Conference PaperPDF Available

Spatial Algal Bloom Characterization by Landsat 8-Oli and Field Data Analysis

July 2018

DOI:10.1109/IGARSS.2018.8518844

Conference: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium

Authors:

Alba German

Instituto de Altos Estudios Espaciales Mario Gulich

Fernanda Garcia

Comisión Nacional de Actividades Espaciales

Show all 6 authorsHide

Carlson scale for Trophic State Index[8]. TSI=30.6 + 9.81*ln(chlorophyll-a)

…

Landsat 8-OLI subset (432), 22/02/2017

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Reflectance obtained from Landsat 8-OLI, 22/02/2017

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Field data from San Roque Dam, 22/02/2017

…

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Content uploaded by Alba German

Content may be subject to copyright.

SPATIAL ALGAL BLOOM CHARACTERIZATION BY

LANDSAT 8-OLI AND FIELD DATA ANALYSIS

Andrea Guachalla Alarc´on1,2, Alba Germ´an3,4, Alejandro Aleksink´o1, Fernanda Garc´ıa

Ferreyra1, Carlos Marcelo Scavuzzo1, and Anabella Ferral1,4

1Instituto Mario Gulich, Comisi´on Nacional de Actividades Espaciales (CONAE), C´ordoba, Argentina

2Instituto de Investigaciones Farmac´euticas y Bioquim´ıcas, Universidad Mayor de San Andr´es, La Paz, Bolivia

3Universidad Blas Pascal, C´ordoba, Argentina

4Departamento de Hidrolog´ıa, SRH de la provincia de C´ordoba, Argentina

Abstract

Water pollution is an important problem around the

world as it is closely related to human and environ-

mental health. Field campaigns are expensive, time

consuming and may provide little information. Remote

sensing provides synoptic spatio-temporal views and

can lead to a better understanding of lake ecology. In

this work an extreme algal bloom event which occurred

in a reservoir is characterized by LANDSAT8-OLI sen-

sor and in situ sampling. Chlorophyll-a concentration

and algae abundance data are measured on samples

collected simultaneously with satellite pass and used

to build semiempirical models. Two linear functions to

calculate chlorophyll-a from satellite data are presented

and compared. A linear model from band 2 (blue)

and band 5 (NIR) presents the best performance with

a determination coeﬃcient equal to 0,89. In situ

and satellite chlorophyll-a lead comparable trophic

class assessment, hypertrophic. Both Models fail to

predict chlorophyll-a concentration near river intrusion

(North), where low values of reﬂectance are recorded.

Keywords: chlorophyll-a, phytoplankton, eutrophi-

cation, LANDSAT8-OLI, linear regression

1. INTRODUCTION

Water pollution is one of the most serious problems

around the world and it is closely related to human

and environmental health. This kind of pollution can

proceed from: mismanagement of organic wastes, oil

spill, mining drainage, and others. Particularly, the

increase of organic wastes in water leads to the prolifer-

ation of microorganisms that can cause eutrophication.

Eutrohpication is a process in which primary produc-

tion in water is enhanced and photosynthetic microor-

ganisms proliferate due to the presence of nitrogen and

phosphorus in unbalanced proportions[1]. These mi-

croorganisms inhabit water surface and interfere with

solar rays reaching lower strata of the water column,

causing: an increase in biomass and a narrowed micro-

bial biodiversity, an unbalanced ecological niche, and a

higher mortality rate in aquatic animals due to anoxic

episodes. Chlorophyll-a concentration can be used as

an index to monitor algal abundance by remote sens-

ing technique since it presents active optical properties

in visible and near infrared regions of the electromag-

netic spectrum [2]. In this work, we analyze an algal

bloom in San Roque Reservoir with satellite imagery

from Landsat 8-OLI and ﬁeld data. This reservoir is

the main source of drinking water for Cordoba city, Ar-

gentina, which has a population of 1,8 millon people.

On the other hand, coastal residents use water for do-

mestic purposes, tourism and ﬁshing. The rivers and

streams that ﬂow into the reservoir contribute a large

amount of nutrients which has been causing, in the last

decades, a process of severe eutrophication, sometimes

reaching the hypereutrophication level[3, 4] and releas-

ing cyanotoxins [5]. This research is a continuation of

previous studies carried out with LANDSAT 5-TM and

TERRA-MODIS sensors to monitor water quality and

harmful algae blooms on this reservoir [6].

2. MATERIALS AND

METHODS

2.1 Study area

Figure 1 shows San Roque reservoir which is located in

Villa Carlos Paz in Cordoba, Argentina at 31◦22’4”S

64◦28’10” and 643 masl (meters above sea level). It

shows sampling sites for In Situ measurements, chemi-

cal analysis and satellite imagery processing.

Figure 1: San Roque Reservoir and sampling sites

2.2 Field data

Eight sampling sites were considered in this work as

shown in Figure 1. In Situ parameters including Sec-

chi depth and coordinates were measured in each site,

while two liters of water were collected aseptically. Sam-

ples for algae counting were collected in separate ﬂasks,

and were preserved with lugol until processing. Sam-

ples then were transported to the laboratory where

chlorophyll-a, and algal species abundance were mea-

sured using standardized methods[7].

2.3 Satellite data

Satellite imagery from the scene of algal blooming in

San Roque Reservoir in February 22nd 2017 was re-

covered from Landsat 8-OLI, available in ”Earth Ex-

plorer“ (https://earthexplorer.usgs.gov/). A level

2 LANDSAT 8-OLI product, atmospheric corrected sur-

face reﬂectance and 30 meter spatial resolution, was

used. The scene corresponds to path 229, row 82 ac-

quired on February 22nd of 2017.

2.4 Chlorophyll-a models

Correlation between chlorophyll-a measured in samples

and reﬂectance from Landsat 8-OLI imagery was per-

formed with Rstudio. Reﬂectance recorded at seven

bands by OLI sensor was correlated with in Situ data

by bivariate analysis, obtaining Pearson correlation co-

eﬃcient. For this, B5-B2 and B5/B4 mathematical

functions were used to generate semiempirical models.

Modeled chlorophyll-a was calculated using simple and

multiple line repression to build mathematical semiem-

pirical models. Garganta point was excluded from re-

gressions because it is located in a very narrow lake

branch.

2.5 Trophic state maps

Statistical data was used to generate chlorophyll-a maps

and Trophic State Index (TSI) maps with two semiem-

pirical models: B5-B2 and B5/B4, using ENVI 4.8.

Carlson index was used to generate the TSI maps from

chlorophyll-a concentration data, see table in Figure 2.

Figure 2: Carlson scale for Trophic State Index[8].

TSI=30.6 + 9.81*ln(chlorophyll-a)

3. RESULTS AND

DISCUSSION

3.1 Field data analysis

Secchi disk depth and chlorophyll-a concentration are

directly associated with the trophic state of a water

body, and are used to evaluate eutrophication in diﬀer-

ent settings. Table 1 shows that all the sampling sites

displayed high concentration of chlorophyll-a as well as

a shorter Secchi depth than expected for oligotrophic

lakes.

Table 1: Field data from San Roque Dam, 22/02/2017

Site Chlorophyll-a (ug/L) Secchi depth

Centro 127,1 0,55

Garganta 197,1 0,5

Zona A 53,8 0,3

Zona B 288,5 0,3

SAT 1 27,6 0,3

SAT 2 132,2 0,5

SAT 3 94,7 0,6

SAT 4 56,7 0,5

From the results a case of eutrophic or hypereu-

trophic state in San Roque reservoir can be inferred[8].

Biological analysis showed diﬀerent species of algae,

cyanobacteria and diatomeas (data not shown). The

most abundant species were: Microcystis sp. in Zona B

and SAT2, and Ceratium sp. in Centro and Garganta.

Other species found in the samples were: Oscillatoria

sp.,Cyclotella sp.,Aulacoseria sp., and Clostertopsis

sp. All the species described in the samples are com-

monly found inhabiting aquatic environments, and are

not related to diseases directly, therefore they do not

represent a threat for human health. However, Micro-

cystis sp., a genre that belongs to Cyanobacteria, is

able to produce neurotoxins and hepatotoxins that are

highly harmful for humans and animals and was found

in this reservoir [5].

3.2 Satellite data analysis

Satellite data was obtained from Earth Explorer for

Landsat 8-OLI imagery with a 30 meter spatial reso-

lution. A pre-processed image RGB (4,3,2) is shown in

Figure 3, where a green tone can be appreciated, due

to the presence of photosynthetic microorganisms.

Figure 3: Landsat 8-OLI subset (432), 22/02/2017

Surface reﬂectance (SR) data from the satellite im-

agery was obtained in every sampling point. Figure

4 presents SR as a function of the wavelength center

of OLI sensor bands for all monitoring sites. It can

be observed that ZB and Garganta show the greatest

values at green band (565 nm) in agreements with the

greatest values obtained over those sites for ﬁeld mea-

surements of Chlorophyll-a concentration, 288,5 and

197,1 ug/L respectively. Although algae composition

for ZB and Garganta sites are markedly diﬀerent, spec-

tral signatures obtained from OLI sensor are similar for

both sites, indicating that distinguishing between dif-

ferent algae abundances by means of this sensor is not

a straightforward issue.

Figure 4: Reﬂectance obtained from Landsat 8-OLI,

22/02/2017

3.3 Chlorophyll-a semiempirical models

Two semiempirical mathematical models were used to

evaluate eutrophication in San Roque reservoir based

on the correlation obtained between reﬂectance and

chlorophyll-a concentration. It was found that B4 (Red)

and B5 (NIR) were highly and signiﬁcantly correlated

with chlorophyll-a concentration since Pearson coeﬃ-

cients greater than 0,9 were calculated. Previous stud-

ies used mathematical functions including B5, B4 and

B2 reﬂectances to assess the trophic state on inland

waters [9, 2]. Equations (1) and (2) show the most

adequate models. (1) obtained by Multiple regression,

negative with B2 and positive with B5 and (2) which

depends positively and linearly with the ratio B5/B4.

Model 1 presents the better determination coeﬃcient,

0.89 (p<0,05), while Model 2 presents a determination

coeﬃcient equal 0.87 (p<0,05).

[clorof ila −a] = 5749.5∗B5−9951.1∗B2 + 128.7 (1)

[clorof ila −a] = 101.03 ∗B5/B4−48.04 (2)

3.4 Trophic state maps

Figures 5 and 6 present chlorophyll-a maps obtained by

Model 1 and 2. In situ and satellite chlorophyll-a and

TSI lead comparable values. Both models fail to predict

chlorophyll-a concentration near Cosquin river intru-

sion (North), where low reﬂectance data are recorded.

In that place, negative values of this variable were cal-

culated that aﬀected the building of TSI maps. Trophic

State Index maps showed that the lakes center tend to

a higher state of eutrophication than the northern and

southern region where river intrusion with fresh water

may dilute the bloom. Artiﬁcial aeration system seems

to be not functioning that day. Both models had some

pixels with no data, due to the negative values afore-

mentioned that could not be taken into account by TSI

formula. In this sense, Model 1 seems to respond better

for low chlorophyll-a concentration. Further studies are

being carrying out to improve and extend these algo-

rithms to perform temporal series analysis and incor-

porate low value of chlorophyll-a.

4. CONCLUSIONS

Combined use of satellite and in situ chlorophyll-a data

improves phytoplankton bloom delimitation, an impor-

tant aspect to manage water supply reservoirs. In ad-

dition, remote sensing enhance understanding of spa-

tial patterns associated with natural and anthropogenic

interventions as rivers intrusion or artiﬁcial aeration

systems results. In situ and satellite chlorophyll-a

(a) Chlorophyll-a map

(b) Trohpic State Index map

Figure 5: Semiempirical model using B5 and B2 bands

lead comparable trophic class assessment, mostly hy-

pertrophic. More studies need to be done in order to

extend these models to perform temporal studies and

to improve low chlorophyll-a concentration values esti-

mation.

ACKNOWLEDGMENT: A.Guachalla Alarcon

thanks CELFI for the fellowship granted.

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The aim of this study was to evaluate the presence of microcystin-LR, microcystin-RR, microcystin-YR, and the neurotoxin anatoxin-a in water samples collected monthly during 1 year in San Roque reservoir (Córdoba, Argentina) to identify the environmental factors that could promote the presence of these cyanotoxins. The HPLC-UV and MS/MS analysis showed the presence of microcystin in most of the sampling times, even when Cyanobacteria were subdominant. Microcystin concentrations varied from not detectable levels to 119.0 μg L−1. Thus, they frequently surpassed the guidelines suggested by WHO for drinking water (1 μg L−1) and recreational exposure (20 μg L−1). To the extent of our knowledge, this is the first report of anatoxin-a in freshwaters in South America. Anatoxin-a concentrations varied from not detectable levels to 6.6 ng L−1, a thousand times below the provisional guideline adopted by New Zealand for drinking water. Microcystin showed significant correlation with Microcystis and Pseudoanabaena while anatoxin-a correlated with Oscillatoria and Anabaena counts. Linear discriminant analysis showed that higher pH levels and more variable chlorophyll-a concentrations were measured in San Roque reservoir when cyanotoxins were present. Lower inorganic nitrogen concentrations were observed in autumn, when the prevalence of Anabaena became significant in Cyanobacteria composition and highest anatoxin-a levels were measured. The observed dynamic of phytoplankton going together with the cyanotoxins occurrence could be explained by the hypothesis of cyanotoxins acting as allelopathic compounds. The microcystin levels measured plus the presence of anatoxin-a show the need of stronger management efforts to preserve human and wildlife health.

A Trophic State Index for Lakes

Article

Full-text available

Mar 1977

Robert E. Carlson

A numerical trophic state index for lakes has been developed that incorporates most lakes in a scale of 0 to 100. Each major division ( 10, 20, 30, etc. ) represents a doubling in algal biomass. The index number can bc calculated from any of several parameters, including Secchi disk transparency, chlorophyll, and total phosphorus. My purpose here is to present a new ap- proach to the trophic classification of lakes. This new approach was developed because of frustration in communicating to the pub- lic both the current nature or status of lakes and their future condition after restoration when the traditional trophic classification system is used. The system presented hcrc, termed a trophic state index (TSI), in- volves new methods both of defining trophic status and of determining that status in lakes. All trophic classification is based on the division of the trophic continuum, howcvcr this is defined, into a series of classes termed trophic states. Traditional systems divide the continuum into three classes: oligotrophic, mesotrophic, and cutrophic. There is often no clear delineation of these divisions. Determinations of trophic state are made from examination of several di- verse criteria, such as shape of the oxygen curve, species composition of the bottom fauna or of the phytoplankton, conccntra- tions of nutrients, and various measures of biomass or production. Although each changes from oligotrophy to eutrophy, the changes do not occur at sharply defined places, nor do they all occur at the same place or at the same rate. Some lakes may be considered oligotrophic by one criterion and eutrophic by another; this problem is

Controlling Eutrophication: Nitrogen and Phosphorus

Article

Full-text available

Jan 2009

ECOLOGY Controlling Eutrophication: Nitrogen and Phosphorus

Article

Full-text available

Mar 2009
SCIENCE

Improvements in the water quality of many freshwater and most coastal marine ecosystems requires reductions in both nitrogen and phosphorus inputs.

IN-SITU and SATELLITE MONITORING of the WATER QUALITY of A EUTROPHIC LAKE INTERVENED with A SYSTEM of ARTIFICIAL AIREATION

Article

Feb 2018
Lat Am Trans IEEE

A temporal-spatial analysis is made of the effect of an underwater artificial air diffusion system for the period 2008-2011, on the water quality of Embalse San Roque, Córdoba, through field data and LANDSAT5-TM satellite imagery. The temperature estimated using TM6 band, resulting with a determination coefficient of 0.94 and a mean square error of 0.4ºC. A multiple regression model was used to calculate log(chlorophyll-a) by means of TM1 and TM4 bands, obtaining a determination coefficient of 0.64 which was validated with a control group with and agreement equal 83 %. The processed images show the localized effect of the underwater artificial air diffusion system, improving the water quality in their neighbours.

Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake

Article

Jan 2018

Phytoplankton indicated by its photosynthetic pigment chlorophyll-a is an important pointer on lake ecology and a regularly monitored parameter within the European Water Framework Directive. Along with eutrophication and global warming cyanobacteria gain increasing importance concerning human health aspects. Optical remote sensing may support both the monitoring of horizontal distribution of phytoplankton and cyanobacteria at the lake surface and the reduction of spatial uncertainties associated with limited water sample analyses. Temporal and spatial resolution of using only one satellite sensor, however, may constrain its information value. To discuss the advantages of a multi-sensor approach the sensor-independent, physically based model MIP (Modular Inversion and Processing System) was applied at Lake Kummerow, Germany, and lake surface chlorophyll-a was derived from 33 images of five different sensors (MODIS-Terra, MODIS-Aqua, Landsat 8, Landsat 7 and Sentinel-2A). Remotely sensed lake average chlorophyll-a concentration showed a reasonable development and varied between 2.3 ± 0.4 and 35.8 ± 2.0 mg·m− 3 from July to October 2015. Match-ups between in situ and satellite chlorophyll-a revealed varying performances of Landsat 8 (RMSE: 3.6 and 19.7 mg·m− 3), Landsat 7 (RMSE: 6.2 mg·m− 3), Sentinel-2A (RMSE: 5.1 mg·m− 3) and MODIS (RMSE: 12.8 mg·m− 3), whereas an in situ data uncertainty of 48% needs to be respected. The temporal development of an index on harmful algal blooms corresponded well with the cyanobacteria biomass development during summer months. Satellite chlorophyll-a maps allowed to follow spatial patterns of chlorophyll-a distribution during a phytoplankton bloom event. Wind conditions mainly explained spatial patterns. Integrating satellite chlorophyll-a into trophic state assessment resulted in different trophic classes. Our study endorsed a combined use of satellite and in situ chlorophyll-a data to alleviate weaknesses of both approaches and to better characterise and understand phytoplankton development in lakes.

Analisis de una serie temporal de clorofila-a a partir de imágenes modis de un embalse eutrófico

A Germán
C Tauro
Verónica
I Andreo
A Bernasconi

Análisis de una serie temporal de clorofila-a a partir de imágenes modis de un embalse eutrófico

Jan 2016
1-6

A Germán
C Tauro
I Verónica Andreo
A Bernasconi
Ferral

A. Germán, C. Tauro, Verónica Andreo, I. Bernasconi, and A. Ferral. Análisis de una serie temporal de clorofila-a a partir de imágenes modis de un embalse eutrófico. In Biennial Congress of Argentina (ARGENCON), 2016 IEEE, pages 1-6. IEEE, 2016.