Forest and Water Bodies Segmentation Through Satellite Images Using U-Net
Global environment monitoring is a task that requires additional attention in the contemporary rapid climate change environment. This includes monitoring the rate of deforestation and areas affected by flooding. Satellite imaging has greatly helped monitor the earth, and deep learning techniques have helped to automate this monitoring process. This paper proposes a solution for observing the area covered by the forest and water. To achieve this task UNet model has been proposed, which is an image segmentation model. The model achieved a validation accuracy of 82.55% and 82.92% for the segmentation of areas covered by forest and water, respectively.
Code (0)
등록된 구현이 없습니다.
Tasks
Image SegmentationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
GLH-Water: A Large-Scale Dataset for Global Surface Water Detection in Large-Size Very-High-Resolution Satellite Imagery
Global surface water detection in very-high-resolution (VHR) satellite imagery can directly serve major applications such as refined flood mapping and water resource assessment. Although achievements have been made in de…
Semantic SegmentationBD-SAT: High-resolution Land Use Land Cover Dataset & Benchmark Results for Developing Division: Dhaka, BD
Land Use Land Cover (LULC) analysis on satellite images using deep learning-based methods is significantly helpful in understanding the geography, socio-economic conditions, poverty levels, and urban sprawl in developing…
Deep LearningSemi-supervised Change Detection of Small Water Bodies Using RGB and Multispectral Images in Peruvian Rainforests
Artisanal and Small-scale Gold Mining (ASGM) is an important source of income for many households, but it can have large social and environmental effects, especially in rainforests of developing countries. The Sentinel-2…
Change DetectionSemi-supervised Change DetectionApplication of Multifractal Analysis to Segmentation of Water Bodies in Optical and Synthetic Aperture Radar Satellite Images
A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method co…
Mapping bathymetry of inland water bodies on the North Slope of Alaska with Landsat using Random Forest
The North Slope of Alaska is dominated by small waterbodies that provide critical ecosystem services for local population and wildlife. Detailed information on the depth of the waterbodies is scarce due to the challenges…