scholarly journals Spatiotemporal Land-Use Changes of Batticaloa Municipal Council in Sri Lanka from 1990 to 2030 Using Land Change Modeler

Geographies ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 166-177
Author(s):  
Ibra Lebbe Mohamed Zahir ◽  
Sunethra Thennakoon ◽  
Rev. Pinnawala Sangasumana ◽  
Jayani Herath ◽  
Buddhika Madurapperuma ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Environmental Changes ◽  
Learning Algorithm ◽  
Land Use Changes ◽  
Land Change ◽  
Spatial And Temporal Scales ◽  
Municipal Council ◽  
Land Change Modeler ◽  
Medium Resolution

Land-use change is a predictable and principal driving force of potential environmental changes on all spatial and temporal scales. A land-use change model is a tool that supports the analysis of the sources and consequences of land-use dynamics. This study aims to assess the spatiotemporal land-use changes that occurred during 1990–2020 in the municipal council limits of Batticaloa. A land change modeler has been used as an innovative land planning and decision support system in this study. The main satellite data were retrieved from Landsat in 1990, 2000, 2010, and 2020. For classification, the supervised classification method was employed, particularly with the medium resolution satellite images. Land-use classes were analyzed by the machine learning algorithm in theland change modeler. The Markov chain method was also used to predict future land-use changes. The results of the study reveal that only one land-use type, homestead, has gradually increased, from 12.1% to 34.1%, during the above-mentioned period. Agriculture land use substantially declined from 26.9% to 21.9%. Bare lands decreased from 11.5% to 5.0%, and wetlands declined from 13.9% to 9.6%.

Prediksi Perubahan Lahan Terbangun Dengan OBIA LCM Pada Citra Terfusi di Kota Kendari

2021 ◽  
Vol 5 (2) ◽  
pp. 170
Author(s):  
Adnan Adnan ◽  
Fitra Saleh ◽  
Iradat Salihin
Keyword(s):  
Land Use ◽  
Landsat Imagery ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Land Change ◽  
Land Use Classification ◽  
Landsat 8 Oli ◽  
Land Change Modeler ◽  
Two Factors ◽  
Land Changes

Abstrak: Penggunaan lahan disetiap tahunnya akan mengalami perubahan. Perkembangan tersebut bisa jadi tidak terkendali, sehingga perencanaan prediksi perubahan lahan penting untuk dikaji. Dalam memprediksi dapat dilakukan dengan menggunakan citra, khususnya citra Landsat. Penelitian ini bertujuan untuk: (1) distribusi penggunaan lahan terbangun di Kota Kendari pada tahun 2014 dan 2019 dengan metode OBIA pada citra terfusi; (2) melihat arah perubahan penggunaan lahan terbangun di Kota Kendari pada tahun 2024 dan 2029 dengan metode Land Change Modeler (LCM). Metode yang digunakan dalam penelitian ini  yaitu metode klasifikasi penggunaan lahan berbasis piksel OBIA dan pemodelan prediksi perubahan penggunaan lahan Land Change Modeler (LCM). Hasil penelitian ini antara lain: (1) luas lahan terbangun pada tahun 2014 di Kota Kendari seluas 6.061,85 hektar dan luas penggunaan lahan terbangun di Kota Kendari pada tahun 2019 seluas 6.716,96 hektar dengan perubahan penggunaan lahan terbangun tahun 2014 sampai dengan tahun 2019 dengan pertambahan luas 2,43%; (2) Arah perubahan penggunaan lahan terbangun di Kota Kendari diprediksikan cenderung berkembang ke arah Kecamatan Baruga karena dipengaruhi oleh dua faktor yaitu kemiringan lereng dan jaringan jalan. Kata Kunci : Penggunaan Lahan, Landsat 8 OLI, Penajaman Citra, OBIA, LCM Abstract: Land use will change every year. The development may be uncontrollable, so predictive planning of land changes is important to review. In predicting  can be done using  imagery, especially Landsat imagery. This study aims to:(1)  the distribution of land  use  built  in Kendari City in 2014 and 2019 with OBIA method on diffusion imagery; (2) see the direction of land use changes built in Kendari City in  2024 and 2029 with land change modeler  (LCM) method. The methods used in this study are OBIA pixel-based land  use  classification method and land use change prediction modeling land change modeler (LCM).  The results of this study include: (1) land area  built in 2014 in Kendari City aswide as 6,061.85 hectars and land use area built in Kendari City in 2019 aswide as 6,716.96 hectars with land use changes built in 2014 to 2019 with an increase  of  2.43%; (2) The direction of land use changes built in Kendari City  is predicted   to tend to  develop  towards  Baruga Subdistrict because it is influenced by two factors, namely slope and road network. Keywords: Land Use,  Landsat 8 OLI,  Image Sharpening,  OBIA, LCM

scholarly journals Land use changes in Prague suburban area according to different prediction modelling approaches

Geografie ◽  
2015 ◽  
Vol 120 (3) ◽  
pp. 422-443 ◽  
Author(s):  
Magdalena Indrová ◽  
Lucie Kupková
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Use Changes ◽  
Residential Development ◽  
Software Tools ◽  
Suburban Area ◽  
Soil Protection ◽  
Land Change ◽  
Land Change Modeler ◽  
Prediction Modelling

The main objective of this study was to compare the capabilities of the Dyna- CLUE and Land Change Modeler (LCM) software based on the results of land use/cover development predictions in selected cadastres of the Prague suburban area. Time series of land use data, land use plans of the municipalities, and data on soil protection were used for this analysis. Land use prediction maps for the year 2020 were created using both software tools. The results of the comparison showed that the models respect the restriction of development. In accordance with the local land use plans, new residential development was properly allocated. As for commercial areas, the requirements were not completely fulfilled. It is evident that both models are able to produce correct maps of future land use based on specified requirements at the level of several cadastral units (area approx. 2,000 ha). However, the instability of LCM and the necessity of using other software while working with Dyna-CLUE somewhat complicated the work.

scholarly journals Assessment and prediction of land use changes in the Anzali wetland Basin, Based on Land Change Modeler (LCM)

2019 ◽  
Vol 11 (2) ◽  
pp. 93-114
Author(s):  
رضا شاکری ◽  
کامران شایسته ◽  
مهدی قربانی
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Land Change ◽  
Anzali Wetland ◽  
Land Change Modeler

scholarly journals Impacts of land use changes and climate variability on transboundary Hirmand River using SWAT

2019 ◽  
Vol 11 (4) ◽  
pp. 1695-1711 ◽  
Author(s):  
Mohammadreza Hajihosseini ◽  
Hamidreza Hajihosseini ◽  
Saeed Morid ◽  
Majid Delavar ◽  
Martijn J. Booij
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Land Use Change ◽  
Environmental Changes ◽  
Swat Model ◽  
Land Use Changes ◽  
River Basins ◽  
Irrigated Area ◽  
The Impact ◽  
Annual Discharge

Abstract Many river basins are facing a reduction of flows which might be attributed to changes in climate and human activities. This issue is very important in transboundary river basins, where already existing conflicts about shared water resources between riparian countries can easily escalate. The decrease of streamflow in the transboundary Hirmand (Helmand) River is one of the main challenges for water resources management in Iran and Afghanistan. This research aims to quantify the causes of this problem which has a direct impact on the dryness of the Hamoun wetlands being an international Ramsar site. To achieve this, the land use changes in the Middle Helmand Basin (MHB) in Afghanistan were evaluated for three time periods between 1990 and 2011 using remote sensing data and the Soil and Water Assessment Tool (SWAT) Model for understanding watershed response to environmental changes. It was concluded that the total irrigated area in the region has increased from 103,000 ha in 1990 to 122,000 ha in 2001 and 167,000 ha in 2011 (62% increase). According to the results, the average annual discharge when adapting the land use during the simulations was 4,787 million cubic meters (MCM)/year and while employing the land use of 1990 from the beginning of the simulations, the average annual discharge was 5,133 MCM/year. Therefore, the agricultural developments in the Helmand basin decreased the discharge with about 346 MCM/year accompanying an increase of 64,000 ha in an irrigated area in MHB after 1990. Notably, the impact of land use change increases significantly for more recent periods and causes a reduction of 810 MCM in annual streamflow for the MHB. The amount of water depletion (i.e. actual evapotranspiration) per hectare has increased from 5,690 in 1985 to 7,320 m3 in 2012. The applied methodology of this study is useful to cope with such a data scarcity region. It can help quantify the impact of land use change on the region and formulates strategies that can improve the situation between Iran and Afghanistan.

scholarly journals Land-Use Change in New Moscow: First Outcomes after Five Years of Urbanization

2019 ◽  
Vol 12 (4) ◽  
pp. 24-34 ◽  
Author(s):  
Viacheslav I. Vasenev ◽  
Alexey M. Yaroslavtsev ◽  
Ivan I. Vasenev ◽  
Sofiya A. Demina ◽  
Elvira A. Dovltetyarova
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Spectral Resolution ◽  
Environmental Changes ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Fallow Lands ◽  
Forested Areas ◽  
New Moscow

Urbanization coincides with remarkable environmental changes, including conversion of natural landscapes into urban. Moscow megapolis is among the largest urbanized areas in Europe. An ambitious New Moscow project expanded the megapolis on extra 1500 km2 of former fallow lands, croplands and forests. The research aimed to monitor land use changes in New Moscow between 1989 and 2016 years. Landsat 5 and Landsat 8 images (30 m spectral resolution) and Sentinel – 2 images (10 m spectral resolution) were analyzed. All the images were collected for the similar summer period (from June to August). The images were preprocessed and classified by Semi-Automatic Classification Plugin in open source QGIS software to derive land cover maps. The following land cover classes were identified: water, built-up areas, bare soils, croplands and forested areas, and the total area covered by each class was estimated. The following land-use change pathways were reported: 1) reduction of the forested areas by 2.5% (almost 2000 ha) between 1989 and 1998; 2) partial reforestation (more than 1000 ha) and abandonment of croplands (more than 3000 ha) between 1998 and 2010 and 3) intensive urbanization (more than 11000 ha) between 2010 and 2016. New build-up areas and infrastructures were constructed on former forested areas and croplands. Although, some uncertainties in the absolute estimates are expected due to the classification errors, the general urbanization trend can be clearly distinguished as a principal outcome after the five years of New Moscow project.

Sign in / Sign up

Export Citation Format

Share Document