scholarly journals ANALISIS KECUKUPAN RUANG TERBUKA HIJAU (RTH) KOTA BATAM

2021 ◽  
Vol 4 (2) ◽  
pp. 176
Author(s):  
Shirly Indriana Putri ◽  
Nurul Qomar ◽  
Yossi Oktorini
Keyword(s):  
Land Cover ◽  
Open Space ◽  
Public Works ◽  
Landsat 8 ◽  
Analysis Method ◽  
Land Area ◽  
Dry Land ◽  
Industrial City ◽  
Image Recording ◽  
Spatial Analysis Method

Batam City is an industrial city and has a total area of 1,570.35 km2 with a land area of 715 km2. Following the economic development and increasing population, the green open space in Batam City is decreasing. The purpose of this research was to analyze the adequacy of Batam’s green open space based on the criteria of Law No. 26 of 2007 concerning Spatial Planning and Minister of Public Works Regulation No. 5 of 2008 concerning Guidelines and Utilization of Green Open Space. This research was conducted with a spatial analysis method based on land cover information from the interpretation of Landsat 8 OLI image recording on 05-06-2018. Based on the results showed that Batam’s green open space is still 221.400 ha or 32.05% from land area. It means, Batam City’s open space is still sufficient at least 30% according to Law No. 26 of 2007 and Minister of Public Works Regulation No. 5 of 2008. The largest type of land cover in green open space is secondary dry land forest, covering 79.200 ha (11.45%). Keyword : Batam City, analysis, green open space.

scholarly journals SEBARAN RUANG TERBUKA HIJAU JAGAKARSA

MODUL ◽  
2017 ◽  
Vol 16 (2) ◽  
pp. 76
Author(s):  
Nia Rachmawati
Keyword(s):  
Land Cover ◽  
Urban Development ◽  
Government Policy ◽  
Open Space ◽  
Urban Infrastructure ◽  
Physical Development ◽  
Analysis Method ◽  
Open Spaces ◽  
The Relationship

Acceleration in urban development had impact to environment and urban spatial. The increase of physical development and urban infrastructure influence to decreasing quantity of green open space. The green open space needs as one of solution to bind up the relationship between human. The population increased as benchmark of green open spaces needed in the region.. The purpose of this study is: (1) identify spread of green open spaces in Jagakarsa, (2) analize the needed of green open space The analysis method based on spread and land cover constrained by sub district and district garden in Jagakarsa. The spreading of district garden Jagakarsa had not spread which is need government policy to secure and increase spreading the green open space. 

ANALISIS PENGARUH PEMBANGUNAN JALAN LAYANG JANTI TERHADAP PERKEMBANGAN TATA RUANG KAWASAN JANTI STUDI KASUS : KAWASAN JANTI, DESA CATURTUNGGAL, KABUPATEN SLEMAN, D. I. YOGYAKARTA

2017 ◽  
Vol 11 (3) ◽  
pp. 255
Author(s):  
Jeky El Boru
Keyword(s):  
Road Network ◽  
Open Space ◽  
Qualitative Description ◽  
Analysis Method ◽  
Open Spaces ◽  
The Road ◽  
Before And After ◽  
Linkage Method ◽  
The Impact ◽  
Parking Place

Abstract: This research aims to analyze the impact of Janti Flyover Construction toward the growth of layout at Janti Urban Area, including structured space, open space, and linkage. Method used for data collecting are observation, air photograph monitoring, and interview, whereas the analysis method is qualitative description, which is the superimposed method of two layers, that are the layout condition before and after flyover construction. The result shows that the impact of Janti Flyover construction can be seen on building mass (solid), the increasing number of open spaces, including the road network, parking place, and park, whereas the relation between spaces, visually and structurally, can be seen on the growth of buildings which have new shapes and styles, therefore the performance of the overall building does not have a proportional shape. Considering Janti Street at the collective relation, its role is getting stronger as the main frame road network.Keywords: Flyover construction, layout changing, Janti AreaAbstrak: Penelitian ini bertujuan untuk menganalisis pengaruh pembangunan Jalan Layang Janti terhadap perkembangan tata ruang Kawasan Janti, meliputi ruang terbangun, ruang terbuka, serta hubungan antar ruang (“linkage”). Metode pengumpulan data dilakukan melalui observasi, pengamatan foto udara, dan wawancara; sedangkan metode analisis melalui deskripsi secara kualitatif yang berupa “superimposed method” dari dua lapisan kondisi lahan, yakni kondisi tata ruang sebelum dan sesudah pembangunan jalan layang. Hasil penelitian menunjukkan bahwa pengaruh pembangunan Jalan Layang Janti terdapat pada massa bangunan (“solid”), pertambahan ruang terbuka yang berupa jaringan jalan, parkir, dan taman; sedangkan pada hubungan antar ruang ̶ secara visual dan struktural ̶ yakni tumbuhnya bangunan dengan bentuk dan gaya baru, sehingga bentuk tampilan bangunan secara keseluruhan tidak proporsional. Pada hubungan kolektif, Jalan Janti semakin kuat perannya sebagai kerangka utama jaringan jalan.Kata kunci : Pembangunan jalan layang, tata ruang, Kawasan Janti

FAKTOR-FAKTOR YANG MEMPENGARUHI PENDAPATAN USAHATANI KACANG TANAH DI KECAMATAN SEMAU KABUPATEN KUPANG

2020 ◽  
Vol 21 (1) ◽  
pp. 25-33
Author(s):  
Deni K.L. Mudin ◽  
Paulus Un ◽  
Lika Bernadina
Keyword(s):  
Social Life ◽  
Economic Value ◽  
Coefficient Of Determination ◽  
Labor Costs ◽  
Land Area ◽  
Average Income ◽  
Dry Land ◽  
Regression Methods ◽  
The Cost ◽  
Total Average

ABSTRACT Peanuts are one of the high economic value commodities in the dry land area. This commodity also contributes to the social life of the dry land area. This research has been conducted in Semau Sub-district, Kupang Regency, with the aim to determine the amount of income, break event point (BEP), R / C ratio, efficiency of capital use and factors that affect the income of peanuts farming, with the number of farmer respondents as many as 92 people , simple randomly selected. Data that has been collected by survey, library and interview methods; analyzed quantitatively-descriptive using regression methods. The results showed that the total average income of peanut farming in the study location was IDR 1,739,895 with a total average income of IDR 3,498,261 and a total average cost of IDR 1,758,366. While the break event point average of production is 147 Kg and the break event point price is IDR. 6.509, while for the total average the R / C ratio is 1.99. With factors that affect income are production (X1), seed costs (X2), and labor costs (X3). From the regression results with the Cobb-Douglass function the coefficient of determination (R2) is 0.822 with the meaning that variations in independent variables such as production, seed costs and labor costs explain the dependent variable namely income (Y) of 82.20% and the rest 17.80 % is explained by variables outside of the variables analyzed. From the results of the F test (diversity test) it was found that the factors X1, X2, and X3 had a significant effect on income at ⍺ 1%, then accept H1 at least one of: βi ≠ 0. Whereas the results of the t test (partial test) obtained that factors significant effect on income, namely production (X1) and labor costs (X2), while the cost of seeds (X3) does not significantly affect income.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Pixel- vs. Object-Based Landsat 8 Data Classification in Google Earth Engine Using Random Forest: The Case Study of Maiella National Park

2021 ◽  
Vol 13 (12) ◽  
pp. 2299
Author(s):  
Andrea Tassi ◽  
Daniela Gigante ◽  
Giuseppe Modica ◽  
Luciano Di Martino ◽  
Marco Vizzari
Keyword(s):  
Land Cover ◽  
National Park ◽  
Time Window ◽  
Central Italy ◽  
Google Earth ◽  
Data Cube ◽  
Landsat 8 ◽  
Change Analysis ◽  
Object Based ◽  
Google Earth Engine

With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of the Maiella National Park (central Italy), useful for a future long-term LULC change analysis, this research aimed to develop a Landsat 8 (L8) data composition and classification process using Google Earth Engine (GEE). In this process, we compared two pixel-based (PB) and two object-based (OB) approaches, assessing the advantages of integrating the textural information in the PB approach. Moreover, we tested the possibility of using the L8 panchromatic band to improve the segmentation step and the object’s textural analysis of the OB approach and produce a 15-m resolution LULC map. After selecting the best time window of the year to compose the base data cube, we applied a cloud-filtering and a topography-correction process on the 32 available L8 surface reflectance images. On this basis, we calculated five spectral indices, some of them on an interannual basis, to account for vegetation seasonality. We added an elevation, an aspect, a slope layer, and the 2018 CORINE Land Cover classification layer to improve the available information. We applied the Gray-Level Co-Occurrence Matrix (GLCM) algorithm to calculate the image’s textural information and, in the OB approaches, the Simple Non-Iterative Clustering (SNIC) algorithm for the image segmentation step. We performed an initial RF optimization process finding the optimal number of decision trees through out-of-bag error analysis. We randomly distributed 1200 ground truth points and used 70% to train the RF classifier and 30% for the validation phase. This subdivision was randomly and recursively redefined to evaluate the performance of the tested approaches more robustly. The OB approaches performed better than the PB ones when using the 15 m L8 panchromatic band, while the addition of textural information did not improve the PB approach. Using the panchromatic band within an OB approach, we produced a detailed, 15-m resolution LULC map of the study area.

scholarly journals Geospatial analysis of wetlands based on land use/land cover dynamics using remote sensing and GIS in Sindh, Pakistan

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110261
Author(s):  
Hamza Islam ◽  
Habibuulah Abbasi ◽  
Ahmed Karam ◽  
Ali Hassan Chughtai ◽  
Mansoor Ahmed Jiskani
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Kappa Statistics ◽  
Natural Ecosystem ◽  
Land Use Land Cover ◽  
Dry Land ◽  
Lulc Changes ◽  
Manchar Lake

In this study, the Land Use/Land Cover (LULC) change has been observed in wetlands comprises of Manchar Lake, Keenjhar Lake, and Chotiari Reservoir in Pakistan over the last four decades from 1972 to 2020. Each wetland has been categorized into four LULC classes; water, natural vegetation, agriculture land, and dry land. Multitemporal Landsat satellite data including; Multi-Spectral Scanner (MSS), Thematic Mapper (TM), and Operational Land Imager (OLI) images were used for LULC changes evaluation. The Supervised Maximum-likelihood classifier method is used to acquire satellite imagery for detecting the LULC changes during the whole study period. Soil adjusted vegetation index technique (SAVI) was also used to reduce the effects of soil brightness values for estimating the actual vegetation cover of each study site. Results have shown the significant impact of human activities on freshwater resources by changing the natural ecosystem of wetlands. Change detection analysis showed that the impacts on the land cover affect the landscape of the study area by about 40% from 1972 to 2020. The vegetation cover of Manchar Lake and Keenjhar Lake has been decreased by 6,337.17 and 558.18 ha, respectively. SAVI analysis showed that soil profile is continuously degrading which vigorously affects vegetation cover within the study area. The overall classification accuracy and Kappa statistics showed an accuracy of >90% for all LULC mapping studies. This work demonstrates the LULC changes as a critical monitoring basis for ongoing analyses of changes in land management to enable decision-makers to establish strategies for effectively using land resources.

scholarly journals A Modified Bare Soil Index to Identify Bare Land Features during Agricultural Fallow-Period in Southeast Asia Using Landsat 8

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 231
Author(s):  
Can Trong Nguyen ◽  
Amnat Chidthaisong ◽  
Phan Kieu Diem ◽  
Lian-Zhi Huo
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Urban Areas ◽  
Near Infrared ◽  
Urban Landscape ◽  
Bare Soil ◽  
Critical Element ◽  
Landsat 8 ◽  
Climate Conditions ◽  
Fallow Period

Bare soil is a critical element in the urban landscape and plays an essential role in urban environments. Yet, the separation of bare soil and other land cover types using remote sensing techniques remains a significant challenge. There are several remote sensing-based spectral indices for barren detection, but their effectiveness varies depending on land cover patterns and climate conditions. Within this research, we introduced a modified bare soil index (MBI) using shortwave infrared (SWIR) and near-infrared (NIR) wavelengths derived from Landsat 8 (OLI—Operational Land Imager). The proposed bare soil index was tested in two different bare soil patterns in Thailand and Vietnam, where there are large areas of bare soil during the agricultural fallow period, obstructing the separation between bare soil and urban areas. Bare soil extracted from the MBI achieved higher overall accuracy of about 98% and a kappa coefficient over 0.96, compared to bare soil index (BSI), normalized different bare soil index (NDBaI), and dry bare soil index (DBSI). The results also revealed that MBI considerably contributes to the accuracy of land cover classification. We suggest using the MBI for bare soil detection in tropical climatic regions.

scholarly journals Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

2021 ◽  
Vol 18 (3) ◽  
pp. 1132
Author(s):  
Qijiao Xie ◽  
Qi Sun
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Planning ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
The Impact

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.

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