Mapping of Mangrove Change with Remote Sensing in Samut Songkhram Province, Thailand

Phonphan, Walaiporn; Thanakunwutthirot, Manatsanan

doi:10.1007/978-3-030-44267-5_29

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Besides, the procedure of land's surface can be detected or computed with satellite imagery through a multi-temporal perspective [10]. As a result, remote sensing has emerged as the most effective and reliable method for characterizing and analyzing land-use and land-cover conditions and changes, and its usage has increased significantly over time [11]. The Sentinel-2 satellites equipped with multispectral imaging instruments (MSI) offer high-resolution satellite data that is useful for monitoring LULC [12].…”

Section: Introductionmentioning

confidence: 99%

Spatial Dynamics Evolution of Land use for the Study of the Local Traditional Living Changes

2023

IJG

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Land use data can be used to understand patterns of economic behavior, such as the relationship between land use and property values or the impact of land use on environmental factors like air and water quality. The combination of land use data with other data sources and analysis methods can yield significant insights into economic growth and behavior. In this study, the land use and land cover (LULC) were classified using multi-temporal Sentinel-2 imagery (2019 and 2021) and random forest through the Google Earth Engine platform (GGE) with an overall accuracy of more than 89.79%. According to the results of the change detection analysis, there was a 16.96% increase in miscellaneous surface areas and a 15.50% increase in artificial surface areas. These disclose confirm that the sea salt farm, which are the traditional economic function, are losing 37.40%. Furthermore, the CA-Markov model was utilized to predict alterations in land use patterns in the year 2023 through the extrapolation of existing trends. The predicted LULC map of 2023 publicizes the trend of the sea salt farm decreasing, contrasty the artificial surface areas are increasing. In summary, this research reveals the evidence that LULC is strongly related to traditional living changes, and spatial analysis techniques are reasonable and committing tools for study.

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Section: Introductionmentioning

confidence: 99%

Spatial Dynamics Evolution of Land use for the Study of the Local Traditional Living Changes

2023

IJG

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Remote sensing monitoring of mangrove growth rate at selected planted sites in Mauritius

2023

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Mangroves are highly productive and rich ecosystems that thrive at the interface of land and sea. They provide a wide range of essential goods and services, contribute highly to coastal protection and the livelihood of coastal communities, and are also carbon-rich biomes contributing to carbon sequestration. Mangroves are primarily threatened by anthropogenic activities; a loss in biodiversity has been observed in the past years in many countries including Mauritius. Given their value to the ecosystem, it is important to have effective continuous monitoring of mangrove dynamics. We studied the rate of increase of canopy coverage of planted Rhizophora mucronata forests in two selected sites (Le Morne and Grande Rivière Noire) on a southern African island – Mauritius – using Google Earth Pro historical Landsat 7 and Landsat 8 images. Data were processed using ImageJ software. To our knowledge, this technique has not yet been applied for monitoring mangrove growth. The mangrove sites were classified into four zones based on water level and tidal variations. On average, the rate of increase of canopy coverage expressed by a coefficient ‘b’ at Le Morne (b = 1.901) was higher than that at Grande Rivière Noire (b = 1.823). The coefficient ‘b’ positively correlated with the zonations (r ~ 0.8). Higher ‘b’ values (2.319–2.886) were observed in Zone 1, where the substrate is always covered with water at low tide. The use of remote sensing data along with image processing analysis proved to be an effective tool to obtain relevant information, not only for mapping mangroves but also for monitoring the canopy growth rates of planted mangroves.

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Discrimination of Mangrove Stages Using Multitemporal Sentinel-1 C-Band Backscatter and Sentinel-2 Data—A Case Study in Samut Songkhram Province, Thailand

Upakankaew

Ninsawat

Virdis

et al. 2022

Forests

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Discrimination of mangrove stage changes is useful for the conservation of this valuable natural resource. However, present-day optical satellite imagery is not fully reliable due to its high sensitivity to weather conditions and tidal variables. Here, we used the Vertical Transmit—Vertical Receive Polarization (VV) and Vertical Transmit—Horizontal Receive Polarization (VH) backscatter from the same and multiple-incidence angles from Sentinel-1 SAR C-band along with Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Moisture Index (NDMI), Normalized Difference Red Edge (NDVIRE) and Chlorophyll Index Green (CIGreen) from the optical satellite imageries from Sentinel-2 to discriminate between the changes in disturbance, recovery, and healthy mangrove stages in Samut Songkhram province, Thailand. We found the mean NDVI values to be 0.08 (±0.11), 0.19 (±0.09), and −0.53 (±0.16) for the three stages, respectively. We further found their correlation with VH backscatter from the multiple-incidence angles at about −17.98 (±2.34), −16.43 (±1.59), and −13.40 (±1.07), respectively. The VH backscatter from multiple-incidence angles was correlated with NDVI using Pearson’s correlation (𝑟2 = 0.62). However, Pearson’s correlation of a single plot (ID2) of mangrove stage change from disturbance to recovery, and then on to the healthy mangrove stage, displayed a 𝑟2 of 0.93 (p value is less than 0.0001, n = 34). This indicated that the multitemporal Sentinel-1 C-band backscatter and Sentinel-2 data could be used to discriminate mangrove stages, and that a reduced correlation to significant observations was the result of variations in both optical and SAR backscatter data.

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Mapping of Mangrove Change with Remote Sensing in Samut Songkhram Province, Thailand

Cited by 3 publications

References 2 publications

Spatial Dynamics Evolution of Land use for the Study of the Local Traditional Living Changes

Spatial Dynamics Evolution of Land use for the Study of the Local Traditional Living Changes

Remote sensing monitoring of mangrove growth rate at selected planted sites in Mauritius

Discrimination of Mangrove Stages Using Multitemporal Sentinel-1 C-Band Backscatter and Sentinel-2 Data—A Case Study in Samut Songkhram Province, Thailand

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