High Normalized Difference Vegetation Index Research Articles

Seasonal to interannual variability of vegetation and fires at SAFARI 2000 sites inferred from advanced very high resolution radiometer time series data

NOAA advanced very high resolution radiometer data are used to place the SAFARI 2000 and SAFARI 1992 intensive campaigns in the context of the interannual variability of vegetation conditions in southern Africa. Normalized difference vegetation index (NDVI) measurements and sea surface temperature (SST) indices of El Niño/Southern Oscillation (ENSO) are compared and the connections explained. The paper shows the vegetation evolution for the 2000 growing season, with unprecedented high and persistent NDVI anomalies associated with a cold phase of ENSO (La Niña) and above average rainfall between November and May, south of 15°S. In contrast, the 1992 season showed marked negative NDVI anomalies associated with an extreme drought in the southern part of the region, associated with the warm phase of ENSO (El Niño). These differences in NDVI patterns resulted in different patterns of fire distribution. More satellite detections of active fires were observed in 2000 than in 1992, especially for Botswana, Namibia, southern Zimbabwe, and southern Mozambique. Comparisons between in situ airborne measurements collected in 2000 and 1992 require an understanding of the extremely different vegetation and fire conditions associated with those years. Generalizations from results of the two SAFARI campaigns should be made with careful consideration of the extreme differences in conditions and the large interannual variability encountered in southern Africa, as depicted by the long‐term record of satellite vegetation measurements.

Estudo da variabilidade do NDVI sobre o Brasil, utilizando-se a análise de agrupamentos

Este trabalho analisa a variabilidade do NDVI (Índice de Vegetação por Diferença Normalizada) sobre o Brasil, utilizando-se a análise de agrupamentos. As análises foram feitas através de imagens do sensor Advanced Very High Resolution Radiometer (AVHRR) para o período de janeiro de 1982 a dezembro de 1993. Os resultados obtidos mostram que na região Amazônica o ciclo anual do NDVI não é bem definido, visto que o máximo tipicamente ocorre em junho, dois meses após o período chuvoso, enquanto o mínimo se dá em dois períodos distintos: entre fevereiro e março e setembro e novembro. Na região central do Brasil, o cerrado apresenta um ciclo anual definido, com valores máximos de NDVI entre março e maio, e mínimos em setembro, final do período seco. Por outro lado, a vegetação das regiões da zona da mata nordestina e dos campos de Roraima apresentam um ciclo anual nítido, sendo que os maiores valores de NDVI ocorrem em junho e julho e os menores entre fevereiro e março, alguns meses antes do início das chuvas. No caso da região nordeste do Brasil, a caatinga mostra um ciclo anual bem definido, com um período seco marcante, sendo que os valores mais elevados de NDVI ocorrem entre os meses de abril e maio, que é o final da época das chuvas, e os menores em setembro e outubro. Em parte do Estado de Santa Catarina e no sul do Paraná, o ciclo anual das formações vegetais dominantes (floresta ombrófila aberta e floresta ombrófila mista) não é muito nítido. No sul do Brasil, a região de estepes não apresenta ciclo anual nítido, os valores máximos de NDVI geralmente ocorrem entre março e junho e os valores mínimos no mês de agosto. Além disso, constatou-se que os eventos El Niño, independente da sua intensidade, afetam distintamente os vários tipos de vegetação.

Interannual variability of NDVI in northwest Mexico. Associated climatic mechanisms and ecological implications

The relation between the Normalized Difference Vegetation Index (NDVI) interannual variability, precipitation and atmospheric circulation at 700 mbar in northwest Mexico is analyzed during the warm and cold phases of the El Niño Southern Oscillation (ENSO). A conditional probability test was conducted between this phenomenon and NDVI values. It was found that the negative ENSO phase is associated with drought conditions with a delay of 4–6 months related to the start of event, while the positive phase is related to high NDVI values during the driest season in the region. Clustering the NDVI values by terciles, it was determined that summers with high NDVI values are related to an intensification of the Mexican summer monsoon; while, in dry summers, the flow is characterized by the presence of an enhanced ridge of high-pressure aloft over most of the national territory. In winters with high NDVI values, a very intense low-pressure trough induces a meridional flow with penetration of humid air associated with frontal activity. This circulation pattern is common during the ENSO warm phase. Winters with low NDVI are associated atmospheric circulation patterns typical of the so-called Pacific North American (PNA) type. Based on the bio-seasonality and precipitation modulation in northwest Mexico due to the ENSO, it is concluded that the delay of a few months observed in NDVI values with respect to precipitation inputs supports the Seed Hydration Memory (SHM) concept. The ecological implications of this phenomenon for the region are also discussed.

Determining land surface fractional cover from NDVI and rainfall time series for a savanna ecosystem

Savanna ecosystems are water limited and responsive to rainfall on short time scales, characteristics that can be exploited to estimate fractional cover of trees, grass, and bare soil over large-scale areas from synthesis of remote sensing and rainfall measurements. A method is presented to estimate fractional cover based upon the differing ways in which grasses and trees respond to rainfall, and implementation of this method is demonstrated along the Kalahari Transect (KT), an aridity gradient in southern Africa. Seasonally averaged normalized difference vegetation index (NDVI) and the sensitivity of the NDVI to interannual variations in wet season rainfall are used as state-space variables in a linear unmixing model. End members for this analysis were determined on the basis of best fit to the observed data. The realized end members were consistent with the qualitative characteristics of trees (high NDVI, low sensitivity of NDVI to interannual variations in rainfall), bare soil (low NDVI, low sensitivity), and the transient grass/ bare soil area (moderate NDVI, high sensitivity). Observed sensitivity of NDVI to rainfall was measured as the relationship between wet season NDVI and normalized rainfall over a 16-year period (1983–1998). The unmixing model yields a north-to-south decrease in tree fractional cover that corresponds to the decrease in mean wet season precipitation from 1600 to 300 mm along the KT ( R 2=.87). The fractional tree cover results compare favorably with available ground-based observations. The potential extent of grass cover is limited by the dominance of trees on the northern end of the transect, peaks at the location with approximately 450 mm of mean wet season rainfall, and is limited by rainfall in the arid southern portion of the transect. With mean NDVI for grass inferred from the data, yearly estimates of tree, grass, and bare soil fractional cover can be derived. These annual estimates, which are difficult to obtain from traditional unmixing procedures, are important parameters in fuel load and land–atmosphere exchange models. No calibration or training sets were required for this analysis, and this method has the additional capability to predict fractional-cover components for future rainfall scenarios.

Green manuring: its effect on soil properties and crop growth under rice–wheat cropping system

A field experiment was conducted on rice ( Oryza sativa L.) and wheat ( Triticum aestivum L.) during rainy and winter seasons of 1994–95 in a clay loam soil (Typic Ustochrept) at the experimental farm of Indian Agricultural Research Institute, New Delhi, India. The objectives were to study the influence of different green manuring ( Sesbania rostrata, Sesbania aculeata, green gram ( Vigna radiata) residues) and in combination with different levels of nitrogen (0, 60, and 120 kg N ha −1) on physical properties, organic matter and total nitrogen contents of soil and on root growth and spectral response of rice and wheat crop. The organic matter and total soil nitrogen concentrations were found to be higher under green manuring treated plots than summer fallow. The magnitude of reduction in bulk density due to green manuring over fallow was 0.03–0.07 Mg m −3 in 0–15 cm soil layer and 0.05–0.09 Mg m −3 in 15–30 cm soil layer during the growth of rice and wheat. Green manuring improved the soil physical environments as was evident from higher values of mean weight diameter and saturated hydraulic conductivity than fallow. The better physical and chemical environment in Sesbania ( S) and green gram residue incorporated plots influenced higher Normalized Difference Vegetation Index (NDVI) than under fallow. The NDVI attained peak values at 62 days after transplanting of rice and 90 days after sowing of wheat. The root length density (RLD) and yields were higher in green manure plots than in fallow both in rice as well as in succeeding wheat crop. In all cases, in both rice and wheat the application of 120 kg N ha −1 treatment resulted in higher RLD than 60 kg N ha −1 and no nitrogen treatments. Poor soil conditions were mainly responsible for restricted root growth and its distribution in surface soil layer in summer fallow plots.

Spatial distribution and its seasonality of satellite‐derived vegetation index (NDVI) and climate in Siberia

AbstractThe Normalized Difference Vegetation Index (NDVI) distribution and its seasonal cycle were investigated in relation to temperature and precipitation over Siberia and its surrounding regions. The analyses used 5‐year (1987–1991) monthly means. The monthly mean NDVI was calculated from the third‐generation monthly Global Vegetation Index (GVI) product; monthly temperature and precipitation at 611 stations were calculated from Global Daily Summary (GDS) data.The 611 stations were classified by cluster analysis into 10 classes based on the NDVI seasonal cycle (March–October). The geographical distribution characteristics of the NDVI cycle were described using temperature, precipitation and Olson's land‐cover type. In northern regions, where tundra vegetation prevails and temperatures and precipitation are low, the amplitude of the NDVI seasonal cycle is small. In southern regions, where temperatures are high and there is little precipitation, the seasonal amplitude of the NDVI is small because of the arid land type. Forested regions were split into six classes, each characterized by large amplitudes in the NDVI seasonal cycle. The phenological characteristics of the forest classes were noted. For example, a forest‐class localized near Lake Baikal shows higher NDVI values, even with the presence of snow cover in March, compared with other regions. This high NDVI value suggests that the exposed green canopy of the coniferous forest can be observed even when snow is present. In addition, the NDVI peaks at stations near 60°N, where the maximum monthly temperature is around 18°C. This result suggests that the optimum temperature‐precipitation environment coincides to the area in Siberia where the maximum monthly temperature is 18°C. Copyright © 2001 Royal Meteorological Society

Distribution and Habitat Associations of Baboons (Papio hamadryas) in Central Eritrea

At least three diurnal primate taxa are still present in Eritrea, NE Africa: hamadryas baboons (Papio hamadryas hamadryas), olive baboons (Papio h. anubis) and grivet monkeys (Chlorocebus aethiops aethiops). However, information on status and distribution of primates and their habitats in Eritrea is outdated and incomplete. We conducted a primate survey, focussing on hamadryas baboons, to obtain data which will be integrated in a national wildlife management and conservation plan in Eritrea. We obtained information about the geographical distribution and abundance of baboons, their altitudinal range, habitat quality of their home-ranges, aggregation sizes at sleeping cliffs and predator presence. We described habitat quality via the Normalized Difference Vegetation Index (NDVI), a vegetation classification of Landsat MSS satellite data. Hamadryas and olive baboons are still present in Eritrea in ample numbers. Their geographical distributions in 1997 and 1998 did not deviate significantly from their historical distributions. An estimated 15,000 Papio hamadryas hamadryas lived in the 25,000-km2 area of survey (0.58 baboons/km2). Population densities of hamadryas baboons in many parts of the survey area are higher than at Kummer's (1968) study site in Ethiopia. Hamadryas baboons live at all altitudes in four of five ecogeographical zones of Eritrea. Olive baboons replaced them in the western lowlands. Both baboon taxa tend to select better quality habitats, characterized by a higher normalized difference vegetation index (NDVI) than the average for the respective ecogeographical zones. Hamadryas baboons show a greater ecological plasticity than olive baboons, which are confined to riverbeds with extended gallery forest. By the end of 1999, a hybrid zone could not be confirmed.

High temporal resolution NDVI phenology from micrometeorological radiation sensors

The boreal forest is a region characterized by wide swings in temperature and light levels over the course of a year. This seasonal variability strongly effects the vegetation of this biome. Normalized difference vegetation index (NDVI) values were observed at daily timescales for key land cover types of the boreal forest, developing a more detailed description of seasonal changes in NDVI than could be produced from satellite data. NDVI values were calculated from tower‐mounted photosynthetically active radiation (PAR) and global solar sensors measuring both incoming and reflected radiation above the canopies at four Boreal Ecosystem‐Atmosphere Study (BOREAS) sites. Comparisons were made between the tower‐based broadband hemispherical NDVI values and the narrowband nadir‐viewed NDVI values from helicopter modular multiband radiometer (MMR). The comparisons indicate that the tower NDVI values are close to the MMR NDVIs in value for the BOREAS sites, but the range in tower NDVIs is not so great as in the MMR NDVIs. In 1996, BOREAS towers operated from before thaw to freeze‐up, allowing a complete picture of growing season NDVI for fen, young jack pine, black spruce, and aspen sites. The tower‐based NDVI time series display different patterns for each vegetation type, showing the effects of snow cover and vegetation green‐up and senescence. Changes in solar zenith angles are shown to have little effect on the seasonal NDVI patterns.

Evaluating Change in Rangeland Condition using Multitemporal AVHRR Data and Geographic Information System Analysis

Coarse-scale, multitemporal satellite image data were evaluated as a tool for detecting variation in vegetation productivity, as a potential indicator of change in rangeland condition in the western U.S. The conterminous U.S. Advanced Very High Resolution Radiometer (AVHRR) biweekly composite data set was employed using the six-year time series 1989–1994. Normalized Difference Vegetation Index (NDVI) image bands for the state of New Mexico were imported into a Geographic Information System (GIS) for analysis with other spatial data sets. Averaged NDVI was calculated for each year, and a series of regression analyses were performed using one year as the baseline. Residuals from the regression line indicated 14 significant areas of NDVI change: two with lower NDVI, and 11 with higher NDVI. Rangeland management changes, cross-country military training activities, and increases in irrigated cropland were among the identified causes of change.

Use of climatic data and satellite imagery to model the abundance of Culicoides imicola, the vector of African horse sickness virus, in Morocco.

African horse sickness (AHS) is a vector-borne, infectious disease of equids caused by African horse sickness virus (AHSV). The only proven field vector of the virus is the biting midge Culicoides imicola. Following a recent epizootic (1989-91) of AHS in Morocco, light traps and automatic weather stations were operated for 2 years at twenty-two sites distributed over much of the country. The annually-averaged mean daily trap catch of C. imicola at these sites was negatively correlated with wind speed, and positively correlated with the average and mean annual minimum NDVI (Normalized Difference Vegetation Index, a remotely sensed measure of vegetation activity). There were no significant correlations between the mean daily trap catch and air temperature, soil temperature, relative humidity, saturation deficit, rainfall, altitude or the mean annual maximum or range of NDVI. The best two-variable model, which combined WindspeedMnAvMn (the average daily minimum wind speed of the least windy month) and NDVImin (the average annual minimum NDVI) as predictors, explained over 50% of the variance in the annually-averaged mean daily trap catch of C. imicola. There was a significant, positive correlation between minimum wind speed at night and the daily mortality rate of adult female C. imicola and it is suggested that the relationship between wind speed and the abundance of C. imicola arises from effects on adult mortality or dispersal. Considering several climatic variables, in North Africa NDVImin was most significantly correlated with total annual rainfall. It is suggested that the relationship between NDVImin and the abundance of C. imicola arises from the impact of soil moisture on both. It is proposed that areas of Morocco with higher levels of soil moisture in late summer or autumn provide more, larger and/or more enduring breeding sites for C. imicola, as well as supporting more photosynthetically active vegetation and hence having higher NDVI.

Estimating maize production in Kenya using NDVI: Some statistical considerations

A regression model approach using a normalized difference vegetation index (NDVI) has the potential for estimating crop production in East Africa. However, before production estimation can become a reality, the underlying model assumptions and statistical nature of the sample data (NDVI and crop production) must be examined rigorously. Annual maize production statistics from 1982-90 for 36 agricultural districts within Kenya were used as the dependent variable; median area NDVI (independent variable) values from each agricultural district and year were extracted from the annual maximum NDVI data set. The input data and the statistical association of NDVI with maize production for Kenya were tested systematically for the following items: (1) homogeneity of the data when pooling the sample, (2) gross data errors and influence points, (3) serial (time) correlation, (4) spatial autocorrelation and (5) stability of the regression coefficients. The results of using a simple regression model with NDVI as the only independent variable are encouraging (r 0.75, p 0.05) and illustrate that NDVI can be a responsive indicator of maize production, especially in areas of high NDVI spatial variability, which coincide with areas of production variability in Kenya.

Spatial analysis of the distribution of Lyme disease in Wisconsin.

Surveillance measures for human cases of Lyme disease in Wisconsin were compared and associated with tick distribution and vegetation coverage. During 1991-1994, 1,759 confirmed human cases of Lyme disease reported to the Wisconsin Division of Health were assigned a county of residence, but only 329 (19%) could be assigned with certainty a county of exposure. Distributions of cases by county of exposure and residence were often consistent from year to year. Tick distribution in 46 of 72 Wisconsin counties was mapped based on collections by researchers, statewide surveys of infested deer, and submissions from the public. Satellite data were used to calculate a normalized difference vegetation index (NDVI) for each county. A geographic information system (GIS) was used to map distributions of human Lyme disease cases, ticks, and degree of vegetation cover. Human case distribution by county of exposure was significantly correlated with tick distribution; both were positively correlated with high NDVI values in spring and fall, when wooded vegetation could be distinguished from agricultural crops in the satellite image. Statistical analysis of spatial patterns using a measure of spatial autocorrelation indicated that counties with most human cases and ticks were clustered in parts of western Wisconsin. A map delineating the counties with highest risk for Lyme disease transmission was generated based on numbers of exposed human cases and tick concentrations.

The effect of microphytes on the spectral reflectance of vegetation in semiarid regions

The normalized difference vegetation index (NDVI), which is derived from satellite sensor images, is widely used as a measure of vegetation and ecosystem dynamics, change in land use, desertification, and climatic change processes on a regional or global scale. Surprisingly, in semiarid regions, relatively high values of NDVI were measured in landscapes where little, if any, photosynthetic activity of higher plants exists. We tested the hypothesis that the high NDVI values may be caused by the photosynthetic activity of microphytes (lower plants), consisting of mosses, lichens, algae, and cyanobacteria, which cover most of the rock and soil surfaces in semiarid regions. We found that the spectral reflectance curves of lower plants can be similar to those of the higher ones and their derived NDVI values can be as high as 0.30 units. We conclude that, in semiarid environments, the reflectance of lower plant communities may lead to misinterpretation of the vegetation dynamics and overestimation of ecosystem productivity.

Population densities of sheep related to Landsat Thematic Mapper radiance

Abstract The mean annual population densities of free-ranging sheep in upland North Wales were significantly correlated with near-infrared (0.76–0.90 μm) radiance recorded by the Landsat Thematic Mapper. The relationship between sheep density and the normalized difference vegetation index (NDVI) indicated that high sheep densities always occurred on vegetation with high NDVI values, but low sheep densities may occur on vegetation with either low or high NDVI values.

Monitoring the grasslands of the Sahel 1984-1985

Normalized difference vegetation index data obtained from polar-orbiting meteorological satellites were used to compare the growing or rainy seasons of 1984 and 1985 for the Sahelian zone of Africa. A substantial difference was found between these two years, with 1985 generally having higher normalized difference vegetation index values indicating higher levels of primary production in 1985 than in 1984. 1 km data were compared for Senegal, Mali, Niger and Sudan, and 7 km data were compared for sub-Saharan Africa. The qualitative comparison of these data suggests the use of similar data to assist in centralized monitoring of rangeland conditions, to identify areas of deficiencies in primary production and provide synoptic information in support of regional drought monitoring.