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

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

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

scholarly journals Cartographie De L’état Du Couvert Végétal Du Nord De La Côte D’ivoire À Partir D’images Satellites: Exemple De La Zone De Korhogo

2016 ◽  
Vol 12 (29) ◽  
pp. 204
Author(s):  
Avy StéphaneKoff ◽  
Abderrahman Ait Fora ◽  
Hicham Elbelrhiti
Keyword(s):  
Cote D'ivoire ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Côte D’Ivoire ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
The State ◽  
Cote D’Ivoire ◽  
Côte D'ivoire ◽  
Landsat Satellite

The purpose of this study is to determine the state of the vegetation cover in the region of Korhogo through remote sensing. Nowadays, the problem of desertification in the Sahel is serious. This could be explained by the phenomenon of climate change. We want to map the state of the vegetation cover in the study area. This study therefore focuses on the state of the vegetation cover in the region of Korhogo in northern Côte d’Ivoire. We will use one Landsat satellite image from December 16th 2000 and proceed with image processing. Processing techniques by the normalized difference vegetation index, the index armor and colorful composition 472. After these treatments in our pictures, we observe the behavior of vegetation. We can then get an overview of the vegetation in this area.

scholarly journals DETECTION AGRICULTURE DEGRADATION FOR THE SOUTH OF BAGHDAD CITY USING REMOTE SENSING DATA FOR YEARS 2010-2019

2020 ◽  
pp. 57-67
Author(s):  
Taif Adil DHAMIN ◽  
Ebtesam F. KHANJER ◽  
Fouad K. MASHEE
Keyword(s):  
Remote Sensing ◽  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Military Operations ◽  
The South ◽  
Water Index ◽  
Rs And Gis ◽  
Landsat Satellite

Recently, the develop of the science of remote sensing enabled humanity to achieve the accuracy and wide coverage for different natural phenomena, disasters and applications (such as desertification, rainstorms, floods, fires, sweeping torrents, urban planning, and even in military). The main aim of this study is monitoring, highlighting and assessing maps for the degradation of agriculture in the south areas of Baghdad governorate (Al-Rasheed, Al-Yusufiyah, Al-Mahmudiyah, Al-Latifiyah, and Al-Madaen). Based to several factors, including the economic, social and military operations, the area had suffer the lands degradation which led to agriculture retreating. Remote sensing and Geographic information system (GIS) was applied, using ArcGIS 10.4.1 to process, manage, and analysis datasets, beside field verification to estimate the severity assessment of a computerized land degradation. Two satellites were adapted Landsat5 TM+ and Landsat8 OLI/TIRS imageries to assess the extent of land degradation for the study area during the years (5th May 2010 and 2nd May 2019). Two indices used in this research are: The Normalized Difference Vegetation Index “NDVI”, and The Normalized Differential Water Index “NDWI”. The results showed that there is a clear spatial reduction in both NDVI and NDWI, where the NDVI reduced from 2461082400 m2 to 1552698000 m2, accounting for 89.67 and 56.57 percent, respectively, while the NDWI reduced from 14166000 m2 to 12053700 m2, accounting for 0.52, and 0.44 percent, respectively. Keywords: Agriculture Degradation, RS And GIS Techniques, Landsat Satellite Imagery, NDVI And NDWI.

scholarly journals CLASSIFYING AND MAPPING OF VEGETATED AREA IN AL- BAHA REGION, SAUDI ARABIA USING REMOTE SENSING. I. EXTENT AND DISTRIBUTION OF GROUND VEGETATED COVER CATEGORIES.

2020 ◽  
pp. 75-80
Author(s):  
Abdullah Saleh Al-Ghamdi
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Type ◽  
Regional Scale ◽  
Vegetation Indices ◽  
Vegetation Mapping ◽  
Primary Objective ◽  
High Density ◽  
Vegetation Density

Classifying and mapping vegetation is an important technical task for managing natural resources; the primary objective of the vegetation-mapping inventory is to produce high quality, standardized maps and associated data sets of vegetation. Satellite remote sensing has proven to be effective technology for mapping forest vegetation at the landscape to regional scale. In the remote sensing technique, vegetation density can be directly indicated by vegetation indices. Although there are several vegetation indices, the most widely used is the Normalized Difference Vegetation Index (NDVI), formulated by transforming raw satellite data into NDVI values, ranging from -1 to 1. NDVI enables the creation of images and other products that provide a rough measure of vegetation type, amount, and condition on land surfaces. The results show that medium to high density vegetation is mostly found in the central part of Al-Baha region separating the highlands and lowlands. The relationship study between NDVI and vegetation cover percentage in this study depicts an NDVI value of only 0.20–1.00, which indicates that vegetation covers over 60% of Al-Baha. This is probably because vegetation here may not only comprise trees but also other plant forms such as herbs and shrubs. However, only 862.5 km2 (7.7%) of Al-Baha is covered with medium-high density vegetation, found mainly at the 6 –15km width horizontal central belt (in the Al-Mandaq, Al-Baha, and south Baljurashi districts) along a high, foggy mountainous plateau. Conversely, about 65% of Al-Baha region has very low to no vegetation density; vegetation is found extensively in the Tihama low plain towards the Red Sea and in the north-eastern desert plain. This study has provided a comprehensive report on vegetation mapping in the Al-Baha region.

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 Fine-Scale NDVI Reconstruction Back to 1906 from Tree-Rings in the Greater Yellowstone Ecosystem

Forests ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1324
Author(s):  
Hang Li ◽  
Ichchha Thapa ◽  
James H. Speer
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Ring Width ◽  
Regime Shifts ◽  
Vegetation Density ◽  
Greater Yellowstone ◽  
Land Covers ◽  
Ecological Legacies ◽  
Landsat Satellite ◽  
Fine Resolution

Global warming and related disturbances, such as drought, water, and heat stress, are causing forest decline resulting in regime shifts. Conventional studies have combined tree-ring width (TRW) and the normalized difference vegetation index (NDVI) to reconstruct NDVI values and ignored the influences of mixed land covers. We built an integrated TRW-NDVI model and reconstructed the annual NDVI maps by using 622 Landsat satellite images and tree cores from 15 plots using point-by-point regression. Our model performed well in the study area, as demonstrated by significant reconstructions for 71.14% (p < 0.05) of the area with the exclusion of water and barren areas. The error rate between the reconstructed NDVI using the conventional approach and our approach could reach 10.36%. The 30 m resolution reconstructed NDVI images in the recent 100 years clearly displayed a decrease in vegetation density and detected decades-long regime shifts from 1906 to 2015. Our study site experienced five regime shifts, markedly the 1930s and 1950s, which were megadroughts across North America. With fine resolution maps, regime shifts could be observed annually at the centennial scale. They can also be used to understand how the Yellowstone ecosystem has gradually changed with its ecological legacies in the last century.

scholarly journals Biophysical Parameters and Actual Evapotranspiration of Bean Culture by Means of Remote Sensing

2019 ◽  
Vol 11 (13) ◽  
pp. 156 ◽  
Author(s):  
Allisson Lucas Brandão Lima ◽  
Roberto Filgueiras ◽  
Everardo Chartuni Mantovani ◽  
Daniel Althoff ◽  
Robson Argolo dos Santos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Simple Algorithm ◽  
Actual Evapotranspiration ◽  
Estimation Methods ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Biophysical Parameters

Agricultural irrigation is involved in an important chain that involves all sectors of the economy, either directly, by increasing food production, or indirectly, by withdrawing large amounts of fresh water. The relevance of this theme forces the search for alternatives to make water use as rational as possible. Evapotranspiration estimation methods based in remote sensing, such as the SAFER (Simple Algorithm for Evapotranspiration Retrieving) model, become extremely relevant in these scenarios, since it is possible to estimate this parameter in large scales. Therefore, the aim of this research was to apply the SAFER model in the estimation of bean crop actual evapotranspiration using Landsat-8 satellite image data. One of the parameters used as input in the SAFER model is the NDVI (Normalized Difference Vegetation Index), which presented a coefficient of determination (r&sup2;) equal to 0.80 when compared to the crop coefficient. The actual evapotranspiration (ETa) estimated by the SAFER model were compared to the FAO 56 model estimates for later correlation between the models. This information is expected to assist the producer in a better management of water resources used in irrigation. The correlation between the two models presented a relevant coefficient of determination (r2 = 0.73), representing the potential of the SAFER model in relation to the FAO model 56.

scholarly journals REMOTE SENSING METHOD FOR LAND COVER CHANGE MONITORING USING LANDSAT MULTI-TEMPORAL DATA (Case study: Tuy Duc and Dak Rap Districts, Dak Nong Province, Central Highlands of Vietnam)

2020 ◽  
Vol 12 (3) ◽  
pp. 357-365
Author(s):  
Hung TRINH ◽  
◽  
Tuyen VU ◽  
Bien TRAN ◽  
Trinh PHAM ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat Tm ◽  
Vegetation Coverage ◽  
Landsat 8 ◽  
Coverage Density ◽  
Central Highland ◽  
Landsat Satellite

In this study, vegetation coverage changes over a 30-year period for the Tuy Duc and Dak R’lap districts,Dak Nong province (central highland of Vietnam) were assessed using remote sensing and Geographic Information Systems (GIS) techniques. 03 Landsat satellite images,including Landsat TM February 13, 1990, Landsat TM February 22, 2005 and Landsat 8 January, 15 2020 were used to calculate the normalized difference vegetation index (NDVI), then assessed the changes in vegetation coverage density. The NDVI differencing method is also used as a change detection method and provides detailed information for monitoring changes in land cover in periods 1990 – 2005, 2005 – 2020 and 1990 – 2020. Analysis of the obtained results showed that the vegetation coverage declined sharply during 1990 – 2005 period,then the vegetation coverage has begun to recover in period 2005 – 2020. From the findings of this study, it can be easily concluded that the Tuy Duc and Dak R’lap areas has lost its valuable vegetation cover both qualitatively and quantitatively.

HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

2020 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Faradina Marzukhi ◽  
Nur Nadhirah Rusyda Rosnan ◽  
Md Azlin Md Said
Keyword(s):  
Oil Palm ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Soil Nutrient ◽  
Oil Palm Plantation ◽  
Sustainable Environment ◽  
Moisture Analysis ◽  
The Relationship

The aim of this study is to analyse the relationship between vegetation indices of Normalized Difference Vegetation Index (NDVI) and soil nutrient of oil palm plantation at Felcra Nasaruddin Bota in Perak for future sustainable environment. The satellite image was used and processed in the research. By Using NDVI, the vegetation index was obtained which varies from -1 to +1. Then, the soil sample and soil moisture analysis were carried in order to identify the nutrient values of Nitrogen (N), Phosphorus (P) and Potassium (K). A total of seven soil samples were acquired within the oil palm plantation area. A regression model was then made between physical condition of the oil palms and soil nutrients for determining the strength of the relationship. It is hoped that the risk map of oil palm healthiness can be produced for various applications which are related to agricultural plantation.

Sign in / Sign up

Export Citation Format

Share Document