Pemanfaatan Citra Landsat 8 Operational Land Imager (Oli) Untuk Klasifikasi Tutupan Lahan  Di Taman Nasional Gunung Merbabu

Siregar, Diyanti Isnani; Asbi, Adnin Musadri

doi:10.31849/forestra.v15i2.4731

Cited by 4 publications

(5 citation statements)

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“…The overall accuracy of 82.52% indicates that the results of land cover classification in this study are considerably good. The total accuracy value obtained in this study is not significantly different from the classification results obtained in several research studies, which are in the range of 80% or higher, despite the use of images with lower resolutions such as Landsat 8 with spatial resolution of 30 meters (Derajat et al, 2020;Rini, 2018;Siregar & Asbi, 2020;Wulansari, 2017). Moreover, Kappa coefficient value produced by the confusion matrix is 79.66 and categorized as substantial (61.00 < Kappa < 80.00).…”

Section: Resultscontrasting

confidence: 66%

The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java

Hidayah

Armono²,

Wardhani³

et al. 2022

Geos. Ind.

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Land cover dynamics in a small island can be determined using Geographic Information System (GIS) approach based on multitemporal image analysis. This study aimed to classify major land cover types and to map land cover changes of Bawean Island. Two sets of 10 meter resolution satellite data ALOS AVNIR (2010) and Sentinel-2A (2020) were used in this study. Satellite image analysis was carried out through several stages namely image pre-processing including radiometric and geometric correction, supervised image classification and accuracy test. Image classification results from 2010 to 2020 showed a significant change in land cover on Bawean Island. The forest vegetation land cover declined significantly from 13,470.5 Ha in 2010 to 8,543.4 Ha in 2020. Most of the area have been converted into paddy fields and built-up areas. The accuracy test and validation were determined by comparing the 2020 Sentinel image classification results with field observation conducted in 2021. The analysis showed good results with 82.52% overall accuracy and 79.66 Kappa coefficient. Further investigation found that changes in land cover on Bawean Island occured due to the agriculture and infrastucture development. Keywords : Geographic Information System (GIS); land cover; satellite images; small island Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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Section: Resultscontrasting

confidence: 66%

The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java

Hidayah

Armono²,

Wardhani³

et al. 2022

Geos. Ind.

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“…This research took place in Medan, Pekanbaru and Padang as National Activity Centres (PKN) on Sumatera. This research uses a quantitative method, and the data used in the study is obtained from remote sensing and document studies [16]. The data analysis methods used in this research include satellite image processing, land cover change analysis, and suitability analysis of land projection to the regional spatial planning.…”

Section: Methodsmentioning

confidence: 99%

Assessing Land Cover Change Projections and Its Suitability with Urban Spatial Pattern Plan Using Google Earth Engine and Cellular Automata in the National Activity Centres on Sumatera Island

Sukmawati,

Simorangkir,

Juniati

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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The national activity centres (Pusat Kegiatan Nasional – PKN) areas, especially in Sumatera Island, are closely related to the land cover change phenomenon. This study aimed to identify the land cover change projection and assess its suitability with the spatial pattern plan in the “Rencana Tata Ruang Wilayah” (RTRW) which focuses on the study area including Medan, Pekanbaru, and Padang. The integration of remote sensing data, geographic information systems (GIS), and spatial analysis techniques are used to identify and assess the patterns of land cover change over the specific period. The analysis of land cover change patterns is performed using Landsat-7 and Sentinel-2A imagery data which processed in Google Earth Engine (GEE). Furthermore, Cellular Automata and Artificial Neural Network (CA-ANN) modelling is used to identify land cover prediction using transition rules like main road as driving factor then followed by overlay analysis to assess its suitability with the spatial pattern plan. The result shows the different level of each land cover classification in sub-district level. The proportion of the land cover projection suitability in Medan at 2042 was 84,92%; in Pekanbaru at 2040 was only 58,51%; while in Padang at 2030 was 77%. This findings can be able to serve as a suggestion for stakeholders in formulating effective strategies for spatial planning evaluation and managing land cover uses, especially in several national activity centers in Sumatera.

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“…Land use changes continue to occur along with the development process [22]. The land cover of a particular region can provide very important information for making policies to control environmental degradation at both the national and international levels [23]. In the results of this research, the next stage of Structural Equation Modeling (SEM) analysis is carried out, divided into 3 stages, namely, overall model fit analysis, measurement model fit analysis, and structural model fit [24,25].…”

Section: Land Covermentioning

confidence: 99%

Environmental and Demographic Effects on Vector Borne Disease Incidence: Welfare Role on DHF Reduction

Bakri,

Apriliani,

Kurniawaty

et al. 2024

J. Hum. Earth Future

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Many regions in developing countries are transitioning to an industrial economic model, accompanied by rapid population growth, which from one side is a welfare driver (WLF) and on the other side is a demographic pressure, especially a health problem such as vector-borne disease. The problem climaxes when this transition is always accompanied by environmental degradation (ENV), which begins with deforestation. Objective: [1] Determine the direct influence of: [1a] Demographic on DHF incidence, [1b] Demographic on Welfare improvement, [1c] Welfare on DHF incidence, [1d] Environment improvement on DHF incidence, [1e] Environment improvement on performance Welfare; and [2] The indirect influence of Welfare in mediating [2a] Demographic pressure and [2b] Environment improvement on DHF incidence. Research Method: Lampung Province was used as the research locus. Forest Resources Inventory Laboratory of Lampung University as a place for analysis. Postulate SEM (Structural Equation Model) was employed at a 95% confidence level. The endogenous variable was vector-borne disease (reflected by DHF incidence). The two exogenous variables were DMG (reflected by population density and the proportion of age of productive, industrial, and service workers) and ENV (reflected by maximum & minimum air temperature, forested areas, and other land uses). The mediating variable is WLF (reflected by poverty and HDI). Findings: [1] Directly, with a significant effect: [1a] DMG pressure increases DHF (P=0.000) and [1.b] WLF (P=0.000); [1.c] Environment improvement increases welfare (P=0.000) while [1d] reduces DHF; and [1.e] WLF improvement can reduce DHF (P=0.010) and [2] The role of WLF improvement [2a] can significantly reduce the incidence of DHF due to demographic pressure (P=0.007) while also [2b] amplifying environmental improvement in reducing DHF significantly (P=0.023). Novelty:To reduce DHF incidence, Welfare improvement can reverse the negative effects of Demographic pressure as well as act as an amplifier for the role of environmental improvement. Doi: 10.28991/HEF-2024-05-01-03 Full Text: PDF

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Pemanfaatan Citra Landsat 8 Operational Land Imager (Oli) Untuk Klasifikasi Tutupan Lahan Di Taman Nasional Gunung Merbabu

Cited by 4 publications

References 0 publications

The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java

The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java

Assessing Land Cover Change Projections and Its Suitability with Urban Spatial Pattern Plan Using Google Earth Engine and Cellular Automata in the National Activity Centres on Sumatera Island

Environmental and Demographic Effects on Vector Borne Disease Incidence: Welfare Role on DHF Reduction

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