Monitoring of land use and land cover changes by using remote sensing and GIS techniques at human-induced mangrove forests areas in Bangladesh

Faruque, Md Jamal; Hasan, Md Yeasir; Islam, Kamal; Young, B.; Ahmed, Mohammad Tofayal; Monir, Minhaj Uddin; Shovon, Shaik Muntasir; Kakon, Jannatul Ferdaus; Kundu, Prionti

doi:10.1016/j.rsase.2022.100699

Cited by 40 publications

(34 citation statements)

References 37 publications

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“…The methodology adopted to study land cover at the different dates and to identify vegetation changes is summarized in Figure 3. The Landsat images used are mainly chosen according to their availability for the study area [Faruque et al 2022;]. The downloaded images followed radiometric corrections (Radiometric calibration extension) and atmospheric (semiautomatic extension by the Dark object subtraction model DOS) on ENVI 5.3 software.…”

Section: Methodsmentioning

confidence: 99%

Monitoring Land Use and Land Cover Change Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Haj¹,

Ouadif²,

Akhssas³

2023

Ecol. Eng. Environ. Technol.

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The study of land use and land cover change (LULC) is essential for the development of strategies, monitoring and control of the ecosystem. The present study aims to describe the dynamics of land cover and land use, and specially the impact of certain climatic parameters on the distribution of vegetation and land cover. For this study, multi-temporal remote sensing data are used to monitor land cover changes in Morocco, using a set of Landsat images, including Landsat 7 (ETM+), Landsat 5 (TM), and Landsat 8 (OLI), captured during the period 2000-2020, those changes were determined by adopting the maximum likelihood (ML) classification method. The classification results show good accuracy values in the range of 90% (2000), 80% (2007), 82% (2010), 93% (2020). The LU/LC change detection showed a decrease of agricultural and forest areas in the order of 5% between the year 2000 and 2020, and an increase of bare soil of 5% to 6%, and a notable change in urban area from 97.31 ha (0.03%) in 2000 to 2988.2637 ha (0.82%) in 2020. The overall results obtained from LULC show that the vegetation cover of the study area has undergone major changes during the study period. In order to monitor the vegetation status, an analysis of the precipitation-vegetation interaction is essential. The normalized difference vegetation index (NDVI) was determined from 2000 to 2020, to identify vegetation categories and quantify the vegetation density in the Lakhdar sub-basin. The obtained NDVI was analyzed using climatic index SPI (Normalized Precipitation Index) based on rainfall data from five stations. The correlation study between NDVI and SPI indices shows a strong linear relation between these two indicators especially while using an annual index SPI12 however, the use of NDVI index based on remote sensing provides a significant result while assessing vegetation. The results of our study can be used for vegetation monitoring and sustainable management of the area, since it is one of the largest basins in the country.

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Section: Methodsmentioning

confidence: 99%

Monitoring Land Use and Land Cover Change Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Haj¹,

Ouadif²,

Akhssas³

2023

Ecol. Eng. Environ. Technol.

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“…NDVI is detected by calculation from multi-band remote sensing data (Szabó et al, 2016;Ekumah et al, 2020). This analysis is performed using combinations of red and near infrared bands of multispectral satellite images (Faruque et al, 2022). Calculation formula of NDVI (Rouse et al, 1973;Tucker and Seller, 1986) (eq.…”

Section: Ndvimentioning

confidence: 99%

“…The Normalized Difference Water Index (NDWI), introduced by McFeeters (1996), is a widely used analysis that uses the green and near infrared spectrum of satellite images to explain the presence of water bodies on the land surface. It is designed to maximize reflection from water while minimizing low reflection in the near infrared band (Eid et al, 2020b;Mishra et al, 2021;Faruque et al, 2022).…”

Section: Ndwimentioning

confidence: 99%

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Monitoring the Changes of Lake Uluabat Ramsar Site and Its Surroundings in the 1985-2021 Period Using Rs and Gis Methods

2022

Global NEST: The International Journal

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<p>Ramsar sites are important ecosystems that are protected by international status, have great value in terms of biodiversity, and constitute a resource in terms of economic, cultural, scientific and recreational aspects. In this study, the change of Lake Uluabat Ramsar Site and its surroundings, between the years 1985-2021 has been observed. For this, Remote Sensing (RS) and Geographic Information Systems (GIS) methods were used. Vegetation change in the lake and its surroundings in 1985, 2000, 2015 and 2021 with Normalized Difference Vegetation Index (NDVI), and changes in water surfaces with the water indices Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (mNDWI) were analyzed by using Landsat multi-band satellite images (Landsat 5 TM, Landsat 7 ETM and Landsat 8 OLI/TIRS) as RS data. The resulting changes were monitored and the success of the indices in determining these areas and the relations of the indices with each other were questioned by Accuracy index, Kappa coefficent, and Correlation analyses. The results show 36-year long-term changes and reveal a 13.06% shrinkage of Uluabat Lake wetland and surrounding water areas with the highest kappa coefficients for mNDWI as 0.83, 0.90, 0.93, 0.97, respectively, over the years studied.</p>

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“…In this regard, remotely sensed data are accessed to track the spatiotemporal dynamics of both accessible and inaccessible data on pixel basis. In geospatial studies, RS and GIS tools are used for thorough analysis, monitoring and managing of different types of land use and land cover (LULC) and their changing characters (Gutman et al, 2008;Rawat & Kumar, 2015;Mantey & Aduah, 2021;Faruque et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Land Cover Dynamics and Landscape Fragmentation in Ijebu Ode, Nigeria

Olayiwola

Salau

2022

jgier

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Landscape fragmentation has been found to be a major consequence of urbanization and of land use/cover (LULC) changes. Thus, this study analyzed the spatiotemporal land use/land cover changes of Ijebu Ode, Nigeria between 1986 and 2021. This is with a view to assessing the pattern of landscape fragmentation in the study area. The study used data obtained through Global Positioning System (GPS) receiver and satellite imageries (Landsat 5 MSS/TM, 1986; Landsat 7 ETM+, 2000 and 2014; and Landsat 8 OLI/TIR, 2021). Data were analyzed using spatial landscape metrics. Results indicated that Ijebu Ode has witnessed dramatic increase of built-up areas between 1986 and 2000 by 11.03%, 2000 to 2014 (65.24%), and 2014 to 2021 by 131.25%. Expansion of the built-up area was aided by reductions in bare land (1986 to 2000, 15.78%; 2014 to 2021, 98.27%), and the cultivated area by 47.74% between 1986 and 2014. Landscape metrics were estimated over the four epochs of study. Results revealed that most of the metrics suggest similar trends over the entire periods of study. However, Largest Patch Index (LPI), Landscape Shape Index (LSI) and Normalized Landscape Shape Index (NLSI) were useful in capturing the spatio-temporal variations in landscape transformation. Also, Class Area (CA) was useful to show the degree of land cover changes. The study concluded that location of spatial structures influenced the landscape patterns influence and urbanization processes in the study area. Hence, the study recommended for regular monitoring of the expansion of the built-up area to check the imminent urban sprawl in the study area.

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Monitoring of land use and land cover changes by using remote sensing and GIS techniques at human-induced mangrove forests areas in Bangladesh

Cited by 40 publications

References 37 publications

Monitoring Land Use and Land Cover Change Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Monitoring Land Use and Land Cover Change Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Monitoring the Changes of Lake Uluabat Ramsar Site and Its Surroundings in the 1985-2021 Period Using Rs and Gis Methods

Evaluation of Land Cover Dynamics and Landscape Fragmentation in Ijebu Ode, Nigeria

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