scholarly journals Comparative Study on NDVI with RVI for Estimated Area and Class Distribution

2019 ◽  
Vol 3 (2) ◽  
pp. 12-20
Author(s):  
I Made Yuliara ◽  
Ni Nyoman Ratini ◽  
I Gde Antha Kasmawan
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Broad Class ◽  
Vegetation Distribution ◽  
Vegetation Analysis ◽  
Rare Class ◽  
Dense Class ◽  
Comparison Of The Results ◽  
Distribution Class ◽  
Area Data

This study aims to determine the differences and comparison of the results of the estimated area, the distribution of clove vegetation using the Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) and to choose a vegetation index that is more suitable for clove vegetation analysis in Buleleng district, Bali. The method used is to compare statistically descriptive area and distribution class produced by the NDVI and RVI models with area data from the Forestry and Plantation Service (FPS), Buleleng regency, Bali in 2014, amounting to 7622.32 ha. The estimated area of ??clove vegetation by the NDVI model was 7852.68 ha and the RVI model was 7669.44 ha. There is an estimated difference in the area of ??clove vegetation of 183.24 ha and a difference in the broad class category of 2453.85 ha for the Rare class (NDVI > RVI) category, for the Medium class of 1611.45 ha (RVI > NDVI), and for the Dense class of 659.16 ha (RVI > NDVI). Comparison of the area with FPS data obtained 97.07% for the NDVI model and 99.39% for the RVI model. This shows that the RVI model vegetation index is more suitable for use in the estimation of the area and class of clove vegetation distribution in Buleleng regency, Bali.

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 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 Vegetation density analysis using normalized difference vegetation index in East Jakarta, Indonesia

2021 ◽  
Vol 912 (1) ◽  
pp. 012053
Author(s):  
A Zaitunah ◽  
Samsuri ◽  
Y M H Marbun ◽  
A Susilowati ◽  
D Elfiati ◽  
...  
Keyword(s):  
Land Use Planning ◽  
Open Space ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Density ◽  
Entire Area ◽  
River Bank ◽  
Density Class ◽  
Dense Class

Abstract East Jakarta, which is included in the DKI Jakarta Province, continues to grow in population. As a result, the demand for settlement land increases. The presence of plants is critical for environmental equilibrium. The purpose of this study was to determine the vegetation density and its variations in East Jakarta year 2020. The method used the Normalized Difference Vegetation Index (NDVI) analysis and classification. In 2020, the highest NDVI value in East Jakarta was 0.1–0.2, covering 7,952.64 ha (43.07 %) of the entire area, while the lowest value was >0.6, covering 0.06 ha of the total area. The highest vegetation density class in East Jakarta was low dense class, accounting for 7,951.26 ha (43.06 percent) of the whole area, while the lowest density class was under high dense class accounted for 1,116.41 ha (6.04 percent) of the total area. In terms of green open space, there were a city park, a cemetery, a green lane on a road, and a river bank. The municipal park was classified as dense, while the rest were classified as medium dense. The presence of trees within the green space has aided in the area’s vegetation density. It also refers to the role of open green space in enhancing the community’s life and environment’s quality. The importance of educating and guiding the surrounding community about the benefits of vegetation or green open space, then replanting less vegetated land, as well as an integrated land use planning and implementation.The first section in your paper

scholarly journals Ecohydrological Optimality in Northeast China Transect

2017 ◽  
Author(s):  
Zhentao Cong ◽  
Qinshu Li ◽  
Kangle Mo ◽  
Lexin Zhang
Keyword(s):  
Water Balance ◽  
Optimality Theory ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Precipitation Amount ◽  
Canopy Cover ◽  
Sensitivity Analyses ◽  
Leaf Angle ◽  
Vegetation Distribution

Abstract. Northeast China Transect (NECT) is one of International Geosphere-Biosphere Program (IGBP) terrestrial transects., where there is a significant precipitation gradient from east to west, as well as a vegetation transition of forest-grasslands-dessert. It is interesting to understand vegetation distribution and dynamics under water limitation in this transect. We take canopy cover (M), derived from Normalized Difference Vegetation Index (NDVI), as an index to describe the properties of vegetation distribution and dynamics in NECT. In Eagleson's ecohydrological optimality theory, the optimal canopy cover (M*) is determined by the trade-off of water supply depending on water balance and water demand depending on canopy transpiration. We apply Eagleson’s ecohydrological optimality method in NECT based on data from 2000 to 2013 to get M*, then compare with M from NDVI, furthermore to discuss the sensitivity of M* to vegetation properties and climate factors. The result indicates that the average M* fits the actual M well (for forest, M* = 0.822 while M = 0.826 for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). The result of water balance also matches the field-measured data in references. The sensitivity analyses show that M* decreases with the increase of LAI, stem fraction, temperature, while increases with the increase of leaf angle and precipitation amount. The Eagleson's ecohydrological optimality method offers a quantitative way to understand the impacts of climate change to canopy cover quantitatively, and provides guidelines for eco-restoration projects.

scholarly journals Geospatial Effect on the Mining Operation in Joda/Barbil Area of Odisha, India

2021 ◽  
pp. 36-55
Author(s):  
Siba Prasad Mishra ◽  
Kamal Kumar Barik ◽  
Smruti Ranjan Panda
Keyword(s):  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Surface Air Temperature ◽  
Mining Operation ◽  
Landsat 8 ◽  
Mining Areas ◽  
Illegal Mining ◽  
Comparison Of The Results

The study aims to investigate the Geospatial effect on the extraction operation in Joda and Barbil mining areas of Keonjhar district, Odisha, India. Present work involves the topography, soil, climate, and stratigraphy investigation of the area. The acquisition of Landsat 8 TIRS (Thermal Infrared), Landsat 5 TM (Thematic Mapper), and CARTOSAT DEM data of temporal and spatial satellite images from various websites. ARC GIS and ERDAS IMAGINE 9.2 software used to find the land use and land cover images (accuracy average 90%). Normalized Difference Vegetation Index (NDVI), and Surface air Temperature (SAT) of Barbil area for 2003, 2007, 2017 and 2018 have been estimated. Comparison of the results have shown that, there is increase in built up, and mining areas whereas the agricultural land and vegetation cover are down scaled. There is constant average SAT rise of 1-2°C in all the land cover classification between 2007 and 2018. The NDVI values show conversion of sparse from dense vegetation in the area. Poor operational strategies in mines operation, like corruption, illegal mining, lack of accountability, overburden wastes/ trailing disposal, ecologic degradation, waterlogging in mine pits, and human rights violations are the root causes of environmental deterioration of the study area. It is pertinent to implement strictly, the Mines and Minerals (Development and Regulation) Amendment Act, India, 2021, regular GIS application to assess the mines volume of extraction, strict vigilance and fixation of accountability for losses of existing mines values, and afforestation/ reforestation of degraded/lost forests in Barbil area.

scholarly journals Application of Innovative Aerospace Technologies for Pastoral Farming of Sheeps

2019 ◽  
Vol 9 (1) ◽  
pp. 4584-4587
Keyword(s):  
Nutritional Value ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Age Groups ◽  
Complex Objects ◽  
Prognostic Assessment ◽  
Remote Assessment ◽  
Uav Images ◽  
The Many ◽  
Comparison Of The Results

Development of an innovative system of livestock husbandry based on the use of digital aerospace technologies and telemetry is a new modern direction in the development of the livestock industry, designed to solve the many problems of restoring fertility of soil and pasture for animals. To develop a methodology for remote assessment of pasture fertility, we used the technological capabilities of using unmanned aerial vehicles and satellite service, which allows us to study the dynamics of the NDVI (Normalized Difference Vegetation Index) of various pasture plots in the Stavropol Territory of the Russian Federation. The analysis of literary sources shows that the main problems associated with the complex automation of forecasting processes for complex objects are not technical, but methodological in nature and are caused by the lack of a theoretical base that should form the basis for creating the corresponding model and algorithmic support. A comparison of the results of a prognostic assessment of the nutritional value of fodder plants obtained from unmanned aerial vehicle (UAV) images, space services with actual nutritional values obtained from studies of the zoochemical composition of feeds showed a high degree of correlation. The UAV capabilities were recognized as promising for assessing the ethological characteristics of the Manych merino sheep, which allows to optimize the acquisition of groups of animals consolidated by forage activity. The article considers the issues of assessing the nutritional value of pasture feed and the vegetation index when raising sheep of the Jalgin merino breed in the conditions of the steppe regions of the Stavropol Territory. The introduction of remote assessment methods in pastoral livestock can optimize the cultivation of various sex and age groups of sheep and reduce the time to achieve production parameters by 5-8%.

scholarly journals Analysis of Land Cover Changing and Vegetation Index at Kuranji Watershed in Padang, West Sumatera, Indonesia

2019 ◽  
Vol 4 (4) ◽  
pp. 286-290
Author(s):  
Rifky Putera ◽  
Junaidi Junaidi ◽  
Ahmad Junaidi
Keyword(s):  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Density ◽  
Landsat Images ◽  
Sensing Technology ◽  
One Year ◽  
Dense Class ◽  
Topographic Condition

Various activities around Kuranji watershed included the land conversioncan be impacted to topographic condition and also contributed to altering the vegetation density. Remote sensing technology is an effective methodfor land cover mapping. The objectives of the present study were to analyze the changing of land cover and classifying the vegetation density index in the upstream Kuranji Watershed. This study was conducted at Kuranji Watershed in Padang, West Sumatera Province. Two Landsat images representing the changing of the watershed area during 2017 and 2018 as well as obtaining the classification of vegetation density during corresponding years.Landsat 8 OLI images were classified using a supervised classification technique, then computed the vegetation index using the Normalized Difference Vegetation Index (NDVI). The result showed that the extension of forest area, settlement area and paddy field (283.92; 35.06; and 27 Ha, respectively) and decline of mix dryland agriculture, shrub and garden area (93.68; 277.43; and 190.95 Ha respectively). Decreasing of dense vegetation found at lower dense class (6.47 Ha) and highest dense class (5535.35 Ha). Therefore, the increasing area found at the cloud, dense and higher dense class (93.17; 5525.1; and 109.94 Ha, respectively). So, it is highlighted that changing land cover and vegetation index happen during the only one-year period.

scholarly journals Investigation on Aneuk Laot Lake Water Depreciation Based on Distribution of Minor Fault with a Remote Sensing Method

2019 ◽  
Vol 8 (2) ◽  
pp. 47-54
Author(s):  
Nindi Yusifa ◽  
Aljikri Yanto ◽  
Shiyasatusy Sairiyyah ◽  
Muhammad Isa
Keyword(s):  
Remote Sensing ◽  
Lake Water ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Distribution ◽  
Vegetation Density ◽  
Fracture Density ◽  
Lake Water Level ◽  
Landsat Satellite

Danau Aneuk Laut berasal dari bekas kepundan gunungapi yang telah mati dan secara bertahap terisi air. Sejak 15 tahun belakangan ini danau mengalami penurunan muka air, hal ini diduga akibat Gempa dan tsunami pada 26 Desembar 2004. Pemantauan penyusutan air danau dilakukan dengan metode penginderaan jauh menggunakan data DEM SRTM dan citra satelit Landsat. DEM SRTM digunakan untuk analisis struktur sesar dan rekahan melalui peta Fault Fracture Density (FFD). Citra satelit landsat digunakan untuk identifikasi sebaran vegetasi menggunakan transformasi Normalized Difference Vegetation Index (NDVI) dan klasifikasi tutupan lahan menggunakan metode Maximum likelhood dari tahun 2001-2017. Berdasarkan peta FFD ditemukan kelurusan tertinggi yaitu danau Aneuk Laot yang memiliki zona permeabel dari struktur geologi sehingga semakin kecil kerapatan struktur maka semakin besar permeabilitasnya. Peta penyusutan air danau dengan menghitung luas permukaan air danau dari periode 2001 -2017 telah mengalami penurunan sebesar 102.600 m². Untuk tahun 2001-2003 mengalami kenaikan sebesar 68700 m² dan pada tahun 2003-2004 mengalami penurunan sebesar -42300 m². Peta sebaran vegetasi di pulau Weh memiliki index vegetasi NDVI maksimum 0,863554 yang artinya memiliki sebaran vegetasi sangat rapat berwarna hijau pekat dan Index vegetasi minimum NDVI sebesar -0,375631 menunjukkan tidak adanya rapat vegetasi berwarna coklat. Aneuk Laot Lake comes from the former crater of a volcano that has died and gradually filled with water. For about 15 years lakes have decreased Lake water level, allegedly caused by earthquake and tsunami on 26 desembar 2004. Monitoring of lake water depreciation is done by remote sensing method using DEM SRTM data and Landsat satellite image. DEM SRTM is used for analysis of fault and fracture structures through the Fault Fracture Density (FFD) map. Landsat satellite imagery was used to identify vegetation distribution using Normalized Difference Vegetation Index (NDVI) transformation and land cover classification using Maximum likelihary method from 2001-2017. Based on the FFD map found the highest alignment of the Aneuk Laot lake that has a permeable zone of geological structure so that the smaller the density of the structure the greater the permeability. Map of the lake's water depreciation by calculating the lake surface area from 2001 -2017 has decreased by 102,600 m². For 2001-2003 increased by 68700 m² and in 2003-2004 decreased by -42300 m². The vegetation distribution map on Weh island has a maximum NDVI vegetation index of 0.863554 having very dense green vegetation density and a minimum vegetation index of NDVI-0.375631 indicating the absence of a brown vegetation meeting. Keywords: AneukLaot lake, DEM SRTM, Landsat, FFD

scholarly journals Mapping mangrove distribution using remote sensing technology in Harapan, Kelapa and Pamegaran Seribu Islands National Park

2021 ◽  
Vol 944 (1) ◽  
pp. 012046
Author(s):  
B F Haikal ◽  
S B Susilo ◽  
S B Agus ◽  
R Z Oktavian
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rapid Development ◽  
Confusion Matrix ◽  
Mangrove Area ◽  
Remote Sensing Technology ◽  
Mangrove Ecosystems ◽  
Sensing Technology ◽  
Dense Class

Abstract The existence of mangrove ecosystems is increasingly threatened due to the rapid development of tourist destinations and the increasing number of residents in Harapan, Kelapa and Pamegaran island, so that monitoring of mangrove ecosystems is necessary. The purpose of the research is to map the distribution of mangroves using remote sensing technology in Harapan, Kelapa and Pamegaran island. The field survey was conducted on April 1-10, 2021, taking 189 sample points using a hemispherical photography method. The maximum likelihood classification method is used to classify mangrove and non-mangrove vegetation. Normalized Difference Vegetation Index (NDVI) is an algorithm used to calculate vegetation indexes from satellite imagery. The Sentinel-2A image was classified into 3 classes of mangrove density, namely dense, moderate, and rare density classes, with the dominant class being the dense class. The total mangrove area on Pamegaran Island in 2015 amounted to 1.81 ha and the total mangrove area in 2021 amounted to 2.97 ha. The area of mangrove distribution in Harapan and Kelapa Island in 2015 amounted to 4.1 ha and in 2021 amounted to 6.56 ha. Mangrove density classification accuracy test using confusion matrix showed an accuracy of 82.95%.

Pemetaan Pulau Kecil Gelasa Kabupaten Bangka Tengah

2019 ◽  
Vol 2 (1) ◽  
pp. 11-14
Author(s):  
Wahyu Adi
Keyword(s):  
Coral Reefs ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Interpretation ◽  
Vegetation Coverage ◽  
Small Island ◽  
Shallow Waters ◽  
Small Islands ◽  
Seagrass Beds ◽  
Cover Density

Pulau Kecil Gelasa merupakan daerah yang belum banyak diteliti. Pemetaan ekosistem di pulau kecil dilakukan dengan bantuan citra Advanced Land Observing Satellite (ALOS). Penelitian terdahulu diketahui bahwa ALOS memiliki kemampuan memetakan terumbu karang dan padang lamun di perairan dangkal serta mampu memetakan kerapatan penutupan vegetasi. Metode interpretasi citra menggunakan alogaritma indeks vegetasi pada citra ALOS yaitu NDVI (Normalized Difference Vegetation Index), serta pendekatan Lyzengga untuk mengkoreksi kolom perairan. Hasil penelitian didapatkan luasan Padang Lamun di perairan dangkal 41,99 Ha, luasan Terumbu Karang 125,57 Ha. Hasil NDVI di daratan/ pulau kecil Gelasa untuk Vegetasi Rapat seluas 47,62 Ha; luasan penutupan Vegetasi Sedang 105,86 Ha; dan penutupan Vegetasi Jarang adalah 34,24 Ha.   Small Island Gelasa rarely studied. Mapping ecosystems on small islands with the image of Advanced Land Observing Satellite (ALOS). Previous research has found that ALOS has the ability to map coral reefs and seagrass beds in shallow water, and is able to map vegetation cover density. The method of image interpretation uses the vegetation index algorithm in the ALOS image, NDVI (Normalized Difference Vegetation Index), and the Lyzengga approach to correct the water column. The results of the study were obtained in the area of Seagrass Padang in the shallow waters of 41.99 ha, the area of coral reefs was 125.57 ha. NDVI results on land / small islands Gelasa for dense vegetation of 47.62 ha; area of Medium Vegetation coverage 105.86 Ha; and the coverage of Rare Vegetation is 34.24 Ha.

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