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>

scholarly journals Analisis Perubahan Penggunaan Lahan Menggunakan Metode NDVI (Normalized Difference Vegetation Index) pada Kecamatan Natar, Kabupaten Lampung Selatan

2021 ◽  
Vol 2 (1) ◽  
pp. 17-22
Author(s):  
Fattur Rachman
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Sector ◽  
Land Conversion ◽  
Field Observations ◽  
Land Uses ◽  
Vegetation Density ◽  
Index Method ◽  
Landsat 7 ◽  
Open Land

Natar District is one of the districts in South Lampung Regency which has an area of 213.77 km2 or around 21,377 HA. In the agricultural sector, most of the land in Natar District is dominated by maize and paddy fields. This study aims to determine changes in land use in 2002, 2009 and 2019 in Natar District, South Lampung Regency. This study uses imagery from Landsat 7 and 8 processed in the NDVI (Normalized Difference Vegetation Index) method with the formula "NDVI = (NIR-RED) / (NIR + RED)". After processing the data, field observations were made to 30 sample points which were spread evenly throughout the Natar District. In this study, the results showed that land conversion to open land increased every year, on the other hand the area of land with low to moderate vegetation density decreased every year. In field observations, it was found that various land uses ranging from settlements, markets, and various uses for agricultural and plantation land.

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 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 Analysis of vegetation dynamics using the normalized difference vegetation index (NDVI) at the archipelago of Fernando de Noronha, Pernambuco, Brazil

2020 ◽  
pp. 885-901
Author(s):  
Kardelan Arteiro da Silva ◽  
Soraya Giovanetti El-Deir ◽  
José Jorge Monteiro Júnior ◽  
João Paulo de Oliveira Santos ◽  
Emanuel Araújo Silva
Keyword(s):  
State Government ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Plan ◽  
Landsat 8 ◽  
Conservation Policies ◽  
Management Plans ◽  
Landsat 7 ◽  
Fernando De Noronha

Island environments have specific biotic and abiotic characteristics, as fragility, limitation of natural resources, geographic isolation, and fragmentation are determining factors that directly affect these areas. Thus, it is relevant to understand the natural evolution of the landscape in the islands, considering the anthropic actions and climate changes in the transformation of vegetation cover, as a means of time series and study of satellite images. This paper aims to analyze the dynamics of the landscape (changes in vegetation cover) of the Fernando de Noronha Archipelago concerning urban development, and other anthropic activities that occurred between 1999 and 2018, through remote sensing images, to establish comparisons with the Island Management Plans that were elaborated in the years of 2005 and 2017. Also, this study intends to raise elements to assist in the spatial management of the Archipelago and to establish Public Conservation Policies for Fernando de Noronha and other island areas. Images from Landsat 7 and Landsat 8 were obtained for scenes from 1999 and 2017, respectively. These images were preprocessed and analyzed in Quantum GIS 2.18 software. And applied the NDVI calculation. It was also used the database found in the sustainable management plan of the archipelago provided by the state government of Pernambuco. With these data, it was possible to diagnose a vegetative growth on the island of about 45.36% in 17 years corroborating with the changes found in the data coming from the island's management plan. However, there are no changes in the phytosociological diversity of the island, this cause is pointed out to the invading and ruderals species of the island that are established and propagate.

scholarly journals Geospatial Analysis of Changes in Vegetation Cover over Nigeria

2017 ◽  
Vol 13 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Olutoyin Fashae ◽  
Adeyemi Olusola ◽  
Oluwatola Adedeji
Keyword(s):  
Information Technology ◽  
Markov Chain ◽  
Environmental Sustainability ◽  
Vegetation Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalised Difference Vegetation Index ◽  
Ecological Hazards ◽  
Spatio Temporal

AbstractVegetation cover over Nigeria has been on the decrease recently, hence the need for adequate monitoring using geo-information technology. This study examined the spatio-temporal variation of vegetation cover over Nigeria for thirty years with a view to developing a strategy for enhancing environmental sustainability. In order to predict the spatial extent of vegetation cover in 2030, the study utilised satellite images from between 1981 and 2010 using the Normalised Difference Vegetation Index (NDVI) coupled with cellular automata and Markov chain techniques in ArcGIS 10.3. The results showed that dense vegetal areas decreased in area from 358,534.2 km2in 1981 to 207,812 km2in 2010, while non-vegetal areas increased from 312,640.8 km2in 1981 to 474,436.4 km2in 2010 with a predicted increase to 501,504.9 km2by 2030, i.e. an increase of about 27,068.4 km2between 2010 and 2030. The study concluded that geoinformation techniques are effective in monitoring long-term intra- and inter-annual variability of vegetation and also useful in developing sustainable strategies for combating ecological hazards.

scholarly journals Analisa NDVI Citra Satelit Landsat Multi Temporal Untuk Pemantauan Deforestasi Hutan Kabupaten Aceh Utara

2017 ◽  
Vol 2 (1) ◽  
pp. 23
Author(s):  
Meraty Ramadhini ◽  
Bangun Muljo Sukojo
Keyword(s):  
Flood Control ◽  
Satellite Images ◽  
Vegetation Index ◽  
Water Infiltration ◽  
Vegetation Density ◽  
Landsat 7 ◽  
Multi Temporal ◽  
Production Forests ◽  
Forest Distribution

One of the functions of the forest is natural disaster such as flood control and the landslide that is how these forests absorb water into the root of the tree. Most forests in North Aceh Regency is protected forest which has undergone deforestation due to the presence of illegal logging and opening of new land like planting oil palm that impact against water infiltration. This research was conducted to identify deforestation forests in 2000, 2003 and 2015 using the techniques of remote sensing by satellite images landsat landsat 7 and 8. The method used was algorithm NDVI to get the classification of forest distribution and the level of deforestation forests based on the density of the vegetation from the Forestry Department 2003. Analysis of the rate of deforestation and loss of vast forests is done by leveraging the value of NDVI and other supporting data.The results showed that the NDVI value for forest distribution based on vegetation density in 2000 was -0,620438 � 0,628743, in 2003 between -0,364238 � 0,530055 and in 2015 between -0,274592 � 0,642049. The rate of deforestation in the district of North Aceh based on the value of the vegetation index (NDVI) yields 3 classes of deforestation are severe deforestation, light deforestation and not deforested, in 2000 there was deforestation of 25,62%, in 2003 it was 99,91% and in 2015 amounted to 15,89%, most deforestation occurs in production forests.

scholarly journals DYNAMICS OF GREEN SPACES IN ST. PETERSBURG ACCORDING TO REMOTE SENSING DATA

2021 ◽  
Vol 2 (6) ◽  
pp. 38-41
Author(s):  
D.K. Alexeev ◽  
◽  
A.V. Babin ◽  
V.Yu. Sargaeva
Keyword(s):  
Spatial Distribution ◽  
Quantitative Assessment ◽  
Satellite Images ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Green Spaces ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Landsat Satellite ◽  
The City

. Urban development is formulated as one of seventeen sustainable development goals for the near future. Among the whole range of environmental problems of a modern city, the issues of urban greening occupy a special place. In the course of the work, the analysis of the spatial distribution and assessment of the dynamics of green spaces on the territory of the city of St. Petersburg and its administrative-territorial units (inner-city districts) was carried out according to the data of multispectral satellite images Landsat 7 and Landsat 8 for the period 2002–2018. The normalized vegetation index (NDVI) was used for quantitative assessment. Maps of the spatial distribution of NDVI for the specified period were built. A decrease in the indicators of the provision of green spaces for the specified period for various districts of the city has been established. The obtained maps of the city’s vegetation cover, based on Landsat satellite images, provide a visual representation of the spatial distribution of landscaping indicators with the possibility of their quantitative assessment, and provide planning of landscaping facilities. The data obtained as a result of the work can supplement existing knowledge when carrying out work on process research and monitoring, as well as when making practical decisions

scholarly journals Detecção de Mudança da Vegetação de Caatinga (Change Detection of Vegetation Caatinga)

2013 ◽  
Vol 5 (6) ◽  
pp. 1473 ◽  
Author(s):  
Paulo Roberto Megna Francisco ◽  
Iêde De Brito Chaves ◽  
Lúcia Helena Garófalo Chaves ◽  
Eduardo Rodrigues Viana de Lima
Keyword(s):  
Change Detection ◽  
River Basin ◽  
Vegetation Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Dry Period ◽  
Caatinga Biome ◽  
Semi Arid

A caatinga é um bioma de grande diversidade que cobre a maior parte da área de clima semiárido brasileiro. Várias técnicas já foram utilizadas com o objetivo de determinar quantitativamente e qualitativamente o estado da vegetação a partir de imagens de satélite e índices de vegetação foram desenvolvidos para auxiliar no mapeamento da vegetação e otimizar os parâmetros presentes nas medidas multiespectrais utilizadas com esse fim. Este trabalho teve como objetivo mapear a vegetação da caatinga, e selecionar um índice de vegetação usando o IBVL para validação dos resultados e detectar mudanças ocorridas. Concluiu-se que o melhor índice que se correlaciona com a cobertura vegetal da caatinga foi o Normalized Difference Vegetation Index, do período seco, e que a metodologia utilizada mostrou-se eficiente para caracterização, classificação e separação em 9 classes. A maior recuperação ocorreu em áreas de drenagem e em declividade mais acentuada. A classe detectada de não mudança ocorreu em áreas de menor cobertura vegetal e de solos propensos à erosão. Estimou-se que 38,71% da área da bacia do rio Taperoá esteja em processo de desertificação.Palavras-chave: Semiárido, Geoprocessamento, Degradação. Change Detection of Vegetation Caatinga ABSTRACTThe caatinga biome is a large diversity that covers most of the area of Brazilian semi-arid climate. Several techniques have been used in order to determine quantitatively and qualitatively the state of vegetation from satellite images and vegetation indices were developed to assist in vegetation mapping and optimizing the parameters present in the multispectral measurements used for this purpose. This study aimed to map the vegetation of the caatinga, and select a vegetation index using IBVL to validate the results and detect changes. It was concluded that the best index that correlates with the vegetation of the caatinga was the Normalized Difference Vegetation Index, the dry period, and that the methodology used was efficient for characterization, classification and separation into nine classes. The best recovery occurred in areas of drainage and steeper slope. The class detected no change occurred in areas with less vegetation cover and soils prone to erosion. It was estimated that 20.21% of the area of the river basin Taperoá is in an advanced process of desertification.Keywords: Semiarid, Geoprocessing, Degradation.

scholarly journals REMOTE MONITORING OF ECOLOGICAL STATE OF OIL-PRODUCING AREAS OF TOMSK REGION

2020 ◽  
Vol 4 (2) ◽  
pp. 41-46
Author(s):  
Tatiana O. Peremitina ◽  
Irina G. Yashchenko
Keyword(s):  
Spatial Resolution ◽  
Satellite Data ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Western Siberia ◽  
Free Access ◽  
Environmental Status ◽  
Tomsk Region ◽  
Access To Data ◽  
Hydrocarbon Deposits

The article discusses the possibility of using satellite data to solve problems of monitoring the environmental status of oil producing territories in Western Siberia. The analysis includes MODIS satellite data of medium spatial resolution, which combine the advantages of free access to data and spatial resolution that is acceptable for detecting changes in the state of vegetation cover. The time series of the values of the vegetation index EVI (Enhanced Vegetation Index) of hydrocarbon deposits vegetation cover in the Tomsk Region: Archinsky, Shinginsky, Kazan, South Tabagansky and West Ostaninsky for the growing periods from 2007 to 2019 were calculated. The analysis of the dynamics of changes in the average values of the advanced EVI index allowed determining the minimum and maximum values of the index for the studied territories, as well as to identify trends in the increase of its values over a 10-year period.

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