scholarly journals 4SM Method Tested in the Gulf of California Suggests Field Data are Not Needed to Derive Satellite Bathymetry

2017 ◽  
Author(s):  
Fabio Favoretto ◽  
Yann Morel ◽  
Andrew Waddington ◽  
Jorge Lopez-Calderon ◽  
Marco Cadena-Roa ◽  
...  
Keyword(s):  
Time Series ◽  
Gulf Of California ◽  
Field Data ◽  
Control Method ◽  
Spectral Characteristics ◽  
Landsat 8 ◽  
Multispectral Images ◽  
Band Ratio ◽  
Average Accuracy ◽  
Satellite Bathymetry

Satellite derived bathymetry methods over coastal areas were born to deliver basic and useful information like bathymetry. However, the process is not straightforward, the main limitation being the need of field data. The Self-calibrated Spectral Supervised Shallow-water Modeler (4SM) method was tested to obtain coastal bathymetry without the use of any field data. Using LANDSAT-8 multispectral images from 2013 to 2016, a bathymetric time series was produced. Groundtruthed depths and an alternative method, Stumpf’s Band Ratio Algorithm, were used to verify the results. Retrieved (4SM) vs groundtruthed depths scored an average r2 (0.90), and a low error (RMSE = 1.47 m). Also 4SM showed, over the whole time series, the same average accuracy of the control method (40%). Advantages, limitations and operability under complex atmosphere and water column conditions, and high and low-albedo bottom processing capabilities of 4SM are discussed. In conclusion, the findings suggest that 4SM is equally accurate as the commonly used Stumpf’s method, the only difference being the independence of 4SM to previous field data, and the potential to deliver bottom spectral characteristics for further modelling. 4SM represents a significative advance in coastal remote sensing potential to obtain bathymetry and optical properties of the marine bottom.

scholarly journals Comparison of LAI Estimates from High Resolution Satellite Observations Using Different Biophysical Processors

2021 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Federico Filipponi
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Agricultural Land ◽  
Spectral Characteristics ◽  
Earth Observation ◽  
Estimation Accuracy ◽  
Landsat 8 ◽  
Biophysical Parameters ◽  
Area Index ◽  
Satellite Sensors

Earth observation provides timely and spatially explicit information about crop phenology and vegetation dynamics that can support decision making and sustainable agricultural land management. Vegetation spectral indices calculated from optical multispectral satellite sensors have been largely used to monitor vegetation status. In addition, techniques to retrieve biophysical parameters from satellite acquisitions, such as the Leaf Area Index (LAI), have allowed to assimilate Earth observation time series in numerical modeling for the analysis of several land surface processes related to agroecosystem dynamics. More recently, biophysical processors used to estimate biophysical parameters from satellite acquisitions have been calibrated for retrieval from sensors with different high spatial resolution and spectral characteristics. Virtual constellations of satellite sensors allow the generation of denser LAI time series, contributing to improve vegetation phenology estimation accuracy and, consequently, enhancing agroecosystems monitoring capacity. This research study compares LAI estimates over croplands using different biophysical processors from Sentinel-2 MSI and Landsat-8 OLI satellite sensors. The results are used to demonstrate the capacity of virtual satellite constellation to strengthen LAI time series to derive important cropland use information over large areas.

scholarly journals A Hybrid Bio-Optical Transformation for Satellite Bathymetry Modeling Using Sentinel-2 Imagery

2019 ◽  
Vol 11 (23) ◽  
pp. 2746 ◽  
Author(s):  
Athanasios K. Mavraeidopoulos ◽  
Emmanouil Oikonomou ◽  
Athanasios Palikaris ◽  
Serafeim Poulos
Keyword(s):  
Optical Properties ◽  
Field Data ◽  
Sea Water ◽  
Aegean Sea ◽  
Multispectral Images ◽  
Inherent Optical Properties ◽  
Sentinel 2A ◽  
Satellite Bathymetry ◽  
Optical Transformation ◽  
Sentinel 2

The article presents a new hybrid bio-optical transformation (HBT) method for the rapid modelling of bathymetry in coastal areas. The proposed approach exploits free-of-charge multispectral images and their processing by applying limited manpower and resources. The testbed area is a strait between two Greek Islands in the Aegean Sea with many small islets and complex seabed relief. The HBT methodology implements semi-analytical and empirical steps to model sea-water inherent optical properties (IOPs) and apparent optical properties (AOPs) observed by the Sentinel-2A multispectral satellite. The relationships of the calculated IOPs and AOPs are investigated and utilized to classify the study area into sub-regions with similar water optical characteristics, where no environmental observations have previously been collected. The bathymetry model is configured using very few field data (training depths) chosen from existing official nautical charts. The assessment of the HBT indicates the potential for obtaining satellite derived bathymetry with a satisfactory accuracy for depths down to 30 m.

scholarly journals Comparison of Different Multispectral Images to Map Hydrothermal Alteration Zones in Kokap, Kulon Progo

2021 ◽  
Vol 6 (2) ◽  
pp. 86
Author(s):  
Bayu Raharja ◽  
Agung Setianto ◽  
Anastasia Dewi Titisari
Keyword(s):  
Remote Sensing ◽  
Hydrothermal Alteration ◽  
Remote Sensing Data ◽  
Component Analysis ◽  
Landsat 8 ◽  
Accuracy Evaluation ◽  
Multispectral Images ◽  
Band Ratio ◽  
Alteration Zones ◽  
Sentinel 2

Using remote sensing data for hydrothermal alteration mapping beside saving time and reducing  cost leads to increased accuracy. In this study, the result of multispectral remote sensing tehcniques has been compare for manifesting hydrothermal alteration in Kokap, Kulon Progo. Three multispectral images, including ASTER, Landsat 8, and Sentinel-2, were compared in order to find the highest overall accuracy using principle component analysis (PCA) and directed component analysis (DPC). Several subsets band combinations were used as PCA and DPC input to targeting the key mineral of alteration. Multispectral classification with the maximum likelihood algorithm was performed to map the alteration types based on training and testing data and followed by accuracy evaluation. Two alteration zones were succeeded to be mapped: argillic zone and propylitic zone. Results of these image classification techniques were compared with known alteration zones from previous study. DPC combination of band ratio images of 5:2 and 6:7 of Landsat 8 imagery yielded a classification accuracy of 56.4%, which was 5.05% and 10.13% higher than those of the ASTER and Sentinel-2 imagery. The used of DEM together with multispectral images was increase the accuracy of hydrothermal alteration mapping in the study area.

scholarly journals Testing of the 4SM Method in the Gulf of California Suggests Field Data Are not Needed to Derive Satellite Bathymetry

Sensors ◽  
2017 ◽  
Vol 17 (10) ◽  
pp. 2248 ◽  
Author(s):  
Fabio Favoretto ◽  
Yann Morel ◽  
Andrew Waddington ◽  
Jorge Lopez-Calderon ◽  
Marco Cadena-Roa ◽  
...  
Keyword(s):  
Gulf Of California ◽  
Field Data ◽  
Satellite Bathymetry

scholarly journals The Method of Detection of Clay Minerals and Iron Oxide Based on Landsat Multispectral Images (as Exemplified in the Territory of Thai Nguyen Province, Vietnam)

2019 ◽  
Vol 4 (1) ◽  
pp. 65-75
Author(s):  
Le Hung Trinh ◽  
V. R. Zabloskii
Keyword(s):  
Iron Oxide ◽  
Clay Minerals ◽  
Spectral Characteristics ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Mineral Deposits ◽  
Landsat 8 ◽  
Multispectral Images ◽  
Landsat 8 Oli ◽  
The World

Landsat multispectral images have been successfully used for discovering some mineral deposits in different regions of the world. Some minerals, including clay minerals and iron oxide, can be detected by multispectral surveys due to their spectral characteristics. This paper presents the results of the application of principal component analysis and Crosta technique for detecting accumulations of clay minerals and iron oxide based on a Landsat 8 Oli multispectral image of Thai Nguyen Province, north of Vietnam. The obtained results have demonstrated the feasibility and suitability of prompt detecting mineral deposits based on the remote sensing data. The image processing methods and facilities tested in this study can be used to create maps of distribution of clay minerals and iron oxide for effective and expedient prospecting and exploration for minerals.

Algae Migration Characteristics in Fresh Water Red Tide

1993 ◽  
Vol 28 (7) ◽  
pp. 197-201 ◽  
Author(s):  
Dunchun Wang ◽  
Isao Somiya ◽  
Shigeo Fujii
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Fresh Water ◽  
Field Data ◽  
Field Survey ◽  
Red Tide ◽  
Bottom Layer ◽  
Total Biomass ◽  
Quality Indices ◽  
Vertical Distributions

To understand the algae migration characteristics in the fresh water red tide, we performed a field survey in the Shorenji Reservoir located in Nabari City, Japan. From the analysis of the field data, it is found that the patterns of vertical distributions of the indices representing biomass are very different in the morning and the afternoon. Since some water quality indices have reverse fluctuations between the surface and the bottom layer in respect of the time series changes and the total biomass of the vertical water column is relatively constant, it is concluded that vertical and daily biomass variation of red tide alga is caused by its daily migration, that is the movement from the bottom layer to the surface in the morning and the reverse movement in the afternoon.

scholarly journals First record of the occurrence of sea ice in the Cordillera Darwin fjords (54°S), Chile

2021 ◽  
pp. 1-11
Author(s):  
Charles Salame ◽  
Inti Gonzalez ◽  
Rodrigo Gomez-Fell ◽  
Ricardo Jaña ◽  
Jorge Arigony-Neto
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
First Record ◽  
Ice Formation ◽  
Future Research ◽  
Landsat 8 ◽  
Surface Salinity ◽  
Air Temperatures ◽  
Aerial Reconnaissance ◽  
High Precipitation

Abstract This paper provides the first evidence for sea-ice formation in the Cordillera Darwin (CD) fjords in southern Chile, which is farther north than sea ice has previously been reported for the Southern Hemisphere. Initially observed from a passenger plane in September 2015, the presence of sea ice was then confirmed by aerial reconnaissance and subsequently identified in satellite imagery. A time series of Sentinel-1 and Landsat-8 images during austral winter 2015 was used to examine the chronology of sea-ice formation in the Cuevas fjord. A longer time series of imagery across the CD was analyzed from 2000 to 2017 and revealed that sea ice had formed in each of the 13 fjords during at least one winter and was present in some fjords during a majority of the years. Sea ice is more common in the northern end of the CD, compared to the south where sea ice is not typically present. Is suggested that surface freshening from melting glaciers and high precipitation reduces surface salinity and promotes sea-ice formation within the semi-enclosed fjord system during prolonged periods of cold air temperatures. This is a unique set of initial observations that identify questions for future research in this remote area.

scholarly journals A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth

2021 ◽  
Vol 13 (15) ◽  
pp. 2869
Author(s):  
MohammadAli Hemati ◽  
Mahdi Hasanlou ◽  
Masoud Mahdianpari ◽  
Fariba Mohammadimanesh
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Policy Development ◽  
Atmospheric Correction ◽  
Open Data ◽  
Detection Methods ◽  
Landsat 8 ◽  
Landsat Images ◽  
Detection Analysis ◽  
The Impact

With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding of the dynamics of the Earth’s surface at a spatial scale relevant to management, scientific inquiry, and policy development. In this study, we identify trends in Landsat-informed change detection studies by surveying 50 years of published applications, processing, and change detection methods. Specifically, a representative database was created resulting in 490 relevant journal articles derived from the Web of Science and Scopus. From these articles, we provide a review of recent developments, opportunities, and trends in Landsat change detection studies. The impact of the Landsat free and open data policy in 2008 is evident in the literature as a turning point in the number and nature of change detection studies. Based upon the search terms used and articles included, average number of Landsat images used in studies increased from 10 images before 2008 to 100,000 images in 2020. The 2008 opening of the Landsat archive resulted in a marked increase in the number of images used per study, typically providing the basis for the other trends in evidence. These key trends include an increase in automated processing, use of analysis-ready data (especially those with atmospheric correction), and use of cloud computing platforms, all over increasing large areas. The nature of change methods has evolved from representative bi-temporal pairs to time series of images capturing dynamics and trends, capable of revealing both gradual and abrupt changes. The result also revealed a greater use of nonparametric classifiers for Landsat change detection analysis. Landsat-9, to be launched in September 2021, in combination with the continued operation of Landsat-8 and integration with Sentinel-2, enhances opportunities for improved monitoring of change over increasingly larger areas with greater intra- and interannual frequency.

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