Cambios en el paisaje de menorca desde 1975 hasta 2010 mediante teledetección

La isla de Menorca, Reserva de la Biosfera, ha originado una fuerte atracción turística a consecuencia de su gran riqueza paisajística. En este estudio, se analizaron 265 imágenes Landsat procedentes del United States Geological Service para el periodo 1975-2010, todas examinadas y clasificadas en un determinado lapso de tiempo con el fin de poder caracterizar correctamente el desarrollo territorial espacial y temporalmente. Los resultados muestran como entre 1975 y 1990 no existe desarrollo del paisaje. Entre 1990 y 2000, hay un gran aumento de la vegetación a consecuencia de la protección recibida por la Unesco. En el periodo 2000-2010, es evidente el efecto del clima en el desarrollo del paisaje. The island of Menorca, Reserve of the Biosphere, has created a strong tourist attraction due to its rich landscape. In this research, 265 Landsat satellite images from the United States Geological Service were analyzed or the 1975 to 2010 eriod, each of which was examined and classified in a certain period of time in order to characterize right way the territorial development both spatially and temporally. The results show how between 1975 and 1990 there is virtually no landscape development. Between 1990 and 2000, there is a strong increase of vegetation as a result of the protection received by UNESCO. In the period 2000-2010, it was evident the effect of climatic factors in the landscape development.

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Visualization of Lake Mead Surface Area Changes from 1972 to 2009

10.32920/14639064.v1 ◽

2021 ◽

Author(s):

K. Wayne Forsythe ◽

Barbara Schatz ◽

Stephen J. Swales ◽

Lisa-Jen Ferrato ◽

David M. Atkinson

Keyword(s):

United States ◽

Water Level ◽

Surface Area ◽

Satellite Images ◽

Strong Relationship ◽

The United States ◽

Water Levels ◽

Lake Area ◽

Lake Mead ◽

Landsat Satellite

For most of the last decade, the south-western portion of the United States has experienced a severe and enduring drought. This has caused serious concerns about water supply and management in the region. In this research, 30 orthorectified Landsat satellite images from the United States Geological Service (USGS) Earth Explorer archive were analyzed for the 1972 to 2009 period. The images encompassed Lake Mead (a major reservoir in this region) and were examined for changes in water surface area. Decadal lake area minimums/maximums were achieved in 1972/1979, 1981/1988, 1991/1998, and 2009/2000. The minimum lake area extent occurred in 2009 (356.4 km2), while the maximum occurred in 1998 (590.6 km2). Variable trends in water level and lake area were observed throughout the analysis period, however progressively lower values were observed since 2000. The Landsat derived lake areas show a very strong relationship with actual measured water levels at the Hoover Dam. Yearly water level variations at the dam vary minimally from the satellite derived estimates. A complete (yearly) record of satellite images may have helped to reduce the slight deviations in the time series.

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Visualization of Lake Mead Surface Area Changes from 1972 to 2009

10.32920/14639064 ◽

2021 ◽

Author(s):

K. Wayne Forsythe ◽

Barbara Schatz ◽

Stephen J. Swales ◽

Lisa-Jen Ferrato ◽

David M. Atkinson

Keyword(s):

United States ◽

Water Level ◽

Surface Area ◽

Satellite Images ◽

Strong Relationship ◽

The United States ◽

Water Levels ◽

Lake Area ◽

Lake Mead ◽

Landsat Satellite

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Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study

Frontiers in Public Health ◽

10.3389/fpubh.2021.766707 ◽

2021 ◽

Vol 9 ◽

Author(s):

Joshua J. Levy ◽

Rebecca M. Lebeaux ◽

Anne G. Hoen ◽

Brock C. Christensen ◽

Louis J. Vaickus ◽

...

Keyword(s):

United States ◽

Deep Learning ◽

Mortality Rate ◽

Satellite Images ◽

The United States ◽

Mortality Rates ◽

Image Features ◽

County Level ◽

Crude Mortality Rate ◽

Crude Mortality

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age.Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

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An Analysis of the Prevalence of Heat Waves in the United States between 1948 and 2015

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-17-0274.1 ◽

2018 ◽

Vol 57 (7) ◽

pp. 1535-1549 ◽

Cited By ~ 9

Author(s):

Evan M. Oswald

Keyword(s):

United States ◽

Heat Wave ◽

Great Plains ◽

Heat Waves ◽

Estimation Method ◽

The United States ◽

Northern Great Plains ◽

Strong Increase ◽

Climate Data ◽

Nighttime Temperatures

AbstractUnusually hot weather is a major concern to public health as well as other systems (e.g., ecological, economical, energy). This study utilized spatially continuous and homogenized observational surface climate data to examine changes in the regularity of heat waves in the continental United States. This included the examination of heat waves according only to daytime temperatures, nighttime temperatures, and both daytime and nighttime temperatures. Results confirmed a strong increase in the prevalence of heat waves between the mid-1970s and the dataset end (2015), and that increase was preceded by a mild decrease since the dataset beginning (1948). Results were unclear whether the prevalence of nighttime or simultaneous daytime–nighttime heat waves increased the most, but it was clear that increases were largest in the summer. The largest gains occurred in the West and Southwest, and a “warming hole” was most conspicuous in the northern Great plains. The changes in heat wave prevalence were similar to changes in the mean temperatures, and more so in the daytime heat waves. Daytime and nighttime heat waves coincided with one another more frequently in recent years than they did in the 1970s. Some parts of the United States (West Coast) were more likely than other parts to experience daytime and nighttime heat waves simultaneously. While linear trends were not sensitive to the climate dataset, trend estimation method, or heat wave definition, they were mildly sensitive to the start and end dates and extremely sensitive to the climate base period method (fixed in time or directly preceding any given heat wave).

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FORESTRY AS AN AID TO RE-ESTABLISHMENT AFTER THE WAR

The Forestry Chronicle ◽

10.5558/tfc17126-3 ◽

1941 ◽

Vol 17 (3) ◽

pp. 126-131

Author(s):

J. L. Breckon

Keyword(s):

United States ◽

The United States ◽

Civilian Conservation Corps ◽

Tourist Attraction ◽

Northern Ontario ◽

Post War ◽

Future Program ◽

Wild Life

"Forestry as an Aid to Re-establishment After the War" was prepared as a paper for the April meeting of the Northern Ontario Section of the Society. Its purpose was to open a discussion of possibilities for creating employment through forestry work in the post-war period.Much of the article deals with the accomplishments of the Civilian Conservation Corps of the United States. This enterprise was emphasized not only because it may serve as a guide to a future program but also because it shows that concrete results have been obtained in the use of forestry as an aid in reducing unemployment.The importance of indirect uses of the forests, such as tourist attraction and wild life conservation, has been stressed both because of their economic soundness and their value as a selling feature for a program of re-establishment.

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Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Neighborhood Features

10.1101/2020.10.12.20211755 ◽

2020 ◽

Author(s):

Joshua J. Levy ◽

Rebecca M. Lebeaux ◽

Anne G. Hoen ◽

Brock C. Christensen ◽

Louis J. Vaickus ◽

...

Keyword(s):

United States ◽

Deep Learning ◽

Mortality Rate ◽

Satellite Images ◽

The United States ◽

Mortality Rates ◽

Image Features ◽

County Level ◽

Crude Mortality Rate ◽

Crude Mortality

AbstractWhat is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?BackgroundFollowing a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking. We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.MethodsSatellite images were extracted with the Google Static Maps application programming interface for 430 counties representing approximately 68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.ResultsPredicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r=0.72). Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race and age. Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g. sidewalks, driveways and hiking trails) associated with lower mortality.ConclusionsThe application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

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Inventing Iconography on the Accessible Frontier: Harriet Martineau, Anna Jameson, and Margaret Fuller on the Great Lakes

Prospects ◽

10.1017/s0361233300000302 ◽

1999 ◽

Vol 24 ◽

pp. 67-98 ◽

Cited By ~ 2

Author(s):

Victoria Brehm

Keyword(s):

United States ◽

Great Lakes ◽

New Orleans ◽

The United States ◽

Tourist Attraction ◽

Margaret Fuller ◽

Upper Great Lakes ◽

Harriet Martineau ◽

Erie Canal ◽

European Culture

In 1820, three decades before Henry Rowe Schoolcraft would comment on the inabilities of tourists to experience the frontier without reference to European culture, he had accompanied a Gov. Lewis Cass expedition on the upper Great Lakes as mineralogist, traveling through the wilderness in acanot du maîtrepaddled by Indians andvoyageurs— while he read Johnson'sLives of the Poets. Although Schoolcraft's later relationship to Native cultures complicates any facile imperialist-other dichotomies, the Cass expedition to explore the lakes preparatory to securing more land cessions from the Indians was prophetic. When Schoolcraft returned to the East in 1841, by then a tourist attraction himself, 200,000 steamship and schooner passengers a season passed his post on Mackinac Island, crossing the upper lakes while bound for the settlements, prairies, and mineral– producing regions of the United States and Canada. Immigrants came via the Erie Canal; wealthy tourists booked passage to New Orleans, traveled up the Mississippi, and crossed to Chicago and thence through to Buffalo on palatial steamships (Ashworth, 10).

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Horticultural Applications of a Newly Revised USDA Plant Hardiness Zone Map

HortTechnology ◽

10.21273/horttech.22.1.6 ◽

2012 ◽

Vol 22 (1) ◽

pp. 6-19 ◽

Cited By ~ 11

Author(s):

Mark P. Widrlechner ◽

Christopher Daly ◽

Markus Keller ◽

Kim Kaplan

Keyword(s):

United States ◽

Low Temperature ◽

Climatic Factors ◽

The United States ◽

The Pacific ◽

Wide Range ◽

Management And Development ◽

Extreme Minimum Temperature ◽

Site Evaluation ◽

Plant Hardiness

The accurate prediction of winter injury caused by low-temperature events is a key component of the effective cultivation of woody and herbaceous perennial plants. A common method employed to visualize geographic patterns in the severity of low-temperature events is to map a climatological variable that closely correlates with plant survival. The U.S. Department of Agriculture Plant Hardiness Zone Map (PHZM) is constructed for that purpose. We present a short history of PHZM development, culminating in the recent production of a new, high-resolution version of the PHZM, and discuss how such maps relate to winterhardiness per se and to other climatic factors that affect hardiness. The new PHZM is based on extreme minimum-temperature data logged annually from 1976 to 2005 at 7983 weather stations in the United States, Puerto Rico, and adjacent regions in Canada and Mexico. The PHZM is accessible via an interactive website, which facilitates a wide range of horticultural applications. For example, we highlight how the PHZM can be used as a tool for site evaluation for vineyards in the Pacific northwestern United States and as a data layer in conjunction with moisture-balance data to predict the survival of Yugoslavian woody plants in South Dakota. In addition, the new map includes a zip code finder, and we describe how it may be used by governmental agencies for risk management and development of recommended plant lists, by horticultural firms to schedule plant shipments, and by other commercial interests that market products seasonally.

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Constructing a Large-scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates

10.36227/techrxiv.14365502 ◽

2021 ◽

Author(s):

savinay nagendra ◽

srikanth banagere manjunatha ◽

daniel kifer ◽

te pei ◽

weixin li ◽

...

Keyword(s):

United States ◽

Large Scale ◽

Satellite Images ◽

The United States ◽

Specific Model ◽

Google Earth ◽

Landslide Inventory ◽

United States Geological Survey ◽

Heterogeneous Environments ◽

Extensive Data

We use the landslide inventory database provided by the United States Geological Survey. USGS maintains a database of landslide reports with approximate locations and times, but no images. This is the most extensive data of its kind. We extract satellite images from Google Earth by using this inventory.<br>

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The Electronics Industry and Their Chemical Effects in the Environment of Arid Regions of Northwest of Mexico

Indian Journal of Advanced Chemistry ◽

10.54105/ijac.b2007.101221 ◽

2021 ◽

pp. 5-13

Author(s):

Gustavo Lopez Badilla ◽

◽

Juan Manuel Terrazas Gaynor ◽

Keyword(s):

United States ◽

Climatic Factors ◽

The United States ◽

Environmental Problems ◽

Electronics Industry ◽

Water Levels ◽

Chemical Waste ◽

Health Crisis ◽

Electronic Products ◽

Soil And Water

The electronics industry is very important in the world economy, because is one of more dynamic activities, due to a great quantity and different electronic products manufactured and used in a lot quotidian operations. This type of industry has strongly attracted attention to the environmental authorities in the recent 10 years, due to the deterioration that causes to the ecosystems. The electronics industry generates a lot liquid chemical waste, which are thrown into soils and aquifers that are close to companies. The interest of the relation of environmental problems and the electronics industry has manifested with more frequency, from 20 years ago, especially in countries that regulate strictly to care the ecosystems, being some countries of Europe, United States and Japan. The lack of control in certain liquid wastes from activities of the electronics industry, that are discharged into areas next to companies or by the drainage systems has caused a great deterioration of the ecosystems. This occurs with some companies installed in the Mexicali city dedicated to manufacture electronic products. This city is located in the northwest of Mexico that is a border city with the United States of America (USA), where some soils and aquifers are been damaged for some years. This has negative effects in the population too, by the generation and proliferation of respiratory diseases (RD), being a beginning of some environmental and health crisis, particularly in areas adjacent to these companies. This study examined the environmental problems of the industry electronics in Mexicali, and the increase of persons that suffer of RD, being principally in the winter periods. The analysis was made based in two steps, being the first to evaluate the pollution of soil and water levels with the principal climatic factors as relative humidity (RH) and temperature variations around two companies of the electronics sector to be correlated with the RD levels. The second step was to analyze the pH of soil and water, around the three companies evaluated in this city and to elaborate an evaluation of soils with the Scanning Electron Microscopy (SEM) technique to know their level of deterioration. The study was made from 2018 to 2019.

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