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Spatial
Environmental, Atmospheric, and Earth Sciences
The Ki-Spatial™ platform uses AI, deep learning, satellite data from NASA and ESA, IoT sensors, and GIS for real-time pollution and geophysical event monitoring. It tracks air, water, and soil quality, detects wildfires, and collects data on erosion, forestry, and agriculture to support food poverty risks. Ki-Spatial combines sensor inputs with digital tools like Esri's ArcGIS to identify pollution hotspots and interpolate data. As a cloud SaaS, it enables users to create, share, and collaborate on web maps, with over 2,000 geoprocessing tools for spatial analysis. It also offers 3D city modeling for scenario testing and real-time GIS tracking.
Black Cactus collaborates with NASA to leverage advanced geospatial technologies, extensive satellite data archives, and Artificial Intelligence (AI) to monitor and address environmental challenges. They use machine learning (ML) to analyze large datasets and generate actionable insights for climate initiatives, disaster response, and resource management.
Spatial
Rivers Spaital
Hotspots
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GGIS-based pollution detection employs satellite remote sensing to monitor chemical pollutants in land, air, and water environments. It enables the identification of pollution hotspots and environmental changes like sea-level temperature fluctuations. Major data sources include Sentinel-5P (TROPOMI) for air quality, MODIS/VIIRS for aerosol distribution, and satellite altimetry for ocean level measurements. Regarding water quality, NASA satellite data tracks chlorophyll-a levels, turbidity, and surface temperatures to oversee aquatic pollution and detect harmful algal blooms.
Satellite data for GIS-based detection of water and river pollution identify chemicals by analyzing water spectral reflectance, measuring optically active constituents (OACs) such as chlorophyll a and suspended solids, and inferring non-optically active chemicals (NOACs) such as nutrients (nitrogen, phosphorus) and heavy metals, especially using machine learning. Key sensors include Sentinel-2 (ESA), Landsat 8/9 (NASA/USGS), and hyperspectral platforms like PRISMA, providing multispectral and hyperspectral data for real-time monitoring, mapping, and forecasting of water pollution.
Black Cactus's GIS-based wildfire detection utilizes satellite sensors like VIIRS and MODIS to identify, monitor, and analyze fire hotspots, smoke plumes, and burn severity almost in real time. These sensors detect infrared thermal anomalies, allowing for quick mapping of active fires within seven days and offering emergency responders valuable insights into fire behavior. Black Cactus delivers critical data on fire location, intensity, and spread.