Andy J Humane Near Real Time Monitoring Of Deforestation Using A Neural Aug 2009
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The document describes the HUMANE approach for near-real time monitoring of deforestation using machine learning and MODIS satellite data. HUMANE uses a neural network to learn patterns in MODIS NDVI data over time to predict greenness levels, and detects anomalies from actual data as areas of potential deforestation. It provides monitoring at 250m resolution over Latin America with a 3 week turnaround time from data availability. Validation tests found HUMANE detected some smaller, isolated deforestation events that other models missed, though it also had some false positives that can be addressed through calibration.
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Explainable AI for distinguishing future climate change scenarios
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- 1. Near-real time monitoring of deforestation using a neural network and MODIS data: the HUMANE approach Andy Jarvis, Louis Reymondin, Jerry Touval CIAT and TNC
- 6. NDVI Evolution and novelty detection Novelty/Anomoly
- 8. Methodology As required by the ARD algorithm, each input and the hidden output is a weights class with its own α α 0 α c INPUTS : Past NDVI (MODIS 3b42) Previous rainfall (TRMM) Temperature (WorldClim) OUTPUT : 16 day predicted NDVI NDVI t Precipitation (t) Temperature (t) … … w 0 w 1 w 2 NDVI (t-1) NDVI (t-2) NDVI (t-n) w p1 w p2 w p3 w o1 w o2 w o3
- 13. HUMANE vs. DETER Validation tests
- 16. HUMANE true positives 2004 2006 Parasid model is, sometimes more sensitive, and detects events that Deter doesn’t detect.
- 17. HUMANE True Positives It seems Parasid model detects quite small and isolate events which Deter doesn’t detect. 2006 2004
- 18. HUMANE False positives On the other hand, Parasid is more sensitive to false positives. Here, around a river. 2004 2006
- 19. HUMANE False Positives In this example, Parasid doesn’t detect as well as Deter the big new field (red circle) but, is more precise to detect the small fields on the top right corner (blue circle) . 2004 2006
- 21. HUMANE vs. FORMA Validation tests
- 23. Models’ output HUMANE detections First detection in 2004 FORMA probabilities First detection in 2000
- 26. Detailed comparison Top FORMA Bottom PARASID Images from google earth PARASID - FORMA Maybe due to the rescaled pixel size from 250 [m] to 500 [m], FORMA model doesn’t fit perfectly some fields (the red bound around the fields on the comparison map).
- 27. Detailed comparison Top FORMA Bottom PARASID Images from google earth PARASID - FORMA Parasid is a bit more sensitive.
- 28. Detailed comparison Clear change in 2006 Softer change in 2008 Maybe vegetation degradation The pixel plotted is shown in red on the map .