Felix Kogan

Global Drought Watch from Space

Abstract Drought is the most damaging environmental phenomenon. During 1967–91, droughts affected 50% of the 2.8 billion people who suffered from weather-related disasters. Since droughts cover large areas, it is difficult to monitor them using conventional systems. In recent years the National Oceanic and Atmospheric Administration has designed a new Advanced Very High Resolution Radiometer- (AVHRR) based Vegetation Condition Index (VCI) and Temperature Condition Index (TCI), which have been useful in detecting and monitoring large area, drought-related vegetation stress. The VCI was derived from the Normalized Difference Vegetation Index (NDVI), which is the ratio of the difference between AVHRR-measured near-infrared and visible reflectance to their sum. The TCI was derived from the 10.3–11.3-mm AVHRR-measured radiances, converted to brightness temperature (BT). Algorithms were developed to reduce the noise and to adjust NDVI and BT for land surface nonhomogeneity. The VCI and TCI are used to determine...

Remote sensing of weather impacts on vegetation in non-homogeneous areas.

Abstract Successful application of the normalized difference vegetation index (NDVI) for estimating weather impacts on vegetation is currently hindered in non-homogeneous areas. The problem is that the differences between the level of vegetation in these areas can be related, in addition to weather impacts, to the differences in geographic resources (climate, soil, vegetation type and topography). These differences should be eliminated when weather impacts on vegetation are estimated from NDVI data. This paper discusses a concept and a technique for eliminating that portion of the NDVI which is related to the contribution of geographic resources to the amount of vegetation. The Advanced Very High Resolution Radiometer (AVHRR) data of the Global Vegetation Index format were used for the 1984-1987 seasons in Sudan. The procedure suggests normalization of NDVI values relative to the absolute maximum and the absolute minimum of NDVI. These two criteria were shown to be an appropriate characteristic of geograp...

Application of vegetation index and brightness temperature for drought detection

In recent years the National Oceanic and Atmospheric Administration (NOAA) has designed a new AVHRR-based Vegetation Condition Index (VCI) that has showed to be useful for drought detection and tracking. Validations showed that the VCI has excellent ability to detect drought and to measure time of its onset, intensity, duration, and impact on vegetation. The VCI provides accurate drought information not only for well-defined, prolonged, widespread, and intensive droughts, but also for very localized, short-term, and non well-defined droughts. In addition to the VCI, the AVHRR-based observations in thermal bands were used to develop the Temperature Condition Index (TCI). This index was used to determine temperature-related vegetation stress and also stress caused by an excessive wetness. This paper provides principles of these indices, describes data processing, and gives examples of VCI/TCI application in different ecological environments of the United States.

Droughts of the Late 1980s in the United States as Derived from NOAA Polar-Orbiting Satellite Data

Abstract Drought is one of the most adverse and powerful weather-related disasters that occur every year across a portion of the United States. The consequences of droughts quite often can be devastating. To mitigate these consequences, droughts require careful monitoring. Recently, NOAAs National Environmental Satellite Data and Information Service developed a new Advanced Very High Resolution Radiometer-based vegetation condition index (VCI) that showed good results when it was used for drought detection and tracking. The VCI is a vegetation index with reduced noise and is adjusted for land climate, ecology, and weather conditions. This index provides a quantitative estimate of weather impact on vegetation and also measures vegetation conditions. Several large-area experiments showed that the VCI had excellent ability to detect drought and to measure the time of its onset and its intensity, duration, and impact on vegetation. The VCI provides accurate drought information not only for the cases with wel...

Drought Monitoring and Corn Yield Estimation in Southern Africa from AVHRR Data

Abstract Drought is one of the major environmental disasters in southern Africa. In recent years, the damage from droughts to the environment and economies of some countries was extensive, and the death toll of livestock and wildlife was unprecedented. Weather data often come from a very sparse meteorological network, incomplete and/or not always available in good time to enable relatively accurate and timely large scale drought detection and monitoring. Therefore, data obtained from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring and climate impact assessment in southern Africa. The AVHRR-based vegetation condition index (VCI) and temperature condition index (TCI) developed recently were used in this study because in other parts of the globe they showed good results when used for drought detection and tracking, monitoring excessive soil wetness, assessment of weather impacts on vegetation, and evaluation of vegetation health and productivity. The results clearly show that temporal and spatial characteristics of drought in southern Africa can be detected, tracked, and mapped by the VCI and TCI indices. These results were numerically validated by in situ data such as precipitation, atmospheric anomaly fields, and agricultural crop yield. In the later case, it was found that usable corn yield scenarios can be constructed from the VCI and TCI at approximately 6 (in some regions up to 13) weeks prior to harvest time. These indices can be especially beneficial when used together with ground data.

Monitoring regional drought using the Vegetation Condition Index

Abstract NDVI (Normalized Difference Vegetation Index) images generated from NOAA AVHRR GVI data were recently used to monitor large scale drought patterns and their climatic impact on vegetation. The purpose of this study is to use the Vegetation Condition Index (VCI) to further separate regional NDVI variation from geographical contributions in order to assess regional drought impacts. Weekly NDVI data for the period of July 1985 to June 1992 were used to produce NDVI and VCI images for the South American continent. NDVI data were smoothed with a median filtering technique for each year. Drought areas were delineated with certain threshold values of the NDVI and VCI. Drought patterns delineated by the NDVI and VCI agreed quite well with rainfall anomalies observed from rainfall maps of Brazil. NDVI values reflected the different geographical conditions quite well. Seasonal and interannual comparisons of drought areas delineated by the VCI provided a useful tool to analyse temporal and spatial evolution ...

Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India

The Advanced Very High Resolution Radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) series of satellites has been used for mapping vegetation cover and classification employing the Normalized Difference Vegetation Index (NDVI). Recently, this technique has been improved by converting NDVI with radiation measured in one of the thermal channels and converting brightness temperature into the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). These indices are being used for estimation of vegetation health and monitoring drought. The present study shows the application of vegetation and temperature condition indices for drought monitoring in India.

World droughts in the new millennium from AVHRR‐based vegetation health indices

The new millennium has started with a series of large-area droughts which have had grim consequences for the affected countries and regions. The enormous impacts of the 2000 and 2001 droughts were experienced on both physical and psychological levels, in part because no large-scale drought occurred in 1999. In some regions, severe drought continued for two years in a row.

AVHRR-Based Spectral Vegetation Index for Quantitative Assessment of Vegetation State and Productivity: Calibration and Validation

The goal of the work was to estimate, quantitatively, vegetation state and productivity using AVHRR-based Vegetation Condition Index (VCI). The VCI algorithm includes application of post-launch calibration to visible channels, calculation of NDVI from channels’ reflectance, removal of high-frequency noise from NDVI’s annual time series, stratification of ecosystem resources, and separation of ecosystem and weather components in the NDVI value. The weather component was calculated by normalizing the NDVI to the difference of the extreme NDVI fluctuations (maximum and minimum), derived from multi-year data for each week and land pixel. The VCI was compared with wheat density measured in Kazakhstan. Six test fields were located in different climatic (annual precipitation 150 to 700 mm) and ecological (semi-desert to steppe-forest) zones with elevations from 200 to 700 m and a wide range of NDVI variation over space and season from 0.05 to 0.47. Plant density (PD) was measured in wheat fields by calculating the number of stems per unit area. PD deviation from year to year (PDD) was expressed as a deviation from median density calculated from multi-year data. The correlation between PDD and VCI for all stations was positive and quite strong (r 2 � 0.75) with the Standard Errors of Estimates (SEE) of PDD less than 16 percent; for individual stations, the SEE was less than 11 percent. The results indicate that VCI is an appropriate index for monitoring weather impact on vegetation and for assessment of pasture and crop productivity in Kazakhstan. Because satellite observations provide better spatial and temporal coverage, the VCI-based system will provide efficient tools for management of water resources and the improvement of agricultural planning. This system will serve as a prototype in the other parts of the world where ground observations are limited or not available.

Derivation of pasture biomass in Mongolia from AVHRR-based vegetation health indices

Early drought detection and impact assessment on the amount of pasture biomass are important in Mongolia, whose economy strongly depends on livestock production. The countrys large area and a lack of information on grass availability due to the sparseness of biomass-observing and/or meteorological stations make it difficult to optimize nomadic livestock output in the Mongolian dry climate. The application of a new satellite-based method for drought detection and for assessment of wild biomass in Mongolia was investigated. Measurements of biomass at an experimental station in a semi-dry steppe ecosystem during 1985–1997 were compared with the Advanced Very High Resolution Radiometer (AVHRR)-based vegetation health (VH) indices. The results showed the indices can be used as proxies for biomass production estimation (biomass anomaly, BA) applying the following equation BA=43.201+0.881 VHI (R 2=0.658).