scholarly journals IDENTIFIKASI PERUBAHAN KERAPATAN VEGETASI KOTA MANADO TAHUN 2001 SAMPAI 2015

2017 ◽  
Vol 19 (1) ◽  
pp. 65
Author(s):  
Nurlita Indah Wahyuni ◽  
Diah Irawati Dwi Arini ◽  
Afandi Ahmad
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Forage Crops ◽  
Area Change ◽  
Gis And Remote Sensing ◽  
Crown Density ◽  
Landsat 7 ◽  
The Impact

<p class="judulabstrakindo">                                                                 ABSTRAK</p><p class="judulabstrakindo">Kebutuhan manusia akan lahan di wilayah perkotaan menyebabkan perubahan fungsi lahan terutama pada area bervegetasi. Penelitian bertujuan untuk mengkaji perubahan kerapatan vegetasi tahun 2001 dan 2015 di Kota Manado serta pengaruhnya terhadap kualitas lingkungan. Penelitian dimulai dengan melakukan pengumpulan data citra satelit Landsat 7 tahun 2001 tanggal akuisisi 14 Februari 2001 dan Landsat 8 tanggal akusisi 25 Maret 2015, data-data pendukung lainnya yaitu peta administrasi kota Manado tahun 2010, peta rupa bumi kota Manado skala 1:50.000. Metode yang digunakan dalam penelitian ini adalah perbandingan nilai normalized difference vegetation index (NDVI) dengan kanal merah (red) dan infra merah dekat (NIR) yang sudah dikonversi ke nilai reflektan. Teknik analisis menggunakan Sistem Informasi Geografis (SIG) dan penginderaan jauh dengan menentukan kerapatan vegetasi dan diklasifikasikan menjadi kelas kerapatan. Hasil penelitian menunjukkan bahwa perbandingan kelas kerapatan antara 2001 dan 2015 sebagai berikut kelas tidak bervegetasi (air dan awan) mengalami peningkatan sebesar 14,29%, kelas tidak rapat (lahan kosong, pemukiman, bangunan, dan industri) mengalami peningkatan sebesar 42,56%, kelas cukup rapat (tegalan dan tumbuhan ternak) mengalami peningkatan sebesar 48,94%, kelas rapat (perkebunan, sawah kering, dan semak belukar) mengalami penurunan sebesar 68,46% dan kelas sangat rapat (hutan lebat) mengalami penurunan sebesar 314,07%. Selama kurun waktu 15 tahun penurunan areal bervegetasi di Kota Manado diperkirakan 10,57%. Perubahan areal bervegetasi di Kota Manado signifikan terjadi karena kegiatan reklamasi pantai menjadi lahan terbangun serta lahan kosong dan perkebunan menjadi perumahan. Dampak yang saat ini mulai dirasakan dengan adanya perubahan areal bervegetasi adalah peningkatan suhu dan polusi udara di wilayah perkotaan.</p><p class="katakunci"><strong>Kata kunci</strong>:Landsat, Normalized Difference Vegetation Index (NDVI), kerapatan, Kota Manado</p><p class="judulabstraking"><strong><em>                                                                           ABSTRACT</em></strong></p><p class="judulabstraking"><em>Human demand on urban land has brought various impacts toward land use, one of them is vegetation area change. This study aims to identify vegetation density change between period 2001 and 2015 in Manado area along with its influence toward environment quality. The data was collected from Landsat 7 imagery with acquisition date on February 14<sup>th</sup> 2001 and Landsat 8 imagery with acquisition date on March 25<sup>th</sup> 2015. Supporting data i.e. administrative map of Manado City in 2010 and basic map of Manado in scale 1:50.000. We compared normalized difference vegetation index (NDVI) between red band and near infra red (NIR) band. Geographic Information System (GIS) and remote sensing techniques were used to determine and classify crown density of vegetation. The result showed that the density class comparison between 2001 and 2015 were: no vegetation (water body and cloud) increased 14,29%, low dense (bareland, residence, buildings and industry) increased 42,56%, moderately dense (garden and forage crops) increased 48,94%, dense (plantation, dry field and shrubs) decreased 68,46% and highly dense (forest) decreased 314,07%. In the period 15 years there was decreasing of vegetation area in Manado city 10,57% approximately. The significance change of Manado City was occurred due to coast reclamation into building area as well as bare land and plantation become residence. The impact of vegetation area change is the increasing of temperature and air pollution in urban area.</em></p><p><strong><em>Keywords</em></strong><em>: Landsat,</em><em> Normalized Difference Vegetation Index (NDVI)</em><em>, </em><em>density, Manado City</em><em></em></p>

scholarly journals Monitoring Sugarcane Growth Phases Based on Satellite Image Analysis (A Case Study in Indramayu and its Surrounding, West Java, Indonesia)

2019 ◽  
Vol 26 (3) ◽  
pp. 117
Author(s):  
Tri Muji Susantoro ◽  
Ketut Wikantika ◽  
Agung Budi Harto ◽  
Deni Suwardi
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Landsat 8 ◽  
Gas Field ◽  
Research Results ◽  
The Third ◽  
Third Phase ◽  
The Impact

This study is intended to examine the growing phases and the harvest of sugarcane crops. The growing phases is analyzed with remote sensing approaches. The remote sensing data employed is Landsat 8. The vegetation indices of Normalized Difference Vegetation Index (NDVI) and Enhanced Normalized Difference Vegetation Index (ENDVI) are employed to analyze the growing phases and the harvest of sugarcane crops. Field survey was conducted in March and August 2017. The research results shows that March is the peak of the third phase (Stem elonging phase or grand growth phase), the period from May to July is the fourth phase (maturing or ripening phase), and the period from August to October is the peak of harvest. In January, the sugarcane crops begin to grow and some sugarcane crops enter the third phase again. The research results also found the sugarcane plants that do not grow well near the oil and gas field. This condition is estimated due as the impact of hydrocarbon microseepage. The benefit of this research is to identify the sugarcane growth cycle and harvest. Having knowing this, it will be easier to plan the seed development and crops transport.

scholarly journals Analisis Perubahan Penggunaan Lahan Menggunakan Metode NDVI (Normalized Difference Vegetation Index) pada Kecamatan Natar, Kabupaten Lampung Selatan

2021 ◽  
Vol 2 (1) ◽  
pp. 17-22
Author(s):  
Fattur Rachman
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Sector ◽  
Land Conversion ◽  
Field Observations ◽  
Land Uses ◽  
Vegetation Density ◽  
Index Method ◽  
Landsat 7 ◽  
Open Land

Natar District is one of the districts in South Lampung Regency which has an area of 213.77 km2 or around 21,377 HA. In the agricultural sector, most of the land in Natar District is dominated by maize and paddy fields. This study aims to determine changes in land use in 2002, 2009 and 2019 in Natar District, South Lampung Regency. This study uses imagery from Landsat 7 and 8 processed in the NDVI (Normalized Difference Vegetation Index) method with the formula "NDVI = (NIR-RED) / (NIR + RED)". After processing the data, field observations were made to 30 sample points which were spread evenly throughout the Natar District. In this study, the results showed that land conversion to open land increased every year, on the other hand the area of land with low to moderate vegetation density decreased every year. In field observations, it was found that various land uses ranging from settlements, markets, and various uses for agricultural and plantation land.

scholarly journals Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity

2016 ◽  
Vol 185 ◽  
pp. 57-70 ◽  
Author(s):  
D.P. Roy ◽  
V. Kovalskyy ◽  
H.K. Zhang ◽  
E.F. Vermote ◽  
L. Yan ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Landsat 7

scholarly journals Soil erosion and sediment transport modelling using hydrological models and remote sensing techniques in Wadi Billi, Egypt

2021 ◽  
Author(s):  
O. Almasalmeh ◽  
Ahmed Adel Saleh ◽  
Khaldoon A. Mourad
Keyword(s):  
Sediment Transport ◽  
Soil Erosion ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Transport Modelling ◽  
Upland Erosion ◽  
Sediment Transport Modelling ◽  
Remote Sensing Techniques ◽  
The Impact

AbstractModelling soil erosion and sediment transport are vital to assess the impact of the flash floods. However, limited research works have studied sediment transport, especially in Egypt. This paper employs the HEC-HMS lumped hydrological model to predict the sediment load due to the flood event of 9th March 2014 in Wadi Billi, Egypt. The Modified USLE model has been used to calculate the total upland erosion, while Laursen-Copeland has been used to simulate load streams’ sediment transport potential. The Normalized Difference Vegetation Index (NDVI) has been applied over Landsat 8 image captured on 20th February 2014 using ArcMap 10.5 to determine the vegetation cover based on its spectral footprint. The resulted sedigraph showed accumulation of more than five thousand tons of sediments at the Wadi’s outlet. The results are crucial to design a suitable stormwater management system to protect the downstream urban area and to use flood water for groundwater recharge.

scholarly journals Multi-criteria modelling of drought: a study of Brandenburg Federal State, Germany

2021 ◽  
Author(s):  
Christopher Ihinegbu ◽  
Taiwo Ogunwumi
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Federal State ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Drought Assessment

AbstractDrought is the absence or below-required supply of precipitation, runoff and or moisture for an extended time period. Modelling drought is relevant in assessing drought incidence and pattern. This study aimed to model the spatial variation and incidence of the 2018 drought in Brandenburg using GIS and remote sensing. To achieve this, we employed a Multi-Criteria Approach (MCA) by using three parameters including Precipitation, Land Surface Temperature and Normalized Difference Vegetation Index (NDVI). We acquired the precipitation data from Deutsche Wetterdienst, Land Surface Temperature and NDVI from Landsat 8 imageries on the USGS Earth Explorer. The datasets were analyzed using ArcGIS 10.7. The information from these three datasets was used as parameters in assessing drought prevalence using the MCA. The MCA was used in developing the drought model, ‘PLAN’, which was used to classify the study area into three levels/zones of drought prevalence: moderate, high and extreme drought. We went further to quantify the agricultural areas affected by drought in the study area by integrating the land use map. Results revealed that 92% of the study area was severely and highly affected by drought especially in districts of Oberhavel, Uckermark, Potsdam-Staedte, and Teltow-Flaeming. Finding also revealed that 77.54% of the total agricultural land falls within the high drought zones. We advocated for the application of drought models (such as ‘PLAN’), that incorporates flexibility (tailoring to study needs) and multi-criteria (robustness) in drought assessment. We also suggested that adaptive drought management should be championed using drought prevalence mapping.

scholarly journals Modelling and Delineation of Hydrocarbon Micro - Seepage Prone Zones on Soil and Sediment in Ugwueme, South Eastern Nigeria with Soil Adjustment Vegetation Index (SAVI)

2020 ◽  
pp. 13-33
Author(s):  
Mfoniso Asuquo Enoh ◽  
Uzoma Chinenye Okeke ◽  
Needam Yiinu Barinua
Keyword(s):  
Remote Sensing ◽  
Image Classification ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Landsat 8 ◽  
Landsat Images ◽  
Landsat 7 ◽  
Soil And Sediment

Remote Sensing is an excellent tool in monitoring, mapping and interpreting areas, associated with hydrocarbon micro-seepage. An important technique in remote sensing known as the Soil Adjusted Vegetation Index (SAVI), adopted in many studies is often used to minimize the effect of brightness reflectance in the Normalized Difference Vegetation Index (NDVI), related with soil in areas of spare vegetation cover, and mostly in areas of arid and semi–arid regions. The study aim at analyzing the effect of hydrocarbon micro – seepage on soil and sediments in Ugwueme, Southern Eastern Nigeria, with SAVI image classification method. To achieve this aim, three cloud free Landsat images, of Landsat 7 TM 1996 and ETM+ 2006 and Landsat 8 OLI 2016 were utilized to produce different SAVI image classification maps for the study.  The SAVI image classification analysis for the study showed three classes viz Low class cover, Moderate class cover and high class cover.  The category of high SAVI density classification was observed to increase progressive from 31.95% in 1996 to 34.92% in 2006 and then to 36.77% in 2016. Moderately SAVI density classification reduced from 40.53% in 1996 to 38.77% in 2006 and then to 36.96% in 2016 while Low SAVI density classification decrease progressive from 27.51% in 1996 to 26.31% in 2006 and then increased to 28.26% in 2016. The SAVI model is categorized into three classes viz increase, decrease and unchanged. The un – changed category increased from 12.32km2 (15.06%) in 1996 to 17.17 km2 (20.96%) in 2006 and then decelerate to 13.50 km2 (16.51%) in 2016.  The decrease category changed from 39.89km2 (48.78%) in 1996 to 40.45 km2 (49.45%) in 2006 and to 51.52 km2 (63.0%) in 2016 while the increase category changed from 29.57km2 (36.16%) in 1996 to 24.18 km2 (29.58%) in 2006 and to 16.75 km2 (20.49%) in 2016. Image differencing, cross tabulation and overlay operations were some of the techniques performed in the study, to ascertain the effect of hydrocarbon micro - seepage.  The Markov chain analysis was adopted to model and predict the effect of the hydrocarbon micro - seepage for the study for 2030.  The study expound that the SAVI is an effective technique in remote sensing to identify, map and model the effect of hydrocarbon micro - seepage on soil and sediment particularly in areas characterized with low vegetation cover and bare soil cover.

scholarly journals ANALISIS VEGETASI DI TAMAN WISATA ALAM (TWA) SUNGAI DUMAI, RIAU

2021 ◽  
Vol 16 (1) ◽  
pp. 25-36
Author(s):  
Hanifah Ikhsani
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Vegetation Analysis ◽  
Landsat 8 Oli ◽  
Density Class ◽  
Vegetation Class ◽  
Do So

TWA Sungai Dumai is a tourist forest area and ensuring the preservation of natural potential. However, there are problems that can disrupt the sustainability of it, including forest and land fires and conversion of land use to agriculture and oil palm plantations. Until now, there is no vegetation analysis using satellite imagery in TWA Sungai Dumai, so it is important to do so that can be managed sustainably. This study  classification of vegetation density classes which are presented in the form of a vegetation density class map in it. This research uses Landsat-8 OLI / TIRS images from October 2017 and October 2020 which are processed to determine density class using Normalized Difference Vegetation Index algorithm. The vegetation density class with the highest area in 2017 was the vegetation density class (2380,832 ha or 66,819% of the total area), while the lowest area was the non-vegetation class (75,737 ha or 2,126% of the total area). The vegetation density class with the highest area in 2020 in TWA Sungai Dumai is dense vegetation density class (3205,039 ha or 89,950% of the total area), while the lowest area is non-vegetation class (1,637 ha or 0.046% of the total area)

scholarly journals EVALUATION OF THE POTENTIAL OF GREEN ROOFS APPLIED TO AN URBAN FABRIC USING GIS AND REMOTE SENSING DATA CASE OF THE NADOR CITY / MOROCCO

2022 ◽  
Vol XLVI-4/W3-2021 ◽  
pp. 177-184
Author(s):  
R. Lambarki ◽  
E. Achbab ◽  
M. Maanan ◽  
H. Rhinane
Keyword(s):  
Surface Area ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Plant Cover ◽  
Green Roofs ◽  
Living Environment ◽  
Green Spaces ◽  
Surface Model ◽  
Landsat 8 ◽  
Gis And Remote Sensing

Abstract. Accelerated urban growth has affected many of the planet's natural processes. In cities, most of the surface is covered with asphalt and cement, which has changed the water and air cycles. To restore the balance of urban ecosystems, cities must find the means to create green spaces in an increasingly gray world. Green spaces provide the city and its inhabitants a better living environment. This article uses Nador city as a case study area, this project consists in studying the possibility for the roofs to receive vegetation. The first axis of this project is the quantification of the current vegetation cover at ground level by calculating the Normalized Difference Vegetation Index (NDVI) based on Satellite images Landsat 8, then the classification of the LiDAR point cloud, and the generation of a digital surface model (DSM) of the urban area. This type of derived data was used as the basis for the various stages of estimating the potential plant cover at the roof level. In order to study the different possible scenarios, a set of criteria was applied, such as the minimum roof area, the inclination and the duration of the sunshine on the roof, which is calculated using the linear model of angstrom Prescott based on solar radiation. The study shows that in the most conservative scenario, 21771 suitable buildings that had to be redeveloped into green roofs, with an appropriate surface area of 369.26Ha allowing a 63,40% increase in the city's green space by compared to the current state contributing to the improvement of the quality of life and urban comfort. The average budget for the installation of green roofs in a building with a surface area of 100 m2 varies between 60000dh and 170000dh depending on the type of green roofs used, extensive or intensive. These results would enable planners and researchers in green architecture sciences to carry out more detailed planning analyzes.

scholarly journals Analysis of vegetation dynamics using the normalized difference vegetation index (NDVI) at the archipelago of Fernando de Noronha, Pernambuco, Brazil

2020 ◽  
pp. 885-901
Author(s):  
Kardelan Arteiro da Silva ◽  
Soraya Giovanetti El-Deir ◽  
José Jorge Monteiro Júnior ◽  
João Paulo de Oliveira Santos ◽  
Emanuel Araújo Silva
Keyword(s):  
State Government ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Plan ◽  
Landsat 8 ◽  
Conservation Policies ◽  
Management Plans ◽  
Landsat 7 ◽  
Fernando De Noronha

Island environments have specific biotic and abiotic characteristics, as fragility, limitation of natural resources, geographic isolation, and fragmentation are determining factors that directly affect these areas. Thus, it is relevant to understand the natural evolution of the landscape in the islands, considering the anthropic actions and climate changes in the transformation of vegetation cover, as a means of time series and study of satellite images. This paper aims to analyze the dynamics of the landscape (changes in vegetation cover) of the Fernando de Noronha Archipelago concerning urban development, and other anthropic activities that occurred between 1999 and 2018, through remote sensing images, to establish comparisons with the Island Management Plans that were elaborated in the years of 2005 and 2017. Also, this study intends to raise elements to assist in the spatial management of the Archipelago and to establish Public Conservation Policies for Fernando de Noronha and other island areas. Images from Landsat 7 and Landsat 8 were obtained for scenes from 1999 and 2017, respectively. These images were preprocessed and analyzed in Quantum GIS 2.18 software. And applied the NDVI calculation. It was also used the database found in the sustainable management plan of the archipelago provided by the state government of Pernambuco. With these data, it was possible to diagnose a vegetative growth on the island of about 45.36% in 17 years corroborating with the changes found in the data coming from the island's management plan. However, there are no changes in the phytosociological diversity of the island, this cause is pointed out to the invading and ruderals species of the island that are established and propagate.

scholarly journals Dinamika Suhu Permukaan dan Kerapatan Vegetasi di Kota Cirebon

2019 ◽  
Author(s):  
Moh. Dede ◽  
Millary Agung Widiawaty
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Open Space ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Significant Negative Correlation ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Vegetation Greenness ◽  
Industrial Estates

Increasing air temperature is the effects of global warming and vegetation reduced. In the urban area, significant increasing of air temperature rises urban heat island phenomenon which in the long term is able to change the microclimate. Estimation of land surface temperature (LST) and vegetation greenness are obtained from multi-temporal remote sensing satellite data. This study aims to analyze the dynamics of LST and vegetation greenness in Cirebon City. This study utilizes Landsat-5 TM and Landsat-8 OLI imagery data which are validated with MODIS data in 1998, 2008 and 2018. The LST value extracted using the radiative transfer equation, while vegetation density information is obtained by normalized difference vegetation index (NDVI). The interaction between LST and vegetation greenness is known through spatial correlation analysis. During 1998 to 2018, LST is increased of 1.18 oC, while high greenness vegetation area decreased reach 12.683 km2. This study also showed a significant negative correlation between LST and vegetation greenness in Cirebon City. The highest of LST distribution is concentrated in CBD, harbor, traffic jam zone, industrial estates, and terminals. Based on this study, the effort of LST management in the city needs the provision of green open space, green belt, and reforestation.

Sign in / Sign up

Export Citation Format

Share Document