water hyacinth, an invasive aquatic plant, has seriously infested the waterbodies of Sri Lanka and disturbed the freshwater aquatic environment. This study presents a rapid assessment of water hyacinth mapping in Sri ...
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ISBN:
(数字)9798350390346
ISBN:
(纸本)9798350390353
water hyacinth, an invasive aquatic plant, has seriously infested the waterbodies of Sri Lanka and disturbed the freshwater aquatic environment. This study presents a rapid assessment of water hyacinth mapping in Sri Lanka using earth observation (EO) and machine learning techniques, highlighting its potential for circular economic opportunities. While posing significant environmental challenges, water hyacinth offers economic potential through its use in biofuel production, composting, bioremediation, and as biochar soil ameliorant. The methodology integrates Principal Component Analysis, K-means clustering and Otsu thresholding for precise water hyacinth area delineation. Initial results indicate a total biomass estimate of the weed to be $4111 \pm 584$ tons per year for the selected 28 water bodies. These water bodies are chosen for their location, size and reported water hyacinth invasion. The findings underscore the potential of integrating EO and machine learning into ecological management and offer a scalable model for similar assessments in other regions.
To monitor the vegetation condition during extreme weather events, this article suggests an approach for mimicking vegetation indices, notably the Normalized Difference Vegetation Index (NDVI), using microwave data. T...
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ISBN:
(数字)9798350390346
ISBN:
(纸本)9798350390353
To monitor the vegetation condition during extreme weather events, this article suggests an approach for mimicking vegetation indices, notably the Normalized Difference Vegetation Index (NDVI), using microwave data. The main goal is to generate simulated NDVI images from microwave data to improve temporal availability and fill the data gaps in the time series when optical data is unavailable. A neural network regression model was developed, using SAR data as input features to predict optical data. The network architecture included an input layer, followed by a dense layer with 32 ReLU-activated nodes, and an output layer with a single node. The model was trained using the Adam optimizer and mean squared error (MSE) as the loss function. Initial results show an $R^{2}$ of 0.62. Pearson’s correlation coefficient is $\mathbf{- 0. 7 9}$ and 0.019 for red vs VV and NIR vs VH bands, respectively.
Reservoirs play a vital role in water resource management and provide essential ecosystem services. The study focuses on extracting the water extent of Maithon reservoir, Jharkhand, India, from 2017 to 2023 by delinea...
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ISBN:
(数字)9798350390346
ISBN:
(纸本)9798350390353
Reservoirs play a vital role in water resource management and provide essential ecosystem services. The study focuses on extracting the water extent of Maithon reservoir, Jharkhand, India, from 2017 to 2023 by delineating the boundaries between the water and non-water class extracted from Sentinel-1 data. The scenes were processed using Google Earth Engine to obtain water extent using the Otsu method. This research extends the application of the extracted water extent values, precipitation data from CHIRPS, and weekly historical water level data of the reservoir obtained from the Central water Commission to monthly forecasts of the water level using the Long Short-Term Memory (LSTM) model. The forecasts were obtained with a mean absolute error of around 80 cm with test data. The study provides initial results and is under further modification, where the improved estimation shall be integrated into flood early warning systems and help to provide actionable insights to stakeholders and decision-makers to mitigate risks and optimize water usage.
Reservoirs play a vital role in water resource management and provide essential ecosystem services. The study focuses on extracting the water extent of Maithon reservoir, Jharkhand, India, from 2017 to 2023 by delinea...
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