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 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 ΑΞΙΟΛΟΓΗΣΗ TOY ΔΕΙΚΤΗ ΒΛΑΣΤΗΣΗΣ TVI ME ΤΗ ΣΥΝΔΡΟΜΗ ΤΗΣ ΘΕΩΡΙΑΣ ΠΙΘΑΝΟΤΗΤΩΝ

2004 ◽  
Vol 36 (3) ◽  
pp. 1338
Author(s):  
Γ. Αιμ. Σκιάνης ◽  
Δ. Βαϊόπουλος ◽  
Κ. Νικολακόπουλος
Keyword(s):  
Probability Theory ◽  
Standard Deviation ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Environmental Research ◽  
Theoretical Predictions ◽  
Landsat 7 ◽  
The Right ◽  
Western Greece

In the present paper the statistical behaviour of the Transformed Vegetation Index TVI is studied. TVI is defined by: (equation No1) - or, alternatively, by: (equation No2) u is the numerical value of the vegetation index, χ and y are the brightness values of the near infrared and red zones, respectively. Relation (1) defines the vegetation index TVI. Relation (2) defines the vegetation index TVI'. Using appropriate distributions to describe the histograms of χ and y channels, and taking into account certain theorems from probability theory, the expressions for the distributions of TVI and TVI' values are deduced. According to these expressions, the standard deviation of TVI image is larger than that of TVI', as well as NDVI (Normalized Difference Vegetation Index). The prevailing value of the TVI' histogram is located at the right part of the tonality range. Therefore, according to the mathematical analysis, the TVI image has a better contrast than that of the NDVI and TVI' images. The TVI' has a diffuse luminance. The theoretical predictions were tested with a Landsat 7 ETM image of Zakynthos Island (western Greece) and they were found to be in accordance with the satellite data. It was also observed that lineaments with a dark tonality are expressed more clearly in the TVI image than in the TVI' image. The general conclusion is that the TVI vegetation index is preferable from TVI', since the former produces images with a larger standard deviation and a better contrast than the latter. The results and conclusions of this paper may be useful in geological and environmental research , for mapping regions with a different vegetation cover.

scholarly journals A Long-term Spatial and Temporal Analysis of NDVI Changes in Java Island Using Google Earth Engine

2021 ◽  
Vol 936 (1) ◽  
pp. 012038
Author(s):  
Benedict ◽  
Lalu Muhamad Jaelani
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Data ◽  
Temporal Analysis ◽  
Google Earth ◽  
Vegetation Density ◽  
Angle Sensor ◽  
Study Results ◽  
Google Earth Engine

Abstract Java is Indonesia’s and the world’s most populous island. The increase in population on the island of Java reduces the area of forest and other vegetation covers. Landslides, floods, and other natural disasters are caused by reduced vegetation cover. Furthermore, it has the potential to lead to the extinction of flora and fauna. The Normalized Difference Vegetation Index (NDVI) can be used to monitor the vegetation cover. This study analyzes the NDVI changes value from 2005 to 2020 using Terra and Aqua MODIS image data processed using Google Earth Engine. Processing was carried out in some stages: down-setting, performing NDVI processing, calculating monthly average NDVI, calculating annual average NDVI, and analyzing. From the study results, the NDVI value of Terra and Aqua MODIS data has a solid but imperfect correlation coefficient due to differences in orbital time which causes differences in solar zenith angle, sensor viewing angle, and azimuth angle. Then from this study, it was found that overall, changes in vegetation density cover on the island of Java decreased, which was indicated by the NDVI decline rate of -0.00047/year. The most significant decrease in NDVI value occurred in the period 2015–2016, covering an area of 13994.630 km2, and the most significant increase in NDVI occurred in the period 2010–2011, covering an area of 2256.101 km2.

scholarly journals A Calculation and Compiling Models of Land Cover Quality Index 2019 uses the Geographic Information System in Pariaman City, West Sumatra Province, Indonesia

2019 ◽  
Vol 8 (3) ◽  
pp. 6406-6411
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Quality Index ◽  
Vegetation Index ◽  
Forest Cover ◽  
Normalized Difference Vegetation Index ◽  
Director General ◽  
Environmental Damage ◽  
Vegetation Density ◽  
Forest Region

The purpose of calculation and compiling the Land Cover Quality Index (LCQI) is to evaluate the value of natural and environmental resources based on land cover conditions in an administrative region such as city, regency and province in Indonesia referring to the Regulation Director General of Pollution Control and Environmental Damage Number P.1/PPKL/PKLA.4/2018. The analytical method used in the calculation of the Normalized Difference Vegetation Index (NDVI), the Maximum likelihood classification approach, and the preparation of LCQI calculation methods based on 1) sufficiency area (forest region) and forest cover at minimal 30% on rivers and islands; 2) Ability and suitability of land minimal 25%; and 3) a link with the direction of land use in urban areas of at minimal 30%. The results showed the vegetation density index value in Pariaman city was classified as a good category with a value of 0.474903 μm, the results of a land cover classification in Pariaman City with the largest region are found in mixed gardens land of 2,736.57 ha or 37%. Whereas the smallest region is found in cypress vegetation land as a greenbelt at the coastal border 12.06 ha or 0,16%. and the results of the LCQI calculation indicate the LCQI value in 2019 (24,06) which is in the alert classification (<50). The increase in land cover outside the forest region is mainly directed at increasing green open space because Pariaman City does not have natural forest which are vulnerable to changes in land cover because of its high population density

scholarly journals Green open space analysis in West Binjai, North Sumatra

2021 ◽  
Vol 886 (1) ◽  
pp. 012095
Author(s):  
A Zaitunah ◽  
Samsuri ◽  
Rojula ◽  
A. Susilowati ◽  
D. Elfiati ◽  
...  
Keyword(s):  
Open Space ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Dense Medium ◽  
Vegetation Density ◽  
Open Spaces ◽  
River Bank ◽  
Dense Class ◽  
North Sumatra

Abstract West Binjai is a sub-district located in Binjai City, North Sumatra. Green Open Space is also part of the Binjai city’s planning scheme which has many benefits for the community and the environment. This research used Normalized Difference Vegetation Index (NDVI) analysis and NDVI value classification results in the distribution of vegetation density. Analysis of changes in vegetation density was carried out between 2015 and 2020 in West Binjai. The largest change in the area of vegetation density classes in the West Binjai between 2015 and 2020 was the increase in the area of the high dense class to 19.13%. The sub-district has green open spaces in the form of sub-district parks, public cemeteries, road green lane, river bank and private green open spaces. These green open spaces were in the low dense, medium, dense and high dense classes. There is a need for rearrangement of green open spaces, especially those within low dense class. Replanting trees are also essential to increase the quality of the green area. Improving the quality of green space will lead to the enhancement of quality of environment.

scholarly journals HUBUNGAN ANTARA INDEKS VEGETASI NDVI (NORMALIZED DIFFERENCE VEGETATION INDEX) DAN KOEFISIEN RESESI BASEFLOW PADA BEBERAPA SUBDAS PROPINSI JAWA TENGAH DAN DAERAH ISTIMEWA YOGYAKARTA

2013 ◽  
Vol 2 (2) ◽  
Author(s):  
Bokiraiya Latuamury
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
River Flow ◽  
Image Interpretation ◽  
Low Flow ◽  
Vegetation Density ◽  
Significance Level ◽  
Aquifer Storage ◽  
Central Java ◽  
Recession Coefficient

The background of this research is the decrease of environment capacity in cacthment ecosystem, especially impact of vegetation forest on behavior streamflow. The indicators of cacthment destruction can be seen through hydrograph characteristics. Evaluation of cactment respons of flow hydrographic as an evaluation tools of river catchment responses becomes very important to analyze because it is a benchmark in determination several policy about flood, drough, sedimentation and landslide handling. The research purpose is to analyze the relationship between vegetation index NDVI (Normalized Difference Vegetation Index) and the characteristic of baseflow recession coefficient at several subcatchment areas in province of Central Java and Specific District of Yogjakarta.The method of this research is surveillance on data recording of AWLR (Automatic Water Level Recorder) and data of River Flow Measuring Stations in order to separate the baseflow by calibration curve, and image interpretation of Landsat ETM+ for the transformation of vegetation index (NDVI-Normalized Difference Vegetation Index).The analysis on recession coefficient data (Krb) and NDVI were correlated to analyze the strength of relationship between these two parameters. The results of statistical analysis on index NDVI and recession coefficient showsthat NDVI and recession coefficient value at R2 is 0.1427, F = 2.17 which is not significant at 1% significance level of 0.1646. The result shows a very weak correlation of 0.077 which mean that vegetation density (NDVI index)has a very weak control on low flows. Basically, river baseflow is a genetic component of river flow which comes from aquifer storage and/or other low flow sources. Thus, geology and soil have a significant effect on baseflow.

Analysis of change in vegetation cover linked to public policies, case study: Tenosique, Tabasco, Mexico.

2021 ◽  
Author(s):  
Jacob Nieto ◽  
Gabriela Vidal García ◽  
Mariana Patricia Jácome Paz ◽  
Tania Ximena Ruiz Santos ◽  
Juan Manuel Nuñez ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Agricultural Sector ◽  
Public Policies ◽  
Anthropogenic Activity ◽  
Time Range ◽  
Free Access ◽  
Ecological Processes ◽  
Landsat 7

&lt;p&gt;Currently, natural areas are being devastated by anthropogenic activity. Activities such as agriculture, illegal logging, non-organic farms, and livestock exploitation, disrupt an ecosystem that has been in balance for many years. Therefore, regulations implemented by governments are required for their preservation. However, these regulations are not always the most used in terms of conservation. Such is the case of the town &quot;Tenosique&quot;, in this area is one of the most important rivers in Mesoamerica, the Usumacinta River, which is a great regulator of ecological processes and is connected to Mexico with Guatemala. This site has been under the influence of regulations applied to the economic impulse of the area, whether for agricultural and livestock activities, which has affected the apparent vegetation cover, unlike Guatemala that has opted for regulations with a forest conservation approach. These policies sought to boost the agricultural sector, but many deforested areas to carry out this activity turned out not to be suitable due to the type of soil. With the change of regime, financing ends and with it economic activity decreases, leaving the area quite affected and the communities with financial problems. Recently, conservation and protection actions were implemented in the area together with support for these communities. The proximity between Mexico and Guatemala visually shows the results of the application of different public policies. The objective of this study is to quantify the loss and gain of vegetation over time from satellite images of the area, in order to compare this statistic with the different government programs of each era. For this, at least 10 multispectral satellite images of free access will be used, from the Landsat 7 satellite, which has 30 meters of resolution but visually adjustable to 15 meters with the union of its panchromatic channel, and that cover a time range from 1999 to 2020. On these, two processes will be carried out: 1) a normalized vegetation index calculation and 2) a supervised classification. With which it is intended to measure the area and the greenness of a mask of the vegetation cover. The results will serve to update the projects carried out on the site and detect areas of priority interest resolution for larger projects, as well as the future estimation of the critical state of the site regarding the loss of vegetation cover and quantify the conservation efforts that have been carried out. carried out from 2008 to the present.&lt;/p&gt;

Continued evolution of the Lower Mississippi: changes to fluvial islands over five decades (1965 to 2015)

2020 ◽  
Author(s):  
Paul Hudson
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Human Impacts ◽  
Landsat Imagery ◽  
Sediment Supply ◽  
Vegetation Density ◽  
The Past ◽  
Channel Engineering ◽  
Order Of Magnitude ◽  
Morphologic Evolution

&lt;p&gt;The lower Mississippi continues to adjust to upstream human impacts and channel engineering. Fluvial islands (vegetated sandy bars &gt; 1 ha) are a key mode of riverine adjustment along the Lower Mississippi, and have substantially increased in number and size over the past five decades, from 112 in 1965 to 295 by 2015, which can largely be attributed to groyne construction. This study examines the morphologic evolution of fluvial islands from Cairo, IL to the downstream-most island at about Bonnet Carre Spillway (~5 km upstream of New Orleans). The analysis utilizes lidar DEMs, historic air photos, and adjacent hydrologic (stage) data. Additionally, changes to island vegetation were examined by comparison of the Normalized Difference Vegetation Index (NDVI) calculated from analysis of Landsat imagery for 1996 with 2014.&lt;/p&gt;&lt;p&gt;While each island is somewhat unique and influenced by local scale factors, there are clear geomorphic differences between new islands and older islands. New islands (did not exist in 1965) do not have appreciable natural levees and the island high point is at about flood stage. Older islands that are stable and larger have formed natural levees, which are higher than average flood stage and often higher than the adjacent floodplain surface. The downstream slope of new islands is an order of magnitude higher than old islands, averaging 0.0028 m/m and 0.0009 m/m, respectively. This is likely attributed to the downstream growth of islands, increasing in length and aggradation on the downstream flank. Additionally, between 1996 and 2014 island vegetation matured, with the area of moderate vegetation decreasing at the expense of an increase in denser vegetation. A comparison of the NDVI for the same islands in 1996 and 2014 between Vicksburg and Red River Landing reveals an increase in vegetation health and density. While the area of islands classified as sandy (NDVI 0.1-0.2) and scrubby (NDVI 0.2-0.3) vegetation did not substantially change between 1996 and 2014, the amount of dense vegetation (NDVI &gt; 0.5) considerably increased (from 3.2 km&lt;sup&gt;2&lt;/sup&gt; to 9.8 km&lt;sup&gt;2&lt;/sup&gt;) as the amount of moderate vegetation (NDVI 0.3-0.5) decreased (15.1 km&lt;sup&gt;2&lt;/sup&gt; to 8.4 km&lt;sup&gt;2&lt;/sup&gt;). The increase in vegetation density can be attributed to the increased amount of time since island formation was initiated, and a maturation of the island surface with its geomorphic development.&lt;/p&gt;&lt;p&gt;The change to fluvial islands over the past five decades represents continued geomorphic evolution of the Lower Mississippi. This is of interest because, although it occurs during a period in which sediment supply has dramatically decreased, with the influence of channel engineering there remains sufficient coarse sediment to drive fluvial landform evolution along the Lower Mississippi.&lt;/p&gt;

scholarly journals Post-fire vegetation recovery in Portugal based on spot/vegetation data

2010 ◽  
Vol 10 (4) ◽  
pp. 673-684 ◽  
Author(s):  
C. Gouveia ◽  
C. C. DaCamara ◽  
R. M. Trigo
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Surface ◽  
Recovery Process ◽  
Vegetation Recovery ◽  
Fire Season ◽  
Burned Area ◽  
Vegetation Density ◽  
Fire Event ◽  
Central Portugal

Abstract. A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

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
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