Satellite imaging reveals increased proportion of population exposed to floods

Nature ◽  
2021 ◽  
Vol 596 (7870) ◽  
pp. 80-86
Author(s):  
B. Tellman ◽  
J. A. Sullivan ◽  
C. Kuhn ◽  
A. J. Kettner ◽  
C. S. Doyle ◽  
...  
Keyword(s):  
Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1592
Author(s):  
Jonguk Kim ◽  
Hyansu Bae ◽  
Hyunwoo Kang ◽  
Suk Gyu Lee

This paper suggests an algorithm for extracting the location of a building from satellite imagery and using that information to modify the roof content. The materials are determined by measuring the conditions where the building is located and detecting the position of a building in broad satellite images. Depending on the incomplete roof or material, there is a greater possibility of great damage caused by disaster situations or external shocks. To address these problems, we propose an algorithm to detect roofs and classify materials in satellite images. Satellite imaging locates areas where buildings are likely to exist based on roads. Using images of the detected buildings, we classify the material of the roof using a proposed convolutional neural network (CNN) model algorithm consisting of 43 layers. In this paper, we propose a CNN structure to detect areas with buildings in large images and classify roof materials in the detected areas.


2018 ◽  
Vol 179 ◽  
pp. 03024 ◽  
Author(s):  
Yao Pan ◽  
Zhong Ming Chi ◽  
Qi Long Rao ◽  
Kai Peng Sun ◽  
Yi Nan Liu

Mission planning problem for remote sensing satellite imaging is studied. Firstly, the time constraint satisfaction problem model is presented after analyzing the characteristic of time constraint. Then, An optimal path searching algorithm based on the discrete time window is proposed according to the non-uniqueness for satellite to mission in the visible time window. Simulation results verify the efficiency of the model and algorithm.


2008 ◽  
Vol 177 (4) ◽  
pp. 837-847 ◽  
Author(s):  
James R. Zimbelman ◽  
W. Brent Garry ◽  
Andrew K. Johnston ◽  
Steven H. Williams

2021 ◽  
Author(s):  
Audra Ligafinza ◽  
Farasdaq Muchibbus Sajjad ◽  
Mohammad Abdul Jabbar ◽  
Anggia Fatmawati ◽  
Alvin Derry Wirawan ◽  
...  

Abstract During the blowout event, it is critical to track the oil spill to minimize environmental damage and optimize restoration cost. In this paper, we deliver our success story in handling oil spill from recent experiences. We utilize remote sensing technologies to establish our analysis and plan the remediation strategies. We also comprehensively discuss the techniques to analyze big data from the satellites, to utilize the downloaded data for forecasting, and to align the satellite information with restoration strategies. PHE relies on its principle to maintain minimum damage and ensures safety by dividing the steps into several aspects of monitoring, response (offshore and onshore), shoreline management and waste management. PHE utilizes latest development in survey by using satellite imaging, survey boat, chopper and UAV drone. Spill containment is done using several layers of oil boom to recover oil spill, complemented with skimmers and storage tanks. PHE encourages shoreline remediation using nets and manual recovery for capturing oil sludge. Using this combination of technologies, PHE is able to model and anticipate oil spill movement from the source up until the farthest shoreline. This enables real time monitoring and handling, therefore minimum environmental damage is ensured. PHE also employs prudent engineering design based on real time field condition in order to ensure the equipment are highly suited for the condition, as well as ensuring good supply chain of the material availability. This publication addresses the first offshore blowout mitigation and handling in Indonesia that uses novel technologies such as static oil boom, satellite imaging and integrated effort in handling shoreline damage. It is hoped that the experience can be replicated for other offshore operating contractors in Indonesia in designing blowout remediation.


2017 ◽  
Vol 10 (2) ◽  
pp. 45
Author(s):  
Greyce Bernardes de Mello Rezende ◽  
Telma Lucia Bezerra Alves

The purpose of this article is to identify the areas of environmental vulnerability by flooding in urban areas of the municipalities of Barra dos Garças - MT, Pontal do Araguaia - MT and Aragarças - GO; and demarcate the occupations in permanent preservation areas (PPAs) in the study area. The methodology uses variables such as time series of maximum quotas of the Araguaia River, from 1968 to 2014, the frequency of those floods, as well as the local level curves. From the junction of these data, it was stipulated the levels of environmental vulnerability by floods in five levels: very high, high, medium, low and very low. The results indicate that areas with very high vulnerability correspond to approximately 1,58 square kilometers which equals to 0.5% of the total area studied; the high vulnerability areas, have only 3.19 square kilometers, corresponding to 1% of the area; the medium vulnerability areas have 7.66 square kilometers, which corresponds to 2.41% of the area; low vulnerability areas, have 11.18 square kilometers of extension relating to 3.52% of the area; and finally the remainder of the study area was characterized as very low vulnerability. After this mapping, it was found by satellite imaging from Google earth software dated 2014, the main occupations in PPAs. The main uses and occupations refer to human activities related to tourism, as well as commercial, residential and industrial buildings. It was found that it is of salutary importance that the Government enforces the fulfillment of the restrictions set out in the Forest Code, preventing that more occupations occur in PPAs and areas subject to flooding. Moreover, the mapping of areas of flooding is also a tool for future public policies that aim to guide the recommended areas to urban expansion, as well as ordering the use and occupation of land by developing zoning.


2011 ◽  
Vol 31 (4) ◽  
pp. 771-780 ◽  
Author(s):  
Elizabeth Ferreira ◽  
Joice H. de Toledo ◽  
Antonio A. A. Dantas ◽  
Rafael M. Pereira

Medium-resolution satellite images have been widely used for the identification and quantification of irrigated areas by center pivot. These areas, which present predominantly circular forms, can be easily identified by visual analyses of these images. In addition to identifying and quantifying areas irrigated by center pivot, other information that is associated to these areas is fundamental for producing cadastral maps. The goal of this work was to generate cadastral mapping of areas irrigated by center pivots in the State of Minas Gerais, Brazil, with the purpose of supplying information on irrigated agriculture. Using the satellite CBERS2B/CCD, images were used to identify and quantify irrigated areas and then associate these areas with a database containing information about: irrigated area, perimeter, municipality, path row, basin in which the pivot is located, and the date of image acquisition.3,781 center pivots systems were identified. The smallest area irrigated was 4.6 hectares and the largest one was 192.6 hectares. The total estimated value of irrigated area was 254,875 hectares. The largest number of center pivots appeared in the municipalities of Unaí and Paracatu, with 495 and 459 systems, respectively. Cadastral mapping is a very useful tool to assist and enhance information on irrigated agriculture in the State of Minas Gerais.


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