Slides(pdf for download): An overview of satellites and satellite terminology, the basics of remote sensing, sources of free satellite imagery, and tools for processing and analyzing images. Requirements: A list
LiDAR(4) OpenCV(2) Point Cloud Processing(1) python(9) Remote Sensing(3) tutorial(3) tutorial(1) Recently Added Introduction to Python (A completely free course) We all have only one home, Earth! Step-by-step PDAL setup on Anaconda...
LiDAR(4) OpenCV(2) Point Cloud Processing(1) python(9) Remote Sensing(3) tutorial(3) tutorial(1) Recently Added Introduction to Python (A completely free course) We all have only one home, Earth! Step-by-step PDAL setup on Anaconda...
pythonmachine-learningdeep-learningscikit-learnpoint-cloudgdalremote-sensinglidarsatellite-imagerysatellite-datahyperspectral-image-classificationmultispectral-imagessatellite-imageshyperspectral-imaginglidar-point-cloudpdalgdal-pythonspacenet-datasetgdal-python-librariespython-pdal ...
ARM uses a vast range of sensors; in-situ, column and volumetric remote sensing. The overarching goal of the program is to build a process level understanding of processes pertinent to the improvement of climate models. To achieve this goal modular software and a flexible development architecture...
geemap: A Python package for interactive mapping with Google Earth Engine,ipyleaflet, andipywidgets. Awesome Earth Engine: A curated list of Google Earth Engine resources includng many python libraries geonotebook: Jupyter notebook extension for geospatial visualization and analysis developed by NASA...
本文是论文《Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model》的阅读笔记。 文章解决的是建筑物变化检测问题。在该问题中,由于提取的特征不足够具有辨别性,因此导致识别出的区域不完整或者区域边界不规则。为了解决该问题,文章提出了一个双...
高光谱遥感(Hyperspectral remote sensing) 是将成像技术和光谱技术相结合的多维信息获取技术,同时探测目标的二维集合空间与一维光谱信息,获取高光谱分辨率的连续、窄波段图像数据。 高光谱识别优势: 光谱分辨率高、波段众多,能够获取地物几乎连续的光谱特征曲线,并可以根据需要选择或提取特定波段来突出目标特征; ...
Using a linear operator we can however leverage available open-source implementations of the FFT algorithm such as those in NumPy or FFTW libraries. The operator storage in this case is also limited to a single number, the size of the FFT, while the required storage for the corresponding ...
For maximum efficiency, several open-source libraries are used. For numerical operations, such as matrix operations, we use the Numpy library [9]. Statistical distributions are implemented using the SciPy package [10]. The data are visualized using the Matplotlib [11] and Pylustrator [12] ...