Mapping Tropical Monsoon Forests Using Modis Data Biology essay
Key message We estimate the leaf area index LAI and chlorophyll content CC of the Moso bamboo forest using statistical models based on MODIS data and field measurements. The results showed that the statistical model driven by MODIS data has the potential to accurately estimate LAI and CC, while the structure of the calibration. Research shows that we are developing a new method to map understory forest fires in the Amazon region. We used annual Landsat and MODIS data to track canopy loss and recovery over time. The new method separated fire from deforestation, logging and intact forests. MODIS and Landsat resolutions were suitable for forest fire mapping. The objectives of this study are to 1 map the forests, both evergreen and deciduous cover, at spatial resolution m in monsoon Asia using a decision tree algorithm and the PALSAR and MODIS data, and 2 investigate the uncertainties between our resulting forest-non-forest maps PALSARMOD50m F NF, Fig. an example of NDVI sequences before and after realignment for three forest types, specifically the Northern Hemisphere deciduous broadleaf forest at the Morgan Monroe State Forest site in IN, USA 86. 39. and the Southern Hemisphere Argentina 63. 24 . and the tropical monsoon, Multi-angular remote sensing observation contains crucial information on forest structure parameters. Here our aim is to investigate the ability of multi-angular indices, which are constructed by the typical angular reflections in red and NIR bands from MODIS observations, for retrieving forest biomass based on the above measured field value, the MODIS Aqua data was obtained from the beginning. MODIS Level - with -m resolution representing the - downloaded from NASA and calibrated against the level 1b radiation data, using. More images covered the study area from to. The MODIS hotspot data was also evaluated, indicating that the number of fires has a strong relationship, 0.82, with fire area. We identified hotspot trends in global vegetation fires based on year-long MODIS fire products. In addition, we analyzed the occurrence of fire hotspots in climate zones, global land cover and global biodiversity hotspots. Fire hotspot zones were delineated by combining annual fire data with spatial statistics and space-time patterns. Our forest map PALSARMOD F NF was assessed against randomly selected ground truth samples from high spatial resolution images and had overall accuracy. Total area of forests in monsoon Asia was estimated at 6.3 10 6 km 2. The distribution of evergreen and deciduous forests was quite similar. The MODIS tiles of 10 in size were joined together to create a monthly map of the estimated study area in raster format. The monthly burn date maps were used for further data processing. The MCD14ML active fire data was collected in a point format km resolution. Multi-angular remote sensing observation contains crucial information on forest structure parameters. Here, our aim is to investigate the ability of multi-angular indices, constructed by the typical angular reflections in red and NIR bands from MODIS observations, for retrieving forest biomass based on the minimum monthly rainfall measured above. recorded for the two monsoons and two inter-monsoons are as the inter-monsoon, the inter-monsoon and the south-east monsoon for the north. Zhang et al. 97 produced this map at a resolution of m by combining.