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What is Normalized Difference Vegetation Index (NDVI)

Transcending Humanitarian Engineering Strategies for Sustainable Futures
NDVI is a remote sensing technique that uses different spectrum bands sensed by satellites to quantify vegetation status in an area. The value of this index varies between +1 to -1. A high positive value indicates a high density of vegetation. A value close to zero indicates built-up or urbanised areas. Negate values generally indicate the presence of water bodies.
Published in Chapter:
Humanitarian and Soft Engineering for Disaster Mitigation in Coastal Bangladesh
Syed Labib Ul Islam (University of Birmingham, UK) and G. M. Tarekul Islam (Bangladesh University of Engineering and Technology, Bangladesh)
DOI: 10.4018/978-1-6684-5619-4.ch014
Abstract
Developing countries like Bangladesh are facing multidimensional challenges due to climate change. The traditional engineering sector needs to evolve to contribute to the solution of the emerging problems by incorporating social and technical solutions. Integration of humanitarian and soft engineering and proper project formulation and implementation can go a long way in addressing the challenges. Harmonised and clear policies to this end are of high importance, along with political will and accountability in the public investments. Efficient utilisation of resources are needed through objective and proper prioritisation of projects – free from external influence or interference. Geopolitical cooperation between countries, coordination between the government and non-government sectors, as well as within the departments of the government is crucial for the success of humanitarian and soft engineering in resource-constrained countries.
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Sustainability of Agriculture Territories in South Kazakhstan: Remote Sensing and Geodata for Design of Landscape and Soil Maps
A standardized index allowing you to generate an image displaying greenness (relative biomass). This index takes advantage of the contrast of the characteristics of two bands from a multispectral raster dataset—the chlorophyll pigment absorptions in the red band and the high reflectivity of plant materials in the near-infrared (NIR) band.
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