multiple water bodies of Mississippi using in situ, analytical, and remote sensing techniques. The main objectives of this study were to evaluate the potential of several techniques for phytoplankton enumeration and to develop remote sensing algorithms for several sensors and evaluate the performance of the sensors for quantifying phytoplankton in several water bodies. Analytical techniques such as FlowCam, an imaging flow cytometer; HPLC, high performance liquid chromatography with the chemical taxonomy program ChemTax; spectrofluorometric analyses; and ELISA assay were used to quantify a suite of parameters on algal blooms. Additionally, in-situ algal pigment biomass was measured using fluorescence probes. It was found that that each technique has unique potential. While some of the rapid and simpler techniques can be used instead of more involved techniques, sometimes use of several techniques together is beneficial for managing aquatic ecosystems and protecting human health. Algorithms were developed to quantify chlorophyll a using five remote sensing sensors including three currently operational satellite sensors and two popular sensors onboard the Unmanned Aerial Systems (UASs). Empirical band ratio algorithms were developed for each sensor and the best algorithms were chosen. Cluster analysis helped in differentiating the water types and linear regression was used to develop algorithms for each of the water types. The UAS sensor- Micasense was found to be most useful among the UAS sensors and the best overall with highest R2 value 0.75 with p<0.05 and minimum %RMSE of 28.22% and satellite sensor OLCI was found to be most efficient among the three satellite sensors used in the study for chlorophyll a estimation with R2 of 0.75 with p

Despite increases in global temperature, studies have observed a decrease in evaporation in the Northern Hemisphere. To examine whether a decrease in pan evaporation also indicates decreased evapotranspiration (ET), ET rates were modelled in a geographic information system by integrating climatic data and water-balance data from 1997 to 2007. Average monthly ET values were compared with National Climatic Data Center pan-evaporation (PE) data. PE and ET were significantly related, but the degree of significance and the direction of the relation (positive or negative) varied across eco-divisions and seasons. Thus, decreased pan evaporation does not necessarily imply that ET will decrease as well.

Casuarinas (Casuarina equisetifolia L.) are a problematic invasive plant within the Bahamas, but very little is known about its population dynamics or spread capabilities. This study monitored casuarinas beach populations on San Salvador Island, the Bahamas, over a 2.5 year period to provide basic background data on distribution patterns and degree of spatial variability over time. Casuarinas had a significant clustered distribution along beach transects (P< 0.05). Numerous gaps in between clusters, 20 m or longer, were not colonized during the duration of the study. These patterns occurred among beaches with differing levels of human visitation. It seems that beach populations of casuarinas had low spatial variability within the spatial and temporal context of this study. These results may help guide future research and may be an initial step in developing effective management strategies in the Bahamas and in other areas where it has invaded.

The South has recently become a major economic hub and population magnet in the United States. This study examines if the Black Belt, a historically declining region within the South, has experienced a similar renaissance. The study also examines how local factors differentially influence migrants from the Black Belt and migrants from outside the South. The study identifies primary hot spots for Black Belt and non-Black Belt migrants. The data come from yearly internal migration files from 1996 to 2007 compiled by the Internal Revenue Service and the U.S. Census Bureau. The data show that both the Black Belt and the rest of the South experienced a net in-flow of migrants from other U.S. regions. However, the Black Belt had a net population loss to more prosperous areas within the South. The data also show that the Southern hot spots for migrants from the Black Belt are different than those for non-Black Belt migrants. The findings support a singular conclusion: the population growth of the New South is brought about largely because of changes in migration flows of Black Belt migrants. Abstract: Recientemente el Sur se ha convertido en un importante centro economico y en un iman de poblacion en los Estados Unidos. Este estudio examina si el Cinturon Negro, una region historicamente en depresion en el Sur, ha experimentado un renacimiento similar. El estudio tambien examina como los factores locales influyen en forma diferencial migrantes del Cinturon Negro e inmigrantes de fuera de la del Sur. El estudio identifica principales puntos clave para el Cinturon Negro y migrantes que no son del Negro Cinturon. Los datos provienen de los archivos de migracion interna anuales desde 1996 hasta 2007 compilados por el Servicio de Impuestos Internos y la Oficina del Censo de EE.UU. Los datos muestran que tanto el Cinturon Negro como el resto del Sur experimentaron un flujo neto de inmigrantes de otras regiones de EE.UU. Sin embargo, el Cinturon Negro tuvo una perdida neta de poblacion hacia otras regiones mas prosperas en el Sur. Los datos tambien muestran que los puntos claves del Sur para los migrantes provenientes del Cinturon Negro son diferentes a los de los de los migrantes que no provienen del Cinturon Negro. Los hallazgos apoyan una conclusion: el crecimiento de la poblacion del Nuevo Sur es provocada en gran medida debido a los cambios en los flujos migratorios de los migrantes del Cinturon Negro.

Southern forests contribute significantly to the carbon sink for the atmospheric carbon dioxide (CO2) associated with the anthropogenic activities in the United States. Natural disasters like hurricanes are constantly threatening these forests. Hurricane winds can have a destructive impact on natural vegetation and can adversely impact net primary productivity (NPP). Hurricane Katrina (23–30 August 2005), one of the most destructive natural disasters in history, has affected the ecological balance of the Gulf Coast. This study analyzed the impacts of different categories of sustained winds of Hurricane Katrina on NPP in Mississippi. The study used the Carnegie–Ames–Stanford Approach (CASA) model to estimate NPP by using remote sensing data. The results indicated that NPP decreased by 14% in the areas hard hit by category 3 winds and by 1% in the areas hit by category 2 winds. However, there was an overall increase in NPP, from 2005 to 2006 by 0.60 Tg of carbon, in Mississippi. The authors found that Pearl River, Stone, Hancock, Jackson, and Harrison counties in Mississippi faced significant depletion of NPP because of Hurricane Katrina.

Snow cover helps regulate the temperature of the Earth's surface. Snowmelt recharges groundwater, provides run-off for rivers and creeks, and acts as a major source of local water for many communities around the world. Since 2000, there has been a significant decrease in the snow-covered area in the Northern Hemisphere. Climate change is the major factor influencing the change in snow cover amount and distribution. We analyze spectral properties of the remote sensing sensors with respect to the study of snow and examine how data from some of the major remote sensing satellite sensors, such as (Advanced Spaceborne Thermal Emission and Reflection Radiometer) ASTER, Landsat-8, and Sentinel-2, can be used in studying snow. The study was conducted in Mt. Rainier. Although reflectance values recorded were lower due to the timing of the data collection and the aspect of the study site, data can still be used calculate normalized difference snow index (NDSI) to clearly demarcate the snow from other land cover classes. NDSI values in all three satellites ranged from 0.94 to 0.97 in the snow-covered area of the study site. Any pollutants in snow can have a major influence on spectral reflectance in the VIS spectrum because pollutants absorb more than snow.

In this study, we used image-processing techniques to examine the spatial pattern of land-use and land-cover (LULC) change that occurred in the coffee growing area in the Western Ghats of India during the international coffee crisis in the 1990s. The study also ascertains the driving forces of these changes using qualitative research methods that include archival studies and interviews of knowledgeable individuals. We analyzed Landsat Thematic Mapper (TM) for 1991 and Landsat ETM+ for 2002 to quantify LULC. Historical land-use changes in different land ownership regimes were also analyzed. Global coffee market fluctuations were found to be the major cause of landscape change in the study region. When the global coffee prices increased, more forested areas were cleared for coffee cultivation. Failure of global coffee market forced farmers to convert land from subsistence farming (rice) to short-period commercial crops like ginger. This also resulted in land degradation in rice paddies. For the farmers in the Western Ghats, LULC decisions are one of the methods used to cope with the vulnerability created due to the international coffee crisis. Copyright © 2009 John Wiley & Sons, Ltd.

Expansion of coffee cultivation is one of the causes of deforestation and biodiversity loss. However, shade grown coffee has been promoted as a means for preserving biodiversity in the tropics. In this study we compared tree diversity in two types of coffee management regimes with the sacred groves in the Western Ghats of India. We computed species accumulation curves, species diversity indices and evenness indices to compare the different management regimes. Results of diversity indices showed that shade coffee had less diversity compared to sacred groves. Exotic species dominated the tree diversity in lands where the tree harvesting rights are with the growers. Native trees dominated the tree diversity when growers had no ownership rights on trees. A species accumulation curve suggested that the sacred grove had higher species richness compared to other two habitats. Lack of incentive to preserve endemic species as shade trees is forcing growers to plant more exotic species in shade grown coffee plots. If encouraged, shade grown coffee can preserve some biodiversity, but cannot provide all ecological benefits of a natural forest.

Now that the United Kingdom voted in favor of exiting from the European Union, a process commonly known as Brexit, there is a possibility that we will witness a tremendous migration wave between the EU and the UK once Brexit is implemented. This will ultimately affect every aspect of European society and will have repercussions on the global economy and geopolitics. In this paper, we analyze the migration effectiveness between the EU and the UK. The results indicate that, currently, there is an efficient redistribution of the population in favor of the UK, compared to most other EU countries. For instance, the number of UK citizens living in Belgium, Cyprus, Luxemburg and Spain is greater than the number of citizens of Belgium, Cyprus, Luxemburg and Spain living in the UK. Between France and the UK, there is an almost equal number of migrants living in each country. The UK must contend with the possible migration of a significant percent of the 2.9 million EU migrants currently residing in the UK. In addition, the UK has to update its policies to accommodate the 0.8 million UK citizens living in other EU countries.

The cryosphere is the frozen water part of the Earth’s system. The word is derived from the Greek “kryos,” meaning cold. Snow and ice are the main ingredients of the cryosphere and may be found in many forms, including snow cover, sea ice, freshwater ice, permafrost, and continental ice masses such as glaciers and ice sheets. Snow is precipitation made up of ice particles formed mainly by sublimation (NSIDC, 2011). Ice is the key element in glaciers, ice sheets, ice shelves and frozen ground. Sea ice forms when the ocean water temperature falls below freezing. Permafrost occurs when the ground is frozen for a long period of time, at least two years below 00 C, and varies in thickness from several meters to thousands of meters (NSIDC, 2011). Glaciers are thick masses of ice on land that are caused by many seasons of snowfall. Glaciers move under their own weight, the external effect of gravity, and physical and chemical changes. The cryosphere lowers the earth’s surface temperature by reflecting a large amount of sunlight, stores fresh water for millions of people, and provides habitat for many plants and animals.

In this study, migration data compiled by the Internal Revenue Serve (IRS) and the US Census Bureau for 2006-07 were used to analyse internal migration patterns using migration and income effectiveness for the counties containing the 25 most populous cities in the United States. The results indicated that both large metropolitan and rural counties have lost population and income due to migration. Small metropolitan and non-metropolitan counties closer to cities gained population and income. Counties in South Florida attracted a large number of higher-income migrants from the largest cities in the US. In the last 13 years, New York, Los Angeles and Chicago, the three most populous cities in the US, had negative migration effectiveness. Suburban areas and second-tier cities continued to attract people from large metropolitan areas.

John Shelton Reed's maps of the South and Dixie in 1970s and 1980s indicated the shrinking boundaries of these two vernacular regions. This study revisits the South and Dixie. Using electronic telephone directories, this study collected all business names with "Southern" and "Dixie" in all the cities in the US. A univariate local indicator of spatial association (LISA) analysis was used to identify the clusters of high and low values of normalized values of the terms. These analyses helped identify the current core regions of Dixie land and the South. The results indicate that "the South" and "Dixie" boundary erosion is noticeable. The study identified a previously unnoticed island of "Dixie" in Utah. Southern and Dixie identities are stronger in non-metropolitan counties compared to metropolitan and micropolitan counties. Southern and Dixie identities are eroding gradually: while the erosion of southern identity is very slow, the erosion of Dixie identity seems to be faster. Overall, it may be more appropriate to refer "Dixieland" as "Dixie islands" today, but the South is still the South. Abstract: Los mapas del Sur y Dixie en los 70s y 80s de John Shelton Reed indicaron una reduccion en los limites de esas dos regiones autoctonas. Este analisis estudia al Sur y Dixie. Usando directorios telefonicos electronicos, este estudio recopila los nombres de negocios con "Southern" y "Dixie" en todas las ciudades de Los Estados Unidos. Un analisis univariable LISA (Indicador Local de Asociacion Espacial) fue usado para identificar los conglomerados de valores altos y bajos de los valores normalizados de los terminos. Este analisis ayudo a identificar hoy las regiones de Dixie Land y el Sur. Los resultados indican que la erosion de los limites del "Sur" y "Dixie" es notable. El estudio identifico en Utah una "Isla de Dixie" que no habia sido notada anteriormente. Las identidades de Southern y Dixie son mas fuertes en los condados no-metropolitanos que en los condados metropolitanos y micropolitanos. Las identidades de Southern y Dixie se estan deteriorando gradualmente; mientras que el deterioro de las identidades del sur es bastante lento, el deterioro de Dixie parece ser mas rapido. En general, seria mas apropiado referirse hoy a "Dixieland" como "Islas Dixie", pero el Sur todavia es el Sur.

Urbanization has substantially altered the earth’s surface, and cities’ impervious surfaces for anthropogenic activities often generate an urban heat island (UHI). This paper analyses the effects of the UHI in Bangalore, which in recent years has witnessed tremendous in-migration of people and expansion of infrastructure due to rapid growth of its information technology, biotechnology and manufacturing sectors. Temperature values extracted from the Landsat satellite’s Enhanced Thematic Mapper Plus (ETM+) thermal bands and a “Normalized Difference Vegetation Index” (NDVI) were used to ascertain the relationship between vegetation cover and temperature. Results indicate that the city core has a significantly lower mean temperature than the city’s outgrowth zones. The presence of water bodies and vegetation in the city’s core helped to maintain lower temperatures than those found in the city’s outskirts, even though within the city core temperatures varied from 1 to 7° C within different land cover classes. The continued expansion of urban infrastructure and new, residential neighborhoods which lack vegetation seem to be contributing substantially to higher temperatures in the outgrowth zones.

This paper examines the global coffee crisis that began in the late 1980s and its impact on local livelihoods for smallholding farmers in India. The coffee crisis is characterized by low farm-gate coffee prices caused by oversupply, an unregulated open market, and growing corporate concentration. Smallholding coffee farmers in India suffered severely during the recent crisis as they experienced lower yields, lower coffee prices, and weak market institutions. The impact of the coffee crisis is considered in terms of structural changes in the coffee market and rural institutions and the measures farmers have used to cope with market volatility.