scholarly journals EVALUASI DINAMIKA KERENTANAN LINGKUNGAN BERDASARKAN KERAPATAN VEGETASI DI DAERAH ALIRAN SUNGAI TABUNIO

2021 ◽  
Vol 9 (3) ◽  
pp. 346
Author(s):  
Syarifuddin Kadir ◽  
Ichsan Ridwan ◽  
Wahyuni Ilham ◽  
Nurlina Nurlina
Keyword(s):  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Positive Impact ◽  
Green Revolution ◽  
Environmental Damage ◽  
Vegetation Density ◽  
Environmental Vulnerability ◽  
Density Analysis

A Watershed is an ecosystem whose first component consists of natural resources vegetation, land, water, and human resources. Tabunio watershed covering an area of 62,558.56 hectares consists of 10 sub-watersheds. The Normalized Difference Vegetation Index (NDVI) is used in vegetation density analysis. Vulnerability of environmental damage is the condition of a region that has the potential for environmental damage due to human activities and or activities that have the potential to cause environmental impacts.The purpose of vegetation density analysis is carried out for the evaluation of environmental vulnerability dynamics in Tabunio watershed, i.e: 1). Knowing changes in land cover; 2. Knowing the classification of vegetation density; 3. Determine efforts to increase vegetation density. The benefits of this analysis are to obtain directives that can have a positive impact on the control of flood suppliers' vulnerability and environmental vulnerability by determining forest and land rehabilitation techniques.Based on the results of mapping and analysis obtained: 1) changes in land cover in 2005-2020 are dominant in forest land cover, open land, settlements, plantations, swamp farming, shrubs, and mining; 2) Vegetation density in the upstream sub-watershed is dominated by the classification of dense and very tight vegetation density; 3) The green revolution of the upstream watershed is dominated for ecological purposes with dense and very close vegetation, the central part of the watershed is dominated for ecological, economic and social with tight vegetation, downstream green revolution watershed dominated for economic and social interests with dense and sparse vegetation

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 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 ANALISIS TINGKAT KEHIJAUAN HUTAN DAERAH PERTAMBANGAN SAWAHLUNTO DENGAN METODE NDVI BERDASARKAN CITRA LANDSAT TAHUN 2006-2016

2018 ◽  
Vol 3 (1) ◽  
pp. 37-46
Author(s):  
Bowo Eko Cahyono ◽  
Yazella Feni Frahma ◽  
Agung Tjahjo Nugroho
Keyword(s):  
Land Cover ◽  
Environmental Sustainability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Mining Area ◽  
Vegetation Density ◽  
Dense Vegetation ◽  
Value Range ◽  
Landsat Satellite

Abstrak Pembukaan lahan hutan yang dijadikan lokasi pertambangan merupakan salah satu kegiatan yang dapat merubah jenis tutupan lahan atau sering disebut dengan konversi lahan. Salah satu daerah yang telah mengalami konversi lahan tersebut adalah Sawahlunto. Konversi lahan yang tidak menggunakan prinsip kelestarian lingkungan dapat mengakibatkan banyak hal negatif misalnya degradasi atau penurunan kualitas hutan. Tujuan dari penelitian ini adalah melakukan analisis tingkat degradasi hutan daerah pertambangan Sawahlunto tahun 2006 sampai 2016. Penelitian ini menggunakan teknologi penginderaan jauh berbasis citra satelit landsat. Citra satelit landsat ini diklasifikasikan dengan metode Normalized Difference Vegetation Index (NDVI) berdasarkan kerapatan vegetasi. Kemudian hasil klasifikasi ini dibuat dalam bentuk pemetaan. Klasifikasi pertama dikategorikan menjadi dua yakni hutan dan non hutan. Hasil yang didapatkan dari penelitian ini menunjukkan bahwa terjadi perubahan tutupan lahan yang semula hutan menjadi non hutan meningkat sebesar 7,5% selama kurun waktu sepuluh tahun. Klasifikasi selanjutnya yakni berdasarkan enam kategori yakni vegetasi sangat rapat, rapat, cukup rapat, non vegetasi 1, 2 dan 3. Dari klasifikasi ini, juga terlihat perubahan nilai NDVI maksimum maupun minimumnya. Tahun 2006 memiliki kisaran nilai NDVI maksimum 0,71 dan tahun 2016 memiliki kisaran nilai NDVI maksimum 0,56. Hal ini mengidentifikasi bahwa tingkat kehijauan yang ada di daerah pertambangan Sawahlunto menurun. Kata Kunci : degradasi, hutan, landsat, ndvi, klasifikasi, Sawahlunto.  Abstract The clearing of forest land that is used as a mining site is one of the activities that can change the type of land cover or often called land conversion. One of the forest areas that convert the land is Sawahlunto. Conversion of land that does not use the principles of environmental sustainability can lead to many negative things one of which is the degradation. The purpose of this research is to analyze the level of forest degradation of Sawahlunto mining area in 2006 until 2016. This research uses a remote sen sing technology based on landsat satellite imagery. This landsat satellite image is classified by Normalized Difference Vegetation Index (NDVI) method based on vegetation density. Then the results of this classification is made in the form of mapping. The first classification is categorized into two namely forest and non forest. The results obtained from this study indicate that a change in land cover from forest to non-forest increased by 7.5% over a period of ten years. The next classification is based on six categories namely very dense vegetation, dense vegetation, fairly dense, non vegetation 1, 2 and 3. From this classification, also seen the change in NDVI maximum and minimum value. The year 2006 has a maximum NDVI value range of 0.71 and 2016 has a maximum NDVI value range of 0.56. This identifies that the existing greenness in the mining area of Sawahlunto is decreasing.  Keyword : degradation, forest, landsat, ndvi, classification, Sawahlunto.

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 APPLICATION OF REMOTE SENSING AND GIS FOR ASSESSING LAND COVER RESOURCES VARIABILITY IN THE SELOUS GAME RESERVE, TANZANIA

2017 ◽  
Vol 1 (2) ◽  
pp. 74
Author(s):  
Phillip W. Mambo ◽  
John E. Makunga
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing And Gis ◽  
Vegetation Density ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Game Reserve ◽  
Year 2000

Purpose: The study was conducted in Selous Game Reserve, with intention of developing GIS and Remote Sensing based wildlife management system in the protected area.Methodology: All habitats were digitised using ArcGIS9.3 in which five scenes of Landsat TM and ETM+ digital images were acquired during dry seasons of the year 2000 and 2010. Band 3 and 4 of the Landsat images were used for calculation of normalized difference vegetation index (NDVI) for determination of vegetation spatial distributionResults: The NDVI maps of year 2000 to 2010 revealed the vegetation density depletion from 0.72 (obtained in 0.46─0.72 value interval and covering 46.5% pixel area) in 2000 as compared to 0.56 ( found in 0.38─0.56 value interval and covering 8.04% pixel area) in 2010 NDVI maps.Unique contribution to theory, practice and policy: It was recommended that there was a necessity to integrate applications of remote sensing and GIS techniques for the assessment and monitoring of the natural land cover variability to detect fragmentation and loss of wildlife species.

scholarly journals THE GEO-SPATIAL APPROACH TO DETECT THE CHANGE IN VEGETATION AND LAND SURFACE TEMPERATURE (LST) AFTER FORMATION OF ROHINGYA SETTLEMENTS IN BANGLADESH

2021 ◽  
Vol 12 (2) ◽  
pp. 288-241
Author(s):  
Mahdi Mansur Mahi ◽  
Md. Shahriar Sharif ◽  
Rhyme Rubayet Rudra ◽  
Md. Nazmul Haque
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Tree Plantation

The goal of this study is to examine the effects of Rohingya Influx specially on vegetation land cover and LST in Teknaf Peninsula, Cox’s Bazar, Bangladesh over time. For doing so, the research followed three steps. Firstly, the primary and secondary data were collected from prescribed sources like LANDSAT 8 images from Earth Explorer (USGS) and the Shapefiles were collected from secondary sources. Then, Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) functions are explored in geospatial environment to assess the effect of deforestation on the region. Finally, A correlation is shown between LST and NDVI for making a decision from the environmental perspective. The findings state that, the region around the Rohingya Camps progressively lost its vegetation density as a result of increasing deforestation. According to this analysis, there was 87.87 % vegetation cover in 2013, which gradually decreased before the Rohingya Invasion in 2017. After the incident in 2018, vegetation cover drops to 75.67 %. Similarly, area with no vegetation increased more rapidly than others. The outcome showed that the transition in land cover was quicker and more noticeable in recent time. As a result, the LST has been increasing over the years. According to the study, there were around 8.71 % of areas with high temperatures in 2013, which increased to 36.86 % in 2020. It indicates that a large quantity of vegetation has been lost as a result of deforestation, and the LST of this region has changed dramatically. Furthermore, data was examined by Union to assess the individual effect from 5 Rohingya camps, and it was discovered that the situation in Teknaf Union is terrible, while the situation in Baharchhara Union is comparably better. Finally, the results of the research encourage an extensive regional environmental policy to eradicate this problem. To recompense the loss of nature govt. and responsible department should take necessary steps like hill conservation or tree plantation.

scholarly journals Pemodelan Hujan Netto Berdasarkan Tutupan Lahan untuk Analisa Debit Aliran Rendah

2019 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Adhi Yanuar Avianta ◽  
Rispiningtati Rispiningtati ◽  
Lily Montarcih Limantara ◽  
Ery Suhartanto
Keyword(s):  
Land Cover ◽  
Field Study ◽  
Land Cover Change ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Canopy Interception ◽  
Volume Balance ◽  
Discharge Modeling

This research intends to investigate the land cover change and to obtain the canopy interception in the Lesti sub-watershed, and to produce the rainfall-discharge modeling as the function of net rainfall factor. The methodology consisted of identifying the land cover based on the Normalized Difference Vegetation Index (NDVI) classification of digital satellite images Landsat TM 7 and TM 8, carrying out the field study to obtain the canopy interception used a volume balance approach. The interception rate of Lesti sub-watershed are 5 – 7 % in everage of rainfall, the net-rainfall models of Lesti sub-watershed are Pnetto= P - (-1E07P² + 0.059P +0.260) for land clasification II and Pnetto = P – (-1E07P² + 0.199P + 0.16) for land clasification III, it used as the input on the rainfall-discharge modeling of F.J. Mock, the result showed that the use of net-rainfall on the rainfall-discharge modeling of F.J. Mock increased the accuracy of generated discharge which is strongly influenced by the proportional of land classification.

scholarly journals Assessing and Simulating Impacts of Land Use Land Cover Changes on Land Surface Temperature in Mymensingh City, Bangladesh

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Tahmid Anam Chowdhury ◽  
◽  
Md. Saiful Islam ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Land Use Land Cover ◽  
Remarkable Change

Urban developments in the cities of Bangladesh are causing the depletion of natural land covers over the past several decades. One of the significant implications of the developments is a change in Land Surface Temperature (LST). Through LST distribution in different Land Use Land Cover (LULC) and a statistical association among LST and biophysical indices, i.e., Urban Index (UI), Bare Soil Index (BI), Normalized Difference Builtup Index (NDBI), Normalized Difference Bareness Index (NDBaI), Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI), this paper studied the implications of LULC change on the LST in Mymensingh city. Landsat TM and OLI/TIRS satellite images were used to study LULC through the maximum likelihood classification method and LSTs for 1989, 2004, and 2019. The accuracy of LULC classifications was 84.50, 89.50, and 91.00 for three sampling years, respectively. From 1989 to 2019, the area and average LST of the built-up category has been increased by 24.99% and 7.6ºC, respectively. Compared to vegetation and water bodies, built-up and barren soil regions have a greater LST each year. A different machine learning method was applied to simulate LULC and LST in 2034. A remarkable change in both LULC and LST was found through this simulation. If the current changing rate of LULC continues, the built-up area will be 59.42% of the total area, and LST will be 30.05ºC on average in 2034. The LST in 2034 will be more than 29ºC and 31ºC in 59.64% and 23.55% areas of the city, respectively.

scholarly journals Land Cover Change Assessment of Vaal Harts Irrigation Scheme using Multi-temporal Satellite Sata

2013 ◽  
Vol 39 (4) ◽  
pp. 59-70 ◽  
Author(s):  
Fredrick Ao Otieno ◽  
Olumuyiwa I Ojo ◽  
George M. Ochieng
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Program ◽  
Land Use Land Cover ◽  
Irrigation Scheme ◽  
Multi Temporal

Abstract Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.

scholarly journals Impacts of temperature extremes on European vegetation during the growing season

2017 ◽  
Author(s):  
Lukas Baumbach ◽  
Jonatan F. Siegmund ◽  
Magdalena Mittermeier ◽  
Reik V. Donner
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Extreme Temperature ◽  
Terrestrial Ecosystems ◽  
Growing Season ◽  
Temperature Extremes ◽  
Minor Effect ◽  
European Continent

Abstract. Temperature is a key factor controlling plant growth and vitality in the temperate climates of the mid-latitudes like in vast parts of the European continent. Beyond the effect of average conditions, the timings and magnitudes of temperature extremes play a particularly crucial role, which needs to be better understood in the context of projected future rises in the frequency and/or intensity of such events. In this work, we employ event coincidence analysis (ECA) to quantify the likelihood of simultaneous occurrences of extremes in daytime land surface temperature anomalies and the normalized difference vegetation index (NDVI). We perform this analysis for entire Europe based upon remote sensing data, differentiating between three periods corresponding to different stages of plant development during the growing season. In addition, we analyze the typical elevation and land cover type of the regions showing significantly large event coincidences rates to identify the most severely affected vegetation types. Our results reveal distinct spatio-temporal impact patterns in terms of extraordinarily large co-occurrence rates between several combinations of temperature and NDVI extremes. Croplands are among the most frequently affected land cover types, while elevation is found to have only a minor effect on the spatial distribution of corresponding extreme weather impacts. These findings provide important insights into the vulnerability of European terrestrial ecosystems to extreme temperature events and demonstrate how event-based statistics like ECA can provide a valuable perspective on environmental nexuses.

Sign in / Sign up

Export Citation Format

Share Document