Paper · 2020 · 2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

Analysis of Changes in Density of Mangrove Using Normalized Difference Vegetation Index Algorithm on Sentinel 2A Level 1C (Case Study: Gresik Regency)

Bangun Muljo Sukojo; Debyana Nur Savitri

8
claims
9
verbatim quotes
8
citations
3
research areas
—
Not open access

Abstract

Mangrove forests have important values and roles both ecologically and economically in coastal areas. Over time, the area of mangrove forests in Indonesia decreased due to high rates of deforestation. One of the mangrove forests that has decreased in the area is the mangrove forest on the North Coast of East Java. Therefore, monitoring of changes in the density of the mangrove canopy is needed, especially in Gresik Regency. Mangrove ecosystems can be identified using remote sensing technology. To get the density level of the mangrove canopy, it can be done by calculating the Normalized Difference Vegetation Index (NDVI) algorithm on the Sentinel 2A Level 1C satellite imagery in 2016-2019. Based on the results of the study, it was concluded that the dominant mangroves in Gresik Regency in 2016 to 2019 were mangroves with good density, which amounted to 58.66% in 2016; 53.21% in 2017; 45.22% in 2018, and 46.81% in 2019. Then, the mangrove area in Gresik Regency from 2016 to 2019 increased by 22.09% in 2017, then decreased by 1.74% in 2018 and continued to decrease by 8.28% in 2019. The most influential parameter for the density of mangrove canopy is the water pH with a correlation coefficient of -0.733 which shows that the density of mangroves canopy and the water pH has a strong and significant correlation.

Abstract from the paper’s OpenAlex record, shown for indexing and research. Copyright remains with the authors or the publisher. Read at the source ↗

The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.

Claims 8

Observationobservedoriginal resultmeasured

Claim · model-written summary

Good canopy density was dominant in 2016 at 58.66%.

Taxon
mangrovese0
Outcome
mangroves with good densitye0
Value
58.66%e0
Qualifier
in 2016e0
Setting
Gresik Regencye0

Verbatim

e0

“the dominant mangroves in Gresik Regency in 2016 to 2019 were mangroves with good density, which amounted to 58.66% in 2016; 53.21% in 2017; 45.22% in 2018, and 46.81% in 2019.”

✓ located verbatim in the source · abstract, characters 755–931 · show in text ↑
Observationobservedoriginal resultmeasured

Claim · model-written summary

Good canopy density was dominant in 2017 at 53.21%.

Taxon
mangrovese0
Outcome
mangroves with good densitye0
Value
53.21%e0
Qualifier
in 2017e0
Setting
Gresik Regencye0

Verbatim

e0

“the dominant mangroves in Gresik Regency in 2016 to 2019 were mangroves with good density, which amounted to 58.66% in 2016; 53.21% in 2017; 45.22% in 2018, and 46.81% in 2019.”

✓ located verbatim in the source · abstract, characters 755–931 · show in text ↑
Observationobservedoriginal resultmeasured

Claim · model-written summary

Good canopy density was dominant in 2018 at 45.22%.

Taxon
mangrovese0
Outcome
mangroves with good densitye0
Value
45.22%e0
Qualifier
in 2018e0
Setting
Gresik Regencye0

Verbatim

e0

“the dominant mangroves in Gresik Regency in 2016 to 2019 were mangroves with good density, which amounted to 58.66% in 2016; 53.21% in 2017; 45.22% in 2018, and 46.81% in 2019.”

✓ located verbatim in the source · abstract, characters 755–931 · show in text ↑
Observationobservedoriginal resultmeasured

Claim · model-written summary

Good canopy density was dominant in 2019 at 46.81%.

Taxon
mangrovese0
Outcome
mangroves with good densitye0
Value
46.81%e0
Qualifier
in 2019e0
Setting
Gresik Regencye0

Verbatim

e0

“the dominant mangroves in Gresik Regency in 2016 to 2019 were mangroves with good density, which amounted to 58.66% in 2016; 53.21% in 2017; 45.22% in 2018, and 46.81% in 2019.”

✓ located verbatim in the source · abstract, characters 755–931 · show in text ↑
Observationobservedoriginal resultpositivemeasured

Claim · model-written summary

Mangrove area increased by 22.09% in 2017.

Taxon
mangrovee0
Outcome
mangrove areae0
Direction
increasede0
Value
22.09%e0
Qualifier
in 2017e0
Setting
Gresik Regencye0

Verbatim

e0

“the mangrove area in Gresik Regency from 2016 to 2019 increased by 22.09% in 2017, then decreased by 1.74% in 2018 and continued to decrease by 8.28% in 2019.”

✓ located verbatim in the source · abstract, characters 938–1096 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Mangrove area decreased by 1.74% in 2018.

Taxon
mangrovee0
Outcome
mangrove areae0
Direction
decreasede0
Value
1.74%e0
Qualifier
in 2018e0
Setting
Gresik Regencye0

Verbatim

e0

“the mangrove area in Gresik Regency from 2016 to 2019 increased by 22.09% in 2017, then decreased by 1.74% in 2018 and continued to decrease by 8.28% in 2019.”

✓ located verbatim in the source · abstract, characters 938–1096 · show in text ↑
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Mangrove area decreased by 8.28% in 2019.

Taxon
mangrovee0
Outcome
mangrove areae0
Direction
decreasee0
Value
8.28%e0
Qualifier
in 2019e0
Setting
Gresik Regencye0

Verbatim

e0

“the mangrove area in Gresik Regency from 2016 to 2019 increased by 22.09% in 2017, then decreased by 1.74% in 2018 and continued to decrease by 8.28% in 2019.”

✓ located verbatim in the source · abstract, characters 938–1096 · show in text ↑
Associationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Mangrove canopy density correlated negatively with water pH, with coefficient -0.733.

Taxon
mangrovese0
Compound
water pHe0
Outcome
density of mangroves canopye0
Value
-0.733e1

Not reportedDirection

Verbatim

e0

“the density of mangroves canopy and the water pH has a strong and significant correlation.”

✓ located verbatim in the source · abstract, characters 1237–1327 · show in text ↑
e1

“with a correlation coefficient of -0.733”

✓ located verbatim in the source · abstract, characters 1179–1219 · show in text ↑