Canada Wildfire Prediction Using Deep Learning
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Updated
Jul 2, 2024 - Jupyter Notebook
Canada Wildfire Prediction Using Deep Learning
This is a Science and Technology Society (STS) of Sarasota-Manatee Counties that shows the data from a series of NASA STELLA-Q2 Spectrometer readings on a number of vegetative species with calculations of NDVI to differentiate species using Decision Tree logic and Knn from the mean end member data.
The Science and Technology Society of Sarasota-Manatee Counties use Landsat data to calculate Normalized Difference Vegetative Index (NDVI) from Landsat NIR and Red Bands and Panchromatic Normalized Difference Vegetative Index (PNDVI) from Panchromatic and NIR Bands to assess the health of Mangrove Forests in Sarasota Bay
The NASA STELLA-Q2 can make 18 different measurements from violet/blue portions of the electromagnetic spectrum out to near infrared regions (beyond our range of vision). STELLA instruments are portable low-cost do-it-yourself (DIY) instruments that support science education.
Sample code downloading a GeoTIF image from Sentinel Hub and calculates the average NDVI on a certain area, which is provided by a polygon within the script
ClimateSERV allows development practitioners, scientists/researchers, and government decision-makers to visualize and download historical rainfall data, vegetation condition data, and 180-day forecasts of rainfall and temperature to improve understanding of, and make improved decisions for, issues related to agriculture and water availability.
oolkit created to do extraction, gap-filling and trend analysis over Sentinel 2 time-series from Earth Engine
Toolkit created to do extraction, gap-filling and trend analysis over Sentinel 2 time-series from Earth Engine
A scalable implimentation of HANTS for time sereis reconstruction in remote sensing on Google Earth Engine platform
A Jupyter notebook for detecting deforestation using GeoTIFF satellite images and NDVI analysis with OpenCV.
A Collection of Python Codes that work in QGIS (Quantum GIS) that work on Orthomosaic Maps Generated by Aerial Photogrammetry Software such as the free to use VisualSFM or commercial software DroneDeploy or PIX4D. The Goal of these codes is to create free to use classification and NDVI on orthomosaics generated using freeware or trial versions o…
Python coding that takes images acquired using a Near-Infrared (NIR) converted camera and generates a modified Normalized Differential Vegetation Index (NDVI). Contains standalone with colorbar legend and batch versions. ENDVI and SAVI Indexes also available and with greyscale options.
Geospatial Programming: Modern Integrated Surveying Technology 2024, Presented by Thepchai Srinoi
A step-by-step guide to vegetation classification and calculation of unvegetated - vegetated ratio of salt marshes with public aerial imagery
Mangrove Ecosystem Mapping Using Multisumber Images (Sentinel-2A and Sentinel-1) Using Cloud-Based Computing In Balikpapan Bay in 2019 and 2022.
Monitor Vegetation Health by Viewing & Comparing NDVI Values & Satellite Images On The Fly!
A service for indexing and using Sentinel 2 satellite data
GEE code for pixel-based land cover classification with Random Forest (RF) algorithm, and for NDVI time series visualization.
Custom library to access data through ClimateSERV API
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