scholarly journals A Bayesian approach for estimating vertical chlorophyll profiles from satellite remote sensing: proof-of-concept

2010 ◽  
Vol 68 (4) ◽  
pp. 792-799 ◽  
Author(s):  
Robert Williamson ◽  
John G. Field ◽  
Frank A. Shillington ◽  
Astrid Jarre ◽  
Anet Potgieter
Keyword(s):  
Remote Sensing ◽  
Bayesian Approach ◽  
Satellite Remote Sensing ◽  
Marine Ecosystem ◽  
Satellite Image ◽  
Remotely Sensed ◽  
Proof Of Concept ◽  
Remotely Sensed Data ◽  
Chl A ◽  
Subsurface Light

Abstract Williamson, R., Field, J. G., Shillington, F. A., Jarre, A., and Potgieter, A. 2011. A Bayesian approach for estimating vertical chlorophyll profiles from satellite remote sensing: proof-of-concept. – ICES Journal of Marine Science, 68: 792–799. A proof-of-concept demonstration is presented using a novel method for estimating vertical distributions of chlorophyll a (Chl a) from archives of data from ships, combined with remotely sensed data of sea surface temperature, surface Chl a, and wind (U and V vectors) from satellites. Our study area has contrasting hydrographic regimes that include the dynamic southern Benguela upwelling system and the stratified waters of the Agulhas Bank. Cluster analysis is used to identify “typical” Chl a profiles from an archive of profiles recorded in 2002–2008. Bayesian networks were then used to relate characteristic profiles to remotely sensed surface features, subregions, seasons, and depths. The proposed method could be used to predict daily Chl a profiles for each pixel of a satellite image to estimate biomass and subsurface light fields, and these combined with a light algorithm to model primary production for the Benguela large marine ecosystem.

THE ROLE OF REMOTE SENSING DATA FOR COASTAL ZONE MONITIORING AND MANAGEMENT (CASE STUDY FOR THE EAST PART OF GULF OF FINLAND)

2017 ◽  
Author(s):  
Nikifor Ostanin ◽  
Nikifor Ostanin
Keyword(s):  
Remote Sensing ◽  
Coastal Zone ◽  
Environmental Changes ◽  
Rapid Development ◽  
Water Environment ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Gulf Of Finland ◽  
Coastal Protection ◽  
Remotely Sensed Data

Coastal zone of the Eastern Gulf of Finland is subjected to essential natural and anthropogenic impact. The processes of abrasion and accumulation are predominant. While some coastal protection structures are old and ruined the problem of monitoring and coastal management is actual. Remotely sensed data is important component of geospatial information for coastal environment research. Rapid development of modern satellite remote sensing techniques and data processing algorithms made this data essential for monitoring and management. Multispectral imagers of modern high resolution satellites make it possible to produce advanced image processing, such as relative water depths estimation, sea-bottom classification and detection of changes in shallow water environment. In the framework of the project of development of new coast protection plan for the Kurortny District of St.-Petersburg a series of archival and modern satellite images were collected and analyzed. As a result several schemes of underwater parts of coastal zone and schemes of relative bathymetry for the key areas were produced. The comparative analysis of multi-temporal images allow us to reveal trends of environmental changes in the study areas. This information, compared with field observations, shows that remotely sensed data is useful and efficient for geospatial planning and development of new coast protection scheme.

scholarly journals GIS and Remote Sensing Application in Water Management in Agriculture Field

2020 ◽  
Author(s):  
Sassi Mohamed Taher
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Resources ◽  
Land Surface ◽  
Remotely Sensed ◽  
Irrigated Agriculture ◽  
Accurate Information ◽  
Remotely Sensed Data ◽  
Gis And Remote Sensing ◽  
Practical Applications

This document is meant to demonstrate the potential uses of remote sensing in managing water resources for irrigated agriculture and to create awareness among potential users. Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere transfer processes can lead to a better understanding of the relationships between crop growth and water management. Remote sensing and GIS was used to map the agriculture area and for detect the change. This was very useful for mapping availability and need of water resources but the problem was concentrating in data collection and analysis because this kind of information and expertise are not available in all country in the world mainly in the developing and under developed country or third world country. However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing.

scholarly journals Characteristics Fishing Areas of Bigeye Tuna (Thunnus Obesus) in Depth of 155 m Based on Remotely Sensed Data

2020 ◽  
Vol 5 (1) ◽  
pp. 62-70
Author(s):  
Achmad Fachruddin-Syah ◽  
Jonson Lumban Gaol ◽  
Mukti Zainuddin ◽  
Nadela Rista Apriliya ◽  
Dessy Berlianty ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Remotely Sensed ◽  
Eastern Indian Ocean ◽  
Bigeye Tuna ◽  
Remotely Sensed Data ◽  
Surface Salinity ◽  
Chl A ◽  
Fishing Vessels ◽  
Thunnus Obesus ◽  
Daily Data

Bigeye tuna (Thunnus obesus) is one of the commercially important pelagic species that caught mostly in the eastern Indian Ocean. This species prefers to stay close, and is usually below the thermocline layer. Remotely sensed data was used to determine the characteristics of Bigeye tuna fishing areas at a depth of 155 meter. Fishing vessels for Bigeye tuna were obtained from vessel monitoring systems (VMS) from January through December, 2015-2016. Daily data on sub-surface temperature (SST), sub-surface chlorophyll-a concentration (SSC), and sub-surface salinity (SSS) were obtained from the INDESO Project website. All oceanographic parameter data were selected at a depth of 155 m. The position of Bigeye tuna and oceanographic data were then grouped into 2 group monsoon, southeast monsoon (April – September) and northwest monsoon (October – March). The results showed that, during the southeast and northwest monsoon, Bigeye tuna mostly found in SSC of 0.03 – 0.05 mg/m3, SST of 16° - 18°C and salinity of 34 psu. These results showed that at depth of 155 m, Bigeye Tuna prefers to stay in small chl-a (0.03 – 0.04 mg/m3), low SST (16° - 18°C) and salinity of 34 psu. These information were essential and could be used to support fisheries management decisions especially for Bigeye Tuna in the eastern Indian Ocean.

Prediction Changes for Nonstationary Multi-Temporal Satellite Images using HMM

2017 ◽  
pp. 387-406
Author(s):  
Ali Ben Abbes ◽  
Imed Riadh Farah
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Satellite Image ◽  
Remotely Sensed ◽  
High Temporal Resolution ◽  
Remotely Sensed Data ◽  
Vegetation Monitoring ◽  
Area Of Interest ◽  
Multi Temporal ◽  
The Difference

Due to the growing advances in their temporal, spatial, and spectral resolutions, remotely sensed data continues to provide tools for a wide variety of environmental applications. This chapter presents the benefits and difficulties of Multi-Temporal Satellite Image (MTSI) for land use. Predicting land use changes using remote sensing is an area of interest that has been attracting increasing attention. Land use analysis from high temporal resolution remotely sensed images is important to promote better decisions for sustainable management land cover. The purpose of this book chapter is to review the background of using Hidden Markov Model (HMM) in land use change prediction, to discuss the difference on modeling using stationary as well as non-stationary data and to provide examples of both case studies (e.g. vegetation monitoring, urban growth).

scholarly journals Remote Sensing of Boreal Wetlands 1: Data Use for Policy and Management

2020 ◽  
Vol 12 (8) ◽  
pp. 1320 ◽  
Author(s):  
Laura Chasmer ◽  
Danielle Cobbaert ◽  
Craig Mahoney ◽  
Koreen Millard ◽  
Daniel Peters ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remotely Sensed ◽  
Decision Makers ◽  
Remotely Sensed Data ◽  
Ramsar Convention ◽  
Canadian Perspective ◽  
History Of ◽  
Wetland Inventory ◽  
Monitoring And Measurement ◽  
Underlying Processes

Wetlands have and continue to undergo rapid environmental and anthropogenic modification and change to their extent, condition, and therefore, ecosystem services. In this first part of a two-part review, we provide decision-makers with an overview on the use of remote sensing technologies for the ‘wise use of wetlands’, following Ramsar Convention protocols. The objectives of this review are to provide: (1) a synthesis of the history of remote sensing of wetlands, (2) a feasibility study to quantify the accuracy of remotely sensed data products when compared with field data based on 286 comparisons found in the literature from 209 articles, (3) recommendations for best approaches based on case studies, and (4) a decision tree to assist users and policymakers at numerous governmental levels and industrial agencies to identify optimal remote sensing approaches based on needs, feasibility, and cost. We argue that in order for remote sensing approaches to be adopted by wetland scientists, land-use managers, and policymakers, there is a need for greater understanding of the use of remote sensing for wetland inventory, condition, and underlying processes at scales relevant for management and policy decisions. The literature review focuses on boreal wetlands primarily from a Canadian perspective, but the results are broadly applicable to policymakers and wetland scientists globally, providing knowledge on how to best incorporate remotely sensed data into their monitoring and measurement procedures. This is the first review quantifying the accuracy and feasibility of remotely sensed data and data combinations needed for monitoring and assessment. These include, baseline classification for wetland inventory, monitoring through time, and prediction of ecosystem processes from individual wetlands to a national scale.

scholarly journals Remote Sensing Approaches and Related Techniques to Map and Study Landslides

2020 ◽  
Author(s):  
Ram L. Ray ◽  
Maurizio Lazzari ◽  
Tolulope Olutimehin
Keyword(s):  
Remote Sensing ◽  
Hazard Assessment ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Landslide Monitoring ◽  
In Situ Observation ◽  
Remotely Sensed Data ◽  
Sensing Data ◽  
Stability Model

Landslide is one of the costliest and fatal geological hazards, threatening and influencing the socioeconomic conditions in many countries globally. Remote sensing approaches are widely used in landslide studies. Landslide threats can also be investigated through slope stability model, susceptibility mapping, hazard assessment, risk analysis, and other methods. Although it is possible to conduct landslide studies using in-situ observation, it is time-consuming, expensive, and sometimes challenging to collect data at inaccessible terrains. Remote sensing data can be used in landslide monitoring, mapping, hazard prediction and assessment, and other investigations. The primary goal of this chapter is to review the existing remote sensing approaches and techniques used to study landslides and explore the possibilities of potential remote sensing tools that can effectively be used in landslide studies in the future. This chapter also provides critical and comprehensive reviews of landslide studies focus¬ing on the role played by remote sensing data and approaches in landslide hazard assessment. Further, the reviews discuss the application of remotely sensed products for landslide detection, mapping, prediction, and evaluation around the world. This systematic review may contribute to better understanding the extensive use of remotely sensed data and spatial analysis techniques to conduct landslide studies at a range of scales.

scholarly journals Satellite remote sensing for an ecosystem approach to fisheries management

2011 ◽  
Vol 68 (4) ◽  
pp. 651-666 ◽  
Author(s):  
Emmanuel Chassot ◽  
Sylvain Bonhommeau ◽  
Gabriel Reygondeau ◽  
Karen Nieto ◽  
Jeffrey J. Polovina ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Fisheries Management ◽  
Satellite Remote Sensing ◽  
Ecosystem Approach ◽  
Fish Population ◽  
Remotely Sensed Data ◽  
In Situ Data ◽  
Promising Tool ◽  
High Resolution Images ◽  
Fish Aggregation

Abstract Chassot, E., Bonhommeau, S., Reygondeau, G., Nieto, K., Polovina, J. J., Huret, M., Dulvy, N. K., and Demarcq, H. 2011. Satellite remote sensing for an ecosystem approach to fisheries management. – ICES Journal of Marine Science, 68: 651–666. Satellite remote sensing (SRS) of the marine environment has become instrumental in ecology for environmental monitoring and impact assessment, and it is a promising tool for conservation issues. In the context of an ecosystem approach to fisheries management (EAFM), global, daily, systematic, high-resolution images obtained from satellites provide a good data source for incorporating habitat considerations into marine fish population dynamics. An overview of the most common SRS datasets available to fishery scientists and state-of-the-art data-processing methods is presented, focusing on recently developed techniques for detecting mesoscale features such as eddies, fronts, filaments, and river plumes of major importance in productivity enhancement and associated fish aggregation. A comprehensive review of remotely sensed data applications in fisheries over the past three decades for investigating the relationships between oceanographic conditions and marine resources is provided, emphasizing how synoptic and information-rich SRS data have become instrumental in ecological analyses at community and ecosystem scales. Finally, SRS data, in conjunction with automated in situ data-acquisition systems, can provide the scientific community with a major source of information for ecosystem modelling, a key tool for implementing an EAFM.

scholarly journals Mapping Dragon Fruit Croplands from Space Using Remote Sensing of Artificial Light at Night

2020 ◽  
Vol 12 (24) ◽  
pp. 4139
Author(s):  
Ruirui Wang ◽  
Wei Shi ◽  
Pinliang Dong
Keyword(s):  
Remote Sensing ◽  
Infrared Imaging ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Important Indicator ◽  
Artificial Lighting ◽  
Sensing Data ◽  
Dragon Fruit ◽  
Positive Correlations

The nighttime light (NTL) on the surface of Earth is an important indicator for the human transformation of the world. NTL remotely sensed data have been widely used in urban development, population estimation, economic activity, resource development and other fields. With the increasing use of artificial lighting technology in agriculture, it has become possible to use NTL remote sensing data for monitoring agricultural activities. In this study, National Polar Partnership (NPP)-Visible Infrared Imaging Radiometer Suite (VIIRS) NTL remote sensing data were used to observe the seasonal variation of artificial lighting in dragon fruit cropland in Binh Thuan Province, Vietnam. Compared with the statistics of planted area, area having products and production of dragon fruit by district in the Statistical Yearbook of Binh Thuan Province 2018, values of the mean and standard deviation of NTL brightness have significant positive correlations with the statistical data. The results suggest that the NTL remotely sensed data could be used to reveal some agricultural productive activities such as dragon fruits production accurately by monitoring the seasonal artificial lighting. This research demonstrates the application potential of NTL remotely sensed data in agriculture.

scholarly journals Investigation of surface area of lakes and marshes from satellite images by using remote sensing and geographic information system integration in Iraq

2018 ◽  
Vol 162 ◽  
pp. 03016
Author(s):  
Alaa Dawood ◽  
Yousif Kalaf ◽  
Nagham Abdulateef ◽  
Mohammed Falih
Keyword(s):  
Remote Sensing ◽  
Surface Area ◽  
System Integration ◽  
Hydrological Regime ◽  
Remotely Sensed ◽  
Total Surface Area ◽  
Water Levels ◽  
Remotely Sensed Data ◽  
Surface Areas ◽  
Water Volumes

Water level and distribution is very essential in almost all life aspects. Natural and artificial lakes represent a large percentage of these water bodies in Iraq. In this research the changes in water levels are observed by calculating the areas of five different lakes in five different regions and two different marshes in two different regions of the country, in a period of 12 years (2001 - 2012), archived remotely sensed images were used to determine surface areas around lakes and marshes in Iraq for the chosen years . Level of the lakes corresponding to satellite determined surface areas were retrieved from remotely sensed data .These data were collected to give explanations on lake level and surface area fluctuations. It is important to determine these areas at different water levels to know areas which are being flooded in addition to the total area inundated .The behavior of hydrological regime of these lakes during the period was assessed using an integration of remote sensing and GIS techniques which found that the total surface area of the lakes had diminished and their water volumes reduced. The study further revealed that the levels of the lakes surfaces had lowered through these years.

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