Making Of Classification Land Cover Through Result Of Visual Data Satellite Image Analysis Landsat 8 OLI : Case Study in Tapaktuan District, South Aceh District

2021 ◽  
Vol 6 (1) ◽  
pp. 59-65
Author(s):  
Safridatul Audah ◽  
Muharratul Mina Rizky ◽  
Lindawati
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Technology ◽  
Open Land ◽  
Cover Class ◽  
Satellite Image Analysis

Tapaktuan is the capital and administrative center of South Aceh Regency, which is a sub-district level city area known as Naga City. Tapaktuan is designated as a sub-district to be used for the expansion of the capital's land. Consideration of land suitability is needed so that the development of settlements in Tapaktuan District is directed. The purpose of this study is to determine the level of land use change from 2014 to 2018 by using remote sensing technology in the form of Landsat-8 OLI satellite data through image classification methods by determining the training area of the image which then automatically categorizes all pixels in the image into land cover class. The results obtained are the results of the two image classification tests stating the accuracy of the interpretation of more than 80% and the results of the classification of land cover divided into seven forms of land use, namely plantations, forests, settlements, open land, and clouds. From these classes, the area of land cover change in Tapaktuan is increasing in size from year to year.

scholarly journals PERUBAHAN TUTUPAN LAHAN HUTAN LINDUNG GUNUNG GUNTUR TAHUN 2014 SAMPAI DENGAN TAHUN 2017

2020 ◽  
Vol 21 (1) ◽  
pp. 30
Author(s):  
Prasetyo Widodo ◽  
Abdul Japar Sidik
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Image ◽  
Image Interpretation ◽  
Landsat 8 ◽  
Land Protection ◽  
Community Activities ◽  
Protected Forests ◽  
Open Land

High pressure by community activities on the existence of forests, especially protected forests that affect the quality of the environment that can cause a disaster, such as the occurrence of flash floods that occurred in 2016 in Garut regency, cannot be separated from damage to the upstream cover of cimanuk-citanduy. This prompted investigators to analyze the three year change of land protection prevailing in Mt. Guntur RPH Simpang BKPH Bayongbong. The objective of research is to calculate how large changes land cover area in Mt. Guntur Protected Area (MGPA), RPH Simpang BKPH Bayongbong KPH Garut in three years. The data collected on July to August 2017 by geographic information system (GIS) and satellite image. The results of land cover interpretation by landsat 8 OLI image 2014 and 2017 describe the condition of land use and land cover change in MGPA. Land cover of MGPA dominated by shrub (B) is 287.58 Ha (57.52%) at 2014 and 202.89 Ha (40.58%) at 2017, so deforestation as three years is 31.24 Ha or 32.13%. The results of ground check there is a land use change to open land and farming dryland. According to data of image interpretation at 2017, the open land is 20.03 Ha but after ground checking is 20.51 Ha. The reduction of it based on data of image interpretation at 2017 is 200.33 Ha to 201.85 Ha after ground checking.

scholarly journals Land cover classification using Landsat 8 OLI in West Langsa Sub district, Langsa City

2022 ◽  
Vol 951 (1) ◽  
pp. 012080
Author(s):  
A A Nasution ◽  
A M Muslih ◽  
U H Ar-Rasyid ◽  
A Anhar
Keyword(s):  
Land Cover ◽  
Image Classification ◽  
Spatial Information ◽  
Rice Fields ◽  
Landsat 8 ◽  
Mangrove Forests ◽  
Land Cover Class ◽  
Landsat 8 Oli ◽  
Remote Sensing Techniques ◽  
Cover Class

Abstract Land cover information is needed by various parties as a consideration in controlling land cover changes. The latest land cover information can be obtained using remote sensing techniques in the form of image classification maps. This technique is very effective in monitoring land cover because of its ability to quickly, precisely, and easily provide spatial information on the earth’s surface. The purpose of this study was to classify land cover in West Langsa Sub district, Langsa City using Landsat 8 OLI (Operational Land Imager) imagery. The classification method used in this study is the maximum likelihood classification (MLC) method. There are several considerations of various factors in the MLC method, including the probability of a pixel to be classified into a certain type or class. The results of Landsat 8 OLI image classification in West Langsa Sub district resulted in 6 land cover classes, namely mangrove forests, settlements, rice fields, shrubs, ponds and bodies of water. The largest land cover class is ponds with an area of 1981.54 ha (38.71%) and the smallest land cover is rice fields with an area of 115.58 ha (2.26%) of the total land cover class. Classification accuracy is indicated by the overall accuracy and kappa accuracy of 91.15% and 82.75%, respectively. These results meet the requirements set by the USGS (Overall Accuracy > 85%) and indicate that the Landsat 8 OLI image classification map can be used for various purposes.

scholarly journals ALTERAÇÃO NA COBERTURA FLORESTAL DA REGIÃO NOROESTE DA AMAZÔNIA MATOGROSSENSE

Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 520
Author(s):  
Luani Rosa de Oliveira Piva ◽  
Rorai Pereira Martins Neto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Forest Conversion ◽  
Landsat 8 ◽  
Amazon Forest ◽  
Landsat 8 Oli ◽  
Mato Grosso ◽  
The Past ◽  
Landsat 5 Tm

Nos últimos anos, a intensificação das atividades antrópicas modificadoras da cobertura vegetal do solo em território brasileiro vem ocorrendo em larga escala. Para fins de monitoramento das alterações da cobertura florestal, as técnicas de Sensoriamento Remoto da vegetação são ferramentas imprescindíveis, principalmente em áreas extensas e de difícil acesso, como é o caso da Amazônia brasileira. Neste sentido, objetivou-se com este trabalho identificar as mudanças no uso e cobertura do solo no período de 20 anos nos municípios de Aripuanã e Rondolândia, Noroeste do Mato Grosso, visando quantificar as áreas efetivas que sofreram alterações. Para tal, foram utilizadas técnicas de classificação digital de imagens Landsat 5 TM e Landsat 8 OLI em três diferentes datas (1995, 2005 e 2015) e, posteriormente, realizada a detecção de mudanças para o uso e cobertura do solo. A classificação digital apresentou resultados excelentes, com índice Kappa acima de 0,80 para os mapas gerados, indicando ser uma ferramenta potencial para o uso e cobertura do solo. Os resultados denotaram uma conversão de áreas florestais principalmente para atividades antrópicas agrícolas, na ordem de 472 km², o que representa uma perda de 1,3% de superfície de floresta amazônica na região de estudo.Palavras-chave: conversão de áreas florestais; uso e cobertura do solo; classificação digital; análise multitemporal. CHANGE IN FOREST COVER OF THE NORTHWEST REGION OF AMAZON IN MATO GROSSO STATE ABSTRACT: In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil’s land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuanã and Rondolândia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km², representing a loss of 1.3% of Amazon forest surface in the study region.Keywords: forest conversion; land use and land cover; digital classification; multitemporal analysis.

scholarly journals Urban Bare Land Classification Using NDBaI Index Based on Combination of Sentinel 2 MSI and Landsat 8 Multiresolution Images

2020 ◽  
Vol 36 (2) ◽  
Author(s):  
Trinh Le Hung
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Image ◽  
Urban Land ◽  
Landsat 8 ◽  
Land Classification ◽  
Infrared Band ◽  
Urban Land Cover ◽  
Bare Land ◽  
Sentinel 2

The classification of urban land cover/land use is a difficult task due to the complexity in the structure of the urban surface. This paper presents the method of combining of Sentinel 2 MSI and Landsat 8 multi-resolution satellite image data for urban bare land classification based on NDBaI index. Two images of Sentinel 2 and Landsat 8 acquired closely together, were used to calculate the NDBaI index, in which sortware infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) of Landsat 8 image were used to improve the spatial resolution of NDBaI index. The results obtained from two experimental areas showed that, the total accuracy of classifying bare land from the NDBaI index which calculated by the proposed method increased by about 6% compared to the method using the NDBaI index, which is calculated using only Landsat 8 data. The results obtained in this study contribute to improving the efficiency of using free remote sensing data in urban land cover/land use classification.

scholarly journals NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

scholarly journals Landsat 8 OLI Satellite Image Classification using Convolutional Neural Network

2020 ◽  
Vol 167 ◽  
pp. 987-993 ◽  
Author(s):  
Amit Kumar Rai ◽  
Nirupama Mandal ◽  
Akansha Singh ◽  
Krishna Kant Singh
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Satellite Image Classification

scholarly journals Transformações do uso e cobertura da terra na bacia hidrográfica do rio Murucupi, Barcarena, Pará

2020 ◽  
Vol 13 (5) ◽  
pp. 2340
Author(s):  
Layse Gomes Furtado ◽  
Gundisalvo Piratoba Morales ◽  
Davi Farias Da Silva ◽  
Altem Nascimento Pontes
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Impacts ◽  
Population Expansion ◽  
Forest Vegetation ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Urbanized Area ◽  
Urbanized Areas ◽  
Landsat 5 Tm

A importância de estudos que relacionem as alterações de cobertura, uso e manejo da terra são fundamentais para compreender a dinâmica da paisagem em determinadas áreas. O presente trabalho teve por objetivo analisar as transformações do uso e cobertura da terra na bacia hidrográfica do rio Murucupi, no município de Barcarena/PA, ao longo dos últimos 29 anos. Por meio de geotecnologias foi realizada a identificação, classificação e quantificação dos tipos de uso e cobertura da terra, utilizando imagens de satélite Landsat 5 TM e Landsat 8 OLI, correspondentes aos anos de 1990, 2000, 2010 e 2019. Após o processamento das imagens, os elementos encontrados no interior da bacia foram classificados e analisados para a compreensão do seu processo de evolução ou regressão. Os resultados apontaram que houve um crescimento progressivo de áreas urbanizadas desde 1990, em detrimento da vegetação florestal. Porém, somente em 2000, foi observada a crescente evolução das áreas sem vegetação, onde 21,19% correspondia a área urbanizada e 4,08% a área de solo exposto. Em 2010, foi registrado uma perda superior a 50% de vegetação florestal, dando espaço, principalmente, para área urbanizada (35,01%). Diferentemente do ano 2000, em 2019 mais de 50% (1,505 ha) da bacia encontrava-se antropizada. Conclui-se que a maioria de áreas de floresta foram convertidas em áreas urbanizadas, onde a expansão delas é proporcional a expansão industrial e populacional do munícipio. Tais mudanças propiciaram diversos impactos ambientais, dentre eles o intenso desflorestamento e a poluição do solo e do rio Murucupi por dejetos domésticos e industriais. Land use and land cover transformations in the Murucupi river basin, Barcarena, Pará A B S T R A C TThe importance of studies that relate to changes in land cover, use and management are fundamental to understand the dynamics of the landscape in certain areas. The present work aims to analyze the transformations of land use and coverage in the hydrographic basin of the Murucupi River, in the municipality of Barcarena / PA, over the past 29 years. Geotechnologies were used to identify, classify and quantify the types of land use and land cover, using satellite images Landsat 5 TM and Landsat 8 OLI, corresponding to the years 1990, 2000, 2010 and 2019. After processing the images, the elements found inside the basin were classified and analyzed to understand their evolution or regression process. The results showed that there has been a progressive growth in urbanized areas since 1990, to the detriment of forest vegetation. However, only in 2000, there was an increasing evolution of areas without vegetation, where 21.19% corresponded to the urbanized area and 4.08% to the exposed soil area. In 2010, a loss of more than 50% of forest vegetation was recorded, giving space, mainly, to the urbanized area (35.01%). Unlike the year 2000, in 2019 more than 50% (1,505ha) of the basin was anthropized. It is concluded that the majority of forest areas have been converted into urbanized areas, where their expansion is proportional to the industrial and population expansion of the municipality. Such changes have led to several environmental impacts, including soil and Murucupi river pollution by domestic and industrial waste.Keywords: Landscape dynamics, Geotechnologies, Environmental impacts.

Sign in / Sign up

Export Citation Format

Share Document