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 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 NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

scholarly journals LAND USE/LAND COVER CHANGES IN SEMI-ARID MOUNTAIN LANDSCAPE IN SOUTHERN INDIA: A GEOINFORMATICS BASED MARKOV CHAIN APPROACH

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 231-237 ◽  
Author(s):  
S. A. Rahaman ◽  
S. Aruchamy ◽  
K. Balasubramani ◽  
R. Jegankumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
Forest Cover ◽  
Normalized Difference Vegetation Index ◽  
Southern India ◽  
Vegetation Changes ◽  
Land Use Land Cover ◽  
Mountain Landscape ◽  
Semi Arid

Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.

scholarly journals Spatiotemporal Assessment of Vegetation Indices and Land Cover for Erbil City and Its Surrounding Using Modis Imageries

2017 ◽  
Vol 10 (1-2) ◽  
pp. 31-39 ◽  
Author(s):  
Shwan O. Hussein ◽  
Ferenc Kovács ◽  
Zalán Tobak
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Natural Vegetation ◽  
Visual Interpretation ◽  
Surrounding Areas ◽  
The Impact

Abstract The rate of global urbanization is exponentially increasing and reducing areas of natural vegetation. Remote sensing can determine spatiotemporal changes in vegetation and urban land cover. The aim of this work is to assess spatiotemporal variations of two vegetation indices (VI), the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), in addition land cover in and around Erbil city area between the years 2000 and 2015. MODIS satellite imagery and GIS techniques were used to determine the impact of urbanization on the surrounding quasi-natural vegetation cover. Annual mean vegetation indices were used to determine the presence of a spatiotemporal trend, including a visual interpretation of time-series MODIS VI imagery. Dynamics of vegetation gain or loss were also evaluated through the study of land cover type changes, to determine the impact of increasing urbanization on the surrounding areas of the city. Monthly rainfall, humidity and temperature changes over the 15-year-period were also considered to enhance the understanding of vegetation change dynamics. There was no evidence of correlation between any climate variable compared to the vegetation indices. Based on NDVI and EVI MODIS imagery the spatial distribution of urban areas in Erbil and the bare around it has expanded. Consequently, the vegetation area has been cleared and replaced over the past 15 years by urban growth.

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 A COMPARATIVE STUDY OF LAND SURFACE TEMPERATURE WITH DIFFERENT INDICES ON HETEROGENEOUS LAND COVER USING LANDSAT 8 DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 389-394 ◽  
Author(s):  
R. Bala ◽  
R. Prasad ◽  
V. P. Yadav ◽  
J. Sharma
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sensor Data ◽  
Landsat 8 ◽  
Temperature Relation

<p><strong>Abstract.</strong> The temperature rise in urban areas has become a major environmental concern. Hence, the study of Land surface temperature (LST) in urban areas is important to understand the behaviour of different land covers on temperature. Relation of LST with different indices is required to study LST in urban areas using satellite data. The present study focuses on the relation of LST with the selected indices based on different land cover using Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) data in Varanasi, India. A regression analysis was done between LST and Normalized Difference Vegetation index (NDVI), Normalized Difference Soil Index (NDSI), Normalized Difference Built-up Index (NDBI) and Normalized Difference Water Index (NDWI). The non-linear relations of LST with NDVI and NDWI were observed, whereas NDBI and NDSI were found to show positive linear relation with LST. The correlation of LST with NDSI was found better than NDBI. Further analysis was done by choosing 25 pure pixels from each land cover of water, vegetation, bare soil and urban areas to determine the behaviour of indices on LST for each land cover. The investigation shows that NDSI and NDBI can be effectively used for study of LST in urban areas. However, NDBI can explain urban LST in the better way for the regions without water body.</p>

scholarly journals Vegetation Cover Change and Its Diversity in Urban Areas of Medan

2021 ◽  
Author(s):  
Anita Zaitunah ◽  
Samsuri ◽  
Fauziah Sahara
Keyword(s):  
Land Cover ◽  
Environmental Quality ◽  
Vegetation Cover ◽  
Urban Areas ◽  
Open Space ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Change Analysis ◽  
Vegetation Class

Abstract Vegetation plays an important role in maintaining the environmental quality of urban areas. Increase in population and development of cities has led to land conversion with lesser vegetated areas. Land cover change analysis in urban areas is needed, especially for urban regional planning with green open space consideration. This research was conducted to analyze urban vegetation cover and its changes in two sub-districts of Medan between the years 1999 and 2019. Normalized difference vegetation index (NDVI) and change analysis were conducted in the research. The diversity of plant within this areas was observed. The results showed changes in vegetation cover areas in the mentioned years. In 1999, most of the areas were under a highly dense vegetation class while in 2019, they were under a low-density vegetation class. This indicates a decrease in vegetation cover due to changes to non-vegetation cover or land cover areas with less vegetation. There are a diverse of plants within the area such as paddy, cassava, corn etc and also many tree species. It is recommended to optimize the land by replanting in the area with no or less vegetation to maintain the environmental quality.

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 FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORING

2018 ◽  
Vol XLII-1 ◽  
pp. 155-160 ◽  
Author(s):  
M. Gašparović ◽  
D. Medak ◽  
I. Pilaš ◽  
L. Jurjević ◽  
I. Balenović
Keyword(s):  
Land Cover ◽  
Spatial Resolution ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Characteristics ◽  
Land Cover Classification ◽  
Vegetation Monitoring ◽  
Sentinel 2

<p><strong>Abstract.</strong> Different spatial resolutions satellite imagery with global almost daily revisit time provide valuable information about the earth surface in a short time. Based on the remote sensing methods satellite imagery can have different applications like environmental development, urban monitoring, etc. For accurate vegetation detection and monitoring, especially in urban areas, spectral characteristics, as well as the spatial resolution of satellite imagery is important. In this research, 10-m and 20-m Sentinel-2 and 3.7-m PlanetScope satellite imagery were used. Although in nowadays research Sentinel-2 satellite imagery is often used for land-cover classification or vegetation detection and monitoring, we decided to test a fusion of Sentinel-2 imagery with PlanetScope because of its higher spatial resolution. The main goal of this research is a new method for Sentinel-2 and PlanetScope imagery fusion. The fusion method validation was provided based on the land-cover classification accuracy. Three land-cover classifications were made based on the Sentinel-2, PlanetScope and fused imagery. As expected, results show better accuracy for PS and fused imagery than the Sentinel-2 imagery. PlanetScope and fused imagery have almost the same accuracy. For the vegetation monitoring testing, the Normalized Difference Vegetation Index (NDVI) from Sentinel-2 and fused imagery was calculated and mutually compared. In this research, all methods and tests, image fusion and satellite imagery classification were made in the free and open source programs. The method developed and presented in this paper can easily be applied to other sciences, such as urbanism, forestry, agronomy, ecology and geology.</p>

scholarly journals Spatio-temporal pattern of urban forest vegetation density, Medan Baru city, Indonesia

2021 ◽  
Vol 918 (1) ◽  
pp. 012021
Author(s):  
Samsuri ◽  
C A B Ginting ◽  
A Zaitunah ◽  
A Susilowati
Keyword(s):  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Forest ◽  
Vegetation Indices ◽  
Stand Density ◽  
Development Planning ◽  
Vegetation Density ◽  
Dense Vegetation ◽  
Spatio Temporal

Abstract The growth of urban areas and the population generally requires the guarantee of a healthy and comfortable environment. The expansion of physical developments and urban areas, year after year, can no longer support human existence. In Indonesia, the city should have at least 10% of its surface area committed to private urban forest and 20% for public urban forest. Jakarta is Indonesia’s largest city, and has only 9.98% urban forest coverage. Medan Baru city is facing the same issue, as it continues to grow year after year. The population requires a comfortable environment, which includes safe drinking water and clean, fresh air. As a result, vegetation is an important component of Medan Baru sub-district that offers numerous benefits. It is necessary to conduct research on the analysis of vegetation density in the Medan Baru, using vegetation indices such as Normalized Difference Vegetation Index (NDVI). The research aimed to analyze vegetation density change and mapping the vegetation density of Medan Baru city. The research found the largest area was relatively dense vegetation, about 262.00 hectares (47.87%). The research also found a decrease in urban forest quality, indicated by an increase in the sparse density class of 41.90 hectares and a decrease in the relative-dense vegetation class with 51.65 hectares. This reduction of vegetation density will reduce the urban forest quality by influencing urban forest capability in absorbing carbon dioxide and alleviating the oxygen productivity volume. Areas with lower stand density must be considered in future urban development planning. Moreover, decrease in vegetation density and urban forest area should be a primary consideration in Medan urban forest management.

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