Abstract
Vegetation health (VH) method was developed for space-based monitoring of moisture and thermal and total health conditions in vegetation. This chapter is very important in explaining the theoretical and practical principals of the new development. The method stems from the properties of green vegetation to reflect sunlight and emit absorbed solar radiation in the visible (VIS) and near-infrared (NIR) parts of solar spectrum. In drought-free years, vegetation is normally healthy being very green (contains much chlorophyll) and vigorous (contains much water). Such vegetation reflects very little solar radiation in the VIS and much in the NIR parts of solar spectrum. As a result, the normalized difference vegetation index (NDVI), calculated from VIS and NIR, has a very high value, symbolizing good vegetation health, moisture, and thermal conditions. Healthy vegetation also emits less absorbed thermal infrared (IR) radiation, resulting in a lower brightness temperature (BT) and a cooler canopy. Drought depresses vegetation greenness and vigor and makes the canopy hot due to an increase in VIS (due to depletion of chlorophyll), decrease in NIR (due to a drop in water content), a reduction of NDVI, and an increase in BT making canopy hot. Therefore, NDVI and BT serve as indicators of healthy/non-healthy vegetation. Their data are composited and processed to reduce noise related to clouds, aerosols, water vapor, sun-sensor geometry, orbit degradation, satellite position, sensor deterioration, random noise, and other errors. Further, processing includes a development of NDVI and BT multiyear climatology and three indices in the form of deviation from that climatology. The indices are vegetation condition index (VCI), temperature condition index (TCI) and vegetation health index (VHI), combining the first two together. They characterize vegetation moisture (VCI), thermal (TCI), and total health (VHI) conditions. These indices were based on the three biophysical laws: the Leibig’s Law of Minimum, the Shelford’s Law of Tolerance, and the Principal of Carrying Capacity. This chapter describes the three indices and their applications for monitoring vegetation moisture, thermal, and health conditions.
The vegetation health (VH) method derives vegetation conditions or health. This method is extremely theoretically grounded (from biophysical laws), validated comprehensively against weather, climate, and economic land data, has 38-year history (1981–2018), and is widely used (100–400 users per day). The method was developed from data observed by the NOAA operational polar-orbiting satellites since 1980. The new global vegetation health data set has been developed for operational purposes and investigated scientifically. The VH 38-year data set has advantages over other data sets with similar applications, being the longest, global, highest spatial (0.5, 1 and 4 km2) and temporal (1 week) resolution. The VH contains, in addition to NDVI, data and products from infrared channels (brightness temperature, BT), originally observed reflectance/emission values, highest quality (no-noise) original indices (NDVI and BT), biophysical climatology, and, what is most important, products (drought, moisture/thermal stress, fire risk, soil moisture, malaria, crop production, etc.) used for monitoring the environment and socioeconomic activities. The processed data and products are ready to be used without additional processing for monitoring, assessments, and predictions in agriculture, forestry, climate change, health, invasive species, diseases, ecosystem addressing such topics as food security, land cover–land change, climate change, environmental security, and others.
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Kogan, F. (2019). Vegetation Health Method. In: Remote Sensing for Food Security. Sustainable Development Goals Series. Springer, Cham. https://doi.org/10.1007/978-3-319-96256-6_4
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