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Fruit and Vegetable Pigments as Indicators
Science, 1930(1) Solutions of many fruit pigments act as indicators. (2) These solutions are easily prepared and stable, and the pH range of their color changes is in most cases conveniently near the neutral point. (3) As liquid indicators they can be used in titrating acids, but not bases.
O B, Pratt, H O, Swartout
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Interpreting vegetation indices
Preventive Veterinary Medicine, 1991Remotely sensed spectral vegetation indices are widely used and have benefited numerous disciplines interested in the assessment of biomass, water use, plant stress, plant health and crop production. The successful use of these indices requires knowledge of the units of the input variables used to form the indices, and an understanding of the manner in
Ray D. Jackson, Alfredo R. Huete
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A review of vegetation indices
Remote Sensing Reviews, 1995Abstract In the field of remote sensing applications, scientists have developed vegetation indices (VI) for qualitatively and quantitatively evaluating vegetative covers using spectral measurements. The spectral response of vegetated areas presents a complex mixture of vegetation, soil brightness, environmental effects, shadow, soil color and moisture.
A. Bannari +3 more
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Vegetation as an indicator of environmental changes
Environmental Monitoring and Assessment, 1983Composition of the vegetation and the properties of its environment are related, as was shown by research. In these, mostly statistical-correlative studies, both the vegetation and some growth factors, such as plant nutrients and moisture supply were analyzed and studied on interdependence.At present the environmental conditions can be estimated in the
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Analysis of Topographic Effects on Vegetation Indices
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019In the field of remote sensing, vegetation indices (VIs) have been wieldy used in vegetation monitoring such as the growth status and fractional vegetation cover. However, topographic influence on VIs is an important and inevitable issue when VIs are applied in the large scale. In this study, theoretical error analysis of topographic effects is applied
Junxiong Zhou 0003, Jin Chen
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A comparison of vegetation indices for corn and soybean vegetation condition monitoring
2009 IEEE International Geoscience and Remote Sensing Symposium, 2009The continuous crop condition monitoring with a full geospatial coverage and sufficient granularity throughout the season is critical to decision making in agricultural policy, production, and food prices. The USDA NASS currently uses bi-weekly 1km AVHRR NDVI composited data to monitor the US crop condition in the growing season.
Zhengwei Yang +3 more
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Monitoring Vegetation Water Content Using Microwave Vegetation Indices
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008Effectively monitoring vegetation water is essential to improve our understanding of agriculture and hydrology. Vegetation water content is often estimated using vegetation indices derived from optical satellite sensors. In this study, we introduced the new microwave vegetation indices (MVIs) and derived the new MVIs using observation from the Advanced
Jing Tao +5 more
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Refinement of microwave vegetation indices
SPIE Proceedings, 2010Previous investigations have established the basis for a new type of vegetation index, Microwave Vegetation Indices (MVIs), based on passive microwave satellite observations. In this technique, the quantitative basis of the MVIs can be derived from the zeroth-order radiative transfer solution.
L. Chai, J. Shi, L. Zhang, T. Jackson
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2011
Most remote sensing satellite sensors offer multispectral images besides panchromatic images. This multispectral information is extremely valuable to detect various objects in the image. In this book, we summarize the multispectral information via vegetation and shadow–water indices.
Cem Ünsalan, Kim L. Boyer
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Most remote sensing satellite sensors offer multispectral images besides panchromatic images. This multispectral information is extremely valuable to detect various objects in the image. In this book, we summarize the multispectral information via vegetation and shadow–water indices.
Cem Ünsalan, Kim L. Boyer
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Vegetation spatial variability and its effect on vegetation indices
International Journal of Remote Sensing, 1987Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR).
J. P. ORMSBY, B. J. CHOUDHURY, M. OWE
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