Best AI tools for< Geospatial Analyst >

Gemini AI is a cutting-edge AI and ML solutions provider that focuses on accelerating innovation through artificial intelligence. The company is leading the revolution of artificial intelligence for augmented intelligence, leveraging the power of AI and ML to solve humankind's most challenging problems. Gemini AI specializes in areas such as computer vision, geospatial science, human health, and integrative technologies. Their services include data and sensors analysis, modeling using deep learning techniques, and deployment of predictive models for real-time insights.

Blackshark.ai is an AI-based platform that generates real-time accurate semantic photorealistic 3D digital twin of the entire planet. The platform extracts insights about the planet's infrastructure from satellite and aerial imagery via machine learning at a global scale. It enriches missing attributes using AI to provide a photorealistic, geo-typical, or asset-specific digital twin. The results can be used for visualization, simulation, mapping, mixed reality environments, and other enterprise solutions. The platform offers end-to-end geospatial solutions, including globe data input sources, no-code data labeling, geointelligence at scale, 3D semantic map, and synthetic environments.

Unearth AI is a platform offering geospatial data and location solutions. It provides various products like Unearth Lite, Unearth Insights, and Unearth Platform to cater to different needs. Unearth Lite is a ChatGPT-powered location explorer that offers a simple dashboard to explore locations worldwide. The platform aims to democratize geospatial data and is trusted by fast-growing businesses. With modern location solutions powered by AI, Unearth AI is revolutionizing the way businesses interact with and analyze location-based data.

Orbital Insight is a leading geospatial data analytics platform that provides users with the ability to query the world with three basic parameters: WHAT type of activity? WHERE on earth? WHEN? The platform automates the most difficult steps of deriving insights, allowing you to answer many challenging geospatial questions. Orbital Insight's GO platform is designed for enterprise collaboration and transforms multiple geospatial data sources to accelerate and streamline team member's research, reporting, due diligence, and more.

GeoSpy.ai is a web-based geospatial intelligence platform that provides users with access to a variety of geospatial data and tools. The platform allows users to create and share maps, analyze data, and collaborate with others. GeoSpy.ai is used by a variety of professionals, including law enforcement, intelligence analysts, and environmental scientists.

HEAVY.AI is a cutting-edge analytics and location intelligence platform that empowers users to make time-sensitive, high-impact decisions over vast datasets. The platform offers Conversational Analytics, enabling users to ask questions about their data in natural language and view actionable visualizations instantly. With HeavyEco, the platform also supports emergency response efforts by streamlining the management of weather events. HEAVY.AI combines interactive visual analytics, hardware-accelerated SQL, and advanced analytics & data science framework to uncover hidden opportunities and risks within enterprise datasets.

Pointly is an intelligent, cloud-based B2B software solution that enables efficient automatic and advanced manual classification in 3D point clouds. It offers innovative AI techniques for fast and precise data classification and vectorization, transforming point cloud analysis into an enjoyable and efficient workflow. Pointly provides standard and custom classifiers, tools for classification and vectorization, API and on-premise classification options, collaboration features, secure cloud processing, and scalability for handling large-scale point cloud data.

FlyPix is an AI-enabled geospatial solutions platform that leverages advanced AI technology to transform object detection, localization, tracking, and monitoring in the field of geospatial technology. The platform offers a wide range of capabilities, including AI-driven object analysis, change and anomaly detection, dynamic tracking, and custom use cases tailored to meet unique industry needs. FlyPix aims to provide unparalleled precision and efficiency in operations by converting complex imagery into actionable, geo-referenced insights.

Bayanat is an AI-powered geospatial intelligence company that offers predictive intelligence solutions, smart operations solutions, and smart mobility solutions to various sectors such as defense, environment, energy & resources, smart cities, and transportation. With over 50 years of experience, Bayanat provides high-quality geospatial data, geo-intelligence, and AI-powered data analytics to drive human progress and create game-changing advantages for its clients in the UAE, the Middle East, and beyond.

Picterra is a geospatial AI platform that offers reliable solutions for sustainability, compliance, monitoring, and verification. It provides an all-in-one plot monitoring system, professional services, and interactive tours. Users can build custom AI models to detect objects, changes, or patterns using various geospatial imagery data. Picterra aims to revolutionize geospatial analysis with its category-leading AI technology, enabling users to solve challenges swiftly, collaborate more effectively, and scale further.

Terragentic is an AI-driven geospatial technology company that empowers sustainable resource management and transformative decision-making. They provide cutting-edge geospatial services, precise mapping, advanced data analytics, and innovative applications of artificial intelligence to solve complex challenges across diverse sectors. Terragentic is committed to environmental stewardship, ethical business practices, and delivering high-quality, AI-enhanced, accurate, and actionable geospatial intelligence to empower industries.

Geolocation-OSINT is a repository that provides a comprehensive list of resources, tools, and platforms for geolocation challenges and open-source intelligence. It includes a wide range of mapping services, image search tools, AI-powered geolocation estimators, and satellite imagery archives. The repository covers various aspects of geolocation, from finding GPS coordinates to estimating the size of objects in images. Users can access tools for social media monitoring, street-level imagery, and geospatial analysis. Geolocation-OSINT is a valuable resource for individuals interested in geolocation, mapping, and intelligence gathering.

geoai is a Python package designed for utilizing Artificial Intelligence (AI) in the context of geospatial data. It allows users to visualize various types of geospatial data such as vector, raster, and LiDAR data. Additionally, the package offers functionalities for segmenting remote sensing imagery using the Segment Anything Model and classifying remote sensing imagery with deep learning models. With a focus on geospatial AI applications, geoai provides a versatile tool for processing and analyzing spatial data with the power of AI.

FarmVibes.AI is a repository focused on developing multi-modal geospatial machine learning models for agriculture and sustainability. It enables users to fuse various geospatial and spatiotemporal datasets, such as satellite imagery, drone imagery, and weather data, to generate robust insights for agriculture-related problems. The repository provides fusion workflows, data preparation tools, model training notebooks, and an inference engine to facilitate the creation of geospatial models tailored for agriculture and farming. Users can interact with the tools via a local cluster, REST API, or a Python client, and the repository includes documentation and notebook examples to guide users in utilizing FarmVibes.AI for tasks like harvest date detection, climate impact estimation, micro climate prediction, and crop identification.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

Geoweaver is an in-browser software that enables users to easily compose and execute full-stack data processing workflows using online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries. It provides server management, code repository, workflow orchestration software, and history recording capabilities. Users can run it from both local and remote machines. Geoweaver aims to make data processing workflows manageable for non-coder scientists and preserve model run history. It offers features like progress storage, organization, SSH connection to external servers, and a web UI with Python support.

fAIr is an open AI-assisted mapping service developed by the Humanitarian OpenStreetMap Team (HOT) to improve mapping efficiency and accuracy for humanitarian purposes. It uses AI models, specifically computer vision techniques, to detect objects like buildings, roads, waterways, and trees from satellite and UAV imagery. The service allows OSM community members to create and train their own AI models for mapping in their region of interest and ensures models are relevant to local communities. Constant feedback loop with local communities helps eliminate model biases and improve model accuracy.

This repository contains the official code for the paper 'Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning'. It provides tools for point cloud segmentation experiments based on different settings, tree parameters extraction, handling large point clouds through tiling, predicting, and merging workflows. Additionally, it includes commands for training, testing, and evaluating the models, along with the necessary datasets and pretrained models.

The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as a repository of AI-ready Earth Observation (EO) datasets. It can be easily applied for a variety of Earth Observation tasks, such as land use and cover classification, crop type prediction, localization of specific objects (semantic segmentation), etc. The main goal of AiTLAS is to facilitate better usability and adoption of novel AI methods (and models) by EO experts, while offering easy access and standardized format of EO datasets to AI experts which allows benchmarking of various existing and novel AI methods tailored for EO data.

AI-TOD is a dataset for tiny object detection in aerial images, containing 700,621 object instances across 28,036 images. Objects in AI-TOD are smaller with a mean size of 12.8 pixels compared to other aerial image datasets. To use AI-TOD, download xView training set and AI-TOD_wo_xview, then generate the complete dataset using the provided synthesis tool. The dataset is publicly available for academic and research purposes under CC BY-NC-SA 4.0 license.

Rapid is a web-based modern editor for OpenStreetMap. It integrates advanced mapping tools, authoritative geospatial open data, and cutting-edge technology to empower mappers at all levels to get started quickly, making accurate and fresh edits to maps. Rapid is enhanced with authoritative open data sources and AI-generated roads from the Facebook Map With AI service + buildings from Microsoft open buildings dataset to make adding and editing roads, buildings, and more quick and simple. Rapid also includes data integrity checks to ensure that new map edits are consistent and accurate.

The Microsoft AI for Earth program hosts geospatial data on Azure that is important to environmental sustainability and Earth science. This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth. It also serves as a "staging ground" for the Planetary Computer Data Catalog.

Top AI Tools is a comprehensive, community-curated directory that aims to catalog and showcase the most outstanding AI-powered products. This index is not exhaustive, but rather a compilation of our research and contributions from the community.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Extractous offers a fast and efficient solution for extracting content and metadata from various document types such as PDF, Word, HTML, and many other formats. It is built with Rust, providing high performance, memory safety, and multi-threading capabilities. The tool eliminates the need for external services or APIs, making data processing pipelines faster and more efficient. It supports multiple file formats, including Microsoft Office, OpenOffice, PDF, spreadsheets, web documents, e-books, text files, images, and email formats. Extractous provides a clear and simple API for extracting text and metadata content, with upcoming support for JavaScript/TypeScript. It is free for commercial use under the Apache 2.0 License.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

Awesome-TimeSeries-SpatioTemporal-LM-LLM is a curated list of Large (Language) Models and Foundation Models for Temporal Data, including Time Series, Spatio-temporal, and Event Data. The repository aims to summarize recent advances in Large Models and Foundation Models for Time Series and Spatio-Temporal Data with resources such as papers, code, and data. It covers various applications like General Time Series Analysis, Transportation, Finance, Healthcare, Event Analysis, Climate, Video Data, and more. The repository also includes related resources, surveys, and papers on Large Language Models, Foundation Models, and their applications in AIOps.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

Enhanced Geolocation Intelligence Expert

生成 GPS 的 GPT

I analyze Street View images to guess countries and cities.

Explains SAR technology for elevation monitoring.

Build geospatial mixed-reality experiences for live events using Fabric's Platform

ArcPy specialist for ESRI's ArcGIS applications.

Expert in GIS, guiding users through learning, troubleshooting, automation and practical applications.