Relevant bibliographies by topics / Environmental management – remote sensing

Academic literature on the topic 'Environmental management – remote sensing'

Author: Grafiati
Published: 25 July 2024
Last updated: 26 July 2024

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Journal articles on the topic "Environmental management – remote sensing"

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Herbei, Mihai Valentin, Roxana Herbei, Laura Smuleac, and Tudor Salagean. "Using Remote Sensing Techniques in Environmental Management." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Agriculture 73, no. 2 (November 30, 2016): 230. http://dx.doi.org/10.15835/buasvmcn-agr:12441.

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The Geographical Information Systems technology is used in many fields where the spatial information is very important and relevant, that means in all fields that use a system for saving, analyzing and representing the data which are processed. The aim of this paper is using modern technology for monitoring the environment. Geographical Information System together with remote sensing have a very important role in decision process regarding the environment. Integration of remote sensing images in a Geographical Information System which enables complex spatial analysis is a useful and modern solution for environmental management and decision-making process. Satellite images contain various information that can support environmental monitoring, images that can be analyzed and interpreted in various ways by using the Geographical Information System tools.
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Tu, Thanh Tri. "Application of Remote Sensing for Environmental Management in Vietnam." European Modern Studies Journal 7, no. 2 (May 22, 2023): 39–46. http://dx.doi.org/10.59573/emsj.7(2).2023.04.

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Remote sensing technology has become an important tool for environmental management in Vietnam. The country has a diverse range of environments, from dense forests to vast agricultural lands and coastlines, making remote sensing an ideal method for monitoring and managing natural resources. In this study, some examples of remote sensing applications for environmental management in Vietnam were studied in detail.
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Dube, Timothy, Munyaradzi D. Shekede, and Christian Massari. "Remote Sensing for Water Resources and Environmental Management." Remote Sensing 15, no. 1 (December 21, 2022): 18. http://dx.doi.org/10.3390/rs15010018.

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In line with the United Nations Sustainable Development Goal (SDG) 6, the main goal of the Special Issue on “Remote sensing for water resources and environmental management” was to solicit papers from a diverse range of scientists around the world on the use of cutting-edge remote sensing technologies to assess and monitor freshwater quality, quantity, availability, and management to ensure water security. Special consideration was given to scientific manuscripts that covered, but were not limited to, the development of geospatial techniques and remote sensing applications for detecting, quantifying, and monitoring freshwater water resources, identifying potential threats to water resources and agriculture, as well as other themes related to water resources and environmental management at various spatial scales. The Special Issue attracted over thirteen peer-reviewed scientific articles, with the majority of manuscripts originating from China. Most of the studies made use of satellite datasets, ranging from coarse spatial resolution data, such as the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO), to medium spatial resolution data, such as the Landsat series, ERA5, Modern-Era Retrospective Analysis for Research and Application Land version 2 reanalysis product (MERRA2), CLSM and NOAH ET, and MODIS (Moderate Resolution Imaging Spectroradiometer). Google Earth Engine (GEE) data, together with big data processing techniques, such as the remote sensing-based energy balance model (ALEXI/DisALEXI approach) and the STARFM data fusion technique, were used for analyzing geospatial datasets. Overall, this Special Issue demonstrated significant knowledge gaps in various big data image processing techniques and improved computing processes in assessing and monitoring water resources and the environment at various spatial and temporal scales.
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Ampofo, Justice Agyei. "THE USE OF REMOTE SENSING IN GHANA TO SUSTAINABLY MANAGE THE ENVIRONMENT." International Journal of Applied Research in Social Sciences 4, no. 6 (August 29, 2022): 214–20. http://dx.doi.org/10.51594/ijarss.v4i6.364.

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A prerequisite for achieving the objectives of sustainable development is knowledge of the nature, extent, geographical distribution, along with the potentials and limits of natural resources. The mapping, monitoring, measuring, and management of many elements of the built, natural, and biophysical environments are all made possible through satellite remote sensing. Remote sensing is a crucial tool for advancing solutions and offers useful insights into urgent environmental concerns. Thus, data collection for efficient resource management in Ghana has shown to be greatly aided by remote sensing, which may also be used for environmental monitoring and management. Because of this, it is crucial for remote sensing technology to progress in order to acquire data more effectively and efficiently, which helps with rapid change detection, sustainable environmental management, and sustainability. This review's goal was to provide a thorough analysis of the literature on Ghana's use of remote sensing for environmental management and sustainability. Wiley, Taylor & Francis, Science Direct (Elsevier), and Scopus (Elsevier) were a few of the databases used for the review. The findings indicate that there are numerous remote sensing applications for sustainable environmental management in Ghana, including environmental impact assessments of various projects, analyses of changes in land use and land cover, mapping of watersheds and hydrologic features, estimation of soil loss, management of water resources, management of forestry resources, and management of natural disasters. The outcomes also demonstrate that natural, biophysical, and constructed ecosystems might be appropriately monitored and sustainably managed for the benefit of both the present and future generations with the use of remote sensing technology. Governments, municipal managers, environmentalists, and planners may develop useful plans and strategies for sustainable development and effective environmental management with the aid of the information supplied by remote sensing. Keywords: Ghana, Sustainable Management, Environment, Remote Sensing.
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Kenneth Agbemehia, Ibrahim Abubakari Imoro, Shiraz Yakubu Anas, and Ibrahim Issahaku. "The application of remote sensing in sustainable environmental management in Ghana." Engineering Science & Technology Journal 5, no. 6 (June 1, 2024): 1817–25. http://dx.doi.org/10.51594/estj.v5i6.1163.

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One of the most essential tools for environmental management and sustainability in Ghana in recent times is the use of Remote sensing. Ghana is a country blessed with varied natural resources, but anthropogenic activities such as illegal mining, waste management, deforestation and agricultural practices have led to environmental degradation. Remote sensing technology therefore provides a less expensive means of monitoring these activities, assessing their effects on the environment, and providing guiding policy decisions. The aim of this current review is to provide a detailed analysis of literature on the application of remote sensing for environmental management and sustainability. Google scholar, Scopus (Elsevier) and Science Direct (Elsevier), were a few of the databases used for the review. The findings indicate that there are numerous remote sensing applications for sustainable environmental management in Ghana, including examining the state of rural roads, making a foundation map for visual reference, gathering images of earth from space, controlling forest fires, land use and land cover detection, climate change observation, estimating the likelihood of landslides, estimating forest resources, recognizing crop conditions, increasing farming precision, determining the moisture content of the soil, forecasting crop production, crop damage and crop progress. Based on the review it is clear that, the use of remote sensing in environmental management in Ghana has proven to be a valuable tool because it has aided in improving our understanding of environmental dynamics, guiding policy decisions and monitoring the environmental impact of human activities. Remote sensing will continue to play an important role in environmental management in Ghana as technology advances. Keywords: Remote Sensing, Ghana, Environment, Sustainable Management.
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Lougeay, Ray, P. N. Gupta, and A. K. Roy. "Mountain Resource Management and Remote Sensing." Mountain Research and Development 16, no. 3 (August 1996): 329. http://dx.doi.org/10.2307/3673961.

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Verma, Badal, Muskan Porwal, A. K. Jha, R. G. Vyshnavi, Alok Rajpoot, and Ashish Kumar Nagar. "Enhancing Precision Agriculture and Environmental Monitoring Using Proximal Remote Sensing." Journal of Experimental Agriculture International 45, no. 8 (July 5, 2023): 162–76. http://dx.doi.org/10.9734/jeai/2023/v45i82168.

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Proximal remote sensing is a cutting-edge technology that has emerged as a powerful tool in precision agriculture and environmental monitoring. By capturing high-resolution data from a close range, it provides valuable insights into crop health, soil conditions, and ecosystem dynamics. This paper explores the applications, advantages, and limitations of proximal remote sensing, focusing on its use in precision agriculture and environmental management. The applications of proximal remote sensing in precision agriculture include crop monitoring, disease detection, and resource optimization. In environmental management, it aids in habitat mapping, biodiversity assessment, and environmental impact analysis. The advantages of proximal remote sensing lie in its high spatial resolution, real-time data acquisition, and flexibility in sensor selection. However, limitations such as limited coverage area and skill requirements need to be considered. The future perspectives of proximal remote sensing encompass advancements in sensor technology, automation, integration with other technologies, and enhanced data storage and analysis. By leveraging these advancements, proximal remote sensing can contribute to more sustainable practices and informed decision-making for a better and resilient future.
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Huang, Shiyuan. "Application of Remote Sensing Technology in the Field of Lake Pollution Control and Monitoring." Highlights in Science, Engineering and Technology 69 (November 6, 2023): 135–41. http://dx.doi.org/10.54097/hset.v69i.11850.

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Lake pollution has always been one of the significant environmental concerns for humanity. This article explores the hazards of lake pollution and analyzes whether remote sensing technology is meaningful for monitoring and controlling lake pollution in the context of abundant remote sensing resources. The results show that remote sensing technology can help people monitor the pollution status of lakes and assess the effectiveness of their management more easily. This article investigates the role of remote sensing technology in eutrophication, organic pollution, and heavy metal contamination, along with the challenges faced. It also examines the application of remote sensing technology in lake degradation, restoration, and management. It concludes that remote sensing technology can indeed play a role in lake pollution monitoring and control, offering benefits such as reduced labor, time, and spatial costs. The article aims to find more reasonable ways to address lake pollution control and lake environmental management issues while minimizing the ecological impacts of lake pollution.
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Wu, Yue, Maoguo Gong, Qiguang Miao, and Kai Qin. "Computational Intelligence in Remote Sensing." Remote Sensing 15, no. 22 (November 12, 2023): 5325. http://dx.doi.org/10.3390/rs15225325.

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With the development of Earth observation techniques, vast amounts of remote sensing data with a high spectral–spatial–temporal resolution are captured all the time, and remote sensing data processing and analysis have been successfully used in numerous fields, including geography, environmental monitoring, land survey, disaster management, mineral exploration and more [...]
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Getie, Sintayehu, Asabeneh Alemayehu, and Antensay Mekoya. "Relevance of Remote Sensing and its Applications in Forestry. A Critical Review." East African Journal of Forestry and Agroforestry 7, no. 1 (March 13, 2024): 87–112. http://dx.doi.org/10.37284/eajfa.7.1.1818.

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For several nations who are developing, forests play a crucial role in rural life. Due to the incredible challenges associated with staff, logistics, and chronological consistency of field-based surveys for forest management, a variety of sources of data obtained by airborne, space-borne, and terrestrial remote sensing sensors are now essential sources of knowledge for studies on the spatiotemporal patterns of forests. Most recently, understanding of forests and their conservation has been derived primarily from satellite imagery. The process of organizing and carrying out procedures for the management and use of forests can be done with the assistance of remote sensing in order to achieve economic, social, cultural, and environmental goals. Satellite remote sensing has been providing ever-more-advanced knowledge about woodland structure, management, monitoring, and oversight whenever the first civilian earth-observing program was launched. This article reviewed the application of remote sensing on forestry. Data were gathered from published research papers, books, internet resources, and expert observation. Remote sensing’s synoptic view, availability in a rage of spatial-temporal scales, high degree of homogeneity, inexpensiveness as well as the increasing trend in availability make it special in forest science. As observed from the review, remote sensing technology is critical in forest management. It helps to provide up to date information on forest cover change, forest fire, forest disturbance, forest wildlife management, forest biomass and others. Remote sensing is vital in providing scientific information in forest resources monitoring and management
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Dissertations / Theses on the topic "Environmental management – remote sensing"

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Pretorius, Cindy. "Digital satellite remote sensing for terrestrial coastal zone management." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52804.

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Thesis (MA)--Stellenbosch University, 2002.
ENGLISH ABSTRACT: The unique and often fragile environment of the coastal zone is placed under increasing pressure by human development. It is expected that three quarters of the world's population will be living within 60km of the coast by the year 2020. Thorough planning and management are required to prevent coastal degradation. In South Africa, coastal management efforts are being promoted through the implementation of a White Paper for sustainable coastal development. A Coastal Decision Support System (CDSS) was developed to empower local authorities to demarcate and manage sensitive coastal areas by giving them access to relevant botanical and physical information. Land cover/use information for the CDSS was previously mapped manually from hardcopy aerial photography. This method was found to be time-consuming and costly. This study investigated the potential for digital satellite imagery as primary source of data for populating the land cover/use information of the CDSS. A methodology was designed utilising semi-supervised isodata clustering for extracting relevant information for a study area covering 40x20km of coast along the southern coastal sector of South Africa. Digital mapping of SPOT 4 multispectral satellite data was used successfully to map land cover/use information such as wetlands, coastal lakes, dune vegetation, urban areas, forest plantations, natural forest and agricultural areas. A cost comparison was also made between the digital mapping method from satellite imagery used in this research project and the manual mapping from aerial photography. Digital mapping from satellite imagery was found to be more cost-effective in terms of both data and human resource costs. The method outlined and discussed in the research project should provide sufficient guidance for future application of the techniques in populating the CDSS with land cover/use information.
AFRIKAANSE OPSOMMING: Die unieke en dikwels sensitiewe landskap in die kussone is onder aansienlike druk weens ontwikkeling deur mense. Daar word verwag dat 'n derde van die wêreldbevolking teen die jaar 2020 binne 60km van die kus woonagtig sal wees. Dit sal deeglike beplanning en bestuur verg om die agteruigang van hierdie gebied te bekamp. Kussonebestuur word in Suid Afrika aangemoedig deur die implementering van 'n Witskrif vir volhoubare kussone-ontwikkeling. 'n Kusgebied-besluitnemingsondersteuningstelsel (KBOS) is ontwikkel in 'n poging om plaaslike owerhede te bemagtig om sensitiewe kusgebiede af te baken en te bestuur. Die KBOS verleen plaaslike owerhede toegang tot toepaslike inligting oor botaniese en fisiese o~standighede. Grondbedekkinginligting vir die KBOS is in die verlede vanaf hardekopie lugfoto's gekarteer. Hierdie metode is tydrowend en duur. Die potensiaal van digitale satellietbeelde as hoof databron om grondbedekkinginligting vir die KBOS te voorsien is in hierdie studie ondersoek. 'n Metode word in die tesis uiteengesit om 'semi-supervised isodata clustering' te gebruik om die nodige inligting uit die data te onttrek. Die studiegebied sluit 'n area van 40x20km langs die suid kus van Suid Afrika in. Digitale kartering vanaf SPOT 4 multispektrale satellietdata is suksesvol gebruik om grondbedekkingsinligting soos vleilande, kusmere, duin-plantegroei, stedelike gebiede, bosbou, natuurlike bos en landbougebiede te karteer. 'n Kostevergelyking is gedoen tussen die digitale karteringsmetode vanaf satellietbeelde in vergeleke met handkartering vanaf lugfotografie. Die digitale karteringsmetode blyk meer koste-effektief te wees beide in terme van die datakoste sowel as die koste verbonde aan mannekrag. Die omskrywing van die metode in die tesis behoort as goeie riglyn te dien vir die toepassing van die tegniek om grondbedekkinginligting voor te berei vir die KBOS.
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Flores, Cordova Africa Ixmucane. "Hyperspectral remote sensing of water quality in Lake Atitlan, Guatemala." Thesis, The University of Alabama in Huntsville, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1549067.

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Lake Atitlan in Guatemala is a vital source of drinking water. The deteriorating conditions of water quality in this lake threaten human and ecological health as well as the local and national economy. Given the sporadic and limited measurements available, it is impossible to determine the changing conditions of water quality. The goal of this thesis is to use Hyperion satellite images to measure water quality parameters in Lake Atitlan. For this purpose in situ measurements and satellite-derived reflectance data were analyzed to generate an algorithm that estimated Chlorophyll concentrations. This research provides for the first time a quantitative application of hyperspectral satellite remote sensing for water quality monitoring in Guatemala. This approach is readily transferable to other countries in Central America that face similar issues in the management of their water resources.

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Tooke, Thoreau Rory. "Remote sensing applications for vegetation management in urban environments." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/11502.

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Vegetation has been identified as an essential component of healthy urban environments, and the benefits of urban vegetation range widely from influences on the physical conditions of the city to the social well-being of the people who reside in these areas. As a result, ongoing research is important to understand the dynamic spatial components of urban vegetation to help urban planners and scholars manage this valuable resource. Advanced remote sensing technologies, such as high spatial resolution sensors and laser scanning devices, are useful tools for examining urban environments since they can capture detailed information regarding the material and structural composition of the urban surface. By providing a complete coverage of urban environments remote sensing technologies enable new possibilities to quantify the contributions of urban vegetation for a wealth of active processes in urban areas. The studies in this thesis examine several remote sensing devices to demonstrate the influence of urban vegetation on both physical and social aspects of urban environments. Three studies comprise the body of this work. They present new geographic techniques using remote sensing for: 1) the detailed classification of urban vegetation conditions; 2) quantifying the contribution of trees to solar radiation available for building rooftops; and 3) examining socioeconomic disparities related to urban green-space.
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Almamalachy, Yousif. "Utilization of Remote Sensing in Drought Monitoring Over Iraq." Thesis, Portland State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10283891.

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Agricultural drought is a creeping disaster that overshadows the vegetative cover in general and cropland specifically in Iraq, a country that was well known for its agricultural production and fertile soil. In the recent years, the arable lands in Iraq experienced increasing land degradation that led to desertification, economic losses, food insecurity, and deteriorating environment. Remote sensing is employed in this study and four different indices are utilized, each of which is derived from MODIS satellite mission products. Agricultural drought maps are produced from 2003 to 2015 after masking the vegetation cover. Year 2008 was found the most severe drought year during the study period, where drought covered 37% of the vegetated land. This part of the study demonstrated the capability of remote sensing in fulfilling the need of an early warning system for agricultural drought over such a data-scarce region.

This study also aims to monitor hydrological drought. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived monthly Terrestrial Water Storage (TWS) is the hydrological drought indicator, that is used to calculate the deficit. Severity of drought events are calculated by integrating monthly water deficit over the drought period. In addition, drought recovery time is assessed depending on the estimated deficit. Major drought events are classified into several levels of severity by applying a drought monograph approach. The results demonstrated that GRACE TWS is a reliable indicator for drought assessment over Iraq, and provides useful information for decision makers which can be utilized in developing drought adaptation and mitigation strategies.

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Li, Yan. "An integrated water quality monitoring system with dynamic remote sensing feedback /." Online version of thesis, 2007. http://hdl.handle.net/1850/5834.

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Yetman, Gregory George. "Spatial information and environmental decision making : the Windermere Valley, British Columbia." Thesis, McGill University, 1999. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=30231.

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Local participation in environmental decision making processes is a recognized need if the goals of sustainable development are to be met. Spatial information is an important part of environmental decision making, but so far, technical barriers have prevented effective public participation in spatial data management and analysis. These barriers need to be overcome if participants are to take part in a decision making process in a manner that is both fair and competent. The study was undertaken to quantify land cover change in a particular region and, through this exercise, to determine what the practical barriers to public participation in decision making might be. The work was conducted in the Windermere Valley, British Columbia. Community questions about local environmental change were determined from a local newspaper and discussions with Environmental Non-Governmental Organizations (ENGO's). Using satellite imagery and other geospatial data, community questions about local environmental change were answered through the detection of land cover change for the period 1974--1991. The processes of acquiring the data and completing the analysis were evaluated with the criteria of fairness and competence. The products of the change detection analysis were evaluated based on how well they answered community questions. Suggestions are presented on what tools and resources ENGO's would require to complete a similar study to answer questions about the environment.
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Cabezas, Rabadán Carlos. "Beach Morphology and its Dynamism from Remote Sensing for Coastal Management Support." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/165076.

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[ES] Las playas son espacios costeros que desarrollan numerosas funciones ambientales. Éstas proporcionan importantes beneficios a la sociedad y a las comunidades costeras, entre las que destacan la función ecológica, el suministro de protección para los territorios costeros y el hecho de que constituyen un recurso básico de la industria turística. De forma ligada al cambio climático, así como a acciones humanas que alteran el dinamismo natural de la costa, las playas están experimentando procesos erosivos cada vez más dañinos que afectan a su integridad física y al mantenimiento de sus funciones. La gestión de las playas en muchas ocasiones no se encuentra adaptada a las particularidades de los diferentes segmentos costeros. La toma de decisiones no se sustenta en información suficiente sobre las características, el dinamismo y el estado actual de las playas, dando lugar a soluciones cortoplacistas o ineficaces. Las características geomorfológicas son esenciales en el desarrollo de sus funciones al condicionar sus dimensiones físicas y su comportamiento frente a la acción del mar. Por ello, su caracterización de forma detallada y actualizada es necesaria para llevar a cabo acciones eficientes, permitiendo virar hacia una gestión costera más ecosistémica y sostenible. Las técnicas de teledetección presentan una gran capacidad para la adquisición de datos de la superficie terrestre. En concreto, los satélites Sentinel-2 y Landsat (5, 7 y 8) permiten disponer de forma gratuita imágenes de resolución media con cobertura mundial y alta frecuencia de revisitado. Los algoritmos de extracción de la línea de costa desarrollados recientemente por el Grupo de Cartografia GeoAmbiental y Teledetección (CGAT - UPV) permiten definir sobre estas imágenes la posición de la línea de costa, constituyendo datos potencialmente útiles para describir la morfología de las playas y su dinamismo. Universalizar su aplicación requiere su testeo y validación en diferentes tipos de costa. Para ello, el proceso de extracción ha sido adaptado para su explotación en entornos mareales, y las líneas de costa resultantes han sido evaluadas ante diferentes condiciones oceanográficas ofreciendo una precisión cercana a los 5 m RECM (raíz del error cuadrático medio). Teniendo en cuenta las necesidades de información para la gestión existentes, a partir de estas líneas de costa se propone derivar indicadores que permitan caracterizar la geomorfología de las playas y monitorizar sus cambios. Para ello, las metodologías propuestas aseguran una gestión eficiente de grandes volúmenes de líneas de costa, siendo así capaces de caracterizar las playas cubriendo grandes territorios y periodos de tiempo. Así se derivan el ancho de playa y el tamaño de los granos de sedimento como indicadores objetivos y fácilmente comprensibles de la geomorfología de la playa. La modelización espacio-temporal del estado y los cambios de la línea de costa y de la anchura posibilita monitorizar la respuesta de las playas a temporales y a actuaciones antrópicas, permitiendo analizar los cambios ocurridos cada pocos días hasta cubrir décadas. Su cobertura espacial junto a la integración con otras bases de datos cartográficas permite caracterizar la influencia de la geomorfología de la playa en el desempeño de sus funciones, permitiendo un análisis holístico de la costa a escala regional. Las metodologías desarrolladas en esta tesis y los indicadores derivados desde la teledetección brindan apoyo para dotar de criterios y priorizar las acciones de los gestores. Se contribuye así a llenar el espacio existente entre la disponibilidad de técnicas para obtener información remota y su aplicación en los procesos de toma de decisiones sobre la costa.
[CAT] Les platges són espais costaners que desenvolupen nombroses funcions ambientals. Aquestes proporcionen importants beneficis a la societat i comunitats costaneres, entre les quals destaquen la funció ecològica, el subministrament de protecció per als territoris costaners i el fet que constitueixen un recurs bàsic de la indústria turística. De forma lligada al canvi climàtic, així com a accions humanes que alteren el dinamisme natural de la costa, les platges estan experimentant processos erosius cada vegada més nocius que afecten la seua integritat física i al manteniment de les seues funcions. La gestió de les platges en moltes ocasions no es troba adaptada a les particularitats dels diferents segments costaners. La presa de decisions no es sustenta en informació suficient sobre les característiques, el dinamisme i l'estat actual de les platges, donant lloc a solucions curtterministes o ineficaces. Les característiques geomorfològiques són essencials en el desenvolupament de les seues funcions en condicionar les seues dimensions físiques i el seu comportament enfront de l'acció de la mar. Per això, la seua caracterització de manera detallada i actualitzada és necessària per a dur a terme accions eficients, permetent virar cap a una gestió costanera més ecosistèmica i sostenible. Les tècniques de teledetecció presenten una gran capacitat per a l'adquisició de dades de la superfície terrestre. En concret, els satèl·lits Sentinel-2 i Landsat (5, 7 i 8) permeten disposar de manera gratuïta d'imatges de resolució mitjana amb cobertura mundial i alta freqüència de captura d'informació a un mateix punt. Els algorismes d'extracció de la línia de costa desenvolupats recentment pel Grup de Cartografia Geo-Ambiental i Teledetecció (CGAT - UPV) permeten definir sobre aquestes imatges la posició de la línia de costa, constituint dades potencialment útils per descriure la morfologia de les platges i el seu dinamisme. Universalitzar la seua aplicació requereix el seu testatge i validació en diferents tipus de costa. Per a això, el procés d'extracció ha sigut adaptat per a la seua explotació en entorns mareals, i les línies de costa resultants han sigut avaluades davant diferents condicions oceanogràfiques oferint una precisió pròxima als 5 m RMSE (arrel de l'error quadràtic mitjà). Tenint en compte les necessitats d'informació per a la gestió existents, a partir d'aquestes línies de costa es proposa derivar indicadors que permeten caracteritzar la geomorfologia de les platges i monitorar els seus canvis. Per a això, les metodologies proposades asseguren una gestió eficient de grans volums de línies de costa, sent així capaces de caracteritzar les platges cobrint grans territoris i períodes de temps. Així es deriven l'ample de platja i la grandària dels grans de sediment com a indicadors objectius i fàcilment comprensibles de la geomorfologia de la platja. La modelització espai-temporal de l'estat i els canvis de la línia de costa i de l'amplària possibilita monitorar la resposta de les platges a temporals i a actuacions antròpiques, permetent analitzar els canvis ocorreguts cada pocs dies fins a cobrir dècades. La seua cobertura espacial al costat de la integració amb altres bases de dades cartogràfiques permet caracteritzar la influència de la geomorfologia de la platja en l'acompliment de les seues funcions, permetent una anàlisi holística de la costa a escala regional. Les metodologies desenvolupades en aquesta tesi i els indicadors derivats des de la teledetecció brinden suport per a dotar de criteris i prioritzar les accions dels gestors. Es contribueix així a omplir l'espai existent entre la disponibilitat de tècniques per a obtenir informació remota i la seua aplicació en els processos de presa de decisions sobre la costa.
[EN] Beaches are coastal spaces that perform numerous environmental functions. They provide important benefits to society and coastal communities, including the ecological function, the provision of protection for coastal territories, and constitute a basic resource for the tourism industry. Due to climate change and human actions that alter the natural dynamism of the coast, beaches are experiencing increasingly harmful erosive processes that affect their physical integrity and the maintenance of their ecological functions. Beach management is often not adapted to the particularities of the different coastal segments. Decision-making is not based on sufficient information about characteristics, dynamism, and current state of beaches, resulting in short or ineffective solutions. Geomorphological characteristics are essential in the development of beach functions as they condition their physical dimensions and their behavior in response to the action of the sea. Therefore, their detailed and updated characterization is necessary to carry out efficient actions, allowing a more ecosystemic and sustainable coastal management. Remote sensing techniques have a great capacity for acquiring data from the land surface. In particular, Sentinel-2 and Landsat (5, 7, and 8) satellites freely provide medium resolution images with global coverage and high-revisit frequency. The algorithms for extracting the water/land interface recently developed by the Geo-Environmental Cartography and Remote Sensing Group (CGAT - UPV) allow defining the position of the shoreline on these images, constituting potentially useful data to describe beach morphology and dynamics. Universalizing their application requires testing and validation at different coastal types. For this purpose, the extraction process has been adapted for exploitation in tidal environments, and the resulting shorelines have been assessed under different oceanographic conditions offering an accuracy close to 5 m RMSE (Root-Mean-Square Error). From these shorelines, and taking into account the existing information needs for management, it is proposed to derive indicators to characterize the geomorphology of the beaches and to monitor their changes. To this end, the proposed methodologies ensure the efficient management of large volumes of shorelines, being able to characterize the beaches along broad coastal segments and periods. Thus, beach width and sediment grain size are derived as objective and easily understandable indicators of the beach geomorphology. Spatial-temporal modeling of the state and changes of shoreline position and beach width makes it possible to monitor the response to storms and anthropogenic actions, allowing to analyze changes that occur every few days or over decades. The large spatial coverage together with the integration with other cartographic databases allows characterizing the influence of beach geomorphology in the performance of its functions, offering a holistic view of the coast from a regional scale. The methodologies developed in this thesis and the indicators derived from remote sensing provide support and criteria for prioritizing the actions of managers. This contributes to fill the gap between the availability of techniques to obtain remote information and its application in the coastal decision-making process.
This research integrates findings and results obtained within the framework of the contract FPU15/04501 granted to the author by the Spanish Ministry of Education, Culture, and Sports, which has allowed this doctoral thesis to become a reality. The research has been supported by the funds of the project RESETOCOAST, by the Ministry of Economy, Industry, and Competitiveness (chapters 2 to 5), and the project MONOBESAT PID2019-111435RB-I00 by the Ministry of Science, Innovation, and Universities (chapter 6). About my stay in Portugal, it was possible with the funds of the Erasmus+ program. The contribution of Ó. Ferreira was funded by EW-COAST (PTDC/CTA-OHR/28657/2017) and by FCT and Univ. Algarve through the grant UID/MAR/00350/2013, while S. Costas’ was funded by IF/01047/2014. The following institutions have provided free access to essential data for the development of the publications that constitute this thesis: ESA and USGS for the satellite imagery; Puertos del Estado, and the Portuguese Hydrographic Institute in collaboration with CIMA for supplying oceanographic data; Ministry MITECO and DGSCM for data regarding beach sedimentology and nourishments.
Cabezas Rabadán, C. (2021). Beach Morphology and its Dynamism from Remote Sensing for Coastal Management Support [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165076
TESIS
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Brien, Lynn Ferrara. "Modeling eutrophication vulnerability in coastal Louisiana wetlands impacted by freshwater diversion: a remote sensing approach." Diss., Kansas State University, 2015. http://hdl.handle.net/2097/18999.

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Doctor of Philosophy
Department of Geography
Kevin P. Price
A major strategy in response to rapid degradation and loss of Louisiana’s coastal wetlands has been the construction of siphon diversion projects. The diversions are designed to reintroduce nutrient enriched freshwater from the Mississippi River into wetland ecosystems to combat saltwater intrusion and stimulate marsh growth. The lack of consensus regarding the effects of river diversions on nutrient enrichment of wetland ecosystems is coupled with major concerns about eutrophication. Locating, assessing, and monitoring eutrophic marsh vegetation represent major challenges to understanding the impacts of freshwater diversions. As a result, this study was undertaken to investigate the feasibility of modeling eutrophication vulnerability of a coastal Louisiana marsh receiving turbid Mississippi River water. The major objective was to integrate remotely sensed data with field measurements of vegetation biophysical characteristics and historical ecosystem survey data to delineate landscape patterns suggestive of vulnerability to eutrophication. The initial step in accomplishing this goal was to model the spatial distribution of freshwater impacts using satellite image-based turbidity frequency data associated with siphon diversion operation. Secondly, satellite and spectroradiometer band combinations and vegetation indices optimal for modeling marsh biophysical characteristics related to nutrient enrichment were identified. Finally, satellite image data were successfully integrated with measures of historical and concurrent marsh biophysical characteristics to model the spatial distribution of eutrophication vulnerability and to elucidate the impacts of freshwater diversions.
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Gao, Xiang. "Optical-biophysical relationships and validation of MODIS vegetation indices with multiple fine spatial resolution data in semiarid rangelands." Diss., The University of Arizona, 2001. http://hdl.handle.net/10150/279915.

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The vegetation index products from the Moderate Resolution Imaging Spectroradiometer (MODIS) are designed to provide consistent, spatial and temporal comparisons of global vegetation conditions. The objective of this dissertation was to validate the robustness and global implementation of two MODIS VI algorithms, including the normalized difference vegetation index (NDVI) and "enhanced" vegetation index (EVI). Their performances have been evaluated in: (1) the normalization of canopy background (brightness) variations and the extraction of biophysical parameters across different canopy structures; (2) the characterization of seasonal vegetation profiles (phenological, intra-annual); and (3) spatial and temporal discrimination of vegetation differences (inter-annual). The validation was accomplished through multiple means, including canopy radiative transfer models which were utilized to extract pure vegetation spectra and "true" VI value free of background contamination for varying canopy structures and vegetation amount. The experimental field- and airborne-based radiometry and satellite imagery at multiple spatial resolutions were also coupled and scaled-up for comparison with coarse spatial resolution MODIS VI products to quantify characteristics of semiarid rangeland vegetation. The results showed that NDVI was advantageous in yielding biophysical relationships applicable across varying canopy types, but required knowledge of soils for biophysical estimations. The EVI provided biophysical relationships sensitive to canopy structure, thus requiring knowledge of canopy type for biophysical assessments. The MODIS VI products were successfully validated, radiometrically, by coupling field and the MODLAND Quick Airborne Looks (MQUALS) observations to high spatial resolution imagery (AVIRIS and ETM+), and appeared robust across the two parallel sites for depicting their ecological equivalents. MODIS multitemporal VI profiles were able to depict phenological activity, length of the growing season, peak and onset of greenness, and leaf turnover. Among the sensors tested, spatial resolution was found to be most important for discriminating the major land cover subtypes within the two parallel semiarid rangelands, and spectral resolution had major effects on capturing seasonal contrast due to atmosphere influences. The validation strategy utilized in this study to successively aggregate the integrity-inherent multiple fine spatial resolution data to the coarse MODIS pixel sizes appeared to perform well, thus showing potentials in the validation of other satellite products.
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Loew, Teagan K. "Improvement to Total Maximum Daily Load (TMDL) Measurements and Monitoring by Satellite Remote Sensing Applications." Bowling Green State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1333388592.

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Books on the topic "Environmental management – remote sensing"

1

Schultz, Gert A. Remote Sensing in Hydrology and Water Management. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000.

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Wang, Yeqiao. Remote sensing of coastal environments. Boca Raton, FL: CRC Press/Taylor & Francis, 2010.

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Wang, Yeqiao. Remote sensing of coastal environments. Boca Raton, FL: CRC Press/Taylor & Francis, 2010.

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International Symposium on Remote Sensing for Resources Development and Environmental Management. (7th 1986 Enschede, The Netherlands). Remote sensing for resources development and environmental management. Rotterdam, The Netherlands: A. A. Balkema, 1986.

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L, Ustin Susan, and American Society for Photogrammetry and Remote Sensing., eds. Remote sensing for natural resource management and environmental monitoring. Hoboken, NJ: John Wiley & Sons, 2004.

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B, Pandey C., and R. K. Goyal. Remote sensing for natural resources monitoring & management. Jodhpur, India: Scientific Publishers (India), 2016.

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Yeqiao, Wang, ed. Remote sensing of coastal environments. Boca Raton: Taylor & Francis, 2010.

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International Conference of the Remote Sensing Society and the Center for Earth Resource Management (1985 University of London). Advanced technology for monitoring and processing global environmental data: Proceedings of the international conference of the Remote Sensing Society and the Center for Earth Resources Management held in the University ofLondon, 9-12th September 1985. Reading: Remote Sensing Society, 1985.

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Sameena, M. State remote sensing applications centres: Activities and accomplishments. Bangalore: National Natural Resources Management System, Dept. of Space, 2008.

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Regional Seminar on Earth Observation for Tropical Ecosystem Management (6th 1997 Ho Chi Minh City, Vietnam). Remote sensing for tropical ecosystem management: Proceedings of the Sixth Regional Seminar on Earth Observation for Tropical Ecosystem Management, Ho Chi Minh City, Viet Nam, 3-7 November 1997. New York: United Nations, 1997.

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Book chapters on the topic "Environmental management – remote sensing"

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Chopping, Mark J. "Remote Sensing in Environmental Management." In An Integrated Approach to Environmental Management, 397–422. Hoboken, NJ: John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781118744406.ch17.

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Rochon, Gilbert L., Joseph E. Quansah, Souleymane Fall, Bereket Araya, Larry L. Biehl, Thierno Thiam, Sohaib Ghani, et al. "Remote Sensing, Public Health & Disaster Mitigation." In Geospatial Technologies in Environmental Management, 187–209. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9525-1_11.

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Chakraborty, Surajit. "Remote Sensing and GIS in Environmental Management." In Environmental Management: Issues and Concerns in Developing Countries, 185–220. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62529-0_10.

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Dandrawy, Mohamed E., and El-Sayed E. Omran. "Integrated Watershed Management of Grand Ethiopian Renaissance Dam via Watershed Modeling System and Remote Sensing." In Environmental Remote Sensing in Egypt, 533–74. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39593-3_17.

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Somvanshi, Shivangi Saxena, Aditi Vashisht, Umesh Chandra, and Geetanjali Kaushik. "Delhi Air Pollution Modeling Using Remote Sensing Technique." In Handbook of Environmental Materials Management, 1–27. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-58538-3_174-1.

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Bhartiya, Anubhav, Deepak Kumar, and Praveen Kumar Rai. "Multispectral Remote Sensing for Urban Planning and Development." In Geospatial Technology for Landscape and Environmental Management, 371–82. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7373-3_19.

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Toutin, Thierry. "Map Making with Remote Sensing Data." In Remote Sensing for Environmental Data in Albania: A Strategy for Integrated Management, 65–87. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4357-8_8.

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Singhroy, V. "Environmental Management in Developing Countries: Remote Sensing Case Studies." In Space of Service to Humanity, 165–77. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5692-9_19.

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Le Lay, Yves-Francois, Marylise Cottet, Hervé Piégay, and Anne Rivière-Honegger. "Ground Imagery and Environmental Perception: Using Photo-Questionnaires to Evaluate River Management Strategies." In Fluvial Remote Sensing for Science and Management, 405–29. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119940791.ch18.

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Saleh, Hussain Aziz, and Georges Allaert. "Scientific Research Based Optimisation and Geo-information Technologies for Integrating Environmental Planning in Disaster Management." In Remote Sensing of the Changing Oceans, 359–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16541-2_19.

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Conference papers on the topic "Environmental management – remote sensing"

1

La Loggia, Goffredo, Elisa Arnone, Giuseppe Ciraolo, Antonino Maltese, Leonardo Noto, and Umberto Pernice. "An integrated information system for the acquisition, management and sharing of environmental data aimed to decision making." In SPIE Remote Sensing, edited by Christopher M. U. Neale and Antonino Maltese. SPIE, 2012. http://dx.doi.org/10.1117/12.976300.

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Lu, Guoying. "Flood and drought disasters and water resource management in Xinjiang." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Xiaoling Pan, Wei Gao, Michael H. Glantz, and Yoshiaki Honda. SPIE, 2003. http://dx.doi.org/10.1117/12.466186.

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Klemm, Horst G., Albert Boehm, and Karl Segl. "Innovative remote sensing applications for environmental management of a military training area." In International Symposium on Remote Sensing, edited by Manfred Ehlers. SPIE, 2002. http://dx.doi.org/10.1117/12.453669.

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Teodoro, A., L. Duarte, N. Sillero, J. A. Gonçalves, J. Fonte, L. Gonçalves-Seco, L. M. Pinheiro da Luz, and N. M. R. dos Santos Beja. "An integrated and open source GIS environmental management system for a protected area in the south of Portugal." In SPIE Remote Sensing, edited by Ulrich Michel, Karsten Schulz, Manfred Ehlers, Konstantinos G. Nikolakopoulos, and Daniel Civco. SPIE, 2015. http://dx.doi.org/10.1117/12.2193578.

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Sullivan, Don, Joseph J. Totah, Steve S. Wegener, Francis Y. Enomoto, Chad R. Frost, John Kaneshige, and Jeremy E. Frank. "Intelligent mission management for uninhabited aerial vehicles." In Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Michael Bevis, Yoshinori Shoji, and Steven Businger. SPIE, 2004. http://dx.doi.org/10.1117/12.582446.

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Ghouzlane, Souad. "Wildfire Remote Sensing Applications." In 6th International Students Science Congress. Izmir International Guest Student Association, 2022. http://dx.doi.org/10.52460/issc.2022.027.

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There is a growing interest in mapping, monitoring, and assessing wildfires' risk, behavior, and environmental impacts. Recent developments in Remote sensing technology and tools facilitate the researcher's job in obtaining spatial information and monitoring land changes and hazards. Moreover, remote sensing technology coupled with geographic information systems permits uncovering the spatial potential, predicting Spatio-temporal change patterns, and supporting sustainable land management. Likewise, Using Remote sensing data and GIS tools in mapping wildfire incidents and their behavior has proven to be highly efficient for land managers and firefighters to control the fire and prevent disastrous consequences. This paper aims to uncover some uses of remote sensing data in assessing forest fire hazards at every phase of the fire management program.
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Zeng, Fanjiang, Ximing Zhang, Andrea Foetzki, Xiangyi Li, Xioaming Li, and Michael Runge. "Water relation characteristics of Calligonum and consequences for a sustainable management of vegetation in the southern fringe of Takelamakan Desert." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Xiaoling Pan, Wei Gao, Michael H. Glantz, and Yoshiaki Honda. SPIE, 2003. http://dx.doi.org/10.1117/12.466569.

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Lejiang Guo, Lei Xiao, Xuanlai Tang, and Zhe Hu. "Application of GIS and remote sensing techniques for water resources management." In 2010 2nd Conference on Environmental Science and Information Application Technology (ESIAT). IEEE, 2010. http://dx.doi.org/10.1109/esiat.2010.5568931.

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Li, Jiren. "Application of Remote Sensing to Water Resources Management in Arid Regions of China." In World Water and Environmental Resources Congress 2004. Reston, VA: American Society of Civil Engineers, 2004. http://dx.doi.org/10.1061/40737(2004)119.

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LEGA, MASSIMILIANO, GABRIELE MEDIO, THEODORE ENDRENY, GERMANA ESPOSITO, VALERIA COSTANTINO, and ROBERTA TETA. "ATTRIBUTION OF POLLUTION DISCHARGES IN COASTAL WATERS DURING THE COVID-19 LOCKDOWN USING REMOTE SENSING AND BIOINDICATORS." In WASTE MANAGEMENT AND ENVIRONMENTAL IMPACT 2022. Southampton UK: WIT Press, 2022. http://dx.doi.org/10.2495/wmei220151.

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Reports on the topic "Environmental management – remote sensing"

1

Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.
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Jackson, Samuel, Christina Saltus, Molly Reif, and Glenn Suir. During Nearshore Event Vegetation Gradation (DUNEVEG) : geospatial tools for automating remote vegetation extraction. Engineer Research and Development Center (U.S.), September 2023. http://dx.doi.org/10.21079/11681/47649.

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Monitoring and modeling of coastal vegetation and ecosystems are major challenges, especially when considering environmental response to hazards, disturbances, and management activities. Remote sensing applications can provide alternatives and complementary approaches to the often costly and laborious field-based collection methods traditionally used for coastal ecosystem monitoring. New and improved sensors and data analysis techniques have become available, making remote sensing applications attractive for evaluation and potential use in monitoring coastal vegetation properties and ecosystem conditions and changes. This study involves the extraction of vegetation metrics from airborne lidar and hyperspectral imagery (HSI) collected by the US Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP) to quantify coastal dune vegetation characteristics. A custom geoprocessing toolbox and associated suite of tools were developed to allow inputs of common NCMP lidar and imagery products to help automate the workflow for extracting prioritized dune vegetation metrics in an efficient and repeatable way. This study advances existing coastal ecosystem knowledge and remote sensing techniques by developing new methodologies to classify, quantify, and estimate critical coastal vegetation metrics which will ultimately improve future estimates and predictions of nearshore dynamics and impacts from disturbance events.
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Grossman, Denny, Paul Hugo Suding, Alejandro Coca, Carolina Navarrete, Alberto Villalba, Karolina Argote, Andy Jarvis, and Louis Reymondin. Road Impact Assessment Using Remote Sensing Methodology for Monitoring Land-Use Change in Latin America: Results of Five Case Studies. Inter-American Development Bank, July 2013. http://dx.doi.org/10.18235/0009124.

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The present publication is a summary of the results from the five case studies including an overview of the methodology. VPS/ESG is further examining the possibilities of this methodology to use it for prospective purposes, as the basis for land use management and other potential applications in the development of infrastructure projects. The potential value of the methodology examined is based on being able to take into account the specific conditions of the respective cases, relevant drivers and their strength and the potential enabling effect of a project. This work complements other ex post analyses of infrastructure projects based on project documents, published as IDB Technical Notes titled "Managing the Environmental and Social Impacts of Major IDB-Financed Road Improvement Projects." VPS/ESG will further explore the use in its work of remote sensing and, in addition, study the options of modeling land use and land cover change.
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Wright, Alex, Peter Sanders, John Proust, Robin Workman, Tadas Andriejauskas, and Hao Ye. The new toolkit for highways asset management. TRL, September 2021. http://dx.doi.org/10.58446/ojct3729.

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The application of consistent, reliable information is a key component of highway asset management. However, the tools to understand asset performance have developed rapidly over the last decade. These include asset surveys, intelligent infrastructure monitoring, crowd sourcing, remote sensing, data analytics and visualisation. However, their potential is not yet being fully exploited within the highway environment. By bringing these components of sensing and measurement together we could better understand highway assets and improve reactive and proactive decisions. This paper discusses the tools now available to understand the performance of highway assets. It explores their current and future capabilities, the benefits they bring, and the possibilities that could be achieved through their application within an integrated toolkit. Whilst these tools are not in themselves “new”, a key objective of the paper has been to highlight their emerging capabilities, bring awareness to highway asset managers, and encourage their take up. Increased application will inevitably lead to further development in capability and, importantly, accessibility. There are a number of challenges to overcome to draw full value from these technologies. These include the technical, commercial, and social barriers that influence development and accessibility. The paper discusses actions that could help overcome these, which are presented within the context of a roadmap to the implementation of an integrated toolkit. The roadmap is not definitive - it aims to stimulate further thinking, debate and discussion. The effective management of infrastructure assets is essential to deliver a clean, efficient, safe, reliable and accessible network. A joined up and collaborative approach will help the community achieve the benefits of the integrated toolkit that will help asset managers achieve this.
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Yurovskaya, M. V., and A. V. Yushmanova. Complex Investigations of the World Ocean. Proceedings of the VI Russian Scientific Conference of Young Scientists. Edited by D. A. Alekseev, A. Yu Andreeva, I. M. Anisimov, A. V. Bagaev, Yu S. Bayandina, E. M. Bezzubova, D. F. Budko, et al. Shirshov Institute Publishing House, April 2021. http://dx.doi.org/10.29006/978-5-6045110-3-9.

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The collection contains materials of the VI All-Russian Scientific Conference of Young Scientists "Complex Investigations of the World Ocean", dedicated to the discussion of the main scientific achievements of young specialists in the field of oceanology, modern methods and means of studying the World Ocean. Within the framework of the conference, issues of modern oceanology were considered in sections: ocean physics, ocean biology, ocean chemistry, marine geology, marine geophysics, marine ecology and environmental management, oceanological technology and instrumentation, as well as interdisciplinary physical and biological research of the ocean. Along with the coverage of the results obtained in the course of traditional oceanological expeditionary research, attention was paid to the development of modern methods of studying the ocean: numerical modeling and remote sensing methods of the Earth from space.
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Friedman, Shmuel, Jon Wraith, and Dani Or. Geometrical Considerations and Interfacial Processes Affecting Electromagnetic Measurement of Soil Water Content by TDR and Remote Sensing Methods. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580679.bard.

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Time Domain Reflectometry (TDR) and other in-situ and remote sensing dielectric methods for determining the soil water content had become standard in both research and practice in the last two decades. Limitations of existing dielectric methods in some soils, and introduction of new agricultural measurement devices or approaches based on soil dielectric properties mandate improved understanding of the relationship between the measured effective permittivity (dielectric constant) and the soil water content. Mounting evidence indicates that consideration must be given not only to the volume fractions of soil constituents, as most mixing models assume, but also to soil attributes and ambient temperature in order to reduce errors in interpreting measured effective permittivities. The major objective of the present research project was to investigate the effects of the soil geometrical attributes and interfacial processes (bound water) on the effective permittivity of the soil, and to develop a theoretical frame for improved, soil-specific effective permittivity- water content calibration curves, which are based on easily attainable soil properties. After initializing the experimental investigation of the effective permittivity - water content relationship, we realized that the first step for water content determination by the Time Domain Reflectometry (TDR) method, namely, the TDR measurement of the soil effective permittivity still requires standardization and improvement, and we also made more efforts than originally planned towards this objective. The findings of the BARD project, related to these two consequential steps involved in TDR measurement of the soil water content, are expected to improve the accuracy of soil water content determination by existing in-situ and remote sensing dielectric methods and to help evaluate new water content sensors based on soil electrical properties. A more precise water content determination is expected to result in reduced irrigation levels, a matter which is beneficial first to American and Israeli farmers, and also to hydrologists and environmentalists dealing with production and assessment of contamination hazards of this progressively more precious natural resource. The improved understanding of the way the soil geometrical attributes affect its effective permittivity is expected to contribute to our understanding and predicting capability of other, related soil transport properties such as electrical and thermal conductivity, and diffusion coefficients of solutes and gas molecules. In addition, to the originally planned research activities we also investigated other related problems and made many contributions of short and longer terms benefits. These efforts include: Developing a method and a special TDR probe for using TDR systems to determine also the soil's matric potential; Developing a methodology for utilizing the thermodielectric effect, namely, the variation of the soil's effective permittivity with temperature, to evaluate its specific surface area; Developing a simple method for characterizing particle shape by measuring the repose angle of a granular material avalanching in water; Measurements and characterization of the pore scale, saturation degree - dependent anisotropy factor for electrical and hydraulic conductivities; Studying the dielectric properties of cereal grains towards improved determination of their water content. A reliable evaluation of the soil textural attributes (e.g. the specific surface area mentioned above) and its water content is essential for intensive irrigation and fertilization processes and within extensive precision agriculture management. The findings of the present research project are expected to improve the determination of cereal grain water content by on-line dielectric methods. A precise evaluation of grain water content is essential for pricing and evaluation of drying-before-storage requirements, issues involving energy savings and commercial aspects of major economic importance to the American agriculture. The results and methodologies developed within the above mentioned side studies are expected to be beneficial to also other industrial and environmental practices requiring the water content determination and characterization of granular materials.
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Douglas, Thomas, M. Jorgenson, Hélène Genet, Bruce Marcot, and Patricia Nelsen. Interior Alaska DoD training land wildlife habitat vulnerability to permafrost thaw, an altered fire regime, and hydrologic changes. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43146.

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Climate change and intensification of disturbance regimes are increasing the vulnerability of interior Alaska Department of Defense (DoD) training ranges to widespread land cover and hydrologic changes. This is expected to have profound impacts on wildlife habitats, conservation objectives, permitting requirements, and military training activities. The objective of this three-year research effort was to provide United States Army Alaska Garrison Fort Wainwright, Alaska (USAG-FWA) training land managers a scientific-based geospatial framework to assess wildlife habitat distribution and trajectories of change and to identify vulnerable wildlife species whose habitats and resources are likely to decline in response to permafrost degradation, changing wildfire regimes, and hydrologic reorganization projected to 2100. We linked field measurements, data synthesis, repeat imagery analyses, remote sensing measurements, and model simulations focused on land cover dynamics and wildlife habitat characteristics to identify suites of wildlife species most vulnerable to climate change. From this, we created a robust database linking vegetation, soil, and environmental characteristics across interior Alaska training ranges. The framework used is designed to support decision making for conservation management and habitat monitoring, land use, infrastructure development, and adaptive management across the interior Alaska DoD cantonment and training land domain.
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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, control, structure and crop). 2. Using these models, develop algorithms for an early detection of deviations from the normal. 3. Develop identifying procedures for the most important faults. 4. Develop accommodation procedures while awaiting a repair. The Technion team focused on the shoot environment and the Cornell University team focused on the root environment. Achievements Models: Accurate models were developed for both shoot and root environment in the greenhouse, utilizing neural networks, sometimes combined with robust physical models (hybrid models). Suitable adaptation methods were also successfully developed. The accuracy was sufficient to allow detection of frequently occurring sensor and equipment faults from common measurements. A large data base, covering a wide range of weather conditions, is required for best results. This data base can be created from in-situ routine measurements. Detection and isolation: A robust detection and isolation (formerly referred to as 'identification') method has been developed, which is capable of separating the effect of faults from model inaccuracies and disturbance effects. Sensor and equipment faults: Good detection capabilities have been demonstrated for sensor and equipment failures in both the shoot and root environment. Water stress detection: An excitation method of the shoot environment has been developed, which successfully detected water stress, as soon as the transpiration rate dropped from its normal level. Due to unavailability of suitable monitoring equipment for the root environment, crop faults could not be detected from measurements in the root zone. Dust: The effect of screen clogging by dust has been quantified. Implications Sensor and equipment fault detection and isolation is at a stage where it could be introduced into well equipped and maintained commercial greenhouses on a trial basis. Detection of crop problems requires further work. Dr. Peleg was primarily responsible for developing and implementing the innovative data analysis tools. The cooperation was particularly enhanced by Dr. Peleg's three summer sabbaticals at the ARS, Northem Plains Agricultural Research Laboratory, in Sidney, Montana. Switching from multi-band to hyperspectral remote sensing technology during the last 2 years of the project was advantageous by expanding the scope of detected plant growth attributes e.g. Yield, Leaf Nitrate, Biomass and Sugar Content of sugar beets. However, it disrupted the continuity of the project which was originally planned on a 2 year crop rotation cycle of sugar beets and multiple crops (com and wheat), as commonly planted in eastern Montana. Consequently, at the end of the second year we submitted a continuation BARD proposal which was turned down for funding. This severely hampered our ability to validate our findings as originally planned in a 4-year crop rotation cycle. Thankfully, BARD consented to our request for a one year extension of the project without additional funding. This enabled us to develop most of the methodology for implementing and running the hyperspectral remote sensing system and develop the new analytical tools for solving the non-repeatability problem and analyzing the huge hyperspectral image cube datasets. However, without validation of these tools over a ful14-year crop rotation cycle this project shall remain essentially unfinished. Should the findings of this report prompt the BARD management to encourage us to resubmit our continuation research proposal, we shall be happy to do so.
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Sparrow, Kent, and Sandra LeGrand. Establishing a series of dust event case studies for North Africa. Engineer Research and Development Center (U.S.), February 2023. http://dx.doi.org/10.21079/11681/46445.

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Dust aerosols often create hazardous air quality conditions that affect human health, visibility, agriculture, and communication in various parts of the world. While substantial progress has been made in dust-event simulation and hazard mitigation over the last several decades, accurately forecasting the spatial and temporal variability of dust emissions continues to be a challenge. This report documents an analysis of atmospheric conditions for a series of dust events in North Africa. The researchers highlight four analyzed events that occurred between January 2016 to present in the following locations: (1) the western Sahara Desert; (2) East Algeria and the Iberian Peninsula; (3) Chad-Bodélé Depression; (4) Algeria and Morocco. For each event, the researchers developed an overview of the general synoptic, mesoscale, and local environmental forcing conditions that controlled the event evolution and used a combination of available lidar data, surface weather observations, upper-air soundings, aerosol optical depth, and satellite imagery to characterize the dust conditions. These assessments will support downstream forecast model evaluation and sensitivity testing; however, the researchers also encourage broader use of these assessments as reference case studies for dust transport, air quality modeling, remote sensing, soil erosion, and land management research applications.
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Ahn, Yushin, and Richard Poythress. Impervious Surfaces from High Resolution Aerial Imagery: Cities in Fresno County. Mineta Transportation Institute, May 2024. http://dx.doi.org/10.31979/mti.2024.2257.

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This study investigates impervious surfaces — areas covered by materials with restricted water permeability, such as pavement, sidewalks, and parking lots—due to their crucial role in influencing water dynamics within urban landscapes. The impermeability of these surfaces disrupts natural water absorption processes, resulting in adverse environmental consequences such as increased flooding, erosion, and water pollution. The research employs impervious surface analysis, a method involving the mapping and analysis of these surfaces within specified study areas, including cities, counties, and census tracts. Remote sensing techniques, specifically satellites and aerial imagery, are commonly utilized for the identification and classification of impervious surfaces. In the context of Fresno County, diverse classification methods, encompassing pixel-based, object-based, and deep learning approaches, are employed to classify and evaluate impervious surfaces. Significantly, the deep learning classification method exhibits exceptional performance, achieving an impressive overall accuracy ranging between 85-92%. The study reveals that the estimated percentage of impervious surfaces in Fresno County cities approximates 45%, comparable to the characteristics of medium density residential areas. Noteworthy is the observation in the Fresno/Clovis city area, where the percentage of impervious surfaces escalated from 53% in 2010 (per EnviroAtlas) to 63% in 2020. This 10% increase over a decade closely aligns with concurrent population growth trends in the region. In conclusion, this research underscores the critical significance of comprehending and monitoring impervious surfaces due to their pivotal role in shaping the environmental quality and resilience of urban areas. The insights gleaned from this study provide valuable guidance for the development of effective land use planning and management strategies, specifically tailored to mitigate the adverse impacts of impervious surfaces on the environment and human well-being.
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