scholarly journals Identifikasi Perubahan Penggunaan Lahan dengan Menggunakan Citra Satelit di Distrik Musatfak Kabupaten Jayawijaya

2020 ◽  
Vol 1 (3) ◽  
pp. 23
Author(s):  
Lukmar Hilungka ◽  
Grace F. E. Suoth ◽  
Helena Sri Sulastriningsih
Keyword(s):  
Land Use ◽  
Spatial Analysis ◽  
Paddy Field ◽  
Research Method ◽  
Land Use Changes ◽  
Paddy Fields ◽  
Land Change ◽  
The People ◽  
The City ◽  
Land Use Functions

The identification of land-use changes in the Musatfak District of Jayawijaya Regency is based on the decreasing level of community income and the change in land use functions. The purpose of this study is to calculate land-use changes in Musatfak District, Jayawijaya Regency in 2015-2020 and to examine the factors that cause changes in land use. The research method is descriptive qualitative and overlays spatial analysis of data using ArGIS. The results showed changes in land use in Musatfak District, Jayawijaya Regency in 2015-2020, respectively for horticultural land 1,787 square hectares, paddy field 15 hectares square, and sleeping area 19 square hectares. It is known that the causes of land change include: horticultural land and paddy fields are converted into idle land, because the people in Musatfak District do not cultivate the land because some have settled in the city, working to sell and buy wood planks, beams, and lima-lima.

scholarly journals The Value of a Decrease in Temperature by One Degree Celsius of the Regional Microclimate—The Cooling Effect of the Paddy Field

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 353
Author(s):  
Ya-Wen Chiueh ◽  
Chih-Hung Tan ◽  
Hsiang-Yi Hsu
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Paddy Field ◽  
Research Area ◽  
Paddy Fields ◽  
Cooling Effect ◽  
Field Temperature ◽  
Bare Land ◽  
The Face ◽  
The Difference

In the face of climate change, extreme climates are becoming more frequent. There were severe droughts in Taiwan in 2020, 2014–2015, and 2002. In these years, the paddy fields were kept fallow to save water and transfer agricultural water to non-agricultural use. On the other hand, with global warming, the existence of paddy fields may be one of the natural solutions to regional temperature mitigation. This study used remote sensing to quantify the difference in temperature between paddy fields and urban areas. The result of overall surface temperature deductive analysis revealed that the temperature in the whole Taoyuan research area was 1.2 °C higher in 2002 than in 2003 because of fallowing of the paddy field, while in the Hsinchu research area, it was 1.5 °C higher in 2002 than in 2003, due to the same reason described above. In terms of the difference in land use, for the Hsinchu research area, the surface temperature deductive result showed that the average paddy field temperature in 2002 was 22.3 °C (sample area average), which was 7.7 °C lower than that of the building and road point and 4.3 °C lower than that of the bare land point. The average paddy field temperature in 2003 was 19.2 °C (sample area average), which was 10.1 °C lower than that of the building and road point and 8.3 °C lower than that of the bare land point. Then this study evaluated the economic valuation of the paddy field cooling effect using the contingent valuation method. Through the paddy field cooling effect and in the face of worsening extreme global climate, the willingness to pay (WTP) of the respondents in Taiwan for a decrease of 1 °C with regard to the regional microclimate was evaluated. It was found that people in Taiwan are willing to pay an extra 8.89 USD/per kg rice/year for the paddy for a decrease in temperature by 1 °C in the regional microclimate due to the paddy field. Furthermore, this study applied the benefits transfer method to evaluate the value of a decrease of 1 °C in the regional microclimate in Taiwan. The value of a decrease of 1 °C in the regional microclimate in Taiwan is 9,693,144,279 USD/year. In this regard, the economic value of 1 °C must not be underestimated. In conclusion, more caution is needed while making decisions to change the land use of paddy fields to other land uses.

scholarly journals Effects of Contemporary Land Use Types and Conversions from Wetland to Paddy Field or Dry Land on Soil Organic Carbon Fractions

2020 ◽  
Vol 12 (5) ◽  
pp. 2094
Author(s):  
Di Zhao ◽  
Junyu Dong ◽  
Shuping Ji ◽  
Miansong Huang ◽  
Quan Quan ◽  
...  
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Constructed Wetland ◽  
Paddy Field ◽  
Heavy Fraction ◽  
Light Fraction ◽  
Paddy Fields ◽  
Dry Land ◽  
Natural Wetlands

Soil organic carbon (SOC) concentration is closely related to soil quality and climate change. The objectives of this study were to estimate the effects of contemporary land use on SOC concentrations at 0–20 cm depths, and to investigate the dynamics of SOC in paddy-field soil and dry-land soil after their conversion from natural wetlands (20 and 30 years ago). We investigated the dissolved organic carbon (DOC), light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC), and other soil properties (i.e., moisture content, bulk density, pH, clay, sand, silt, available phosphorous, light fraction nitrogen, and heavy fraction nitrogen) in natural wetlands, constructed wetlands, fishponds, paddy fields, and soybean fields. The results indicated that the content of DOC increased 17% in constructed wetland and decreased 39% in fishponds, and the content of HFOC in constructed wetland and fishponds increased 50% and 8%, respectively, compared with that in natural wetlands at 0–20 cm. After the conversion of a wetland, the content of HFOC increased 72% in the paddy fields and decreased 62% in the dry land, while the content of DOC and LFOC decreased in both types. In the paddy fields, LFOC and HFOC content in the topmost 0.2 m of the soil layer was significantly higher compared to the layer below (from 0.2 to 0.6 m), and there were no significant differences observed in the dry land. The findings suggest that the paddy fields can sequester organic carbon through the accumulation of HFOC. However, the HFOC content decreased 22% after 10 years of cultivation with the decrease of clay content, indicating that paddy fields need to favor clay accumulation for the purpose of enhancing carbon sequestration in the paddy fields.

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KESEJAHTERAAN MASYARAKAT KOTA PADANG

2020 ◽  
Vol 11 (1) ◽  
pp. 67
Author(s):  
Rizki Afri Mulia ◽  
Nika Saputra
Keyword(s):  
Unemployment Rate ◽  
Research Method ◽  
Quantitative Research ◽  
Regression Coefficient ◽  
Sampling Technique ◽  
Domestic Product ◽  
Poor People ◽  
The People ◽  
Per Capita ◽  
The City

This study aims to analyze the factors that affect the welfare of the people of the City of Padang measured using the Human Development Index consisting of: 1) To determine the effect of the Per Capita Gross Regional Domestic Product on the welfare of the people in the City of Padang. 2) To determine the effect of number of Poor in community welfare in Padang. 3) To determine the effect of Unemployment Rate on the welfare of people in the city of Padang. The research method used in this research is descriptive quantitative research method. The sampling technique in this study is total sampling. Data collection was performed using documentation and hypothesis testing techniques in this study using multiple linear regression test. Based on the results of the study note that: 1) The regression coefficient value of GDP per capita is equal to 0.0000002 with a probability of 0.001 which is smaller than 0.05. 2) The regression coefficient value of the number of poor population is 0.156 with a probability of 0.526 which is smaller than 0.05. 3) The regression coefficient value of the Open Unemployment Rate is -0,00014 with a probability of 0.117 less than 0.05. The conclusions that can be drawn are as follows: 1) Gross Regional Domestic Product (GRDP) has a positive and significant effect on the welfare of the people in Padang City. 2) The number of poor people has no significant effect on the welfare of the people in the city of Padang. 3) Open Unemployment Rate has no negative and significant effect on the welfare of the people in Padang City.

scholarly journals Suelos Y Karst, Origen De Inundaciones Y Hundimientos En Chetumal, Quintana Roo, México

2018 ◽  
Vol 14 (14) ◽  
pp. 33 ◽  
Author(s):  
Patricia Fragoso-Servón ◽  
Alberto Pereira-Corona
Keyword(s):  
Land Use ◽  
Growth Rate ◽  
Population Growth Rate ◽  
Land Use Changes ◽  
Development Program ◽  
Quintana Roo ◽  
Development Programs ◽  
Mexican Caribbean ◽  
The City ◽  
Over Time

The Mexican Caribbean and its main cities have the highest population growth rate in Mexico. This work goal was to analyze the growth of the city of Chetumal and the geopedological characteristics in which it has been developed, to identify potential hazards and thereby improve development programs. The methodology consisted in the study of geopedological characteristics and the analysis of land use changes in the city over time. The main problems of Chetumal are floods and subsidence. Floods are more common in areas where Gleysols soils are found in low-lying areas. The subsidence is associated to Leptosols with a phreatic mantle at a shallow depth where the precipitations favors dissolution of rock. The extrapolation of the relationships between geopedological conditions and the area occupied by the city, allows us to suppose that areas which the current Urban Development Program proposes for future city expansion will develop the same problems of subsidence and flooding as the areas already built in sites with similar conditions.

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 Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 42 ◽  
Author(s):  
Wei Sun ◽  
Zhihong Liu ◽  
Yang Zhang ◽  
Weixin Xu ◽  
Xiaotong Lv ◽  
...  
Keyword(s):  
Land Use ◽  
Wind Speed ◽  
Correlation Coefficient ◽  
Urban Areas ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Simulation Results ◽  
The City ◽  
Better Than

The expansion of urban areas and the increase in the number of buildings and urbanization characteristics, such as roads, affect the meteorological environment in urban areas, resulting in weakened pollutant dispersion. First, this paper uses GIS (geographic information system) spatial analysis technology and landscape ecology analysis methods to analyze the dynamic changes in land cover and landscape patterns in Chengdu as a result of urban development. Second, the most appropriate WRF (Weather Research and Forecasting) model parameterization scheme is selected and screened. Land-use data from different development stages in the city are included in the model, and the wind speed and temperature results simulated using new and old land-use data (1980 and 2015) are evaluated and compared. Finally, the results of the numerical simulations by the WRF-Chem air quality model using new and old land-use data are coupled with 0.25° × 0.25°-resolution MEIC (Multi-resolution Emission Inventory for China) emission source data from Tsinghua University. The results of the sensitivity experiments using the WRF-Chem model for the city under different development conditions and during different periods are discussed. The meteorological conditions and pollution sources remained unchanged as the land-use data changed, which revealed the impact of urban land-use changes on the simulation results of PM2.5 atmospheric pollutants. The results show the following. (1) From 1980 to 2015, the land-use changes in Chengdu were obvious, and cultivated land exhibited the greatest changes, followed by forestland. Under the influence of urban land-use dynamics and human activities, both the richness and evenness of the landscape in Chengdu increased. (2) The microphysical scheme WSM3 (WRF Single–Moment 3 class) and land-surface scheme SLAB (5-layer diffusion scheme) were the most suitable for simulating temperatures and wind speeds in the WRF model. The wind speed and temperature simulation results using the 2015 land-use data were better than those using the 1980 land-use data when assessed according to the coincidence index and correlation coefficient. (3) The WRF-Chem simulation results obtained for PM2.5 using the 2015 land-use data were better than those obtained using the 1980 land-use data in terms of the correlation coefficient and standard deviation. The concentration of PM2.5 in urban areas was higher than that in the suburbs, and the concentration of PM2.5 was lower on Longquan Mountain in Chengdu than in the surrounding areas.

scholarly journals KARAKTERISTIK PERKEMBANGAN STRUKTUR RUANG IBU KOTA KECAMATAN GEMOLONG KABUPATEN SRAGEN

2016 ◽  
Vol 2 (2) ◽  
pp. 118
Author(s):  
Dhoni Setiawan ◽  
Mardwi Rahdriawan
Keyword(s):  
Land Use ◽  
Spatial Structure ◽  
Rapid Development ◽  
Integrated System ◽  
Urban Spaces ◽  
Physical Growth ◽  
Land Use Patterns ◽  
Use Patterns ◽  
The People ◽  
The City

<p>City is a space that serves as a center place of activities, over time the city was experiencing growth and development, both physical and non-physical conditions. So these conditions affect the change in the pattern of land use, activity system as well as the pattern of people and goods mobility that are happening in the urban system. The phenomenon of the emergence of new urban areas (cities and towns) in IKK Gemolong causes changes in land use patterns along the road corridor is experiencing rapid development, it is evidenced by the increased activity and physical growth of the city. The conditions were observed with the growth of new activities such as residential, commercial district and other commercial areas. So that it will affect land use patterns, activities systems and people and goods mobility patterns that occur, which in turn will affect the characteristics of the spatial structure of the development of IKK Gemolong formed as a town in Sragen. The focus of discussion such as land use, population activity systems, as well as the people and goods mobility which the influencing factors of the formation of the spatial structure of a city. The study is considered important because as the basis for consideration in the development of towns in the future. This is because the policy of urban development continues in administrative and sectoral nature, so the presence of the regional autonomy policy of development with regional and integrated system and assessed more quickly to implement. This study used quantitative an quantitative study method. The analysis results indicated the characteristics of land use in Gemolong dominated by settlements, while the commercial district developed along the main streets of this town because Gemolong have function as service centers for its surrounding areas. The residents of Gemolong mostly have work in the non-agricultural sectors, such as trade and services, while the population as a farmer is relatively small, so that these conditions indicated that Gemolong says as urban area. The people mobility in Gemolong originated from both internal and external area of the town in destination location of commercial areas to have studying, working, shopping and other purposes. The residents of Gemolong do not have to big cities to access the daily life necessities for since it is already available in Gemolong. Based on the phenomenon of Gemolong have a compact city type of development, while the structure of urban spaces that were formed have view more functioning of each of the regions even though the condition is still occurring mixture of functions. Then, the structure of urban spaces is the type of sector, although not as ideal as yet which happened in developed countries.</p>

scholarly journals CELLULAR AUTOMATA MODEL – LANDSCAPE DYNAMICS SIMULATION TOOL IN THE PROCESS OF CHANGE IN LAND USE AND COVER IN THE CITY OF GAÚCHA DO NORTE – MT

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 447-451
Author(s):  
E. A. L. Pinheiro ◽  
N. A. Camini ◽  
M. R. S. Soares ◽  
S. S. Sumida
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Land Use Changes ◽  
Environmental Modeling ◽  
Dynamics Simulation ◽  
Cellular Automata Model ◽  
The City ◽  
Land Use And Cover ◽  
Main Factor

Abstract. The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left Brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment.

scholarly journals PREDIKSI SPASIAL DINAMIKA AREAL TERBANGUN KOTA SEMARANG DENGAN MENGGUNAKAN MODEL REGRESI LOGISTIK

2016 ◽  
Vol 18 (2) ◽  
pp. 95 ◽  
Author(s):  
Irmadi Nahib
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Cellular Automata ◽  
Land Cover ◽  
Open Space ◽  
Land Use Changes ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Rate Of Increase ◽  
The City

<p class="JudulABSInd"><strong>ABSTRAK</strong></p><p class="abstrak">Salah satu indikator perkembangan fisik wilayah kota dapat diidentifikasi melalui fenomena perubahan tutupan lahan bervegetasi menjadi lahan terbangun. Perubahan lahan tersebut dapat berdampak terhadap penurunan kualitas lingkungan, akibat berkurangnya ruang terbuka hijau. Kota Semarang dengan visi terwujudnya Semarang sebagai kota perdagangan dan jasa yang berbudaya menuju masyarakat sejahtera, merupakan  wilayah yang rentan mengalami perubahan penggunaan lahan yang cenderung kearah lahan terbangun. Penelitian ini mengintegrasikan model <em>Cellular Automata</em> (CA) dan regresi logistik biner untuk memprediksi dinamika lahan terbangun di Kota Semarang. Citra yang digunakan adalah Citra Ikonos 2002, Ikonos 2006 dan <em>Quic</em><em>kbird</em> 2012. Model CA pada penelitian ini digunakan untuk memprediksi sebaran penutup lahan tahun 2022 dan 2032 dengan mempertimbangkan jarak terhadap jalan, jarak terhadap sungai, jarak terhadap lahan terbangun, ketinggian, kepadatan penduduk, <em>evidence likelihood </em>perubahan lahan dan indeks pengembangan kelurahan yang diakomodasi dalam peta sub-model transisi hasil model regresi logistik biner. Hasil penyusunan model ini adalah peta prediksi penutup lahan dengan akurasi 78,21 % validitas model yang dihasilkan dapat dikategorikan “<em>moderate</em>” mengindikasikan bahwa peta yang dihasilkan dapat digunakan. Hasil pemodelan menunjukkan bahwa Kota Semarang pada tahun 2022 terjadi pertambahan luas lahan terbangun rata-rata 284 ha/tahun dan pada tahun 2032 rata-rata 226 ha/tahun.</p><p><strong><em>Kata </em></strong><strong><em>k</em></strong><strong><em>unci</em></strong><em>: </em><em>cellular automata, pemodelan, regresi logistik biner, lahan terbangun</em></p><p class="judulABS"><em><strong>ABSTRACT</strong></em></p><p class="Abstrakeng">One indicator of the physical development of the city can be identified by phenomenon of land expansion, vegetated land cover changes to be built-up area. The land use changes can impact to environmental degradation, due to reduced green open space. Semarang as a city of trade and services cultured toward a prosperous community, a region that is vulnerable to changes in land use tends toward small plots. This research integrates the model of Cellular Automata (CA) and binary logistic regression to predict the dynamics of builtup area in the city of Semarang. The image used is a Ikonos imagery (2002), Ikonos imagery (2006) and Quickbird (2012). Model CA in this research use to predict the distribution of land cover 2022 and 2032 with respect to: distance to roads, the distance to the river, the distance to the built-up area, elevation, population density, evidence likelihood of land use change and development villages index were accommodated in the map sub-model transition binary logistic regression model results. The results of this study are predictive maps of built-up area  with an accuracy of 78,21 % so that the validity of the resulting model can be categorized as "moderate", indicates that the probability map is valid. Modeling results showed that Semarang City in 2022 predicted rate of increase of  built-up area an average 284  ha / year and in 2032 rate of increase of built-up area an average 226 ha / year.</p><p><strong><em>Keywords</em></strong><em>: cellular automata, modelling, binary logistic regression, built-up area</em></p>

scholarly journals Land Use Changes in Peripheral Rural Areas of the City Parts Bratislava

2012 ◽  
Vol 16 (1) ◽  
pp. 96-105
Author(s):  
Blažena Hógelová ◽  
Marián Kulla ◽  
Peter Spišiak
Keyword(s):  
Land Use ◽  
Rural Areas ◽  
Land Use Changes ◽  
The City
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