Innovative Remote Sensing Identification of Cyanobacterial Blooms Inspired from Pseudo Water Color

نویسندگان

چکیده

The identification and monitoring of cyanobacterial blooms (CBs) is critical for ensuring water security. However, traditional methods are time-consuming labor-intensive not ideal large-scale monitoring. In operational monitoring, the existing remote sensing also due to complex surface features, unstable models, poor robustness thresholds. Here, a novel algorithm, pseudo-Forel-Ule index (P-FUI), developed validated identify based on Terra MODIS, Landsat-8 OLI, Sentinel-2 MSI, Sentinel-3 OLCI sensors. First, three parameters P-FUI, that is, brightness Y, saturation s, hue angle ?, were calculated reflectance. Then, thresholds determined by statistical analysis frequency distribution histogram. We accuracy our approach using high-spatial-resolution satellite data with aid field investigations. Considerable results obtained color differences directly. overall classification more than 93.76%, user’s producer’s 94.60% 94.00%, respectively, kappa coefficient 0.91. identified blooms’ spatial high, medium, low intensity produced consistent compared those data. Impact factors discussed, algorithm was shown be tolerant perturbations clouds high turbidity. This new enables in eutrophic lakes.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Application of hyperspectral remote sensing to cyanobacterial blooms in inland waters

a Ocean Sciences Department, 1156 High Street, University of California Santa Cruz, Santa Cruz, CA, USA b ORAU/NASA Ames Research Center, M.S. 245-4, Bldg. 245, Rm. 120, PO Box 1, Moffett Field, CA 94035, USA c Department of Atmospheric, Ocean, and Space Sciences, University of Michigan, USA d Applied Math and Computer Science, Emory University, Atlanta, GA, USA e Earth Science Division, NASA A...

متن کامل

A novel remote sensing algorithm to quantify phycocyanin in cyanobacterial algal blooms

We present a novel three-band algorithm (PC3) to retrieve phycocyanin (PC) pigment concentration in cyanobacteria laden inland waters. The water sample and remote sensing reflectance data used for PC3 calibration and validation were acquired from highly turbid productive catfish aquaculture ponds. Since the characteristic PC absorption feature at 620 nm is contaminated with residual chlorophyll...

متن کامل

Toxins produced in cyanobacterial water blooms – toxicity and risks

Cyanobacterial blooms in freshwaters represent a major ecological and human health problem worldwide. This paper briefly summarizes information on major cyanobacterial toxins (hepatotoxins, neurotoxins etc.) with special attention to microcystins-cyclic heptapeptides with high acute and chronic toxicities. Besides discussion of human health risks, microcystin ecotoxicology and consequent ecolog...

متن کامل

Monitoring of Harmful Cyanobacterial Blooms

Nowcasting of harmful algal blooms is important both for the public and for environmental management purposes. In the Baltic Sea, summer blooms of nitrogen-fixing cyanobacteria, are regular phenomena but the past years intense and widespread blooms have caused major environmental concern due to its nuisance, increased nitrogen input and toxicity. One of the most abundant species Nodularia sp. c...

متن کامل

Identification of Terrestrial Reflectance From Remote Sensing

Correcting for atmospheric e ects is an essential part of surface-re ectance recovery from radiance measurements. Model-based atmospheric correction techniques improve the accuracy of the identi cation and classi cation of terrestrial re ectances from multi-spectral imagery. Successful and e cient removal of atmospheric e ects from remote-sensing data is a key factor in the success of Earth obs...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Remote Sensing

سال: 2022

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs15010215