Optical water type discrimination and tuning remote sensing band-ratio algorithms: Application to retrieval of chlorophyll and Kd(490) in the Irish and Celtic Seas

2007 ◽  
Vol 73 (3-4) ◽  
pp. 827-834 ◽  
Author(s):  
David McKee ◽  
Alex Cunningham ◽  
Agnes Dudek
Keyword(s):  
Remote Sensing ◽  
Water Type ◽  
Band Ratio

scholarly journals Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters

2019 ◽  
Vol 11 (19) ◽  
pp. 2297 ◽  
Author(s):  
Kristi Uudeberg ◽  
Ilmar Ansko ◽  
Getter Põru ◽  
Ave Ansper ◽  
Anu Reinart
Keyword(s):  
Remote Sensing ◽  
Coastal Waters ◽  
Atmospheric Correction ◽  
Suspended Sediments ◽  
Reflectance Spectra ◽  
Water Type ◽  
Colored Dissolved Organic Matter ◽  
Water Color ◽  
Sentinel 2

The European Space Agency’s Copernicus satellites Sentinel-2 and Sentinel-3 provide observations with high spectral, spatial, and temporal resolution which can be used to monitor inland and coastal waters. Such waters are optically complex, and the water color may vary from completely clear to dark brown. The main factors influencing water color are colored dissolved organic matter, phytoplankton, and suspended sediments. Recently, there has been a growing interest in the use of the optical water type (OWT) classification in the remote sensing of ocean color. Such classification helps to clarify relationships between different properties inside a certain class and quantify variation between classes. In this study, we present a new OWT classification based on the in situ measurements of reflectance spectra for boreal region lakes and coastal areas without extreme optical conditions. This classification divides waters into five OWT (Clear, Moderate, Turbid, Very Turbid, and Brown) and shows that different OWTs have different remote sensing reflectance spectra and that each OWT is associated with a specific bio-optical condition. Developed OWTs are distinguishable by both the MultiSpectral Instrument (MSI) and the Ocean and Land Color Instrument (OLCI) sensors, and the accuracy of the OWT assignment was 95% for both the MSI and OLCI bands. To determine OWT from MSI images, we tested different atmospheric correction (AC) processors, namely ACOLITE, C2RCC, POLYMER, and Sen2Cor and for OLCI images, we tested AC processors ALTNNA, C2RCC, and L2. The C2RCC AC processor was the most accurate and reliable for use with MSI and OLCI images to estimate OWTs.

scholarly journals A Simple Empirical Band-Ratio Algorithm to Assess Suspended Particulate Matter from Remote Sensing over Coastal and Inland Waters of Vietnam: Application to the VNREDSat-1/NAOMI Sensor

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2636
Author(s):  
Dat Dinh Ngoc ◽  
Hubert Loisel ◽  
Vincent Vantrepotte ◽  
Huy Chu Xuan ◽  
Ngoc Nguyen Minh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Band Ratio ◽  
Data Set ◽  
Spectral Bands ◽  
Processing Chain ◽  
Suspended Particulate ◽  
Data Points ◽  
Spm Concentration

VNREDSat-1 is the first Vietnamese satellite enabling the survey of environmental parameters, such as vegetation and water coverages or surface water quality at medium spatial resolution (from 2.5 to 10 m depending on the considered channel). The New AstroSat Optical Modular Instrument (NAOMI) sensor on board VNREDSat-1 has the required spectral bands to assess the suspended particulate matter (SPM) concentration. Because recent studies have shown that the remote sensing reflectance, Rrs(λ), at the blue (450–520 nm), green (530–600 nm), and red (620–690 nm) spectral bands can be assessed using NAOMI with good accuracy, the present study is dedicated to the development and validation of an algorithm (hereafter referred to as V1SPM) to assess SPM from Rrs(λ) over inland and coastal waters of Vietnam. For that purpose, an in-situ data set of hyper-spectral Rrs(λ) and SPM (from 0.47 to 240.14 g·m−3) measurements collected at 205 coastal and inland stations has been gathered. Among the different approaches, including four historical algorithms, the polynomial algorithms involving the red-to-green reflectance ratio presents the best performance on the validation data set (mean absolute percent difference (MAPD) of 18.7%). Compared to the use of a single spectral band, the band ratio reduces the scatter around the polynomial fit, as well as the impact of imperfect atmospheric corrections. Due to the lack of matchup data points with VNREDSat-1, the full VNREDSat-1 processing chain (atmospheric correction (RED-NIR) and V1SPM), aiming at estimating SPM from the top-of-atmosphere signal, was applied to the Landsat-8/OLI match-up data points with relatively low to moderate SPM concentration (3.33–15.25 g·m−3), yielding a MAPD of 15.8%. An illustration of the use of this VNREDSat-1 processing chain during a flooding event occurring in Vietnam is provided.

scholarly journals Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes

2019 ◽  
Vol 11 (2) ◽  
pp. 184 ◽  
Author(s):  
Kun Xue ◽  
Ronghua Ma ◽  
Dian Wang ◽  
Ming Shen
Keyword(s):  
Remote Sensing ◽  
Absorption Coefficient ◽  
Lake Taihu ◽  
Optical Parameters ◽  
Water Type ◽  
Water Types ◽  
Remote Sensing Reflectance ◽  
Inorganic Matter ◽  
Suspended Particulate ◽  
Huai River

Optical water types (OWTs) were identified from remote sensing reflectance (Rrs(λ)) values in a field-measured dataset of several large lakes in the lower reaches of the Yangtze and Huai River (LYHR) Basin. Four OWTs were determined from normalized remote sensing reflectance spectra (NRrs(λ)) using the k-means clustering approach, and were identified in the Sentinel 3A OLCI (Ocean Land Color Instrument) image data over lakes in the LYHR Basin. The results showed that 1) Each OWT is associated with different bio-optical properties, such as the concentration of chlorophyll-a (Chla), suspended particulate matter (SPM), proportion of suspended particulate inorganic matter (SPIM), and absorption coefficient of each component. One optical water type showed an obvious characteristic with a high contribution of mineral particles, while one type was mostly determined by a high content of phytoplankton. The other types belonged to the optically mixed water types. 2) Class-specific Chla inversion algorithms performed better for all water types, except type 4, compared to the overall dataset. In addition, class-specific inversion algorithms for estimating the Chla-specific absorption coefficient of phytoplankton at 443 nm (a*ph(443)) were developed based on the relationship between a*ph(443) and Chla of each OWT. The spatial variations in the class-specific model-derived a*ph(443) values were illustrated for 2 March 2017, and 24 October 2017. 3) The dominant water type and the Shannon index (H) were used to characterize the optical variability or similarity of the lakes in the LYHR Basin using cloud-free OLCI images in 2017. A high optical variation was located in the western and southern parts of Lake Taihu, the southern part of Lake Hongze, Lake Chaohu, and several small lakes near the Yangtze River, while the northern part of Lake Hongze had a low optical diversity. This work demonstrates the potential and necessity of optical classification in estimating bio-optical parameters using class-specific inversion algorithms and monitoring of the optical variations in optically complex and dynamic lake waters.

scholarly journals Uma abordagem metodológica de Sensoriamento Remoto para o monitoramento da contaminação do rio Paraopeba pós-desastre de Brumadinho-MG

2021 ◽  
Vol 43 ◽  
pp. e36
Author(s):  
Neison Cabral Ferreira Freire ◽  
Admilson Da Penha Pacheco ◽  
Vinícius D'Lucas Bezerra Queiroz
Keyword(s):  
Remote Sensing ◽  
Spectral Band ◽  
Ratio Method ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Band Ratio ◽  
Hydrographic Basin ◽  
Search Area ◽  
Brazilian History ◽  
Sentinel 2

The following article aims to present and discuss the monitoring, through Remote Sensing, of the dirt displacement caused by the collapse of the Córrego do Feijão’s dam I of mining waste, which occurred on January 25, 2019, in the rural area of Brumadinho, a city located in the state of Minas Gerais, Brazil. This event is considered one of the greatest technoindustrial disasters in Brazilian history, placing in danger one of the largest hydrographic basin in Brazil: the São Francisco river basin. The search area comprises from where the sludge mud got in contact with the Paraopeba’s right bank to its mouth into the Três Marias Dam, adding up to approximately 315 km. For this monitoring the spectral band ratio method was utilized,  using images from the sensors MSI/Sentinel-2 and OLI/Landsat-8 captured at different dates, employing standardization of means and variances to harmonize the range of the surface reflectance values in each image.

scholarly journals CHROMITITE PROSPECTING USING LANDSAT TM AND ASTER REMOTE SENSING DATA

2015 ◽  
Vol II-2/W2 ◽  
pp. 99-103 ◽  
Author(s):  
A. Beiranvand Pour ◽  
M. Hashim ◽  
M. Pournamdari
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Host Rock ◽  
Regional Scale ◽  
High Potential ◽  
Landsat Tm ◽  
Band Ratio ◽  
Spectral Angle Mapper ◽  
Spectral Transform ◽  
Ophiolitic Rock

Studying the ophiolite complexes using multispectral remote sensing satellite data are interesting because of high diversity of minerals and the source of podiform chromitites. This research developed an approach to discriminate lithological units and detecting host rock of chromitite bodies within ophiolitic complexes using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat Thematic Mapper (TM) satellite data. Three main ophiolite complexes located in south of Iran have been selected for the study. Spectral transform techniques, including minimum noise fraction (MNF) and specialized band ratio were employed to detect different rock units and the identification of high-potential areas of chromite ore deposits within ophiolitic complexes. A specialized band ratio (4/1, 4/5, 4/7) of ASTER, MNF components and Spectral Angle Mapper (SAM) on ASTER and Landsat TM data were used to distinguish ophiolitic rock units. Results show that the specialized band ratio was able to identify different rock units and serpentinized dunite as host rock of chromitites within ophiolitic complexes, appropriately. MNF components of ASTER and Landsat TM data were suitable to distinguish ophiolitic rock complexes at a regional scale. The integration of SAM and Feature Level Fusion (FLF) used in this investigation discriminated the ophiolitic rock units and prepared detailed geological map for the study area. Accordingly, high potential areas (serpentinite dunite) were identified in the study area for chromite exploration targets.The approach used in this research offers the image processing techniques as a robust, reliable, fast and cost-effective method for detecting serpentinized dunite as host rock of chromitite bodies within vast ophiolite complexes using ASTER and Landsat TM satellite data.

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 Assessment of Rice Panicle Blast Disease Using Airborne Hyperspectral Imagery

2016 ◽  
Vol 10 (1) ◽  
pp. 28-34 ◽  
Author(s):  
Takashi Kobayashi ◽  
Masashi Sasahara ◽  
Eiji Kanda ◽  
Kiyoshi Ishiguro ◽  
Shu Hase ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Imagery ◽  
Disease Incidence ◽  
Blast Disease ◽  
Rice Grain ◽  
Large Area ◽  
Potential Yield ◽  
Band Ratio ◽  
Panicle Blast ◽  
Remote Sensing Techniques

Rice blast disease occurs in rice production areas all over the world and is the most important disease in Japan. Remote sensing techniques may provide a mean for detecting disease intensity for large area without being subjected to raters. This study evaluated the use of airborne hyperspectral imagery to measure the severity of panicle blast in field crops. Hyperspectral remote sensing imagery was acquired at the dough stage of rice grain development in northern Japan. The most consistent relationship, with high R2 and low P, was the simple band ratio R498 to 515/R700 to 717 (i.e., the reflectance at 498 to 515-nm divided by the reflectance at 700- to 717-nm). The band ratio of R498 to 515/R700 to 717 increased significantly (P < 0.001) with increasing visual estimates of disease incidence, defined as the percentage of diseased spikelets (R2 = 0.83). Assessment of disease distribution and severity could provide useful information for making decisions regarding the necessity of fungicide application and estimate potential yield loss due to the disease.

scholarly journals MAPPING GLAUCONITE UNITES WITH USING REMOTE SENSING TECHNIQUES IN NORTH EAST OF IRAN

2014 ◽  
Vol XL-2/W3 ◽  
pp. 7-11 ◽  
Author(s):  
R. Ahmadirouhani ◽  
S. Samiee
Keyword(s):  
Remote Sensing ◽  
Ferric Iron ◽  
Silicate Mineral ◽  
Band Ratio ◽  
Spectral Angle Mapper ◽  
Shallow Marine ◽  
North East ◽  
Composition Methods ◽  
East Of Iran ◽  
Remote Sensing Techniques

Glauconite is a greenish ferric-iron silicate mineral with micaceous structure, characteristically formed in shallow marine environments. Glauconite has been used as a pigmentation agent for oil paint, contaminants remover in environmental studies and a source of potassium in plant fertilizers, and other industries. Koppeh-dagh basin is extended in Iran, Afghanistan and Turkmenistan countries and Glauconite units exist in this basin. In this research for enhancing and mapping glauconitic units in Koppeh-dagh structural zone in north east of Iran, remote sensing techniques such as Spectral Angle Mapper classification (SAM), band ratio and band composition methods on SPOT, ASTER and Landsat data in 3 steps were applied.

scholarly journals Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing

2022 ◽  
Vol 12 (1) ◽  
pp. 458
Author(s):  
Julyanne Braga Cruz Amaral ◽  
Fernando Bezerra Lopes ◽  
Ana Caroline Messias de Magalhães ◽  
Sebastian Kujawa ◽  
Carlos Alberto Kenji Taniguchi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Block Design ◽  
Nutrient Content ◽  
Single Band ◽  
Growth Stages ◽  
Least Squares Regression ◽  
Phenological Stages ◽  
Band Ratio ◽  
Remote Sensing Techniques ◽  
Using Data

Although hyperspectral remote sensing techniques have increasingly been used in the nutritional quantification of plants, it is important to understand whether the method shows a satisfactory response during the various phenological stages of the crop. The aim of this study was to quantify the levels of phosphorus (P), potassium (K), calcium (Ca) and zinc (Zn) in the leaves of Vigna Unguiculata (L.) Walp using spectral data obtained by a spectroradiometer. A randomised block design was used, with three treatments and twenty-five replications. The crop was evaluated at three growth stages: V4, R6 and R9. Single-band models were fitted using simple correlations. For the band ratio models, the wavelengths were selected by 2D correlation. For the models using partial least squares regression (PLSR), the stepwise method was used. The model showing the best fit was used to estimate the phosphorus content in the single-band (R² = 0.62; RMSE = 0.54 and RPD = 1.61), band ratio (R² = 0.66; RMSE = 0.65 and RPD = 1.52) and PLSR models, using data from each of the phenological stages (R² = 0.80; RMSE = 0.47 and RPD = 1.66). Accuracy in modelling leaf nutrients depends on the phenological stage, as well as the amount of data used, and is more accurate with a larger number of samples.

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