Geospatial technology in environmental health applications

Faruque, Fazlay

doi:10.1007/s10661-019-7444-x

Cited by 5 publications

(3 citation statements)

References 33 publications

(21 reference statements)

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“…When understanding the changes in water quality caused by land use practices, researchers use this method as it gives greater weight to land use (Kennen et al 2008;Peterson et al 2011). Watershed buffers such as riparian zones and hydrological sensitive areas (HSAs) are considered to be key influences on water quality in the region (Giri et al 2018), whereby HSAs refer to regions with high runoff tendency in the basin (Faruque 2019;Qiu et al 2014). HSAs mainly produce and transport pollutants to rivers and affect river hydrology, and although interesting, there are also shortcomings.…”

Section: Study Of Different Spatial Scales Under Remote Sensing Persp...mentioning

confidence: 99%

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

Cheng

Fei

Shi

et al. 2022

Environ Sci Pollut Res

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Good surface water quality is critical to human health and ecology. Land use determines the surface water heat and material balance, which cause climate change and affect water quality. There are many factors affecting water quality degradation, and the process of influence is complex. As rivers, lakes, and other water bodies are used as environmental receiving carriers, evaluating and quantifying how impacts occur between land use types and surface water quality is extremely important. Based on the summary of published studies, we can see that (1) land use for agricultural and construction has a negative impact on surface water quality, while woodland use has a certain degree of improvement on surface water quality; (2) statistical methods used in relevant research mainly include correlation analysis, regression analysis, redundancy analysis, etc. Different methods have their own advantages and limitations; (3) in recent years, remote sensing monitoring technology has developed rapidly, and has developed into an effective tool for comprehensive water quality assessment and management. However, the increase in spatial resolution of remote sensing data has been accompanied by a surge in data volume, which has caused difficulties in information interpretation and other aspects.

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Section: Study Of Different Spatial Scales Under Remote Sensing Persp...mentioning

confidence: 99%

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

Cheng

Fei

Shi

et al. 2022

Environ Sci Pollut Res

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“…Remote sensing (RS) is useful for examining the spatial components of human-environment interactions (106), as well as for describing the physical impacts and dynamics of a disaster in near real-time. Air pollution, in particular fine particulate matter (PM 2.5 ), is "the most consistent and robust predictor of mortality from cardiovascular, respiratory, and other diseases in studies of long-term exposure to air pollution" (107).…”

Section: Secondary Datamentioning

confidence: 99%

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

Sandifer

Knapp

Lichtveld

et al. 2020

Front. Public Health

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The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental Sandifer et al. Community Health Observing System observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.

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“…Its relevance mainly lies in the fact that it contributes to understanding better world phenomena and the consequences that humans activities have on Earth. A relevant example of the above, among many possible others, is the use of modern geospatial information for air quality monitoring (Faruque, 2019).…”

Section: Introductionmentioning

confidence: 99%

Enabling Air Quality Monitoring With the Open Data Cube: Implementation for Sentinel-5p and Ground Sensor Observations

Jimenez

Oxoli

Brovelli

2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Nowadays, the amount of open geospatial data delivered e.g. by private and public entities, such as environmental agencies, enables outstanding possibilities to any user interested in investigating real-world phenomena. However, the availability of such information presents several challenges in terms of its practical use. These are mainly connected to the heterogeneity of data sources, formats and processing tools which have to be mastered by the user to obtain the desired results. As a relevant example, air quality monitoring requires the integration of multiple data with different spatial and temporal granularities that are often distributed by more than one provider using not uniform formats and access methods. Besides traditional air pollution ground sensors observations, novel data sources have emerged. Among them, the Sentinel-5P mission of the European Copernicus Programme is one of the most recent Earth Observation platforms providing estimates of air pollutants with daily global coverage. These estimates are promising to foster air quality analysis and monitoring by complementing ground sensors observations. Therefore, the development of data handling and analysis strategies – allowing users for a smooth integration of satellite and ground sensor observations – is key to support future air quality studies. To that end, the present work investigates the use of the Open Data Cube as a single data endpoint to incorporate ground sensors and satellite observations into local air pollution analyses. A preliminary implementation is presented using the Lombardy region (Northern Italy) as a case study.

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Geospatial technology in environmental health applications

Cited by 5 publications

References 33 publications

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

Enabling Air Quality Monitoring With the Open Data Cube: Implementation for Sentinel-5p and Ground Sensor Observations

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