scholarly journals Defining the Limits of Spectrally Based Bathymetric Mapping on a Large River

2019 ◽  
Vol 11 (6) ◽  
pp. 665 ◽  
Author(s):  
Carl Legleiter ◽  
Ryan Fosness
Keyword(s):  
Remote Sensing ◽  
Threshold Value ◽  
Large River ◽  
Ratio Analysis ◽  
Calibration Data ◽  
Retrieval Performance ◽  
Band Ratio ◽  
Multibeam Echosounder ◽  
Kootenai River ◽  
Flowing Channel

Remote sensing has emerged as a powerful method of characterizing river systems but is subject to several important limitations. This study focused on defining the limits of spectrally based mapping in a large river. We used multibeam echosounder (MBES) surveys and hyperspectral images from a deep, clear-flowing channel to develop techniques for inferring the maximum detectable depth, d m a x , directly from an image and identifying optically deep areas that exceed d m a x . Optimal Band Ratio Analysis (OBRA) of progressively truncated subsets of the calibration data provided an estimate of d m a x by indicating when depth retrieval performance began to deteriorate due to the presence of depths greater than the sensor could detect. We then partitioned the calibration data into shallow and optically deep ( d > d m a x ) classes and fit a logistic regression model to estimate the probability of optically deep water, P r ( O D ) . Applying a P r ( O D ) threshold value allowed us to delineate optically deep areas and thus only attempt depth retrieval in relatively shallow locations. For the Kootenai River, d m a x reached as high as 9.5 m at one site, with accurate depth retrieval ( R 2 = 0.94 ) in areas with d < d m a x . As a first step toward scaling up from short reaches to long river segments, we evaluated the portability of depth-reflectance relations calibrated at one site to other sites along the river. This analysis highlighted the importance of calibration data spanning a broad range of depths. Due to the inherent limitations of passive optical depth retrieval in large rivers, a hybrid field- and remote sensing-based approach would be required to obtain complete bathymetric coverage.

scholarly journals SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3009 ◽  
Author(s):  
Shanshan Du ◽  
Liangyun Liu ◽  
Xinjie Liu ◽  
Jian Guo ◽  
Jiaochan Hu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Fluorescence ◽  
Seasonal Variations ◽  
Photosynthetic Activity ◽  
Gross Primary Production ◽  
Atmospheric Correction ◽  
Gansu Province ◽  
Optical Measurements ◽  
Calibration Data ◽  
Flux Measurements

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

scholarly journals An investigation into remote sensing techniques and field observations for modeling of dynamic hydraulic roughness from riparian vegetation

2021 ◽  
Author(s):  
Smriti Chaulagain ◽  
Mark Stone ◽  
Daniel Dombroski ◽  
Tyler Gillihan ◽  
Li Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hydrodynamic Model ◽  
Riparian Vegetation ◽  
Airborne Lidar ◽  
Calibration Data ◽  
Local Flow ◽  
Hydraulic Roughness ◽  
Dynamic Roughness ◽  
Spatially Distributed ◽  
Vegetation Parameters

Riparian vegetation provides many noteworthy functions in river and floodplain systems including its influence on hydrodynamic processes. Traditional methods for predicting hydrodynamic characteristics in the presence of vegetation involve the application of static roughness ( n) values, which neglect changes in roughness due to local flow characteristics. The objectives of this study were to: (1) implement numerical routines for simulating dynamic hydraulic roughness ( n) in a two-dimensional (2D) hydrodynamic model; (2) evaluate the performance of two dynamic roughness approaches; and (3) compare vegetation parameters and hydrodynamic model results based on field-based and remote sensing acquisition methods. A coupled vegetation-hydraulic solver was developed for a 2D hydraulics model using two dynamic approaches, which required vegetation parameters to calculate spatially distributed, dynamic roughness coefficients. Vegetation parameters were determined by field survey and using airborne LiDAR data. Water surface elevations modeled using conventional and the proposed dynamic approaches produced similar profiles. The method demonstrates the suitability in modeling the system where there is no calibration data. Substantial spatial variations in both n and hydraulic parameters were observed when comparing the static and dynamic approaches. Thus, the method proposed here is beneficial for describing the hydraulic conditions for the area having huge variation of vegetation. The proposed methods have the potential to improve our ability to simulate the spatial and temporal heterogeneity of vegetated floodplain surfaces with an approach that is more physically-based and reproducible than conventional “look up” approaches. However, additional research is needed to quantify model performance with respect to spatially distributed flow properties and parameterization of vegetation characteristics.

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 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 Modeling the Relationships between the Height and Spectrum of Submerged Tufa Barrage Using UAV-Derived Geometric Bathymetry and Digital Orthoimages

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 6987
Author(s):  
Jinchen He ◽  
Jiayuan Lin ◽  
Yanhao Xu
Keyword(s):  
Nature Reserve ◽  
Low Cost ◽  
Spectral Characteristics ◽  
Future Research ◽  
Contact Method ◽  
Ratio Analysis ◽  
Band Ratio ◽  
Sedimentary Records ◽  
Evolution And Development ◽  
The Relationship

Tufa barrages play an important role in fluviatile tufa ecosystems and sedimentary records. Quantifying the height of tufa barrage is significant for understanding the evolution and development of the Holocene tufa barrage systems. However, for submerged tufa barrages, there is no low-cost non-contact method to retrieve barrage height. Generally, it is difficult to recognize small tufa barrages by means of remotely sensed satellite data, but the combination of unmanned aerial vehicles (UAV) and Structure-from-Motion (SfM) photogrammetry makes it possible. In this study, we used a fixed-wing UAV and a consumer-grade camera to acquire images of the submerged tufa barrage in Lying Dragon Lake, Jiuzhaigou National Nature Reserve, China, and estimated the height of the tufa barrage through UAV-based photogrammetric bathymetry. On this foundation, the relationship between barrage height and its spectrum was established through band ratio analysis using UAV-derived geometric bathymetry and digital orthoimages, which provided an alternative strategy to characterize the height of submerged tufa barrages. However, the spectral characteristics of submerged tufa barrages will oscillate with changes in the environmental conditions. In future research, we will consider using a dedicated aquatic multispectral camera to improve the experimentation.

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.

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