scholarly journals LANDSAT-BASED DETECTION AND SEVERITY ANALYSIS OF BURNED SUGARCANE PLOTS IN TARLAC, PHILIPPINES USING DIFFERENCED NORMALIZED BURN RATIO (dNBR)

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 173-179 ◽  
Author(s):  
A. B. Baloloy ◽  
A. C. Blanco ◽  
B. S. Gana ◽  
R. C. Sta. Ana ◽  
L. C. Olalia
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The Philippines ◽  
Local Economy ◽  
Burn Severity ◽  
Burned Area ◽  
Landsat 8 ◽  
Potential Yield ◽  
Differenced Normalized Burn Ratio ◽  
Normalized Burn Ratio

The Philippines has a booming sugarcane industry contributing about PHP 70 billion annually to the local economy through raw sugar, molasses and bioethanol production (SRA, 2012). Sugarcane planters adapt different farm practices in cultivating sugarcane, one of which is cane burning to eliminate unwanted plant material and facilitate easier harvest. Information on burned sugarcane extent is significant in yield estimation models to calculate total sugar lost during harvest. Pre-harvest burning can lessen sucrose by 2.7% - 5% of the potential yield (Gomez, et al 2006; Hiranyavasit, 2016). This study employs a method for detecting burn sugarcane area and determining burn severity through Differenced Normalized Burn Ratio (dNBR) using Landsat 8 Images acquired during the late milling season in Tarlac, Philippines. Total burned area was computed per burn severity based on pre-fire and post-fire images. Results show that 75.38% of the total sugarcane fields in Tarlac were burned with post-fire regrowth; 16.61% were recently burned; and only 8.01% were unburned. The monthly dNBR for February to March generated the largest area with low severity burn (1,436 ha) and high severity burn (31.14 ha) due to pre-harvest burning. Post-fire regrowth is highest in April to May when previously burned areas were already replanted with sugarcane. The maximum dNBR of the entire late milling season (February to May) recorded larger extent of areas with high and low post-fire regrowth compared to areas with low, moderate and high burn severity. Normalized Difference Vegetation Index (NDVI) was used to analyse vegetation dynamics between the burn severity classes. Significant positive correlation, rho = 0.99, was observed between dNBR and dNDVI at 5% level (p = 0.004). An accuracy of 89.03% was calculated for the Landsat-derived NBR validated using actual mill data for crop year 2015-2016.

scholarly journals Mapping burned areas from landsat-8 imageries on mountainous region using reflectance changes

2018 ◽  
Vol 229 ◽  
pp. 04012
Author(s):  
Suwarsono ◽  
Hana Listi Fitriana ◽  
Indah Prasasti ◽  
Muhammad Rokhis Khomarudin
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Burned Area ◽  
Landsat 8 ◽  
Mountainous Region ◽  
Mountainous Regions ◽  
Burned Areas ◽  
Test And Evaluation ◽  
Normalized Burn Ratio ◽  
D Values

This research tried to detect a burned area that occurred in the mountainous region of Java Island. During this time, forest and land fires mostly occur in lowland areas in Sumatra and Kalimantan. However, it is possible that this phenomenon also occurs in mountainous regions, especially the mountainous regions of Java Island. The data used were Landsat-8, the latest generation of the Landsat series. The research location was on the Northeast slope of Mt. Ijen in East Java. The research methods include radiometric correction, data fusion, sample training retrieval, reflectance pattern analysis, Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) extraction, separability analysis, parameter selection for burned area detection, parameter test, and evaluation. The results show that ρ5 and NBRL parameter shows the highest values of D-values (most sensitive), to detect the burned area. Then, compared to ρ5, NDVI and NBRS, Normalized Burn Ratio long (NBRL) provide better results in detecting burned areas.

scholarly journals A Statistical and Spatial Analysis of Portuguese Forest Fires in Summer 2016 Considering Landsat 8 and Sentinel 2A Data

Environments ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 36 ◽  
Author(s):  
Ana Teodoro ◽  
Ana Amaral
Keyword(s):  
Forest Fires ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Burn Severity ◽  
Landsat 8 ◽  
Fire Event ◽  
Burned Areas ◽  
Area Burned ◽  
Sentinel 2A ◽  
Normalized Burn Ratio

Forest areas in Portugal are often affected by fires. The objective of this work was to analyze the most fire-affected areas in Portugal in the summer of 2016 for two municipalities considering data from Landsat 8 OLI and Sentinel 2A MSI (prefire and postfire data). Different remote sensed data-derived indices, such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR), could be used to identify burnt areas and estimate the burn severity. In this work, NDVI was used to evaluate the area burned, and NBR was used to estimate the burn severity. The results showed that the NDVI decreased considerably after the fire event (2017 images), indicating a substantial decrease in the photosynthesis activity in these areas. The results also indicate that the NDVI differences (dNDVI) assumes the highest values in the burned areas. The results achieved for both sensors regarding the area burned presented differences from the field data no higher than 13.3% (for Sentinel 2A, less than 7.8%). We conclude that the area burned estimated using the Sentinel 2A data is more accurate, which can be justified by the higher spatial resolution of this data.

scholarly journals FUZZY LOGIC BASED BURNED SEVERITY CLASSIFICATION AND MAPPING WITH LANDSAT-8 DATA

2019 ◽  
Vol XLII-2/W16 ◽  
pp. 259-265
Author(s):  
B. Valipour Shokouhi ◽  
M. Eslami
Keyword(s):  
Fuzzy Logic ◽  
Urban Infrastructure ◽  
Training Data ◽  
Burn Severity ◽  
Burned Area ◽  
Landsat 8 ◽  
Area Index ◽  
Average Accuracy ◽  
Multi Temporal ◽  
Normalized Burn Ratio

<p><strong>Abstract.</strong> Wildfire has a strong effect on both land use and land cover so that every year, thousands of hectares of forests, farms, and urban infrastructure are destroyed. Mapping and estimation of damages are crucial for planning and decision making. The aim of this study is classification and mapping burn severity using multi-temporal Landsat data and well-known burn severity indices including Normalized Burn Ratio (NBR) and Burned Area Index (BAI) calculated for pre- and post- Landsat 8 images. Subtracted images such as dNBR (Difference Normalized Burn Ratio), RBR (Relativized Burn Ratio) and dBAI (Difference Burned Area Index) were produced on the bases of indices as classification input. Among classification methods, the fuzzy supervised classification was utilized with three classes. The result shows the strong performance of the Fuzzy Logic system (FLS) in the detection of the area with the limited number of training data so that the average accuracy of the classes is 85%; plus, from the human logic perspective, the result was meaningful so that recognition of the features and changes visually were understandable.</p>

1984–2010 trends in fire burn severity and area for the conterminous US

2016 ◽  
Vol 25 (4) ◽  
pp. 413 ◽  
Author(s):  
Joshua J. Picotte ◽  
Birgit Peterson ◽  
Gretchen Meier ◽  
Stephen M. Howard
Keyword(s):  
Time Series ◽  
Vegetation Classification ◽  
Cumulative Distribution ◽  
Burn Severity ◽  
Burned Area ◽  
Detectable Change ◽  
Historical Trends ◽  
Differenced Normalized Burn Ratio ◽  
Normalized Burn Ratio ◽  
In Fire

Burn severity products created by the Monitoring Trends in Burn Severity (MTBS) project were used to analyse historical trends in burn severity. Using a severity metric calculated by modelling the cumulative distribution of differenced Normalized Burn Ratio (dNBR) and Relativized dNBR (RdNBR) data, we examined burn area and burn severity of 4893 historical fires (1984–2010) distributed across the conterminous US (CONUS) and mapped by MTBS. Yearly mean burn severity values (weighted by area), maximum burn severity metric values, mean area of burn, maximum burn area and total burn area were evaluated within 27 US National Vegetation Classification macrogroups. Time series assessments of burned area and severity were performed using Mann–Kendall tests. Burned area and severity varied by vegetation classification, but most vegetation groups showed no detectable change during the 1984–2010 period. Of the 27 analysed vegetation groups, trend analysis revealed burned area increased in eight, and burn severity has increased in seven. This study suggests that burned area and severity, as measured by the severity metric based on dNBR or RdNBR, have not changed substantially for most vegetation groups evaluated within CONUS.

scholarly journals Dinâmica de Queimadas no Município de Cuiabá-MT por Sensoriamento Remoto

2021 ◽  
Vol 14 (2) ◽  
pp. 607
Author(s):  
Noelto da Cruz Teixeira Da Cruz Teixeira ◽  
Victor Hugo de Morais Danelichen Hugo de Morais Danelichen
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Dynamics ◽  
Kernel Estimator ◽  
High Rate ◽  
Landsat 8 ◽  
Biological Potential ◽  
Erdas Imagine ◽  
Normalized Burn Ratio

O bioma Cerrado é uma das mais ricas fitofisionomias existentes no Planeta com destaque no elevado índice de ocupação humana direcionada à produção agropecuária. Apesar de seu potencial biológico enfrenta ameaças constantes de queimadas devido à conversão da vegetação em parcelas destinada a agricultura e pastagens. Neste contexto o objetivo deste trabalho é estudar a dinâmica espacial e temporal das queimadas no município de Cuiabá-MT, relacionando com as variáveis microclimáticas, classes de vegetação e declividades do terreno com o uso de recursos, de sensoriamento remoto. Foram utilizados os índices espectrais, NBR, NBR2 e NDVI extraídos das imagens Landsat 8 e focos de calor fornecido pelo Banco de Dados de Queimadas do INPE (Instituto Nacional de Pesquisas Espaciais) no período de 2013 a 2017. Os índices espectrais foram extraídos de 25 imagens referente a órbita 226 e ponto 071, utilizando o programa Erdas Imagine e os mapas de fogo através do estimador de Kernel presente no ArcGis 10.3 a fim de avaliar a distribuição e o padrão das queimadas na área proposta. Os resultados avaliados a partir do conjunto dos índices espectrais e dos mapas de estimativa de Kernel mostraram que o município de Cuiabá apresentou um padrão sazonal de queimadas, evidenciando maiores volumes de queimadas nas formações savânicas e nos terrenos de declividades da classe suave-ondulado em todo o período estudado.Palavras-chave: OLI, precipitação, padrão espacial. Dynamics of Fires in the Municipality of Cuiabá-MT by Remote Sensing A B S T R A C T The Brazilian Cerrado biome has several phytophysiognomies and a high rate of human occupation, with emphasis on agricultural production. Despite its biological potential, it faces constant threats of burning due to the conversion of vegetation into plots for agriculture and pasture. In this context, the objective of this work was to identify and relate the spatial and temporal dynamics of the fires in the municipality of Cuiabá-MT, with the microclimate variables, classes of vegetation and slopes of the land through the use of remote sensing resources. The spectral indexes NBR (Normalized Burn Ratio, NBR2 (Variation of Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) extracted from Landsat 8 images and heat sources provided by the INPE (Instituto Nacional de Space Research) from 2013 to 2017. The spectral indexes were extracted from 25 images referring to orbit 226 and point 071, using the Erdas Imagine program, and the fire maps of the Kernel estimator present in ArcGis 10.3 in order to evaluate the distribution and the pattern of fires in the proposed area. There was a 50.68% coincidence of the total number of hot spots on the reference burned areas, with a higher percentage of 72.12% in 2017 and lower in 2014 of 12.95%. These results made it possible to elaborate maps with a characteristic burning pattern and to highlight the classes most affected by fire throughout the studied period. Keywords: OLI, fire, spatial pattern.

scholarly journals Normalized difference vegetation index analysis of the first part impacted with the breaking of the Fundão Dam in Mariana-MG

2020 ◽  
Vol 24 ◽  
pp. e27
Author(s):  
Renan Valério Eduvirgem ◽  
Claudemir Rodrigues Soares ◽  
Elissandro Voigt Beier
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The United States ◽  
Local Economy ◽  
Vegetation Coverage ◽  
United States Geological Survey ◽  
Landsat 8 ◽  
Data Set ◽  
Mutual Cooperation ◽  
The Impact

This paper addresses the exploitation of mineral resources and suggests that an environmental management that meets a set of measures and mutual cooperation between public and private managers, civil society, and mining companies that exploit natural, renewable, and non-renewable resources is needed. Cooperation between managers and joint safety measures can prevent present and future accidents like the one that occurred in Mariana City in Minas Gerais State (MG). The questioning presented puts into discussion the disaster that occurred in Mariana City due to the rupture of the ore tailings dam (Fundão dam) in November 2015. With an estimated population of 60,000 inhabitants, Mariana City has a local economy directly linked to mining activities. Due to the impact caused by the rupture of the Fundão dam, both city and vegetation were destroyed, among other factors observed along the path followed by the tailings. However, what is discussed in this article with greater emphasis is the loss of vegetation in the watershed. The methodology compared the degree of vegetation coverage in the basin area through the analysis of the Normalized Difference Vegetation Index – NDVI for 2013, 2016, 2017, 2018, and 2019 in different months. Some images refer to August and other samples are from September, complementing the process through the use of Landsat 8 satellite images - OLI sensor, acquired from the United States Geological Survey (USGS) repository. 299 points were distributed in the quadrant to perform the analyses (n = 299). The level of significance was set at 5% with a 95% confidence, to ascertain and verify whether the data distribution is in an acceptable condition (dense or semi-dense vegetation cover). Regarding vegetation analysis, the Kolmogorov-Smirnov and Shapiro-Wilk tests were used. Both tests indicated a non-normal distribution for the NDVI data set, which indicates the absence of a vegetation index that was covered by the tailings, resulting in an area with large spaces without the coverage previously registered in 2013. We conclude that the vegetation suffered a drastic alteration provoked by the rupture of the Fundão dam which also led to homeless residents, negative impacts on the livelihood of the small farmers and fishermen, silting up of rivers and streams, death of several animal and plant species, and also affected the ecosystem and the local and regional biodiversity. 

scholarly journals Post-Fire Vegetation Recovery in Elwasita Area of Al-Jabal Al-Akhdar-Libya - Based on Remote Sensing Information

2021 ◽  
Vol 36 (4) ◽  
pp. 288-299
Author(s):  
Moussa J. Masoud
Keyword(s):  
Remote Sensing ◽  
Geographical Information Systems ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Severity ◽  
Geographical Information ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Landsat 8 ◽  
Landsat 8 Oli

Satellite-based remote sensing technologies and Geographical Information Systems (GIS) present operable and cost-effective solutions for mapping fires and observing post-fire regeneration. Elwasita wildfire, which occurred during April and May in 2013 in Libya, was selected as a study site. This study aims to monitor vegetation recovery and investigate the relationship between vegetation recovery and topographic factors by using multi-temporal spectral indices together with topographical factors. Landsat 8 (OLI and TIRS) images from different data were obtained which were for four years; April 2013, June 2014, July 2015, and July 2016, to assess the related fire severity using the widely-used Normalized Burn Ratio (NBR).  Normalized difference Vegetation Index (NDVI) was used to determine vegetation regeneration dynamics for four consecutive years. Also, the state of damage, vegetation recovery and, damage dimensions about the burned area were capable of being effectively detected using the result of supervised classification of Landsat satellite images. In addition, aspect, slope, and altitude images derived from Digital Elevation Model (DEM) were used to determine the fire severity of the study area. The results have found that it could be possible to figure out the degree of vegetation recovery by calculating the NDVI and NBR using Landsat 8 OLI and TIRS images. Analysis showed that it mainly oriented towards the northwest (47%), north (29%), and northeast (12%). The statistical analysis showed that fire was concentrated on the incline by 76%, and the most affected areas are those between 200 m-450 m above sea level, with a percentage of 80%. It is expected that the information can be acquired by various satellite data and digital forests. This study serves as a window to an understanding of the process of fire severity and vegetation recovery that is vital in wildfire management systems.

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses

2020 ◽  
Vol 12 (12) ◽  
pp. 2015 ◽  
Author(s):  
Manuel Ángel Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando José Aguilar ◽  
Dilek Koc-San ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Remote Sensing Techniques ◽  
Image Pairs ◽  
Study Sites ◽  
High Level ◽  
Sentinel 2

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.

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