scholarly journals Suitability of Post-Disaster Coastal Land Cover with Spatial Pattern Plan of Palu City

2021 ◽  
Vol 940 (1) ◽  
pp. 012004
Author(s):  
R R Wirawan ◽  
H S Hasibuan ◽  
R P Tambunan
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Land Cover ◽  
Population Growth ◽  
Natural Disasters ◽  
Spatial Planning ◽  
Permanent Housing ◽  
Coastal Land ◽  
Post Disaster ◽  
Spatial Plan

Abstract The population growth in Palu City has implications for increasing the need for developed land, especially after complex natural disasters in 2018. After these disasters, another impact was the need for the construction of temporary and permanent housing. Therefore, it is essential to adjust the land use with disaster-prone zones. This study aims to analyze the distribution of land cover in the Disaster-Prone Zone and the suitability of the Spatial Plan with the Disaster-Prone Zone. The method used is quantitative through spatial analysis using ArcGIS 10.5 software. The results showed that Disaster Prone Zone 2 is the most dominating zone in both the type of built-up land cover and vegetation so that it still had development opportunities. However, the suitability of the Spatial Planning with Disaster Prone Zone shows that Disaster Prone Zone 4 is still included in the spatial plan as a developed area.

KESESUAIAN LAHAN PERMUKIMAN TERHADAP RENCANA TATA RUANG WILAYAH BERBASIS SIG DI KABUPATEN KEPULAUAN SANGIHE

2021 ◽  
Vol 2 (2) ◽  
pp. 124-130
Author(s):  
Sofiena Mei Nessa ◽  
Selvana Treni Rosita Tewal ◽  
Cahyadi Nugroho
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Geographic Information Systems ◽  
Spatial Planning ◽  
Supervised Classification ◽  
Quantitative Methods ◽  
Image Data ◽  
Land Area ◽  
Border Areas ◽  
Spatial Plan

The problem in this study is related to the number of developments, especially those aimed at their designation, which is not by the existing regional spatial plan. This is because many developments are located in disaster-prone areas, coastal border areas, and protected areas. This also triggers changes in land use that are quite large from time to time. This study aims to determine the use of utilization with a regional spatial plan. This study uses quantitative methods to determine developments based on data in the Sangihe Islands Regency, analyzing image data and knowing the level of suitability of land use with the RTRW. The method of analysis in this study uses a method of spatial analysis based on geographic information systems (GIS) using supervised classification, scoring, weighting, overlay. The variables in this study include land use, spatial planning, and adjustments. The results show that the land area in the Regional Spatial Plan is suitable for land use in particular for an area of ​​3,202.65 hectares and not suitable for an area of ​​17,946.03 hectares from the total area of ​​the existing land use.

scholarly journals Prediction of Future Land Use and Land Cover (LULC) in Makassar City

2021 ◽  
Vol 23 (2) ◽  
pp. 183-189
Author(s):  
Sudirman Nganro ◽  
Slamet Trisutomo ◽  
Roland Barkey ◽  
Mukti Ali ◽  
Hidefumi Imura ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Water Body ◽  
Spatial Planning ◽  
Urban Population ◽  
Agent Based Modeling ◽  
Land Use Classification ◽  
Agent Based ◽  
Settlement Areas

Migration from rural area to urban area increases urban population. It increases and needs for settlements, leading to conversion of agricultural lands into settlement areas. Inconsistent land use compared with spatial planning causes change in land use. Spatial land use expansion can be monitored and predicted by modeling. NetLogo application is a software integrated with Agent-Based Modeling (ABM), which can be used to predict change of land use with various complex parameters. The present study used population growth as a parameter to predict change of land use of Makassar in 2050 based on 2017 land use classification map as the start of the prediction. The analysis result showed that the biggest change of land use happens to Settlement class which is 594.74 hectares and the smallest is Water Body class which is 8.76 hectares.

scholarly journals SPATIAL ANALYSIS OF RESIDENTIAL DEVELOPMENT IN PALU CITY

2021 ◽  
Vol 9 (2) ◽  
pp. 89
Author(s):  
Westi Utami ◽  
Abdul Muzil ◽  
Deny Andriawan ◽  
Maryono Dwi Saputra ◽  
Weni Yolanda Ratnasari
Keyword(s):  
Land Use ◽  
Data Analysis ◽  
Spatial Planning ◽  
Residential Development ◽  
Disaster Mitigation ◽  
Land Area ◽  
Spatial Use ◽  
Post Disaster ◽  
Spatial Plan

The earthquake, tsunami, and liquefaction that hit Palu in 2018 damaged infrastructure and settlements and resulted in 2,101 fatalities. In this context, understanding the level of vulnerability and disaster mitigation is very important, especially in providing directions for spatial use. This study aimed to map the affected areas, map the suitability of land use against spatial planning, and map settlement development in Palu City. Data analysis was carried out spatially through an overlay of spatial pattern maps with disaster-affected areas to map the disaster-affected areas. Next, an overlay was carried out on the land use with the Regional Spatial Plan (RTRW) to map the suitability of land use. Finally, an overlay of disaster-prone space zones was carried out on spatial patterns to map the classification of settlement zones. The results of the analysis show that in Palu City there are locations that are suitable for settlement and development covering an area of 5233.978 Ha or 13%; an area that can be used but conditional for settlement is 26860.36 Ha or 68%; the area that can be used but with certain conditions is 3106,714 Ha or 8%; while the land area of 4057,112 ha or 10% is a forbidden zone. This study is expected to become a consideration for the community in building settlements as well as a consideration in preparing spatial plans to suit disaster mitigation efforts. This effort is made so that the construction of post-disaster settlements is carried out in disaster-safe areas.

RELATIONSHIP BETWEEN POPULATION GROWTH WITH CHANGING LAND-USE PATTERN AND ENVIRONMENTAL CHANGES IN KOLKATA, WEST BENGAL

2021 ◽  
pp. 57-61
Author(s):  
Arunima Dasgupta
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Environmental Degradation ◽  
Urban Sprawl ◽  
West Bengal ◽  
Environmental Changes ◽  
Capital City ◽  
Special Focus ◽  
Rapid Urbanization

Given that urbanization is considered as one of the most signicant anthropogenic alteration of the overall environment, the present study attempts to understand spatial-temporal characteristics of urban population growth and its implications on land-use as well as understanding their relationship with environmental degradation with special focus on the Kolkata, the capital city of West Bengal. Urbanization is one of the major driving forces behind the development of today's land-use and land cover system. A large number of contemporary urbanization has been characterized as urban sprawl namely in an extensive form of land-use for urban uses that have environmentally detrimental effects. There are indications of Urban sprawl and city expansion in our Study Area of Kolkata indicating expansion of settlements and built-up area and thus causing environmental degradation in the city area. The process of urbanization always had signicant implications that can affect cumulative changes in demographic characteristics and/or transformation of the physical environment; unplanned, unsystematic and rapid urbanization can cause intense impacts on various environmental aspects, specically on land and air and water. A thorough understanding of the dynamic relationship between urbanization and its generated land-cover changes thus becomes completely essential for managing environmental changes and enabling sustainability of the environment and its resources.

scholarly journals Post-Disaster Recovery Assessment with Machine Learning-Derived Land Cover and Land Use Information

2019 ◽  
Vol 11 (10) ◽  
pp. 1174 ◽  
Author(s):  
Mohammadreza Sheykhmousa ◽  
Norman Kerle ◽  
Monika Kuffer ◽  
Saman Ghaffarian
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Land Cover ◽  
Functional Recovery ◽  
Disaster Recovery ◽  
Learning Algorithm ◽  
Support Vector ◽  
High Resolution Satellite Images ◽  
Recovery Assessment ◽  
Post Disaster

Post-disaster recovery (PDR) is a complex, long-lasting, resource intensive, and poorly understood process. PDR goes beyond physical reconstruction (physical recovery) and includes relevant processes such as economic and social (functional recovery) processes. Knowing the size and location of the places that positively or negatively recovered is important to effectively support policymakers to help readjust planning and resource allocation to rebuild better. Disasters and the subsequent recovery are mainly expressed through unique land cover and land use changes (LCLUCs). Although LCLUCs have been widely studied in remote sensing, their value for recovery assessment has not yet been explored, which is the focus of this paper. An RS-based methodology was created for PDR assessment based on multi-temporal, very high-resolution satellite images. Different trajectories of change were analyzed and evaluated, i.e., transition patterns (TPs) that signal positive or negative recovery. Experimental analysis was carried out on three WorldView-2 images acquired over Tacloban city, Philippines, which was heavily affected by Typhoon Haiyan in 2013. Support vector machine, a robust machine learning algorithm, was employed with texture features extracted from the grey level co-occurrence matrix and local binary patterns. Although classification results for the images before and four years after the typhoon show high accuracy, substantial uncertainties mark the results for the immediate post-event image. All land cover (LC) and land use (LU) classified maps were stacked, and only changes related to TPs were extracted. The final products are LC and LU recovery maps that quantify the PDR process at the pixel level. It was found that physical and functional recovery can be mainly explained through the LCLUC information. In addition, LC and LU-based recovery maps support a general and a detailed recovery understanding, respectively. It is therefore suggested to use the LC and LU-based recovery maps to monitor and support the short and the long-term recovery, respectively.

scholarly journals Spatial Analysis of Land Use and Land Cover Changes in Recent 30 Years in Manas River Basin

2012 ◽  
Vol 12 ◽  
pp. 906-916 ◽  
Author(s):  
Zhang Qingqing ◽  
Xu Hailiang ◽  
Fu Jingyi ◽  
Yu Pujia ◽  
Zhang Peng
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Land Cover ◽  
River Basin ◽  
Land Cover Changes ◽  
Manas River Basin

An assessment of coastal land-use and land-cover change from 1974–2008 in the vicinity of Mobile Bay, Alabama

2010 ◽  
Vol 15 (1) ◽  
pp. 139-149 ◽  
Author(s):  
Jean T. Ellis ◽  
Joseph P. Spruce ◽  
Roberta A. Swann ◽  
James C. Smoot ◽  
Kent W. Hilbert
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Mobile Bay ◽  
Coastal Land Use ◽  
Coastal Land

scholarly journals Time Series Land Cover Mapping and Change Detection Analysis Using Geographic Information System and Remote Sensing, Northern Ethiopia

2018 ◽  
Vol 11 ◽  
pp. 117862211775160 ◽  
Author(s):  
Gebiaw T Ayele ◽  
Aschalew K Tebeje ◽  
Solomon S Demissie ◽  
Mulugeta A Belete ◽  
Mengistu A Jemberrie ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Population Growth ◽  
Change Detection ◽  
Land Cover Change ◽  
Training Data ◽  
Steady Increase ◽  
Northern Ethiopia ◽  
Detection Techniques

Land use planners require up-to-date and spatially accurate time series land resources information and changing pattern for future management. As a result, assessing the status of land cover change due to population growth and arable expansion, land degradation and poor resource management, partial implementation of policy strategies, and poorly planned infrastructural development is essential. Thus, the objective of the study was to quantify the spatiotemporal dynamics of land use land cover change between 1995 and 2014 using 5 multi-temporal cloud-free Landsat Thematic Mapper images. The maximum likelihood (ML)-supervised classification technique was applied to create signature classes for significant land cover categories using means and variances of the training data to estimate the probability that a pixel is a member of a class. The final Bayesian ML classification resulted in 12 major land cover units, and the spatiotemporal change was quantified using post-classification and statistical change detection techniques. For a period of 20 years, there was a continuously increasing demand for arable areas, which can be represented by an exponential growth model. Excepting the year 2009, the built-up area has shown a steady increase due to population growth and its need for infrastructure development. There was nearly a constant trend for water bodies with a change in slope significantly less than +0.01%. The 2014 land cover change statistics revealed that the area was mainly covered by cultivated, wood, bush, shrub, grass, and forest land mapping units accounting nearly 63%, 12%, 8%, 6%, 4%, and 2% of the total, respectively. Land cover change with agro-climatic zones, soil types, and slope classes was common in most part of the area and the conversion of grazing land into plantation trees and closure area development were major changes in the past 20 years.

scholarly journals ANALISIS PENYIMPANGAN PENGGUNAAN LAHAN BERDASARKAN RENCANA TATA RUANG WILAYAH KABUPATEN SUMEDANG

2018 ◽  
Vol 20 (4) ◽  
pp. 399
Author(s):  
Reny Khaerani ◽  
Santun R.P. Sitorus ◽  
Omo Rusdiana
Keyword(s):  
Principal Component Analysis ◽  
Land Use ◽  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Human Resource ◽  
Spatial Planning ◽  
Rapid Development ◽  
Principal Component ◽  
Spatial Plan

Spatial plan is the result of spatial planning which is done through the process and procedure of arranging and determining based on the prevailing laws and regulations. The phenomenon that often happens is the deviation of existing land use with spatial plan. Sumedang Regency is experiencing a fairly rapid development, so there is an increase in human resource activity that implicate the widespread space needs and consequently deviation of land use is very vulnerable. The purpose of this study to determine the extent of deviation of land use occurs as well as what factors affect the occurence of irregular use of land. The analysis used in this study using GIS approach, Principal Component Analysis and Multiple Regression Analysis. The result of analysis shows that there are 25 types of deviation of existing land use and the most dominant is deviation into wetland (18,364 ha), dryland field (8,405 ha) and widened land (7,741 ha). While the factors that influence the occurence of deviation of land use are population and settlement, availability of land, infrastructure and accessibility, and sosioeconomic condition of society

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