i m interested to know, how to face sudden environmental calamtiies
Satellites help monitor and manage natural disasters such as earthquakes, floods, forest fires, or volcanic eruptions, especially where there may not be enough time to assess damage through conventional ground or aerial surveys. A 02:21 mins video titled Disaster Risk Management and Space Technology, available at https://vimeo.com/92118750, provides details. There is also Asia-Pacific Disasters: The Philippines and Thailand, available at https://vimeo.com/92214515, which spans 06:12 mins, and Space Technology and Sustainable Development, available at https://vimeo.com/92118745, which lasts 02:17 mins.
High resolution (spatial, spectral and temporal ) satellites can be used to remotely monitor plant vigor, water stress and spread of a disease of an area. Plants affected by a certain disease reflect in a different way from healthy ones, hence this can be used as a proxy for assessing the severity of the disease in terms of its stage and spatial coverage
The importance of remote sensing in agriculture/fruit culture are:
1. Determining soil moisture content using active and passive sensors from space.
2. Mapping with laser precision using Light detection and Ranging Technology (LiDAR).
3. Doing the detective work for false crop insurance claim.
4. Identifying forest stands and tallying their area to estimate forest supplies.
5. Measuring wind speed and direction for wind farms, weather forecasting and surfers.
6. Forecasting weather to worn about natural disasters.
7. Detecting land cover/use types for decision making.
8. Quantifying forage and crop conditions with Normalized Difference Vegetation Index (NDVI).
9. Tracking sediment transport into rivers, lakes, oceans.
10. Preventing the degradation and loss of wetland ecosystems.
Dear try to see these articles
1- Hierarchical classification approach for mapping rubber tree growth using per-pixel and object-oriented classifiers with SPOT-5 imagery
2- Mapping Rubber Tree Growth by Spectral Angle Mapper Spectral-based and Pixel-based Classification Using SPOT-5 Image
3- Maximum Likelihood for Land-Use/Land-Cover Mapping and Change Detection Using Landsat Satellite Images: A Case Study “South Of Johor”
4- Feature Extraction and Based Pixel Classification for Estimation the Land Cover thematic map using Hyperspectral data
My regards
Multiple types of vegetation calculations (NDVI, ENDVI, GNDVI etc).
Hi dear friend
1. Water managment (please search around SEBAL model )
2. Vegetation health (please search around of drone uses in agriculture)
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