Os índices de vegetação são hoje amplamente utilizados para avaliar e caracterizar a cobertura vegetal. Na agricultura estes índices permitem obter informações ao longo do ciclo cultural e atuar oportunamente, caso se justifique. Neste estudo foram calculados diferentes índices de vegetação (NDVI - Normalized Difference Vegetation Index, NDRE - Normalized Difference Red Edge Index, EVI - Enhanced Vegetation Index) para avaliação do vigor vegetativo. Estes índices foram obtidos a partir de imagens do satélite Sentinel-2, da Agência Espacial Europeia, de maio a setembro de 2021. Esta análise incidiu sobre a cultura do milho, numa parcela situada no Ribatejo (38.994975°; -8.369681°). No processamento dos dados foram utilizados os softwares ArcGis TM e Microsoft Excel. Este trabalho tem como objetivos: a) desenvolver mapas temáticos de índice de vegetação para avaliar a produtividade da cultura do milho; b) analisar o comportamento dos índices de vegetação ao longo do ciclo cultural; c) perceber qual ou quais os índices que são mais confiáveis nas fases mais avançadas do ciclo cultural. A correlação entre o NDVI e o EVI foi forte (r=0,95) mas o EVI evidenciou diferenças na refletância do milho em fases do ciclo cultural em que o NDVI mostrou saturação. O NDRE apresentou uma forte correlação com o NDVI (r=0,99). Nas fases do ciclo cultural em que a cobertura do solo fica mais densa, principalmente na fase vegetativa da floração, o NDRE superou o EVI e o NDVI, mostrando ser eficiente na deteção espacial das diferenças do vigor vegetativo.

This study aimed to characterize the average seasonal pattern of the vegetation in southern grassland in Brazil, and the variability found in the time series of vegetation indices. It also sought to identify similarities in the seasonal pattern of different grassland typologies. Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images from Feb to Dec, 2000 to 2014 were analyzed for ten regions. The grassland typologies studied showed EVI and NDVI profiles consistent with the seasonal dynamics of grassland vegetation under the influence of a subtropical climate, with highest values in the indices during the warm seasons of the year (spring and summer) and lowest in the colder seasons (autumn and winter). Considering the values of EVI and NDVI, grassland typologies were allocated to four groups with similar temporal profiles. Among the groups formed from the EVI index it is possible to identify differences between grassland typologies during the autumn and winter, while the NDVI showed differences only in winter as compared to the other seasons.

Moçambique é um país localizado ao longo da costa Leste da África Austral, com a economia baseada essencialmente na agricultura. A cultura do milho (Zea mays L.) é a mais importante, cultivada em regime de sequeiro, com rendimentos dependentes das condições meteorológicas. Este trabalho teve como objetivo o ajuste de um modelo agrometeorológico espectral, para estimativa de rendimentos do milho, na província de Manica. A área de estudo envolveu os distritos de Gondola, Manica, Mossurize e Sussundenga, responsáveis por mais de 80% da produção de milho na província de Manica, nos anos de 2000 a 2009. ETr e ETm e ISNA foram as variáveis agrometeorológicas testadas no ajuste, obtidas a partir de estimativas de elementos meteorológicos do modelo do ECMWF. As variáveis espectrais foram os índices EVI e NDVI, provenientes do produto MOD13Q1, e o índice LSWI, calculado utilizando-se as bandas de refletância contidas neste produto. O modelo agrometeorológico espectral, ajustado por meio de regressão linear múltipla, teve como variáveis independentes os índices meteorológicos e espectrais e, como variável dependente, o rendimento médio ou o rendimento relativo. O modelo regional, que incluiu os distritos de Gondola, Manica e Sussundenga, e considerou o rendimento relativo, foi o mais recomendado para estimativa de rendimentos do milho, na região, com r² = 0,762 e RMSE de 9,46%.

Detection of change is the measure of the distinct data framework and thematic change information that can direct to more tangible insights into underlying process involving land cover and landuse changes. Monitoring the locations and distributions of land cover changes is important for establishing links between policy decisions, regulatory actions and subsequent landuse activities. Change detection is the process that helps in determining the changes associated with landuse and land cover properties with reference to geo-registered multi-temporal remote sensing information. It assists in identifying change between two or more dates that is uncharacterized of normal variation. After image to image registrations, the normalized difference vegetation index (NDVI), the transformed normalized difference vegetation index (TNDVI), the enhanced vegetation index (EVI) and the soil-adjusted vegetation index (SAVI) values were derived from Landsat ETM+ dataset and an image differencing algorithm was applied to detect changes. This paper presents an application of the use of multi-temporal Landsat ETM+ images and multi-spectral MODIS (Terra) EVI/NDVI time-series vegetation phenology metrics for the District Sargodha. The results can be utilized as a temporal land use change model for Punjab province of Pakistan to quantify the extent and nature of change and assist in future prediction studies. This will support environmental planning to develop sustainable landuse practices.

ABSTRACT The Pampa biome is an important ecosystem in Brazil that is highly relevant to livestock production. The objective of this study was to analyze the potential use of vegetation indices to discriminate grazing intensities on natural grasslands in the Pampa biome. Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images from Jan to Dec, 2000 to 2013 series, were analyzed for natural grassland experimental units managed under high (forage allowance of 5 ± 2 % live weight – LW), moderate (13 ± 5 % LW) and low grazing intensity (19 ± 7 % LW). Regardless of intensity, the temporal profiles showed lower NDVI and EVI during winter, increased values in spring because of summer species regrowth, slightly decreased values in summer, especially in years when there is a water deficit, and increased values in the fall associated with the beginning of winter forage development. The average temporal profiles of moderate grazing intensity exhibited greater vegetation index values compared with low and high grazing intensities. The temporal profiles of less vegetation index were associated with lower green biomass accumulation caused by the negative impact of stocking rates on the leaf area index under high grazing intensity and a floristic composition with a predominance of tussocks under low grazing intensity. Vegetation indices can be used for distinguishing moderate grazing intensity from low and high intensities. The average EVI values can discriminate moderate grazing intensity during any season, and the NDVI values can discriminate moderate grazing intensity during spring and winter.

ABSTRACT: This study aimed to characterize the average seasonal pattern of the vegetation in southern grassland in Brazil, and the variability found in the time series of vegetation indices. It also sought to identify similarities in the seasonal pattern of different grassland typologies. Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images from Feb to Dec, 2000 to 2014 were analyzed for ten regions. The grassland typologies studied showed EVI and NDVI profiles consistent with the seasonal dynamics of grassland vegetation under the influence of a subtropical climate, with highest values in the indices during the warm seasons of the year (spring and summer) and lowest in the colder seasons (autumn and winter). Considering the values of EVI and NDVI, grassland typologies were allocated to four groups with similar temporal profiles. Among the groups formed from the EVI index it is possible to identify differences between grassland typologies during the autumn and winter, while the NDVI showed differences only in winter as compared to the other seasons.

ABSTRACT Considering that plant phenology studies allow establishing relationships between phenological patterns of vegetation and changes caused by climate variability, the aim of this study was to obtain phenological metrics for the predominant grassland typologies in Rio Grande do Sul State, Brazil (latitudes 27º 05’ and 33º 45’ S and longitudes 49° 43’ and 57º 39’ W) and to evaluate the spatial-temporal distribution pattern of these metrics under the influence of the subtropical climate variability. The phenological metrics were obtained based on the time series of the EVI (Enhanced Vegetation Index), of the sensor MODIS (Moderate Resolution Imaging Spectroradiometer), for the period from 2001 to 2014, through the Timesat program. Eleven phenological metrics were extracted, identifying the presence of two spatial distribution patterns of grass-dominated typologies in the Rio Grande do Sul state, Brazil, one located in the south-central region and the other located in the northeast, along the coast and in the western portion of the state. In addition, it was also observed that the phenological pattern of the grassland vegetation of the state of Rio Grande do Sul, Brazil, is controlled by the seasonality of vegetation, mainly associated with the variations in air temperature.

Composições de 16 dias de índices de vegetação do sensor MODerate resolution Imaging Spectroradiometer (MODIS), com resolução espacial de 1km, a bordo dos satélites TERRA e AQUA, foram usadas para caracterizar a dinâmica sazonal em 2004 de cinco fitofisionomias de Cerrado e analisar a sua separabilidade espectral. Os índices Normalized Difference Vegetation Index (NDVI) e Enhanced Vegetation Index (EVI), calculados a partir dos dados dos sensores de ambas as plataformas e de uma base comum de pixels, foram comparados entre si. Os resultados indicaram que: (a) dentre as fitofisionomias estudadas, a Floresta Estacional decídua apresentou uma dinâmica sazonal muito marcante em função da perda de folhas da estação chuvosa para a seca (substancial redução nos índices) e do rápido verdejamento com o início da precipitação no final de outubro (rápido incremento de NDVI e EVI); (b) o NDVI mostrou maior variabilidade entre as classes de vegetação do que o EVI apenas na estação seca; (c) a discriminação entre as fitofisionomias melhorou da estação chuvosa para a seca; (d) o NDVI foi mais eficiente do que o EVI para discriminar as classes de vegetação na estação seca, ocorrendo o contrário na estação chuvosa; e (e) na maioria das datas selecionadas para estudo, não houve diferenças estatisticamente significativas entre os índices de vegetação gerados de ambas as plataformas, apesar das variações na qualidade dos pixels selecionados para as composições de 16 dias e na geometria de iluminação e de visada.