Hammad Gilani results 18
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Purpose and Methods Crop identification using remotely sensed imagery provides useful information to make management decisions about land use and crop health. This research used phonecams to acquire the Normalized Difference Vegetation Index (NDVI) of various crops for three crop seasons. NDVI time series from Sentinel (L121-L192) images was also acquired using Google Earth Engine (GEE) for the same period. The resolution of s...
Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for...
Global drought monitoring with drought severity index (DSI) using Google Earth EngineNARA Subscribed
Unlike most disasters, drought does not appear abruptly. It slowly builds over time due to the changes in different environmental and climatological factors. It is one of the deadly disasters that has plagued almost every region of the globe since early civilization. Droughts are scientifically being studied with the help of either simple or composite indices. At 500-m spatial resolution, this study presents global scale droug...
Bangladesh has undergone dramatic land use and land cover changes (LULCC) in recent years, but no quantitative analysis of LULCC drivers at the national scale exists so far. Here, we quantified the drivers of major LULCC in combination with biophysical and socioeconomic observations at the sub-district level. We used Landsat satellite data to interpret LULCC from 2000 to 2010 and employed a Global Surface Water Dataset to acco...
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