I have calculated various spectral indices like NDVI, NDBI, NDWI etc. Now I'm Calculating Tasseled Cap Transformation to get greenness, brightness, and wetness. What kind of interpretations one can draw from these parameters from the GIS & Urban point of view..?
Each of the indices calculate similar but slightly different things. NDVI calculates biomass and can be used to calculate temporal changes in vegetation health. NDWI detects water content and is often used to detect biomass of plants and water stress. Tasseled Cap is useful for distinguishing between brightness, greenness, and other land use signatures. From an urban geographical standpoint, tasseled cap is useful for distinguishing between urbanized and nonurbanized areas (e.g., greenness and wetness indicate undeveloped vegetation, whereas increased brightness and low greenness indicates urbanized land or bear soils without vegetation). Basically, tasseled cap helps to classify a given landscape into urbanized and nonurbanized regions as well as account for some varience in moisture/water content. This can be used for interpretations about urban environmental impacts and track urban sprawl over time, as well as overall vegetation health over a period of time, measuring greenness and wetness to discern stress or health in plants (e.g., agricultural productivity).
The other indices can be useful for detecting plant stress, which depending upon your research question may be useful in an urban setting for assessing environmental impacts. There are other indices as well (e.g., SAVI, which removes noise from soil, including brightness), but depending upon what your research question(s) is/are, it is difficult to say what interpretations are possible. Overall I would argue that from an urban perspective, tassels cap is best for distinguishing between developed and undeveloped areas, while the other indices are best for measuring biomass and monitoring vegetation health (although I would say for this endeavour to use NDWI because of its increased sensitivity to moisture differences).
Thank you, Dylan. Can we correlate interpretation of spectral indices with the Land Use Land Cover Change Detection?
Ganjanan,
I would argue that you can correlate the interpretation of spectral indices with land use or land cover change. I would suggest calculating vegetation changes that match the land cover changes in order to have a reliable comparison. For example, if you have a land change that shows widespread urban expansion and you overlay that with vegetation changes, it would be expected that biomass levels would decrease and instances of dry, arid soil would increase, which can be captured by tassels cap and SAVI).
I hope this helps.
Gajanan, your question is too broad and has several directions. Which specific urban application are you dealing with? Urban Planning? Modelling? Forecasting? Hazard Zonation? Emergency Preparedness and Response? Something else, etc.? As Dylan already explained, each spectral index highlights specific features. Although Vegetation Indices are the most popular there are others which help to show the relative abundance of water, urban areas, geologic features etc. I'm sure a quick web search would reveal several studies documenting the application of spectral indices for built-up features. You may start with a Literature Review on the topic if your aim is to pin-point the most appropriate spectral index for urban applications. However, if I were you, I would try to be more specific by clarifying the research problem in the context of a specific urban application. And then move on to determine whether a certain spectral index would be useful in answering that research problem; rather than creating a list of spectral indices and then figuring out how to apply those to urban studies.
Apologies if this does not answer your question directly, but I hope it may give you some inspiration.
- Badges
- Science topic
- Similar topics
- Geoscience
- Geoinformatics
- Geographic Information System