Research on Land Use Classification of Land Change Survey for the Integration of Urban Planning and Land Resource Administration

2013 ◽  
pp. 197-205 ◽  
Author(s):  
Qi Liao ◽  
Mo Su ◽  
Ganghui Luo ◽  
Xiaowu Wei
Keyword(s):  
Land Use ◽  
Urban Planning ◽  
Land Resource ◽  
Land Change ◽  
Land Use Classification

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

LAND-USE CLASSIFICATION OF GRAY-SCALE AERIAL IMAGES USING PROBABILISTIC NEURAL NETWORKS

2004 ◽  
Vol 47 (5) ◽  
pp. 1813-1819 ◽  
Author(s):  
D. Ashish ◽  
G. Hoogenboom ◽  
R. W. McClendon
Keyword(s):  
Neural Networks ◽  
Land Use ◽  
Aerial Images ◽  
Land Use Classification ◽  
Probabilistic Neural Networks ◽  
Gray Scale

scholarly journals Land Use and Its Suitability to the Spatial Pattern in Batam City

2020 ◽  
Vol 4 (2) ◽  
pp. 363-366
Author(s):  
Novika Dora ◽  
Arif Roziqin
Keyword(s):  
Land Use ◽  
Spatial Pattern ◽  
City Government ◽  
Land Use Classification ◽  
Class Iii ◽  
Human Needs ◽  
Bare Land ◽  
The Government ◽  
Land Use Maps

Land use continues to grow as population increases in an area, various activities and human needs require land. Land use will affect the suitability of the spatial pattern determined by the Government stipulated in the laws and regulations governing spatial patterns. The purpose of this research is to identify land use that occurred in Batam City in 2019 and determine the suitability of the land use of the Batam City spatial pattern. In this study, the spatial pattern used is the spatial pattern obtained from BP Batam, this is because the spatial pattern originating from the Batam City Government has not yet been approved. The research method used is the method of Classification of Multispectral Maximum Likelihood and Overlay. The results of the map show the class of land use classifications totaling 11 classes in accordance with the class III land use classification class specified by Malingreau, which consists of lakes, forests, industry, pool, bare land, mangroves, ports, plantations, settlements, airports, and livestock. The results of the suitability of land use maps to the spatial pattern of Batam City indicate that the area of the area that is in accordance with the spatial pattern is 30986.77 Ha and the area that is not suitable is 34554.29 Ha.

scholarly journals AN ITERATIVE INFERENCE PROCEDURE APPLYING CONDITIONAL RANDOM FIELDS FOR SIMULTANEOUS CLASSIFICATION OF LAND COVER AND LAND USE

2015 ◽  
Vol II-3/W5 ◽  
pp. 369-376 ◽  
Author(s):  
L. Albert ◽  
F. Rottensteiner ◽  
C. Heipke
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Random Fields ◽  
Conditional Random Fields ◽  
Main Idea ◽  
Aerial Images ◽  
Land Use Classification ◽  
Inference Procedure ◽  
Cover Layer

Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered. The image sites for land cover and land use classification form a hierarchy consisting of two layers: a <i>land cover layer</i> and a <i>land use layer</i>. We apply Conditional Random Fields (CRF) at both layers. The layers differ with respect to the image entities corresponding to the nodes, the employed features and the classes to be distinguished. In the land cover layer, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Both CRFs model spatial dependencies between neighbouring image sites. The complex semantic relations between land cover and land use are integrated in the classification process by using contextual features. We propose a new iterative inference procedure for the simultaneous classification of land cover and land use, in which the two classification tasks mutually influence each other. This helps to improve the classification accuracy for certain classes. The main idea of this approach is that semantic context helps to refine the class predictions, which, in turn, leads to more expressive context information. Thus, potentially wrong decisions can be reversed at later stages. The approach is designed for input data based on aerial images. Experiments are carried out on a test site to evaluate the performance of the proposed method. We show the effectiveness of the iterative inference procedure and demonstrate that a smaller size of the super-pixels has a positive influence on the classification result.

scholarly journals CLASSIFICATION OF LITHUANIAN TOWNS AND DEFINITION OF THEIR FUNCTIONAL STRUCTURE USED FOR URBAN PLANNING PURPOSES

2006 ◽  
Vol 30 (4) ◽  
pp. 181-191
Author(s):  
Zigmas Jonas Daunora
Keyword(s):  
Land Use ◽  
Urban Planning ◽  
Public Transportation ◽  
Urban System ◽  
The Other ◽  
Functional Structure ◽  
Residential Areas ◽  
Urban Structures ◽  
Ecological Requirements

Comprehensive planning of towns and townships takes a wider scale in the country. Therefore, there appears an urgent need to revise or review some conceptions of planning methodology that should be accepted after various alternatives consideration. According to our opinion: a) classification of centres of a settlement system (towns and townships) requires self-determination and equal understanding which, from one side, should reflect more precisely the existing diversity of development between the centres and their functions and, from the other side, the rank granted to these centres should meet the EU criteria; b) the functional structure of towns and townships, reflected by diversity in the purpose of their territory use and its indefinite character during the process of residential area modernization which takes place under market conditions, forces to give upa detailed setting of plot purpose and look for a more universal model of land- use purpose specification which could be applicable not only for planning of rural agricultural territories but for urban planning of residential areas as well. Proposals presented in the paper (Tables 1 and 2) respect the systematic conception of settlement network, accepted in Lithuania and in the other EU countries and based on the hierarchy of elements and development dependency allowing application of sustainability and balance principles for the system element development. They are prepared taking into account new urban planning conceptions and reflecting the following factors: changing business and production conditions as well as growing qualitative safety, service and ecological requirements for a residential environment; increasing importance of economic factors and resulting need for a more rational land use and broader urban internal integration when developing public transportation and urban system for a common space use; respect to stable urban structural elements of residential areas (urban framework) as well as to local cultural identity and historically formed compositional peculiarities; advantages of the functional and social diversity and polycentric character of urban structures.

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