Integration of Remote Sensing & GIS to Manage the Sustainable Development in the Nile Valley Desert Fringes of Assiut-Sohag Governorates, Upper Egypt

2016 ◽  
Vol 44 (5) ◽  
pp. 759-774 ◽  
Author(s):  
Mostafa kamel ◽  
El Sayed M. Abu El Ella
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Nile Valley ◽  
Upper Egypt ◽  
The Sustainable Development

scholarly journals Monitoring oyster culture rafts and seagrass meadows in Nagatsura-ura Lagoon, Sanriku Coast, Japan before and after the 2011 tsunami by remote sensing: their recoveries implying the sustainable development of coastal waters

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10727
Author(s):  
Hiroki Murata ◽  
Motoyuki Hara ◽  
Chinatsu Yonezawa ◽  
Teruhisa Komatsu
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Coastal Waters ◽  
Coastal Ecosystems ◽  
Oyster Culture ◽  
Sanriku Coast ◽  
The Sustainable Development ◽  
Seagrass Meadows ◽  
Before And After ◽  
Aquaculture Management

Background Coastal ecosystems are blue infrastructures that support coastal resources and also aquaculture. Seagrass meadows, one of coastal ecosystems, provide substrates for epiphytic diatoms, which are food resources for cultured filter feeder organisms. Highly intensive coastal aquaculture degrades coastal environments to decrease seagrass meadows. Therefore, efficient aquaculture management and conservation of seagrass meadows are necessary for the sustainable development of coastal waters. In ria-type bays, non-feeding aquaculture of filter feeders such as oysters, scallops, and ascidians are actively practiced along the Sanriku Coast, Japan. Before the 2011 Great East Japan Earthquake, the over-deployment of oyster culture facilities polluted the bottom environment and formed an hypoxic bottom water layer due to the organic excrements from cultured oysters. The tsunami in 2011 devastated the aquaculture facilities and seagrass meadows along the Sanriku Coast. We mapped the oyster culture rafts and seagrass meadows in Nagatsura-ura Lagoon, Sanriku Coast before and after the tsunami and monitored those and environments after the tsunami by field surveys. Methods We conducted field surveys and monitored the environmental parameters in Nagatsura-ura Lagoon every month since 2014. We used high-resolution satellite remote sensing images to map oyster culture rafts and seagrass meadows at irregular time intervals from 2006 to 2019 in order to assess their distribution. In 2019, we also used an unmanned aerial vehicle to analyze the spatial variability of the position and the number of ropes suspending oyster clumps beneath the rafts. Results In 2013, the number and distribution of the oyster culture rafts had been completely restored to the pre-tsunami conditions. The mean area of culture raft increased after the tsunami, and ropes suspending oyster clumps attached to a raft in wider space. Experienced local fishermen also developed a method to attach less ropes to a raft, which was applied to half of the oyster culture rafts to improve oyster growth. The area of seagrass meadows has been expanding since 2013. Although the lagoon had experienced frequent oyster mass mortality events in summer before the tsunami, these events have not occurred since 2011. The 2011 earthquake and tsunami deepened the sill depth and widened the entrance to enhance water exchange and improve water quality in the lagoon. These changes brought the expansion of seagrass meadows and reduction of mass mortality events to allow sustainable oyster culture in the lagoon. Mapping and monitoring of seagrass meadows and aquaculture facilities via satellite remote sensing can provide clear visualization of their temporal changes. This can in turn facilitate effective aquaculture management and conservation of coastal ecosystems, which are crucial for the sustainable development of coastal waters.

scholarly journals A Review of the Sustainability Concept and the State of SDG Monitoring Using Remote Sensing

2020 ◽  
Vol 12 (11) ◽  
pp. 1770 ◽  
Author(s):  
Ronald Estoque
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Global Scale ◽  
Full Potential ◽  
Observation Data ◽  
The Sustainable Development ◽  
Sustainability Concept ◽  
Development Goals ◽  
Earth Observation Data

The formulation of the 17 sustainable development goals (SDGs) was a major leap forward in humankind’s quest for a sustainable future, which likely began in the 17th century, when declining forest resources in Europe led to proposals for the re-establishment and conservation of forests, a strategy that embodies the great idea that the current generation bears responsibility for future generations. Global progress toward SDG fulfillment is monitored by 231 unique social-ecological indicators spread across 169 targets, and remote sensing (RS) provides Earth observation data, directly or indirectly, for 30 (18%) of these indicators. Unfortunately, the UN Global Sustainable Development Report 2019—The Future is Now: Science for Achieving Sustainable Development concluded that, despite initial efforts, the world is not yet on track for achieving most of the SDG targets. Meanwhile, through the EO4SDG initiative by the Group on Earth Observations, the full potential of RS for SDG monitoring is now being explored at a global scale. As of April 2020, preliminary statistical data were available for 21 (70%) of the 30 RS-based SDG indicators, according to the Global SDG Indicators Database. Ten (33%) of the RS-based SDG indicators have also been included in the SDG Index and Dashboards found in the Sustainable Development Report 2019—Transformations to Achieve the Sustainable Development Goals. These statistics, however, do not necessarily reflect the actual status and availability of raw and processed geospatial data for the RS-based indicators, which remains an important issue. Nevertheless, various initiatives have been started to address the need for open access data. RS data can also help in the development of other potentially relevant complementary indicators or sub-indicators. By doing so, they can help meet one of the current challenges of SDG monitoring, which is how best to operationalize the SDG indicators.

scholarly journals What contributions of Artificial Intelligence in Innovation?

2021 ◽  
Vol 234 ◽  
pp. 00105
Author(s):  
Yassine Barakat ◽  
Salmane Bourekkadi ◽  
Samira Khoulji ◽  
Mohamed Larbi Kerkeb
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Sustainable Development ◽  
Critical Point ◽  
Robot Control ◽  
Medical Diagnostics ◽  
Review Article ◽  
Point Of View ◽  
The Sustainable Development ◽  
Different Levels

Artificial intelligence has proven its effectiveness through many applications in society: medical diagnostics, e-commerce, robot control and remote sensing. It has been able to advance many fields and industries including finance, education, transportation and others. In this review article, the method adopted consists first of all in collecting and analyzing all the data making it possible to certify the existence of a varying impact of artificial intelligence on the environment and the sustainable development, through the description of the contributions of AI at the level of several approaches carried out and projects carried out recently. Secondly, we drew from the different levels of differential paradigms cited in the first part, a synthesis, a critical point of view, as well as the perspectives that the feedbacks to the various points raised in the critical vision create, in particular those related to the limits of artificial intelligence and its implications for sustainable development.

Challenges of the Crisis: How to Measure Sustainable Development?

2015 ◽  
pp. 147-160 ◽  
Author(s):  
S. Bobylev ◽  
N. Zubarevich ◽  
S. Solovyeva
Keyword(s):  
Sustainable Development ◽  
World Bank ◽  
Environmental Indicators ◽  
Calculation Methods ◽  
Basic Principles ◽  
The Sustainable Development ◽  
Development Index ◽  
Development Indicators ◽  
Sustainable Development Indicators ◽  
Adjusted Net Savings

The article emphasizes the fact that traditional socio-economic indicators do not reflect the challenges of sustainable development adequately, and this is particularly true for the widely-used GDP indicator. In this connection the elaboration of sustainable development indicators is needed, taking into account economic, social and environmental factors. For Russia, adaptation and use of concepts and basic principles of calculation methods for adjusted net savings index (World Bank) and human development index (UNDP) as integral indicators can be promising. The authors have developed the sustainable development index for Russia, which aggregates and allows taking into account balanced economic, social and environmental indicators.

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