scholarly journals Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management

2020 ◽  
Vol 12 (7) ◽  
pp. 2854 ◽  
Author(s):  
Boudewijn van Leeuwen ◽  
Zalán Tobak ◽  
Ferenc Kovács
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Remote Sensing Data ◽  
Weather Conditions ◽  
Human Interaction ◽  
Aerial Photographs ◽  
Sensing Data ◽  
Weather Patterns ◽  
Excess Water ◽  
Frequent Monitoring

Changing climate is expected to cause more extreme weather patterns in many parts of the world. In the Carpathian Basin, it is expected that the frequency of intensive precipitation will increase causing inland excess water (IEW) in parts of the plains more frequently, while currently the phenomenon already causes great damage. This research presents and validates a new methodology to determine the extent of these floods using a combination of passive and active remote sensing data. The method can be used to monitor IEW over large areas in a fully automated way based on freely available Sentinel-1 and Sentinel-2 remote sensing imagery. The method is validated for two IEW periods in 2016 and 2018 using high-resolution optical satellite data and aerial photographs. Compared to earlier remote sensing data-based methods, our method can be applied under unfavorite weather conditions, does not need human interaction and gives accurate results for inundations larger than 1000 m2. The overall accuracy of the classification exceeds 99%; however, smaller IEW patches are underestimated due to the spatial resolution of the input data. Knowledge on the location and duration of the inundations helps to take operational measures against the water but is also required to determine the possibilities for storage of water for dry periods. The frequent monitoring of the floods supports sustainable water management in the area better than the methods currently employed.

scholarly journals Applications of Satellite Remote Sensing to Water Governance and the Mitigation of Climate Change Effects

2020 ◽  
Author(s):  
Ilham Ali ◽  
Jay Famiglietti ◽  
Jonathan McLelland
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Remote Sensing ◽  
Water Stress ◽  
Satellite Remote Sensing ◽  
Water Governance ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Climate Change Effects ◽  
Water Issues

Water stress in both surface and groundwater supplies is an increasing environmental and sustainable management issue. According to the UN Environment Program, at current depletion rates almost half of the world's population will suffer severe water stress by 2030. This is further exacerbated by climate change effects which are altering the hydrologic cycle. Understanding climate change implications is critical to planning for water management scenarios as situations such as rising sea levels, increasing severity of storms, prolonged drought in many regions, ocean acidification, and flooding due to snowmelt and heavy precipitation continue. Today, major efforts towards equitable water management and governance are needed. This study adopts the broad, holistic lenses of sustainable development and water diplomacy, acknowledging both the complex and transboundary nature of water issues, to assess the benefits of a “science to policy” approach in water governance. Such negotiations and frameworks are predicated on the availability of timely and uniform data to bolster water management plans, which can be provided by earth-observing satellite missions. In recent decades, significant advances in satellite remote sensing technology have provided unprecedented data of the Earth’s water systems, including information on changes in groundwater storage, mass loss of snow caps, evaporation of surface water reservoirs, and variations in precipitation patterns. In this study, specific remote sensing missions are surveyed (i.e. NASA LANDSAT, GRACE, SMAP, CYGNSS, and SWOT) to understand the breadth of data available for water uses and the implications of these advances for water management. Results indicate historical precedent where remote sensing data and technologies have been successfully integrated to achieve more sustainable water management policy and law, such as in the passage of the California Sustainable Groundwater Management Act of 2014. In addition, many opportunities exist in current transboundary and interstate water conflicts (for example, the Nile Basin and the Tri-State Water Wars between Alabama, Georgia, and Florida) to integrate satellite-remote-sensed water data as a means of “joint-fact finding” and basis for further negotiations. The authors argue that expansion of access to satellite remote sensing data of water for the general public, stakeholders, and policy makers would have a significant impact on the development of science-oriented water governance measures and increase awareness of water issues by significant amounts. Barriers to entry exist in accessing many satellite datasets because of prerequisite knowledge and expertise in the domain. More user-friendly platforms need to be developed in order to maximize the utility of present satellite data. Furthermore, sustainable co-operations should be formed to employ satellite remote sensing data on a regional scale to preempt problems in water supply, quantity, and quality.

scholarly journals Methods of calculating landslide volume using remote sensing data

2020 ◽  
Vol 149 ◽  
pp. 02009
Author(s):  
Maira Razakova ◽  
Alexandr Kuzmin ◽  
Igor Fedorov ◽  
Rustam Yergaliev ◽  
Zharas Ainakulov
Keyword(s):  
Remote Sensing ◽  
Sea Level ◽  
Remote Sensing Data ◽  
Field Studies ◽  
Aerial Photographs ◽  
Field Observations ◽  
Sensing Data ◽  
Quantitative Estimates ◽  
Landslide Volume ◽  
Engineering Protection

The paper considers the issues of calculating the volume of the landslide from remote sensing data. The main methods of obtaining information during research are field observations. The most important results of field studies are quantitative estimates, such as the volume of the embankment resulting from a landslide, morphometric indicators, etc. The study of a remote and remote object was carried out by remote methods using aerial photographs in the Ile Alatau foothills at 1,600 meters above sea level. The obtained materials from the mudflow survey will be useful in developing solutions to mitigate the effects of disasters and in the design of measures for engineering protection from landslides.

scholarly journals Remote sensing and the future of landscape ecology

2009 ◽  
Vol 33 (4) ◽  
pp. 528-546 ◽  
Author(s):  
Adrian C. Newton ◽  
Ross A. Hill ◽  
Cristian Echeverría ◽  
Duncan Golicher ◽  
José M. Rey Benayas ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Landscape Ecology ◽  
Remote Sensing Data ◽  
Scientific Discipline ◽  
Aerial Photographs ◽  
Ecological Data ◽  
Ecological Processes ◽  
Sensing Data ◽  
Landsat Satellite ◽  
The Uk

Landscape ecology focuses on the analysis of spatial pattern and its relationship to ecological processes. As a scientific discipline, landscape ecology has grown rapidly in recent years, supported by developments in GIS and spatial analysis techniques. Although remote sensing data are widely employed in landscape ecology research, their current and potential roles have not been evaluated critically. To provide an overview of current practice, 438 research papers published in the journal Landscape Ecology for the years 2004—2008 were examined for information about use of remote sensing. Results indicated that only 36% of studies explicitly mentioned remote sensing. Of those that did so, aerial photographs and Landsat satellite sensor images were most commonly used, accounting for 46% and 42% of studies, respectively. The predominant application of remote sensing data across these studies was for thematic mapping purposes. This suggests that landscape ecologists have been relatively slow to recognize the potential value of recent developments in remote sensing technologies and methods. The review also provided evidence of a frequent lack of key detail in studies recently published in Landscape Ecology , with 75% failing to provide any assessment of uncertainty or error relating to image classification and mapping. It is suggested that the role of remote sensing in landscape ecology might be strengthened by closer collaboration between researchers in the two disciplines, by greater integration of diverse remote sensing data with ecological data, and by increased recognition of the value of remote sensing beyond land-cover mapping and pattern description. This is illustrated by case studies drawn from Latin America (focusing on forest loss and fragmentation) and the UK (focusing on habitat quality for woodland birds). Such approaches might improve the analytical and theoretical rigour of landscape ecology, and be applied usefully to issues of outstanding societal interest, such as the impacts of environmental change on biodiversity and ecosystem services.

scholarly journals TOWARDS INTELLIGENT GEO-DATABASE SUPPORT FOR EARTH SYSTEM OBSERVATION: IMPROVING THE PREPARATION AND ANALYSIS OF BIG SPATIO-TEMPORAL RASTER DATA

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 485-492
Author(s):  
N. Mazroob Semnani ◽  
M. Breunig ◽  
M. Al-Doori ◽  
A. Heck ◽  
P. Kuper ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Human Interaction ◽  
Earth System ◽  
Data Preparation ◽  
Synthetic Aperture Radar Data ◽  
Sensing Data ◽  
Advanced Analysis ◽  
Geo Database

Abstract. The European COPERNICUS program provides an unprecedented breakthrough in the broad use and application of satellite remote sensing data. Maintained on a sustainable basis, the COPERNICUS system is operated on a free-and-open data policy. Its guaranteed availability in the long term attracts a broader community to remote sensing applications. In general, the increasing amount of satellite remote sensing data opens the door to the diverse and advanced analysis of this data for earth system science.However, the preparation of the data for dedicated processing is still inefficient as it requires time-consuming operator interaction based on advanced technical skills. Thus, the involved scientists have to spend significant parts of the available project budget rather on data preparation than on science. In addition, the analysis of the rich content of the remote sensing data requires new concepts for better extraction of promising structures and signals as an effective basis for further analysis.In this paper we propose approaches to improve the preparation of satellite remote sensing data by a geo-database. Thus the time needed and the errors possibly introduced by human interaction are minimized. In addition, it is recommended to improve data quality and the analysis of the data by incorporating Artificial Intelligence methods. A use case for data preparation and analysis is presented for earth surface deformation analysis in the Upper Rhine Valley, Germany, based on Persistent Scatterer Interferometric Synthetic Aperture Radar data. Finally, we give an outlook on our future research.

scholarly journals Visual characteristics of landscapes and methods for their assessment on GIS (Belogradchik rocks (Bulgaria) as an example)

2021 ◽  
Vol 27 (2) ◽  
pp. 191-204
Author(s):  
Elina Sheremet ◽  
Natalia Kalutskova ◽  
Vladimir Dekhnich
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Visual Quality ◽  
Aerial Photographs ◽  
Main Task ◽  
Field Observations ◽  
North West ◽  
Sensing Data ◽  
Visual Characteristics

Visual characteristics of landscapes are important factors for the assessment of tourist and recreational potential of territories. At present, a number of methodological approaches are applied to assess the visual characteristics of landscapes. They can be divided into traditional, associated exclusively with field research, and innovative, which is based on remote sensing data (RSD) of high spatial resolution and GIS technologies. Field assessment of the visual quality of landscapes utilizes a system of numerous elementary indicators to minimize subjectivity of assessment. They are conducted within separate areas or touristic routes. In its turn, modern GIS and high quality of remote sensing data allow assessing of most indicators of the visual quality of landscapes for any observation point on the entire territory. The main task of our research is to verify the results of automated processing of ultra-high resolution aerial photographs obtained from unmanned aerial vehicles (UAV) by field observations on a touristic route. The research was carried out on the territory of the “Belogradchik Rocks” Geopark (North-West Bulgaria). In our study, we estimated 4 out of 28 aesthetic indicators—the amount of mountain peaks visible from a site, the amount of mountain peaks on the skyline, the percentage of the forest-covered area, and the amount of open spaces in the wooded landscape. The obtained results confirmed that our approach allows calculating these aesthetic indicators at an accuracy level comparable to field observations.

scholarly journals Towards a continuous inland excess water flood monitoring system based on remote sensing data

2017 ◽  
Vol 10 (3-4) ◽  
pp. 9-15 ◽  
Author(s):  
Boudewijn van Leeuwen ◽  
Zalán Tobak ◽  
Ferenc Kovács ◽  
György Sipos
Keyword(s):  
Remote Sensing ◽  
Agricultural Sector ◽  
Remote Sensing Data ◽  
Large Area ◽  
Sensing Data ◽  
Excess Water ◽  
Sufficient Detail ◽  
Flood Monitoring ◽  
First Results ◽  
Hungarian Plain

Abstract Inland excess water (IEW) is a type of flood where large flat inland areas are covered with water during a period of several weeks to months. The monitoring of these floods is needed to understand the extent and direction of development of the inundations and to mitigate their damage to the agricultural sector and build up infrastructure. Since IEW affects large areas, remote sensing data and methods are promising technologies to map these floods. This study presents the first results of a system that can monitor inland excess water over a large area with sufficient detail at a high interval and in a timely matter. The methodology is developed in such a way that only freely available satellite imagery is required and a map with known water bodies is needed to train the method to identify inundations. Minimal human interference is needed to generate the IEW maps. We will present a method describing three parallel workflows, each generating separate maps. The maps are combined to one weekly IEW map. At this moment, the method is capable of generating IEW maps for a region of over 8000 km2, but it will be extended to cover the whole Great Hungarian Plain, and in the future, it can be extended to any area where a training water map can be created.

scholarly journals USING SATELLITE REMOTE SENSING DATA TO SUPPORT WATER MANAGEMENT IN ARID AND SIMI-ARID AREA

2012 ◽  
Vol 29 (2) ◽  
pp. 789-798
Author(s):  
O. M. Mohamed ◽  
A. M. El-Gindy ◽  
Y. A. Arafa ◽  
M. S. Abd-Elwahed
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Arid Area ◽  
Sensing Data

scholarly journals Visual characteristics of landscapes and methods for their assessment on GIS (Belogradchik rocks (Bulgaria) as an example)

2021 ◽  
Vol 27 (2) ◽  
pp. 191-204
Author(s):  
Elina Sheremet ◽  
Natalia Kalutskova ◽  
Vladimir Dekhnich
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Visual Quality ◽  
Aerial Photographs ◽  
Main Task ◽  
Field Observations ◽  
North West ◽  
Sensing Data ◽  
Visual Characteristics

Visual characteristics of landscapes are important factors for the assessment of tourist and recreational potential of territories. At present, a number of methodological approaches are applied to assess the visual characteristics of landscapes. They can be divided into traditional, associated exclusively with field research, and innovative, which is based on remote sensing data (RSD) of high spatial resolution and GIS technologies. Field assessment of the visual quality of landscapes utilizes a system of numerous elementary indicators to minimize subjectivity of assessment. They are conducted within separate areas or touristic routes. In its turn, modern GIS and high quality of remote sensing data allow assessing of most indicators of the visual quality of landscapes for any observation point on the entire territory. The main task of our research is to verify the results of automated processing of ultra-high resolution aerial photographs obtained from unmanned aerial vehicles (UAV) by field observations on a touristic route. The research was carried out on the territory of the “Belogradchik Rocks” Geopark (North-West Bulgaria). In our study, we estimated 4 out of 28 aesthetic indicators—the amount of mountain peaks visible from a site, the amount of mountain peaks on the skyline, the percentage of the forest-covered area, and the amount of open spaces in the wooded landscape. The obtained results confirmed that our approach allows calculating these aesthetic indicators at an accuracy level comparable to field observations.

Applications of Active Remote Sensing Technologies for Natural Disaster Damage Assessments

2019 ◽  
pp. 1014-1025
Author(s):  
Muhammad Tauhidur Rahman
Keyword(s):  
Remote Sensing ◽  
Natural Disaster ◽  
Remote Sensing Data ◽  
Weather Conditions ◽  
Active Sensors ◽  
Sensing Data ◽  
Passive Remote Sensing ◽  
Relief Operations ◽  
Rescue And Relief ◽  
Processing Techniques

Immediately following a natural disaster, it is imperative to accurately assess the damages caused by the disaster for effective rescue and relief operations. Passive remote sensing imageries have been analyzed and used for over four decades for such assessments. However, they do have their limitations including inability to collect data during violent weather conditions, medium to low spatial resolution, and assessing areas and pixels on a damages/no damage basis. Recent advances in active remote sensing data collection methods can resolve some of these limitations. In this chapter, the basic theories and processing techniques of active remote sensing data is first discussed. It then provides some of the advantages and limitations of using active remote sensing data for disaster damage assessments. Finally, the chapter concludes by discussing how data from active sensors are used to assess damages from various types of natural disasters.

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