scholarly journals Análise multitemporal da regeneração natural da candeia após ocorrência de incêndio florestal

2017 ◽  
Vol 12 (2) ◽  
pp. 192
Author(s):  
Ivy Mayara Sanches de Oliveira ◽  
Alex Donizeti Sales ◽  
Eduarda Martiniano de Oliveira Silveira ◽  
Fausto Weimar Acerbi Júnior ◽  
José Marcio De Mello
Keyword(s):  
Forest Fire ◽  
Natural Regeneration ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Minas Gerais ◽  
Landsat Tm ◽  
Fire Occurrence ◽  
Regeneration Pattern ◽  
Serra Do Cipó ◽  
Before And After

<p class="SemEspaamento1">Os sensores de satélites têm a capacidade de fornecer informações sobre regiões afetadas pela atividade do fogo, sendo uma ferramenta eficiente para a detecção e quantificação destas áreas. Objetivou-se avaliar o comportamento da regeneração natural da candeia <em>Eremanthus incanus </em>(Less.) Less<em>,</em> após a ocorrência de incêndio florestal por meio do índice de vegetação da diferença normalizada (NDVI) de forma a identificar a capacidade de resiliência da espécie. O incêndio ocorreu em 1999, ao lado do Parque Nacional da Serra do Cipó no município de Morro do Pilar, Minas Gerais. Foi selecionada uma série temporal de quatro imagens adquiridas entre os anos de 1999 a 2005 do satélite Landsat (TM e ETM<sup>+</sup>). Foram geradas as imagens NDVI e em seguida foram obtidos seus valores de reflectância nas diferentes datas para analisar o comportamento espectral das áreas em regeneração. Posteriormente esses parâmetros foram utilizados para analisar as alterações na cobertura vegetal. Ao comparar os valores de NDVI antes e pós-incêndio, observou-se que num período de 6 anos a candeia apresenta valores de reflectância próximos àqueles encontrados antes do incêndio, o que sugere que a cobertura vegetal está num estágio similar à antes da ocorrência do fogo. O índice aplicado mostrou-se eficiente na análise da capacidade de resiliência da espécie após o fogo.<strong> </strong></p><p align="center"><strong><em>Multitemporal analysis of natural regeneration of Candeia after occurrence of forest fire</em></strong></p><pre><strong>Abstract:</strong> Satellite sensors have the ability to provide information on areas affected by fire activity, being an efficient tool for detection and quantification of these areas. The aim of this study was to analyze the natural regeneration pattern of the <em>Eremanthus incanus </em>(Less.) Less, after the occurrence of forest fire, using the normalized difference vegetation index (NDVI) in order to identify its resilience capacity. The fire occurred in 1999, next to the Serra do Cipó National Park in Morro do Pilar city, Minas Gerais. A time series of four Landsat (TM e ETM</pre><sup>+</sup><pre>) images acquired between the years 1999-2005 were selected. The NDVI images were generated and their reflectance values were obtained at the different dates to analyze the spectral pattern of regenerating areas. Later, these parameters were used to analyze the vegetation cover changes. Comparing the NDVI values before and after the fire, it was observed that, over a period of 6 years the reflectance values were close to those found before the fire, which suggests that the vegetal cover is at a similar stage before the fire occurrence. The applied index proved to be efficient in the analysis of the species capacity of resilience after the fire occurrence.</pre><p><strong> </strong></p><br /><strong></strong>

scholarly journals Using UAV Multispectral Images for Classification of Forest Burn Severity—A Case Study of the 2019 Gangneung Forest Fire

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 1025 ◽  
Author(s):  
Jung-il Shin ◽  
Won-woo Seo ◽  
Taejung Kim ◽  
Joowon Park ◽  
Choong-shik Woo
Keyword(s):  
Forest Fire ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Accurate Method ◽  
Burn Severity ◽  
Spectral Angle Mapper ◽  
Before And After ◽  
Uav Images ◽  
Uav Image

Unmanned aerial vehicle (UAV)-based remote sensing has limitations in acquiring images before a forest fire, although burn severity can be analyzed by comparing images before and after a fire. Determining the burned surface area is a challenging class in the analysis of burn area severity because it looks unburned in images from aircraft or satellites. This study analyzes the availability of multispectral UAV images that can be used to classify burn severity, including the burned surface class. RedEdge multispectral UAV image was acquired after a forest fire, which was then processed into a mosaic reflectance image. Hundreds of samples were collected for each burn severity class, and they were used as training and validation samples for classification. Maximum likelihood (MLH), spectral angle mapper (SAM), and thresholding of a normalized difference vegetation index (NDVI) were used as classifiers. In the results, all classifiers showed high overall accuracy. The classifiers also showed high accuracy for classification of the burned surface, even though there was some confusion among spectrally similar classes, unburned pine, and unburned deciduous. Therefore, multispectral UAV images can be used to analyze burn severity after a forest fire. Additionally, NDVI thresholding can also be an easy and accurate method, although thresholds should be generalized in the future.

scholarly journals Variação Espacial e Temporal de NDVI na Lagoa do Peixe, RS (Spatial and Temporal Variation of NDVI in the Peixe Lagoon, RS)

2012 ◽  
Vol 4 (5) ◽  
pp. 897 ◽  
Author(s):  
Luana Portz ◽  
Laurindo Antonio Guasselli ◽  
Iran Carlos Stalliviere Corrêa
Keyword(s):  
Time Series ◽  
Temporal Variation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Analysis Data ◽  
Landsat Tm ◽  
Spatial And Temporal Variation ◽  
Rainfall Analysis ◽  
Ndvi Time Series ◽  
High Precipitation

Neste estudo foram analisadas as variações espaciais e temporais do Índice de Vegetação por Diferença Normalizada (NDVI) na lagoa do Peixe, no litoral do Rio Grande do Sul. Para alcançar o objetivo proposto foram utilizadas imagens de satélite Landsat TM5, entre os anos de 1986 e 2009, seguindo os procedimentos de elaboração de mosaico das cenas, verificação de campo, geração das imagens de NDVI, análise de dados de precipitação acumulada, geração dos mapas finais e análise qualitativa dos resultados obtidos. Os resultados obtidos com a geração de imagens de NDVI mostraram que a análise espaço-temporal associada aos dados de precipitação fornecem informações de valiosa importância sobre a dinâmica da lagoa do Peixe. A importância  do NDVI neste estudo se destaca pelo contraste existente entre água e vegetação, realçando os diferentes níveis de água sobre os bancos vegetados presentes na borda oeste da lagoa. Estes bancos são um importante controlador da dinâmica de circulação lagunar, onde em períodos de seca ocorre a compartimentação da lagoa, enquanto que em épocas de grande precipitação e acumulação de água estes bancos ficam submersos. Palavras-chave: Landsat TM, série temporal, Parque Nacional.  Spatial and Temporal Variation of NDVI in the Peixe Lagoon, RS  ABSTRACTThis paper analyzed the spatial and temporal variation of Normalized Difference Vegetation Index (NDVI) in the Peixe lagoon. To reach the purpose,  the NDVI time-series were collected from the study area between year 1986 and 2009 derived from Landsat TM5 satellite. The adopted methodology may be subdivided into the following steps: mosaic of scenes, fild verification, generation of NDVI time-series and qualitative analysis, in addition, it was complemented with rainfall analysis.  The results obtained with the NDVI time-series associated with the rainfall analysis data provide valuable information about the environmental dynamics. The importance of NDVI in this work is given by the contrast between water and vegetation, highlighting the different levels of water over vegetated banks present on the western edge of the lagoon. These banks are an important driver circulation in the lagoon, where in periods of drought occurs the partitioning of the lagoo, while in periods of high precipitation and accumulation of water they are submerged.    Keywords: Landsat TM, time-series, National Park.

scholarly journals Mapping Forest Fire Risk—A Case Study in Galicia (Spain)

2020 ◽  
Vol 12 (22) ◽  
pp. 3705
Author(s):  
Ana Novo ◽  
Noelia Fariñas-Álvarez ◽  
Joaquín Martínez-Sánchez ◽  
Higinio González-Jorge ◽  
José María Fernández-Alonso ◽  
...  
Keyword(s):  
Forest Fire ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Risk ◽  
Fire Regimes ◽  
Slope Aspect ◽  
Fire Weather Index ◽  
Novel Approach ◽  
Fuel Model ◽  
Forest Fire Risk

The optimization of forest management in roadsides is a necessary task in terms of wildfire prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk locations, while providing a decision-making support about vegetation management for firefighting. In this study, nine relevant parameters: elevation, slope, aspect, road distance, settlement distance, fuel model types, normalized difference vegetation index (NDVI), fire weather index (FWI), and historical fire regimes, were considered as indicators of the likelihood of a forest fire occurrence. The parameters were grouped in five categories: topography, vegetation, FWI, historical fire regimes, and anthropogenic issues. This paper presents a novel approach to forest fire risk mapping the classification of vegetation in fuel model types based on the analysis of light detection and ranging (LiDAR) was incorporated. The criteria weights that lead to fire risk were computed by the analytic hierarchy process (AHP) and applied to two datasets located in NW Spain. Results show that approximately 50% of the study area A and 65% of the study area B are characterized as a 3-moderate fire risk zone. The methodology presented in this study will allow road managers to determine appropriate vegetation measures with regards to fire risk. The automation of this methodology is transferable to other regions for forest prevention planning and fire mitigation.

scholarly journals Analisis Spasial Ruang Terbuka Hijau (RTH) untuk Penanganan Perubahan Iklim di Kota Ambon

2017 ◽  
Author(s):  
Jan Willem Hatulesila ◽  
Gun Mardiatmoko ◽  
Jusuph Johanis Wattimury
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat Tm

Tata ruang perkotaan dengan arsitektur Ruang Terbuka Hijau (RTH) merupakan komponen lansekap yang sangat mempengaruhi udara perkotaan baik langsung maupun tidak langsung. Standar ideal luasan minimum ruang terbuka hijau yakni minimal 30 % dari total luas kota. Sejauhmana pola penataan ruang kota yang berhubungan dengan perencanaan RTH dan indikator penataan ruang secara spasial dapat dianalisis menggunakan data citra satelit Landsat TM - 8 Tahun 2017 dan Sistem Informasi Geografis (SIG). Kawasan RTH Kota Ambon hasil analisis spasial seluas ± 1,115,900 m2 atau 111,59 ha meliputi Kelurahan Honipopu ± 436,300 m2 atau 43,63 ha; Kelurahan Ahusen, ± 286,500 m2 atau 28,65 ha dan Kelurahan Uritetu ± 393,100 m2 atau 39,31 ha. Pengukuran dan penetapan sembilan lokasi sampling secara purposif dengan luasan ± 25,408.59 m2 atau 2,54 ha atau 2,28 %. Analisis NDVI (Normalized Difference Vegetation Index) untuk tutupan lahan bervegetasi (nilai indeks vegetasi 0,05 – 0,35) seluas 61,58 ha atau 58,31 %, diikuti tutupan lahan terbangun (nilai indeks vegetasi 0,00 – 0,35) seluas 39,63 ha atau 37, 52 % dan tutupan lahan kosong (nilai indeks vegetasi 0,00 – 0,05) seluas 4,40 ha atau 4,17 %. Hasil analisis regresi, uji anova sebesar 0,95 atau 95 %, mampu mejelaskan bahwa hubungan tutupan vegetasi dengan nilai indeks kehijauan mempunyai pengaruh terhadap keseluruhan kondisi tutupan vegetasi pada kawasan RTH di Kota Ambon.

scholarly journals Spatial autocorrelation of ndvi and gvi indices derived from landsat/tm images for soybean crops in the western of the state of Paraná in 2004/2005 crop season

2013 ◽  
Vol 33 (3) ◽  
pp. 525-537 ◽  
Author(s):  
Gustavo H. Dalposso ◽  
Miguel A. Uribe-Opazo ◽  
Erivelto Mercante ◽  
Rubens A. C. Lamparelli
Keyword(s):  
Spatial Autocorrelation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The State ◽  
Landsat Tm ◽  
Crop Season ◽  
Yield Data ◽  
Green Vegetation ◽  
Crop Cycle ◽  
Global And Local

This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.

Transformation in Vegetation and Urban Sprawl in Gotan and Surrounding

2021 ◽  
pp. 111-124
Author(s):  
Rizwan Ahmad ◽  
Ramaraju Sudarshana
Keyword(s):  
Urban Sprawl ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Series Data ◽  
Driving Forces ◽  
Landsat Tm ◽  
Series Data ◽  
Monitoring Frequency ◽  
Government Sector

The main driving forces associated with transformation of vegetation cover and urban sprawl, are undoubtedly climate change and human intervention. Finding the truth behind transformation of Gotan, Rajasthan Landsat TM/ETM+ data of the years 1987,1990, 1995, 2000, 2003, 2010, 2015, and 2018 were used. These time series data comprising total of nine scenes were selected to measure the urban and green cover transformation in the past four decades. Landsat TM/ETM+ data were used because it is inexpensive, with high monitoring frequency and covers large areas. The Normalized Difference Vegetation Index (NDVI) of 1987–2018, derived from the remote sensing dataset along with the application of statistical methods and GIS techniques, were used to quantify vegetation cover change. The results show that human-induced factors can explain most variations at sites with significant cover change. It has been a well-known fact that sustainable development presents a system in order to accomplish economic growth, bring about social justice, implement environmental awareness and most certainly the fortification of government sector.

scholarly journals Estimating Actual Evapotranspiration over Croplands Using Vegetation Index Methods and Dynamic Harvested Area

2021 ◽  
Vol 13 (24) ◽  
pp. 5167
Author(s):  
Neda Abbasi ◽  
Hamideh Nouri ◽  
Kamel Didan ◽  
Armando Barreto-Muñoz ◽  
Sattar Chavoshi Borujeni ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Actual Evapotranspiration ◽  
Monitoring Tool ◽  
Cropping Patterns ◽  
Agricultural Water Use ◽  
Before And After ◽  
Ndvi Time Series ◽  
Translation Methods

Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVIMccL and EVI2MccL) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption.

scholarly journals REMOTE SENSING APPROACH TO EVALUATE POST-FIRE VEGETATION STRUCTURE

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1031-1038
Author(s):  
A. Novo ◽  
H. González-Jorge ◽  
J. Martínez-Sánchez ◽  
H. Lorenzo
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Point Cloud ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Critical Role ◽  
Canopy Cover ◽  
Forest Recovery ◽  
Average Height ◽  
Natural Ecosystems

Abstract. Spain is included in the top five European countries with the highest number of wildfires. Forest fire can produce significant impacts on the structure and functioning of natural ecosystems. After a forest fire, the evaluation of the damage severity and spatial patterns are important for forest recovery planning, which plays a critical role in the sustainability of the forest ecosystem. The process of forest recovery and the ecological and physiological functions of the burned forest area should be continuously monitored. Remote sensing technologies and in special LiDAR are useful to describe the structure of vegetation. The vegetation modelling and the initial changes of forest plant composition are studied in the forest after mapping the burned areas using Landsat-7 images and Sentinel-2 images. Normalized Burn Ratio (NBR) index and Normalized Difference Vegetation Index (NVVI) is calculated as well as the difference before and after fire. The evaluation of temporal changes of vegetation are analysed by statistical variables of the point cloud, average height, standard deviation and variance. Fraction Canopy Cover (FCC) also is calculated and the point cloud is classified following the fuel model by Prometheus. An analysis method based on satellite images was completed in order to analyse the evolution of vegetation in areas that suffer forest fire.

scholarly journals FIRE SEVERITY ASSESSMENT USING NDVI DERIVED FROM LANDSAT TM/ETM IMAGES AND TERRAIN DATA

2017 ◽  
pp. 29-37 ◽  
Author(s):  
Ibrahim Molla ◽  
Emiliya Velizarova ◽  
Mariana Zaharinova
Keyword(s):  
Forest Fires ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Severity ◽  
Landsat 8 ◽  
Fire Occurrence ◽  
One Year ◽  
In Fire

The forest fires influence on the plants and soil depends on the fire severity and time of exposure. Fire severity integrates physical, chemical and biological changes occurring in ecosystems on the area as a consequence of fire influence. The purpose of the current investigation was to examine the role of the forest fire severity on the vegetation cover of the area of Svilengrad Municipality, using NDVI (Normalized Difference Vegetation Index) before fire and after fire, derived from LANDSAT 8 TM/ETM images. The comparison of the data from NDVI and that observed on the terrain data was also targeted. The results show that NDVI are changed significantly in fire affected area depending on vegetation cover and type of fire. This index also is very sensitive to changes during time after fire occurrence. One year after fire occurrence the NDVI values increased to +0.305 (0.048) for whole studied area. Through dNDVI could be distinguish the recovery rates of the fire affected areas with different tree species.

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