scholarly journals Pengolahan Citra Satelit dalam Deteksi Alih Fungsi Hutan Pada Daerah Aliran Sungai Arut Kabupaten Kotawaringin Barat Provinsi Kalimantan Tengah Berbasis Sistem Informasi Geografis

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Gregorius Anung Hanindito
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification

Kabupaten Kotawaringin Barat merupakan salah satu kabupaten di wilayah Kalimantan Tengah yang secara geografis dialiri oleh 3 (tiga) sungai besar yakni: Sungai Kumai, Sungai Lamandau dan Sungai Arut. Seiring berjalannya waktu dan bertambahnya kepadatan penduduk, keberadaan sungai memberikan permasalahan baru akibat pembangunan dan ekspansi pertanian dan perkebunan. Mengacu pada permasalahan tersebut, maka penelitian ini dilakukan untuk mengamati tingkat alih fungsi lahan (land cover change) yang terjadi di daerah aliran sungai Arut, Kecamatan Arut Selatan, Kabupaten Kotawaringin Barat. Penelitian ini dilakukan dengan metode penginderaan jauh dan sistem informasi geografis. Data yang digunakan dalam metode ini ialah data citra satelit Landsat pada tahun 1996, 2010, dan 2016. Ketiga data tersebut diklasifikasikan sesuai dengan kenampakannya dengan metode supervised classification dan dianalisis dengan teknik intersection. Pembatasan alih fungsi dalam penelitian ini hanya dilakukan pada kenampakan hutan dan perkebunan saja. Dalam penelitian ini dihasilkan peta perubahan alih fungsi hutan menjadi perkebunan dalam periode waktu 1996-2016. Penelitian ini juga menghasilkan pola perubahan luas hutan dan perkebunan selama periode waktu tersebut. Kata Kunci: intersection, Landsat,  penginderaan jauh, sistem informasi geografis, supervised classification

scholarly journals Land use and land cover change-induced landscape dynamics: a geospatial study of Durgapur Sub-Division, West Bengal (India).

2021 ◽  
Author(s):  
Sribas Patra ◽  
Kapil Kumar Gavsker
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification ◽  
West Bengal ◽  
Google Earth ◽  
Landscape Dynamics ◽  
Landsat 8 ◽  
Process Of Change ◽  
Detection Analysis

Abstract This article examines the factors and process of change in the land use and land cover change-induced landscape dynamics in the Durgapur Sub-Division region of West Bengal in 1989, 2003, and 2018 by employing the satellite imageries of Landsat 5 (1989 and 2003) and Landsat 8 (2018). The images of the study area were categorized into seven specific land use classes with the help of Google Earth Pro. Based on the supervised classification methodology, the change detection analysis identified a significant increase in built-up land from 11% to 23% between 1989 and 2003 and from 23% to 29% in 2003 and 2018. The areas under fallow land and vegetation cover have mainly decreased, while the areas of industrial activities and urbanization expanded during the study period.

scholarly journals Estimating Per Capita Land Use/Land Cover Change (LULCC) in Makurdi, Northcentral Nigeria

2021 ◽  
Vol 4 (1) ◽  
pp. p97
Author(s):  
Bernard Tarza Tyubee
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification ◽  
Population Data ◽  
Land Use Land Cover ◽  
Cultivated Land ◽  
Landsat Images ◽  
Per Capita

The study estimated annual and temporal variation in per capita Land Use/Land Cover Change (LULCC) in Makurdi, Northcentral Nigeria. A total of four Landsat TM/ETM+ images were acquired in April of 1991, 1996, 2001 and 2006 for the study. A total of five LULC types namely water, forest, undergrowth/wetland, cultivated land and built-up land were derived from the Landsat images using supervised classification method. The per capita LULCC was derived by dividing the areas of LULC types by the actual population data. The result showed that built-up land recorded the highest long-term gain in area by 179km2 (130%), with an increment of 8.7% per anum, and undergrowth/wetland lost 119km2 (32%) in area with a decrease of 2.1% per annum from 1991 to 2006. The per capita LULCC of built-up land has increased from 575m2/person (1991) to 1059m2/person (2006), representing an increment of 481m2/person (83%). The undergrowth/wetland recorded the highest decrease in per capita LULCC from 1542m2/person (1991) to 836m2/person (2006), representing a decline by 706m2/person (46%). The study concludes that undergrowth/wetland is the most vulnerable LULC type due to urbanisation, and sustainable urban planning should be practised to conserve the natural cover materials in the study area.

scholarly journals Land Cover Change and Coastal Sustainability in the Coastal Area of Kendari Bay, Southeast Sulawesi, Indonesia

2021 ◽  
Vol 921 (1) ◽  
pp. 012008
Author(s):  
Ariyani ◽  
M Achmad ◽  
E Morgan
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Use Planning ◽  
Supervised Classification ◽  
Accuracy Assessment ◽  
Coastal Areas ◽  
Maximum Likelihood Algorithm ◽  
Rapid Changes ◽  
Land Cover Map ◽  
Method Accuracy

Abstract Coastal areas provide invaluable resources which have important environment, economic and social value. These resources encourages growing population and development which induced rapid changes in coastal areas. This study aims to analyse the changes in land cover of the coastal areas of Kendari Bay to provide recent perspectives of how land cover has changed using Landsat TM and Landsat OLI images for the period of 1998, 2008 and 2018. The classified land cover classes are categorized as waterbodies, built-up, bareland, forest, wetland, vegetation and mangrove. The land cover map of each period was acquired from supervised classification using maximum likelihood algorithm in ArcGIS, then the land cover change was analysed through post-classification change detection of GIS-based method. . Accuracy assessment of classified images shows the overall accuracy is estimated as 88.71%, 85.81% and 91.61%, and overall Kappa coeffient statistical values of 0.87, 0.83 and 0.90 for the year 1998, 2008 and 2018 respectively. This study found that there was significant land cover change in the coastal areas of Kendari Bay. It was dominated by the expansion of built-up areas and bareland by 55% and 469.77% respectively, which was gained from the conversion of vegetation and wetland. Meanwhile, considerable reduction were shown in mangrove, wetland, forest and vegetation which have declined by 48.65%, 43.39%, 38.72% and 27.20%. Analysing land cover change is an effective way to understand the dynamics of land cover in coastal areas, and can be used for future land use planning and policies.

Quantification of Land use/Land cover change in Qorveh-Dehgolan Basin, Kurdistan Province, Iran Using Remote Sensing and GIS

2018 ◽  
Vol 41 (2) ◽  
pp. 103-112
Author(s):  
Payam Sajadi ◽  
◽  
Saumitra Mukherjee ◽  
Kamran Chapi ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Maximum Likelihood ◽  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification ◽  
Bare Soil ◽  
Remote Sensing And Gis ◽  
Land Use Land Cover ◽  
Landsat 7

This research aimed to analyze the land use/ land cover (LULC) change in Qorveh-Dehgolan Basin (Kurdistan, Iran) from 2000 to 2017 (four sets of data) using Landsat (7 and 8) images. Supervised classification using maximum likelihood generated four series of LULC maps by ENVI 5.3 software. Overall, six major classes including bare soil, water body, vegetation cover, agriculture land, grassland, and settlements were identified and mapped.The LULC style has changed over 17 years. It was determined that the waterbody class has continuously reduced about 173.66 km2 from 2000 to 2017 by 63%. The agriculture class has considerably increased from 2000 to 2017 about 129.43 km2 and finally, the area of settlement class increased about 54.06. km2. The overall accuracy was 81.50%, 85.0%, 92.00%, 92.00% for the years of 2000, 2006, 2013 and 2017 respectively.

scholarly journals Dynamic of the Land Use and Land Cover Change in Banyuwangi Regency From 1995-2019

Jurnal Wasian ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 121-132
Author(s):  
Nurlita Wahyuni ◽  
◽  
Abdul Hasyim ◽  
Soemarno Soemarno
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Mangrove Forest ◽  
Supervised Classification ◽  
Secondary Forest ◽  
Primary Forest ◽  
Forest Plantation ◽  
Climate Control ◽  
Barren Land

The land use and land cover change phenomenon has become one concern over many regions worldwide, including Indonesia. Land use and land cover change due to human activities triggered alteration terrestrial ecosystems and its services including climate control functions. The study aimed to analyze land use and land cover change in Banyuwangi regency during 1995 – 2019. Four satellite images from acquisition year 1995, 2000, 2014 and 2019 were used to analyze the spatial and temporal changes along with field observations. The classification processes of land use and land cover included determination of training areas, supervised classification, and accuracy assessment. There are 12 land use and land cover based on supervised classification as follow primary forest, secondary forest, plantation forest, mangrove forest, plantation, settlement, cropland, paddy field, shrubs, water, fishpond and barren land. The result showed during observation period of 1995 until 2019 land use and land cover which tends to decrease are secondary forest, mangrove forest, and rice fields. On the other hand, the area of settlements, shrubs and fishponds were increased significantly.

scholarly journals Land Use - Land Cover Change Analysis of Karur Town - A GIS Approach

2021 ◽  
pp. 360-366
Author(s):  
S. Ravichandran ◽  
I. K. Manonmani
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Geographical Information ◽  
Land Use Land Cover ◽  
Change Analysis ◽  
Barren Land

Land use / Land cover change is one of the most sensitive factors that show the interactions between human activities and the ecological environment. This research study demonstrated the importance of geographical information system and remote sensing technologies in spatial temporal data analysis and also this paper shows a GIS and remote sensing approach for modeling of spatial - temporal pattern of land use and land cover change (LULC) in a fastest growing towns / industrial region of Karur town. QGIS 3.10 version and Arc GIS 10.2 software platforms were utilized in the study for Image processing, LULC mapping and change detection analysis. USGS Earth explorer Landsat series satellite imageries were acquired and LULC maps were prepared for the years 1991, 2000, 2010 and 2020. Supervised classification with maximum likelihood algorithm is adopted for LULC classification. The LULC classes are Built upland, Agricultural land, Barren land and Water body based on NRSA Level – I supervised classification. The Built-up area has drastically increased from 1991 to 2020. It has increased more than double. It was 17 percent in 1991 and increased to 40 percent in 2020. This clearly shows Karur town is the becoming more and more urbanized.

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