scholarly journals Assessment of Gold Mining Impact on the Vegetation of Itagunmodi-Igun Drainage Basin, Southwestern Nigeria from 1972–2011: A Remote Sensing

2021 ◽  
Vol 4 ◽  
pp. 1-6
Author(s):  
Olawale Oluwafemi ◽  
Akinola Akinwumiju ◽  
Oluseyi Oladepo ◽  
Daniel Oladepo
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Input Data ◽  
Gold Mining ◽  
Vegetation Index ◽  
Drainage Basin ◽  
Southwestern Nigeria ◽  
Artisanal Mining ◽  
Mining Impact ◽  
Landsat 7

Abstract. A GIS-based Normalized Differential Vegetation Index (NDVI) was analyzed using space-based data between 1972 and 2011 as Input data. The result of the NDVI using Landsat 7 ETM+ shows clearly that the values range from 0.19 to −0.31. Mountains and highlands of the Itagunmodi-Igun area revealed stressed vegetation cover between 0.11 to −0.31. The NDVI was also performed on Landsat imageries of four different epoch: 1972, 1986, 2000, and 2010. Results showed that vegetation index ranged from −0.105 to 0.033, −0.25 to 0.480, −0.313 to 0.19 and −0.29 to 0.5 in 1972, 1986, 2000 and 2010 respectively. The analysis revealed that the study area experienced an increase in biomass between 1972 and 1986 but with some areas experiencing outright disappearance of vegetation as indicated by the lower bands of index values in 1972 (−0.105) and 1986 (−0.25). The result showed that the Basin experienced a rapid and significant increase in biomass between 2000 and 2010, as indicated by the lower bands of index values in 2000 (−0.291) and 2010 (0.5). The results of the NDVI in 1972 ranged from −0.105 to 0.033 while NDVI in 1986 ranged from −0.25 to 0.480 which indicated a significant increase in the vegetation index. The results of the NDVI in 2000 ranged from 0.291 to 0.5 also indicated a significant increase in the vegetation index. The study concluded that artisanal mining could cause land and vegetation degradation with consequent loss of biodiversity, ecological modification.

scholarly journals Modelling and Delineation of Hydrocarbon Micro - Seepage Prone Zones on Soil and Sediment in Ugwueme, South Eastern Nigeria with Soil Adjustment Vegetation Index (SAVI)

2020 ◽  
pp. 13-33
Author(s):  
Mfoniso Asuquo Enoh ◽  
Uzoma Chinenye Okeke ◽  
Needam Yiinu Barinua
Keyword(s):  
Remote Sensing ◽  
Image Classification ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Bare Soil ◽  
Landsat 8 ◽  
Landsat Images ◽  
Landsat 7 ◽  
Soil And Sediment

Remote Sensing is an excellent tool in monitoring, mapping and interpreting areas, associated with hydrocarbon micro-seepage. An important technique in remote sensing known as the Soil Adjusted Vegetation Index (SAVI), adopted in many studies is often used to minimize the effect of brightness reflectance in the Normalized Difference Vegetation Index (NDVI), related with soil in areas of spare vegetation cover, and mostly in areas of arid and semi–arid regions. The study aim at analyzing the effect of hydrocarbon micro – seepage on soil and sediments in Ugwueme, Southern Eastern Nigeria, with SAVI image classification method. To achieve this aim, three cloud free Landsat images, of Landsat 7 TM 1996 and ETM+ 2006 and Landsat 8 OLI 2016 were utilized to produce different SAVI image classification maps for the study.  The SAVI image classification analysis for the study showed three classes viz Low class cover, Moderate class cover and high class cover.  The category of high SAVI density classification was observed to increase progressive from 31.95% in 1996 to 34.92% in 2006 and then to 36.77% in 2016. Moderately SAVI density classification reduced from 40.53% in 1996 to 38.77% in 2006 and then to 36.96% in 2016 while Low SAVI density classification decrease progressive from 27.51% in 1996 to 26.31% in 2006 and then increased to 28.26% in 2016. The SAVI model is categorized into three classes viz increase, decrease and unchanged. The un – changed category increased from 12.32km2 (15.06%) in 1996 to 17.17 km2 (20.96%) in 2006 and then decelerate to 13.50 km2 (16.51%) in 2016.  The decrease category changed from 39.89km2 (48.78%) in 1996 to 40.45 km2 (49.45%) in 2006 and to 51.52 km2 (63.0%) in 2016 while the increase category changed from 29.57km2 (36.16%) in 1996 to 24.18 km2 (29.58%) in 2006 and to 16.75 km2 (20.49%) in 2016. Image differencing, cross tabulation and overlay operations were some of the techniques performed in the study, to ascertain the effect of hydrocarbon micro - seepage.  The Markov chain analysis was adopted to model and predict the effect of the hydrocarbon micro - seepage for the study for 2030.  The study expound that the SAVI is an effective technique in remote sensing to identify, map and model the effect of hydrocarbon micro - seepage on soil and sediment particularly in areas characterized with low vegetation cover and bare soil cover.

scholarly journals Análisis del efecto de variables ambientales en la estimación de la erosionabilidad (Factor K) = Analysis of the Effect of Environmental Variables on the Soil Erodibility Estimation (K Factor)

2018 ◽  
pp. 195
Author(s):  
Pedro Perez Cutillas ◽  
Gonzalo G. Barberá ◽  
Carmelo Conesa García
Keyword(s):  
Remote Sensing ◽  
Environmental Variables ◽  
Input Data ◽  
Vegetation Index ◽  
Mineralogical Composition ◽  
Soil Erodibility ◽  
Estimation Algorithms ◽  
K Factor ◽  
Remote Sensing Techniques

El objetivo principal de este trabajo se centra en la determinación y análisis de las variables ambientales que influyen en las divergencias de las estimaciones de erosionabilidad a partir de dos métodos, aplicando tres algoritmos de estimación del Factor K. La exploración de esta información permite conocer el peso que ejerce el origen de los datos de entrada a los modelos en el cómputo de erosionabilidad y qué importancia tiene en función del algoritmo elegido para la estimación del Factor K. Los resultados muestran que las pendientes, así como los índices de vegetación (NDVI) y de composición mineralógico (IOI) obtenidos mediantes técnicas de teledetección han   mostrado los valores de asociación más elevados entre ambos métodos.The main goal of this work is to determine and analyze the influence of environmental variables on the changes of two erodibility methods, through the application of three estimation algorithms of K Factor. The analysis of this information allows knowing the significance of the input data to the models in the erodibility estimation, and likewise the consequence of the algorithm selected for the estimation of K Factor. The results show that the slopes, as well as the vegetation index (NDVI) and the mineralogical composition index (IOI), generated both by remote sensing techniques, have shown the highest values of association between methods.

scholarly journals Spatial and temporal variation of vegetation cover in Al- Soudah area and its relationship to precipitation during the period (2014- 2018 AD) using remote sensing and geographic information systems: التباين المكاني والزمني للغطاء النباتي بمنطقة السودة وعلاقته بالتساقط خلال الفترة (2014- 2018م) باستخدام الاستشعار عن بعد ونظم المعلومات الجغرافية

2021 ◽  
Vol 5 (3) ◽  
pp. 107-87
Author(s):  
Fadi Abdullah alanazi, Yaser Rashed Alzannan, Faten Hamed Na Fadi Abdullah alanazi, Yaser Rashed Alzannan, Faten Hamed Na
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Geographic Information ◽  
Temporal Changes ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Changes ◽  
Modified Soil

Souda is one of the important regions in Saudi Arabia in terms of spatial and temporal changes in vegetation cover; It includes the National Park, which is a leading tourist destination and one of the most beautiful parks in it. by tracking the spatial and temporal changes of vegetation cover by integrating remote sensing and geographic information systems, through the application of the modified soil vegetation index MSAVI during the period (2014- 2018), it became clear the decrease in the quantity and density of vegetation cover in the area. Thus, the study concluded that this indicator is one of the best indicators that can be used to extract vegetation cover from satellite images.

Assessment of the State of the Territories of Closed Waste Disposal Facilities by Vegetation Indices

2021 ◽  
Vol 25 (9) ◽  
pp. 30-37
Author(s):  
N.N. Sliusar ◽  
A.P. Belousova ◽  
G.M. Batrakova ◽  
R.D. Garifzyanov ◽  
M. Huber-Humer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Waste Disposal ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Google Earth ◽  
The State ◽  
Landsat 8 ◽  
The Earth

The possibilities of using remote sensing of the Earth data to assess the formation of phytocenoses at reclaimed dumps and landfills are presented. The objects of study are landfills and dumps in the Perm Territory, which differed from each other in the types and timing of reclamation work. The state of the vegetation cover on the reclaimed and self-overgrowing objects was compared with the reference plots with naturally formed herbage of zonal meadow vegetation. The process of reclamation of the territory of closed landfills was assessed by the presence and homogeneity of the vegetation layer and by the values of the vegetation index NDVI. To identify the dynamics of changes in the vegetation cover, we used multi-temporal satellite images from the open resources of Google Earth and images in the visible and infrared ranges of the Landsat-5/TM and Landsat-8/OLI satellites. It is shown that the data of remote sensing of the Earth, in particular the analysis of vegetation indices, can be used to assess the dynamics of overgrowing of territories of reclaimed waste disposal facilities, as well as an additional and cost-effective method for monitoring the restoration of previously disturbed territories.

Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

ARCTIC ◽  
2009 ◽  
Vol 61 (1) ◽  
pp. 1 ◽  
Author(s):  
Gita J. Laidler ◽  
Paul M. Treitz ◽  
David M. Atkinson
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Response ◽  
Moisture Regime ◽  
Percent Cover ◽  
Multispectral Data ◽  
Arctic Vegetation

Arctic tundra environments are thought to be particularly sensitive to changes in climate, whereby alterations in ecosystem functioning are likely to be expressed through shifts in vegetation phenology, species composition, and net ecosystem productivity (NEP). Remote sensing has shown potential as a tool to quantify and monitor biophysical variables over space and through time. This study explores the relationship between the normalized difference vegetation index (NDVI) and percent-vegetation cover in a tundra environment, where variations in soil moisture, exposed soil, and gravel till have significant influence on spectral response, and hence, on the characterization of vegetation communities. IKONOS multispectral data (4 m spatial resolution) and Landsat 7 ETM+ data (30 m spatial resolution) were collected for a study area in the Lord Lindsay River watershed on Boothia Peninsula, Nunavut. In conjunction with image acquisition, percent cover data were collected for twelve 100 m × 100 m study plots to determine vegetation community composition. Strong correlations were found for NDVI values calculated with surface and satellite sensors, across the sample plots. In addition, results suggest that percent cover is highly correlated with the NDVI, thereby indicating strong potential for modeling percent cover variations over the region. These percent cover variations are closely related to moisture regime, particularly in areas of high moisture (e.g., water-tracks). These results are important given that improved mapping of Arctic vegetation and associated biophysical variables is needed to monitor environmental change.

scholarly journals Mapeamento e Quantificação da Cobertura Vegetal no Agreste Central de Pernambuco Utilizando Técnicas de Empilhamento e o NDVI (Mapping and Quantification of Vegetation Cover from Central Agreste Region of Pernambuco State Using NDVI Technique)

2011 ◽  
Vol 3 (3) ◽  
pp. 157
Author(s):  
Daniel Rodrigues Lira ◽  
Maria do Socorro Bezerra de Araújo ◽  
Everardo Valadares De Sá Barretto Sampaio ◽  
Hewerton Alves da Silva
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Digital Processing ◽  
Sparse Vegetation ◽  
New Sensors

O mapeamento e monitoramento da cobertura vegetal receberam consideráveis impulsos nas últimas décadas, com o advento do sensoriamento remoto, processamento digital de imagens e políticas de combate ao desmatamento, além dos avanços nas pesquisas e gerações de novos sensores orbitais e sua distribuição de forma mais acessível aos usuários, tornam as imagens de satélite um dos produtos do sensoriamento remoto mais utilizado para análises da cobertura vegetal das terras. Os índices de cobertura vegetal deste trabalho foram obtidos usando o NDVI - Normalized Difference Vegetation Index para o Agreste central de Pernambuco indicou 39,7% de vegetação densa, 13,6% de vegetação esparsa, 14,3% de vegetação rala e 10,5% de solo exposto. O NDVI apresentou uma caracterização satisfatória para a classificação do estado da vegetação do ano de 2007 para o Agreste Central pernambucano, porém ocorreu uma confusão com os índices de nuvens, sombras e solos exposto, necessitando de uma adaptação na técnica para um melhor aprimoramento da diferenciação desses elementos, constituindo numa recombinação de bandas após a elaboração e calculo do NDVI.Palavras-chave: Geoprocessamento; sensoriamento remoto; índice de vegetação. Mapping and Quantification of Vegetation Cover from Central Agreste Region of Pernambuco State Using NDVI Technique ABSTRACTIn recent decades, advanced techniques for mapping and monitoring vegetation cover have been developed with the advent of remote sensing. New tools for digital processing, the generation of new sensors and their orbital distribution more accessible have facilitated the acquisition and use of satellite images, making them one of the products of remote sensing more used for analysis of the vegetation cover. The aim of this study was to assess the vegetation cover from Central Agreste region of Pernambuco State, using satellite images TM / LANDSAT-5. The images were processed using the NDVI (Normalized Difference Vegetation Index) technique, generating indexes used for classification of vegetation in dense, sparse and scattered. There was a proportion of 39.7% of dense vegetation, 13.6% of sparse vegetation, 14.3% of scattered vegetation and 10.5% of exposed soil. NDVI technique has been used as a useful tool in the classification of vegetation on a regional scale, however, needs improvement to a more precise differentiation among levels of clouds, shadow, exposed soils and vegetation. Keywords: Geoprocessing, remote sensing, vegetation index

scholarly journals MONITORING DESERTIFICATION IN SOME REGIONS OF IRAQ USING GIS TECHNIQUES

2021 ◽  
Vol 52 (3) ◽  
pp. 620-625
Author(s):  
Y. K. Al-Timimi
Keyword(s):  
Remote Sensing ◽  
Environmental Economic ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Marked Decrease ◽  
Social Systems ◽  
Sand Dunes ◽  
Rate Of Increase ◽  
Remote Sensing Techniques

Desertification is one of the phenomena that threatening the environmental, economic, and social systems. This study aims to evaluate and monitor desertification in the central parts of Iraq between the Tigris and Euphrates rivers through the use of remote sensing techniques and geographic information systems. The Normalized difference vegetation index NDVI and the crust index CI were used, which were applied to two of the Landsat ETM + and OLI satellite imagery during the years 1990 and 2019. The research results showed that the total area of ​​the vegetation cover was 2620 km2 in 1990, while there was a marked decrease in the area Vegetation cover 764 km2 in 2019, accounting for 34.8% (medium desertification) and 10.2% (high desertification), respectively. Also, the results showed that sand dunes occupied an area of ​​767 km2 in 1990, while the area of ​​sand dunes increased to 1723 km2 in 2019, with a rate of 10.2%) medium desertification (and 22.9% (severe desertification), respectively. It was noted that the overall rate of decrease in vegetation cover was 21.33 km2year-1 while the overall rate of increase in ground erosion in the area is 10.99 km2year-1.

scholarly journals RELATIONSHIP OF SPECTRAL REFLECTANCE AND NDVI TO SOME SOIL PROPERTIES OF BRICKS FACTORIES SOILS IN NAHRAWAN AREA,BAGHDAD IRAQ

2019 ◽  
Vol 50 (3) ◽  
Author(s):  
R. K. Abdullatiff
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Spectral Reflectivity ◽  
Tigris River ◽  
The Difference ◽  
Remote Sensing Techniques ◽  
The One ◽  
Relationship Of

A study was conducted to investigate the effect of the brick industry on the environmental system of these project soils of the brick factories in Alnahrawan district. Remote sensing techniques was used to study the relationship between the spectral reflectivity and the vegetative index on the one hand and some surface soil characters of the project and to determine the variation in vegetation cover for the same area and for two different periods.Ten sites were selected to study spectral reflectivity under similar geomorphological conditions near the brickworks project in the Anahrawan district with an area of 10,000 hectares. Soil samples were taken from the surface and at a depth of 0-30 cm. Some chemical and physical characters of research soil were analyzed in the soil department laboratories, college of Agriculture, Baghdad University.Several satellite images taken from the satellite Land sat (ETM) 2013 and another from same satellite in 1990 T.M to determining the change between the two periods. After obtaining remote sensing data (reflectivity and vegetation index).the correlation analysis was carried out between these data. It was observed that the soil salinity values were decreased due to the drainage that the area was confined between the Tigris River and the Diyala tributary which leads to good natural drainage.The attached tables indicate that thedigital numbers of the soil sampling sites in 2013 are highly significant correlated, While some of the characters did not show the use of this region industrially. After calculating the difference between the two images to determine the change. A 100% change was observed and the vegetation cover was sharply reduced between the two images. as well as the extension of the land of empty land, although these lands are still suitable for agriculture.

scholarly journals Changes in vegetation cover on Stara planina: Towards sustainable management of ski resorts in sensitive areas

2015 ◽  
Vol 95 (2) ◽  
pp. 25-40 ◽  
Author(s):  
Ivan Potic ◽  
Marko Joksimovic ◽  
Rajko Golic
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Sustainable Management ◽  
Sustainable Forest Management ◽  
High Mountain ◽  
Landsat 8 ◽  
Mountain Areas ◽  
Ski Resorts ◽  
Landsat 7 ◽  
Multispectral Analysis

Tourism is an indicator and the consequence of the development of many countries. Among the priority areas of the tourism strategy are high mountain areas with complex ecosystems. Mountain tourism in Serbia, as well as continental country is one of the leading forms of tourism through various projects stimulated by the state. In the last ten years, build up and expand the ski slopes of Stara planina in eastern Serbia, leading to various, mostly negative changes in the environment. This paper analyzes the changes in the forest areas of the site Babin Zub in years 2000 and 2013, using satellite imagery (Landsat 7 and Landsat 8) and remote sensing software. We used unsupervised multispectral analysis resolution 30 m and obtained data on forest areas. The aim is to draw attention to the change of vegetation cover and degradation of forest areas. Following to the experiences of the world's ski resorts, the paper presents the opportunities and examples of restoration of ski runs, and sustainable forest management in the studied highland area.

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

<p>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 "Tenosique", 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.</p>

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