Google Satellite will not zoom. Although the scale changes as I zoom, as the map is re-rendered, it zooms out to its maximum extent every time.
This first happened in the latter part of November 2014 and I was able to fix it using unibasil's answer Misplaced Google Maps with OpenLayers plugin in QGIS?.
Unfortunately, Friday morning it started happening again. I can no longer zoom on any Google maps (Physical, Street, Hybrid, or Satellite). Although Bing maps work fine, Bing is not as up to date as Google maps.
Currently I am using QGIS 2.2 with the latest OpenLayers 1.1.4 that will work with that QGIS version. I also installed the newest version of QGIS 2.6.1 which uses OpenLayers 1.3.5 and it also will not zoom on any Google Maps.
I tried uninstalling and re-installing the OpenLayers plugin several times with same results. I also tried recopying the OpenLayers.js file as recommended by Unibasil (see above) with no success.
One more interesting clue is that my friend, who also uses Google Maps in QGIS 2.2, is not having this problem. The only difference I can tell is that he has not logged out of QGIS or removed the Google Satellite layer since last Thursday. I unfortunately log out every night. I believe if he were to remove and add Google Satellite layer, it would not be able to zoom either.
I have searched and have not found any recent posting on this problem. The couple old posting I have found do not solve the problem. I hope someone can help.
Open Layer 1.3.6 finally seems to have solved the problem.
After seeing underdark's comment, I tried using Ubuntu with QGIS 2.4. At first it didn't work, but after reinstalling openlayers, I was able to load Google Satellite and zoom in. But I couldn't zoom in past 1:2300 on Bing maps.
So I did some more searching and found a post on QGIS project wiki - http://hub.qgis.org/issues/11728#change-58357 - that indicated that the problem may have something to do with using the 64bit version of QGIS. After reinstalling QGIS 2.2 32 bit version, the problem solved and I am now able to zoom on Google Maps.
I need to be able to zoom in close (1:100) on both Bing and Google. Using QGIS version 2.2 I can zoom into a scale of 1:1000 on Bing maps while QGIS 2.4 or 2.6 only allows me to zoom to 1:2300 on Bing. Maybe this has more to do with the version of openlayers. QGIS 2.2 uses openlayers 1.1.4 while QGIS version 2.4 uses openlayers 1.3.5.
I tried Terry's (thank you!) solution on my MAC and on my PC (windows).
Terry's solution works fine on windows, although slower than on more recent versions of QGIS. Make sure to download the 32 bit version of QGIS! As stated by Terry, the 64 bit version will not work with the openlayers plugin.
For MAC users, QGIS can only be downloaded in the 64 bit version and the openlayers plugin will therefore not work properly. If you are using a mac, you can use other satellite imagery or you can another trick that I found here on any version of QGIS.
There seem to be a string of questions posed which seek resolution of problems with the OpenLayers and [often] Google Satellite.
I thought I had landed on what seemed to cure the problem: After creating the layer using Google Satellite, I moved that layer to the bottom, as a base map. After that, the pan and zoom issues seem to disappear. I am using QGIS 2.6.1 64k on Win 8, with OpenLayers 1.3.5.
At the end of my work, I closed and saved the project. The next morning, I opened the project and discovered that the google satellite layer, will only display the full earth view, and will not settle on the region of the other layers. I played with closing/opening the project, turning off other layers, and it gets all funky. The programmer in me is not soothed by the non-reproducible nature of this bug, in the various forms it presents itself
QGIS OpenLayers 3 Google Maps not zooming - Geographic Information Systems
GIS APIs: GIS Application Programming Interfaces are collections of library modules that resemble various functionalities of GIS software through programming
GIService: Geographic Information Service
As GIS evolved from desktop packages to distributed solution(s), API has become a popular option for developing customized GIS applications (Chow, 2008). Over a web platform, GIS APIs provide a communication protocol to handle client requests and return the processed response back from a server that provides GIS functionalities and/or datasets as a service (i.e., GIService) (Yue, Ramachandran, & Baumann, 2015). The advantage of communicating GIS requests and responses through an API is to enable interoperability across platforms, systems, and devices. It also empowers a light-client architecture so that a client (e.g., a web browser) can process, analyze, and visualize distributed geographic information with no prior GIS installation or even plug-in(s). GIS APIs are also scalable in that developers can import specific GIS APIs, with or without parallelization, needed for a certain GIS application (Rey, Anselin, Pahle, Kang, & Stephens, 2013). This is consistent with the development of service-oriented architecture in software design, where services are provided as application components to minimize the dependency between different components when designing a large software product (Bouguettaya, Sheng, & Daniel, 2014).
Given the origin of GIS APIs, it is not surprising that desktop GIS developers, such as Esri, QGIS, and GRASS GIS, built their GIS APIs to incorporate many functionalities of their desktop counterparts. However, GIS APIs from other developers, such as Google, remain limited in terms of tools and GIS functionalities. Moreover, some GIS APIs are designed to be developed into a web application (i.e., “online” web mapping) or a customized desktop solution. For example, the ArcPy package developed based on Python is often used for customizing desktop GIS tools. Because GIS APIs evolved from desktop GIS, it is perhaps useful to discuss existing GIS APIs in terms of their functionalities for the “capture, storage, transformation, retrieval, analysis, and display of spatial data” (Clarke, 2003). A common function of GIS APIs is the retrieval and display of spatial data with a dynamic map navigation interface. To many users, being able to view, explore, and overlay map layers is sufficient for basic applications. Another common function of GIS APIs is geocoding (i.e., address matching)- the act of assigning a x- and y-coordinate based on a postal address or a place name. The geocoding function (and sometimes reverse-geocoding) is useful because a significant portion of “Big Data” contains some spatial references, such as spatial coordinates, place names, or geographic metadata (Leszczynski & Crampton, 2016). A few APIs specialize in parsing and geocoding large and heterogeneous data (e.g., Texas A&M Geocoding API, Geoname API, GeoPy).
In the digital era, there has been an overwhelming inundation of geographic data made available through the advancement of remote sensing technologies, crowdsourcing, social media, GPS-enabled smart sensors, Internet of Things (IoT), etc. This creates a large demand for transforming the captured geospatial data into interoperable formats for dissemination and integration. Many data APIs enrich GIS APIs by providing supplementary gateways to query geographic data, including government records (e.g., Census Bureau APIs), social media (e.g., Twitter APIs), private sources (e.g., Google Data APIs), open sources (e.g., Overpass API), etc. The availability of GIS data from multiple sources also presents an opportunity to analyze their geographic distribution, spatial relationship, temporal trend, and semantic pattern. Some APIs (e.g. scikit-learn, TensorFlow API) specialize in analytical functions, like spatial, statistical, mathematical, or machine-learning functions.
Similar to desktop GIS software packages, some GIS APIs are developed by commercial vendors whereas some originated from Free and Open Source Software (FOSS) projects (Table 1). Although commercial GIS APIs may require paid subscriptions, these products often have free versions with reduced functionalities or usage limits. It is important to note that many GIS or data APIs are available in different programming languages. For instance, Twitter allows API access from various popular languages, such as Python, R, or Java. Altogether, these GIS APIs provide the building blocks to develop distributed GIS applications. Besides the GIS APIs listed in Table 1 and a select few that are briefly discussed in the following sections, other GIS APIs include Shapely, Geopandas, Carto, Turf, here, cisco location APIs, Estimote, etc.
3.1 Esri ArcGIS APIs
Esri provides several Python-based APIs for customization. For example, ArcPy is a Python package that provides an effective way to access the data types, spatial analysis functions, and geoprocessing tools in ArcMap through various Python functions, classes, and modules. These ArcPy Python functions correspond to the tools in ArcToolbox, hence, manipulating vector, raster, and tabular data in ArcPy is straight-forward for an experienced ArcMap user with basic Python knowledge. Another Python-based library is “ArcGIS API for Python”, which provides a high-level encapsulation of ArcGIS functionalities (e.g., managing, creating, and analyzing GIS data) for developing web GIS applications. It is implemented using the online and web GIS platform provided by ArcGIS Online and ArcGIS Enterprise, and is also compatible with the new platform ArcGIS Pro. Compared to desktop-based ArcPy, “ArcGIS API for Python” provides a simple solution for integrating ArcGIS into web application development.
3.2 QGIS APIs
QGIS, a continuously growing FOSS GIS project, also offers a Python API to implement its versatile GIS engine for building customized applications. Similar to Esri ArcPy, QGIS APIs offer a versatile package of many GIS functionalities and can process various GIS data models (e.g., vector, raster, database) and formats (e.g., Shapefile, JSON, GeoTiff, etc.). Although QGIS APIs are not designed to develop web applications, there are plug-ins (e.g., qgis2web) that can help QGIS interface with other web GIS APIs like OpenLayers and Leaflet.
3.3 Google Maps APIs
3.4 Microsoft Bing Maps APIs
3.5 OpenLayers API
3.6 Leaflet API
There are other APIs that provide either geographic data or analytical services (e.g., machine learning) that can supplement GIS APIs in the development of advanced GIS applications (Table 2). While some APIs (e.g. OpenStreetMap APIs, Census Bureau APIs), can deliver GIS data, it is noted that some APIs (e.g. Twitter APIs, WhitePages API) can only retrieve data with geographic reference (e.g. latitude/longitude or postal address) that are not necessarily in GIS data format. It requires additional effort to parse and process, such as geocoding, displaying latitude/longitude, joining data with existing GIS data like census units) in order to visualize them in GIS for further analysis. Even though some APIs, such as Scikit learn or TensorFlow, are scientific toolkits, they are included in this discussion to illustrate a broader framework of API integration.
|Name||Primary Function(s) related to GIS APIs||Programming Language(s)||Documentation|
|Twitter APIs||Data||REST||Twitter APIs|
|Flickr API||Data||REST||Flickr APIs|
|OpenStreetMap API||Data||REST||OpenStreetMap API|
|Census Bureau APIs||Data||REST||Census Bureau APIs|
|WhitePages API||Data||REST||WhitePages Pro API|
|Scikit-learn API||Analytics||Python||Scikit-learn API|
4.1 Twitter APIs
The standard Twitter APIs include basic functions such as streaming and searching, whereas more advanced functionalities, such as conducting complex queries and metadata enrichments (e.g., to retrieve improved profile information), are provided in the Premium APIs and Enterprise APIs. Most non-commercial applications of Twitter use the free standard APIs to collect data. The featured functionalities of the free APIs include: collecting real-time streaming data, searching tweets within 7 days, filtering and sampling tweets, retrieving basic user profile information, etc. It is important to note the limitation of free standard APIs before implementing them. First, there is a limit on the number of requests made per 15 minutes. Second, the standard APIs can only obtain around 1% of all tweets, which raises questions of data completeness.
4.2 OpenStreetMap API
OpenStreetMap (OSM) adopts the same collaborative model as Wikipedia, creating a free and editable map project that is available to users all over the world. The map data from OSM is crowdsourced from users and considered the most valuable output of this project. OSM provides a REST API to retrieve, edit, and save the raw geodata to/from the back-end database. Users are able to specify the target area to download using a bounding box or more complicated queries. The downloaded data can be saved as an .osm file, which is an XML-based file format that can be converted to Esri shapefiles using open source GIS tools such as QGIS.
4.3 U.S. Census Bureau APIs
As a U.S. federal agency, the Census Bureau disseminates publicly available demographic datasets through their APIs, including TIGERweb, decennial Censuses, the American Community Survey, economic surveys, etc. Many of these APIs provide access to a specific dataset via RESTful web services and return a JSON object for parsing.
4.4 Scikit-learn APIs
Built upon mathematical Python libraries like NumPy, SciPy, and matplotlib, Scikit-learn is a Python package that provides statistical and data mining tools, including generalized linear models, Naïve Bayes classifications, decision trees, ensemble methods, Support Vector Machines, neural networks, etc. While Scikit-learn is designed for general scientific investigation, these algorithms are useful for conducting cluster analysis, feature extraction, geovisualization, pattern recognition, and prediction common in GIScience research.
4.5 TensorFlow API
TensorFlow is a deep learning Python package developed by Google for advanced Neural Network (NN) modeling. This open-source library is built upon Keras, a high-level API specification that uses layers to organize the input data, configure neuron weights, and setup the activation function to build a convolution NN model. In addition to multi-language support, this API is also flexible in offering a low-level API for experienced developers and also a Lite version for mobile devices. This deep learning API expands the array of analytical tools to be integrated with GIS APIs.
5.2 Loading Google Maps APIs
5.3 Applying API classes, functions, and tools
In this example, our goal is to create a marker for each of the seven wonders, and when clicking on a marker, an info-window with the description of the wonder will display. There are three main classes used in this case study: map, marker, and infowindow. The specific attributes and methods of these classes can be found in the API documentation (Google, 2018).
First, we created a basic map object as a container of the markers (Figure 2), then we populated an array with the description of the image address for each wonder. Next, using a for loop, we created the marker and infowindow for each wonder (Figure 3). Note that we also registered a “click” event for each marker so that when clicking on the marker, an infowindow with description will display. Figure 4 shows the final product.
Figure 2. Example code – creating a map object.
Figure 3. Example code – creating info windows in a for loop.
Figure 4. An example of a web mapping application created using Google Maps API.
APIs provide a flexible way for software development and component integration. In particular, GIS APIs provide a visualization and analytical platform to explore the underlying pattern and formulate questions about the relationship between form and process. In light of the distribution of spatial-data based products, spatial data infrastructure, and cloud computing, GIS APIs are an important component that shapes the continual development of future GIS for multi-disciplinary scientific investigation.
Chow, T. E. (2008). The potential of maps APIs for Internet GIS Applications. Transactions in GIS, 12(2), 179-191. DOI: 10.1111/j.1467-9671.2008.01094.x
Clarke, K. C. (2003). Getting Started with GIS (4th ed.). Upper Saddle River, New Jersey, USA: Prentice Hall.
ESRI. (2018). ArcGIS Developer Program Pricing. Retrieved Dec 7, 2018, from ArcGIS for Developer: https://developers.arcgis.com/pricing/credits/
Google. (2018). Pricing for Maps, Routes and Places. Retrieved Dec 7, 2018, from Google Cloud: https://cloud.google.com/maps-platform/pricing/sheet/
Leszczynski, A., & Crampton, J. (2016). Introduction: Spatial Big Data and everyday life. Big Data & Society, July–December, 1-6. DOI: 10.1177/2053951716661366
Rey, S. R., Anselin, L., Pahle, R., Kang, X., & Stephens, P. (2013). Parallel optimal choropleth map classification in PySAL. International Journal of Geographic Information Science, 27(5), 1023-1039. DOI: 10.1080/13658816.2012.752094
Yue, P., Ramachandran, R., & Baumann, P. (2015). Intelligent GIServices. Earth Science Informatics, 8(3), 461-462. DOI: 10.1007/s12145-015-0237-z
Machine Learning in GIS : Understand the Theory and Practice
This course is designed to equip you with the theoretical and practical knowledge of Machine Learning as applied for geospatial analysis, namely Geographic Information Systems (GIS) and Remote Sensing. By the end of the course, you will feel confident and completely understand the Machine Learning applications in GIS technology and how to use Machine Learning algorithms for various geospatial tasks, such as land use and land cover mapping (classifications) and object-based image analysis (segmentation). This course will also prepare you for using GIS with open source and free software tools.
In the course, you will be able to apply such Machine Learning algorithms as Random Forest, Support Vector Machines and Decision Trees (and others) for classification of satellite imagery. On top of that, you will practice GIS by completing an entire GIS project by exploring the power of Machine Learning, cloud computing and Big Data analysis using Google Erath Engine for any geographic area in the world.
The course is ideal for professionals such as geographers, programmers, social scientists, geologists, and all other experts who need to use maps in their field and would like to learn more about Machine Learning in GIS. If you're planning to undertake a task that requires to use a state of the art Machine Learning algorithms for creating, for instance, land cover and land use maps, this course will give you the confidence you need to understand and solve such geospatial problem.
One important part of the course is the practical exercises. You will be given some precise instructions and datasets to create maps based on Machine Learning algorithms using the QGIS software and Google Earth Engine.
In this course, I include downloadable practical materials that will teach you:
- How to install open source GIS (QGIS, OTB toolbox) software on your computer and correctly configure it
- QGIS software interface including its main components and plug-ins
- Learn how to classify satellite images with different machine learning algorithms (random forest, support vector machines, decision trees and so on) in QGIS
- Learn how to perform image segmentation in QGIS
- Learn how to prepare your first land cover map using the cloud computing Google Earth Engine Platform.
Stacks: MEAN, Open Geo-Stack, LAMP, WISA, Python/Django Technologies - Drone Imagery Processing, Point Cloud, Geo Tiff processing, Potree - GIS: GeoDjango, Mapserver, GeoServer, PostGIS, PostgreSQL, OpenLayers 2/3, Leaflet, Mapbox, OSM, Google maps, Here and Bing Maps - Web: Python, Django, PHP, ASP.NET MVC, Node.js, AngularJS, AngularJS 2/4, D3.js, React / Redux - Mobile: iOS (ARKIT), Android, Cross platform (Ionic 3, React Native, Phonegap, Xamarin) - Deployments: Nginx, Docker, Apache, AWS - AWS: Elastic Containers, Elastic Load Balancers, Elastic Auto Scale, S3 buckets, Cloud Front and Root53 - Searching Algorithms: Elastic.
GeoJSON Google Maps
Data Layer: Drag and Drop GeoJSON, alert("Not a GeoJSON file!") > zoom(map) > /** * Update a map's viewport to fit each geometry in a dataset */ function zoom(map: google.maps. GeoJSON is an extension of the JSON data format and represents geographical data. Using this utility, you can store geographical features in GeoJSON format and render them as a layer on top of the
Machine Learning in GIS and Remote Sensing: 5 Courses in 1
This course is designed to equip you with the theoretical and practical knowledge of Machine Learning and Deep Learning in QGIS and ArcGIS as applied for geospatial analysis, namely Geographic Information Systems (GIS) and Remote Sensing. By the end of the course, you will feel confident and completely understand the Machine and Deep Learning applications in Remote Sensing & GIS technology and how to use Machine and Deep Learning algorithms for various Remote Sensing & GIS tasks, such as land use and land cover mapping (classifications) and object-based image analysis (segmentation, object detection) and regression modeling in QGIS and ArcGIS software. This course will also prepare you for using GIS with open source and free tools (QGIS) and a market-leading software (ArcGIS).
This course is designed to take users who use QGIS & ArcGIS for basic geospatial data/GIS/Remote Sensing analysis to perform more advanced geospatial analysis tasks including object-based image analysis using a variety of different data and applying Deep Learning & Machine Learning state of the art algorithms. In addition to making you proficient in QGIS for spatial data analysis, you will be introduced to another powerful processing toolbox – Orfeo Toolbox, and to the exciting capabilities of ArcMap and ArcGIS PRO!
In the course, you will be able to apply such Machine Learning algorithms as Random Forest, Support Vector Machines, Decision Trees, Convolutional Neural Networks (and others) for Remote Sensing and geospatial tasks. You will also learn how to conduct regression modeling for GIS tasks in ArcGIS. On top of that, you will practice GIS & Remote Sensing by completing two independent GIS projects by exploring the power of Machine Learning and Deep Learning analysis in QGIS and ArcGIS.
This course is different from other training resources. Each lecture seeks to enhance your GIS and Remote Sensing skills in a demonstrable and easy-to-follow manner and provide you with practically implementable solutions. You’ll be able to start analyzing spatial data for your projects and gain appreciation from your future employers with your advanced GIS & Remote Sensing skills and knowledge of cutting-edge geospatial methods.
The course is ideal for professionals such as geographers, programmers, social scientists, geologists, GIS & Remote Sensing experts, and all other experts who need to use maps in their field and would like to learn more about Machine Learning in GIS.
One important part of the course is the practical exercises. You will be given some precise instructions and datasets to create maps based on Machine Learning algorithms using the QGIS and ArcGIS software tools.
QGIS OpenLayers 3 Google Maps not zooming - Geographic Information Systems
Geographic Information Systems
Geospatial Analyses & Remote Sensing : from Beginner to Pro
Description Geospatial Data Analyses & Remote Sensing: 5 Classes in 1 Do you need to design a GIS map or satellite-imagery based map for your Remote Sensing or GIS project but you don't know how to do this? Have you heard about Remote Sensing object-based image analysis and machine learning or maybe QGIS or Google Earth Engine but did not know where to start with such analyses? Do you find Remote Sensing and GIS manuals too not practical and looking for a course that takes you by hand, teach you all the concepts, and get you started on a real-life GIS mapping project? I'm very excited that you found my Practical Geospatial Masterclass on Geospatial Data Analyses & Remote Sensing. This course provides and information that is usually delivered in 4 separate Geospatial Data Analyses & Remote Sensing courses, and thus you with learning all the necessary information to start and advance with Geospatial analysis and includes more than 9 hours of video content, plenty of practical analysis, and downloadable materials.
NVIDIA is Making the Largest 3D Map of the Universe
Reportedly the world's fastest supercomputer, Perlmutter, has been powered up at the National Energy Research Scientific Computing Center (NERSC). Packing 6159 NVIDIA A100 Tensor Core GPUs, one of the supercomputer's first projects is to build the largest 3D map of the Universe. To make the world's largest 3D map of the Universe, the Perlmutter will use data from the Dark Energy Spectroscopic (DESI). DESI is an instrument used to capture pictures of deep space and can capture more than 5,000 galaxies in one picture. In a post on the NVIDIA blog, the company stated that using the power of NVIDIA's A100 Tensor Core GPUs, researchers can process the images from on night so that they know where to point DESI the next time.
Google Maps to add more detailed maps, crowd indicators, better routing and more – TechCrunch
Google has announced a series of updates soon coming to Google Maps, as part of the company's larger goal of delivering over 100 A.I.-powered improvements to the platform by year-end. Among the new improvements, detailed during Google I/O's developer conference this week, are new routing updates, Live View enhancements, an expansion of detailed street maps, a new "area busyness" feature, and a more personalized Maps experience. The new routing updates will involve the use of machine learning and navigation information to help reduce "hard-braking moments" -- meaning, those times when traffic suddenly slows, and you have to slam on your brakes. Today, when you get your directions in Maps, Google calculates multiple route options based on a variety of factors, like how many lanes a road has or how direct the route is. With the update, it will add one more: which routes are least likely to cause a "hard-braking moment."
Google Maps adds indoor AR directions and prioritizes eco-friendly routes
Google has been working hard to make Maps a useful tool for navigating the world and it's continuing to roll out new features. Today, the company is unveiling a set of updates that should make the app more helpful in more scenarios. For one thing, it's bringing its AR navigation tool Live View to some indoor locations like select malls, airports and transit stations. As a recap, Live View is an AR feature that let you see exactly where your destination is by pointing your camera at your surroundings and overlaying directions on the scene. To make that work indoors though, Google had to "develop an entirely new technology" that it's calling "global localization."
The science and technology that can help save the ocean
Here on Earth, we have more detailed maps of Mars than of our own ocean, and that's a problem. A massive force for surviving climate change, the ocean absorbs 90% of the heat caused by emissions and generates 50% of the oxygen we breathe. "We have the ocean to thank for so many aspects of our safety and well-being," says Dawn Wright, oceanographer and chief scientist at geographic information system (GIS) provider Esri, who notes the ocean also provides renewable energy, a major food source, and a transportation corridor for not only ships but submarine internet cables. Now, the same type of smart maps and geospatial technology guiding outer space exploration support the quest to better understand and protect our ocean. "For the first time, our knowledge of the ocean can approach our knowledge of the land," Wright says.
Google Maps uses AI to better predict when there's a massive traffic jam
Google confirmed this week that more than 1 billion kilometres are driven with Google Maps in more than 220 countries and territories. That's a lot of traffic data to digest. Yet somehow, Google Maps can you show instant traffic updates from the moment you start navigating. Which direction to take, how long the trip will take, whether traffic along the route is heavy or light, and so much more. While all of this appears simple, there's a ton going on behind the scenes which enable Google Maps to crunch the numbers and get you from Point A to Point B safely and on time.
Google Maps and AI: getting you where you want to go - quicker than ever before -- AI Daily - Artificial Intelligence News
Like other companies using preference-based algorithms, Google are even hoping to introduce a TikTok style "for you page", recommending new restaurants, landmarks and shops based on personal preferences, as well as directing the user on how to go there. To do so, a "Match Score" system determines your likelihood of actually being interested in this recommendation. In addition to this, Google already use algorithms to suggest the quickest routes based on user traffic, through location services enabled on their users' phones, whilst the company are pushing to improve accessibility by catering directions and suggestions to those with disabilities. Google Maps has over 1 billion users per month and to further grow this already massive number, AI will be integral to further improving and expanding the user's capabilities - from Live View to finding wheelchair-accessible navigation routes.
New Google Maps feature will show routes to nearest public transport
Google Maps is working on a new feature that will show you how to reach the nearest public transport connection, according to new leaked screenshots. The new Maps filter will let users choose what mode of transportation they will be using at the very beginning of their daily commute, the screenshots show. Once rolled out, the feature will allow commuters to work out their preferred route to various transport connections, such as the train station, when they return to the workplace after the coronavirus pandemic. The screenshots also reveal an option to get more accurate Uber fares using data from Google Maps and a slightly new design for the Maps interface. 'Google Maps is working on route options with "Connections to Public Transit", such as car and transit, bicycle and transit, auto rickshaw, ride service [and] motorcycle and transit,' said Jane Wong, a Hong Kong-based hacker, tech blogger and software engineer, who leaked the screenshots.
How to Create a Location Based App Geolocation application ideas
The mobile app development industry is taking the world by storm, with the new technologies trending across the market. Geolocation is one such trend that is predicted to reach a revenue of $40 billion by 2024 for the location-based service market, according to MarketsandMarkets report. Geolocation applications open up new opportunities for entrepreneurs to explore. They are also a gateway for the service industry to improve customer experience and interact with their user base. The rising number of location-based apps, like on-demand service apps, is proof that geolocation is quintessential to survival in the mobile app market.
Experiments on route choice set generation using a large GPS trajectory set
Several route choice models developed in the literature were based on a relatively small number of observations. With the extensive use of tracking devices in recent surveys, there is a possibility to obtain insights with respect to the traveler's choice behavior. In this paper, different path generation algorithms are evaluated using a large GPS trajectory dataset. The dataset contains 6,000 observations from Tel-Aviv metropolitan area. An initial analysis is performed by generating a single route based on the shortest path. Almost 60% percent of the 6,000 observations can be covered (assuming a threshold of 80% overlap) using a single path. This result significantly contrasts previous literature findings. Link penalty, link elimination, simulation and via-node methods are applied to generate route sets, and the consistency of the algorithms are compared. A modified link penalty method, which accounts for preference of using higher hierarchical roads, provides a route set with 97% coverage (80% overlap threshold). The via-node method produces route set with satisfying coverage, and generates routes that are more heterogeneous (in terms number of links and routes ratio).
Google Maps first started as a C++ program designed by two Danish brothers, Lars and Jens Eilstrup Rasmussen, and Noel Gordon and Stephen Ma, at the Sydney-based company Where 2 Technologies. It was first designed to be separately downloaded by users, but the company later pitched the idea for a purely Web-based product to Google management, changing the method of distribution.  In October 2004, the company was acquired by Google Inc.  where it transformed into the web application Google Maps.
In the same month, Google acquired Keyhole, a geospatial data visualization company (with investment from the CIA), whose marquee application suite, Earth Viewer, emerged as the highly successful Google Earth application in 2005 while other aspects of its core technology were integrated into Google Maps.  In September 2004, Google acquired ZipDash, a company that provided realtime traffic analysis. 
The launch of Google Maps was first announced on the Google Blog on February 8, 2005. 
In September 2005, in the aftermath of Hurricane Katrina, Google Maps quickly updated its satellite imagery of New Orleans to allow users to view the extent of the flooding in various parts of that city.  
On November 28, 2007, Google Maps for Mobile 2.0 was released.    It featured a beta version of a "My Location" feature, which uses the GPS / Assisted GPS location of the mobile device, if available, supplemented by determining the nearest wireless networks and cell sites.   The software looks up the location of the cell site using a database of known wireless networks and sites.   By triangulating the different signal strengths from cell transmitters and then using their location property (retrieved from the database), My Location determines the user's current location. 
On September 23, 2008, coinciding with the announcement of the first commercial Android device, Google announced that a Google Maps app had been released for its Android operating system.  
In October 2009, Google replaced Tele Atlas as their primary supplier of geospatial data in the US version of Maps and used their own data. 
On April 19, 2011, Map Maker was added to the American version of Google Maps, allowing any viewer to edit and add changes to Google Maps. This provides Google with local map updates almost in real-time instead of waiting for digital map data companies to release more infrequent updates.
On January 31, 2012, Google, due to offering its Maps for free, was found guilty of abusing the dominant position of its Google Maps application and ordered by a court to pay a fine and damages to Bottin Cartographer, a French mapping company.  This ruling was overturned on appeal. 
In June 2012, Google started mapping Britain's rivers and canals in partnership with the Canal and River Trust. The company has stated that it would update the program during the year to allow users to plan trips which include locks, bridges and towpaths along the 2,000 miles of river paths in the UK. 
In December 2012, the Google Maps application was separately made available in the App Store, after Apple removed it from its default installation of the mobile operating system version iOS 6 in September 2012. 
On January 29, 2013, Google Maps was updated to include a map of North Korea.  As of May 3, 2013 [update] , Google Maps recognizes Palestine as a country, instead of redirecting to the Palestinian territories. 
In August 2013, Google Maps removed the Wikipedia Layer, which provided links to Wikipedia content about locations shown in Google Maps using Wikipedia geocodes. 
On April 12, 2014, Google Maps was updated to reflect the 2014 Crimean crisis. Crimea is shown as the Republic of Crimea in Russia and as the Autonomous Republic of Crimea in Ukraine. All other versions show a dotted disputed border. 
In April 2015, on a map near the Pakistani city of Rawalpindi, the imagery of the Android logo urinating on the Apple logo was added via Map Maker and appeared on Google Maps. The vandalism was soon removed and Google publicly apologized.  However, as a result, Google disabled user moderation on Map Maker, and on May 12, disabled editing worldwide until it could devise a new policy for approving edits and avoiding vandalism. 
On April 29, 2015, users of the classic Google Maps were forwarded to the new Google Maps with the option to be removed from the interface. 
On July 14, 2015, the Chinese name for Scarborough Shoal was removed after a petition from the Philippines was posted on Change.org. 
On June 27, 2016, Google rolled out new satellite imagery worldwide sourced from Landsat 8, comprising over 700 trillion pixels of new data.  In September 2016, Google Maps acquired mapping analytics startup Urban Engines. 
In 2016, the Government of South Korea offered Google conditional access to the country's geographic database – access that already allows indigenous Korean mapping providers high-detail maps. Google declined the offer, as it was unwilling to accept restrictions on reducing the quality around locations the South Korean Government felt were sensitive. 
On October 16, 2017, Google Maps was updated with accessible imagery of several planets and moons such as Titan, Mercury, and Venus, as well as direct access to imagery of the Moon and Mars.  
In May 2018, Google announced major changes to the API structure starting June 11, 2018. This change consolidated the 18 different endpoints into three services and merged the basic and premium plans into one pay-as-you-go plan.  This meant a 1400% price raise for users on the basic plan, with only six weeks of notice. This caused a harsh reaction within the developers community.  In June, Google postponed the change date to July 16, 2018.
In August 2018, Google Maps designed its overall view (when zoomed out completely) into a 3D globe dropping the Mercator projection that projected the planet onto a flat surface. 
In January 2019, Google Maps added speed trap and speed camera alerts as reported by other users.  
On October 17, 2019, Google Maps was updated to include incident reporting, resembling a functionality in Waze which was acquired by Google in 2013. 
In December 2019, Incognito mode was added, allowing users to enter destinations without saving entries to their Google accounts. 
In February 2020, Maps received a 15th anniversary redesign.  It notably added a brand-new app icon, which now resembles the original icon in 2005.
On 23 September 2020, Google announced a COVID-19 Layer update for Google maps, which is designed to offer a seven-day average data of the total COVID-19-positive cases per 100,000 people in the area selected on the map. It also features a label indicating the rise and fall in the number of cases. 
In January 2021, Google announced that it will be launching a new feature which is displaying the COVID-19 vaccinations sites. 
In January 2021 Google announced updates to the route planner that will accommodate drivers of electric vehicles. Routing will take into account the type of vehicle, vehicle status including current charge, and the location of charging stations. 
Directions and transit Edit
Google Maps provides a route planner,  allowing users to find available directions through driving, public transportation, walking, or biking.  Google has partnered globally with over 800 public transportation providers to adopt General Transit Feed Specification (GTFS), making the data available to third parties.   The app can indicate users' transit route in an October 2019 update. The incognito mode, eyes-free walking navigation features were released earlier.  A July 2020 update provided bike share routes. 
Traffic conditions Edit
In 2007, Google began offering traffic data as a colored overlay on top of roads and motorways to represent the speed of vehicles on particular roads. Crowdsourcing is used to obtain the GPS-determined locations of a large number of cellphone users, from which live traffic maps are produced.   
Google has stated that the speed and location information it collects to calculate traffic conditions is anonymous.  Options available in each phone's settings allow users not to share information about their location with Google Maps.  Google stated, "Once you disable or opt out of My Location, Maps will not continue to send radio information back to Google servers to determine your handset's approximate location".  [ failed verification ]
Street View Edit
On May 25, 2007, Google released Google Street View, a new feature of Google Maps which provides 360° panoramic street-level views of various locations. On the date of release, the feature only included five cities in the US. It has since expanded to thousands of locations around the world. In July 2009, Google began mapping college campuses and surrounding paths and trails.
Street View garnered much controversy after its release because of privacy concerns about the uncensored nature of the panoramic photographs, although the views are only taken on public streets.   Since then, Google has begun blurring faces and license plates through automated facial recognition.   
In late 2014, Google launched Google Underwater Street View, including 2,300 kilometres (1,400 mi) of the Australian Great Barrier Reef in 3D. The images are taken by special cameras which turn 360 degrees and take shots every 3 seconds. 
In 2017, in both Google Maps and Google Earth, Street View navigation of the International Space Station interior spaces became available.
45° imagery Edit
In December 2009, Google introduced a new view consisting of 45° angle aerial imagery, offering a "bird's-eye view" of cities. The first cities available were San Jose and San Diego. This feature was initially available only to developers via the Google Maps API.  In February 2010, it was introduced as an experimental feature in Google Maps Labs.  In July 2010, 45° imagery was made available in Google Maps in select cities in the United States and worldwide. 
Business listings Edit
Google collates business listings from multiple on-line and off-line sources. To reduce duplication in the index, Google's algorithm combines listings automatically based on address, phone number, or geocode,  but sometimes information for separate businesses will be inadvertently merged with each other, resulting in listings inaccurately incorporating elements from multiple businesses.  Google allows business owners to create and verify their own business data through Google My Business.  Owners are encouraged to provide Google with Business information including address, phone number, business category and photos.  Google has staff in India who check and correct listings remotely as well as support businesses with issues.  Google also has teams on the ground in most countries, that validate physical addresses in person.  After the business listing has been verified, business owners can further optimize their profile by logging into their Google account and GMB dashboard. In mid August 2020 Google made it more convenient for business owners to edit their business profile directly from search, simply by typing the word My business or their company name. Google My Business allows businesses to create a website for free. 
Google Maps can be manipulated by businesses which are not physically located in the area in which they record a listing. There are cases of people abusing Google Maps to overtake their competition by placing unverified listings on online directory sites knowing the information will roll across to Google (duplicate sites). The people who update these listings do not use a registered business name. Keywords and location details are placed on their Google Maps business title which can overtake credible business listings. In Australia in particular, genuine companies and businesses are noticing a trend of fake business listings in a variety of industries. 
Genuine business owners can also optimise their business listings to gain greater visibility in Google Maps, through a type of search engine marketing called Local search engine optimisation. 
Indoor maps Edit
In March 2011, indoor maps were added to Google Maps, giving users the ability to navigate themselves within buildings such as airports, museums, shopping malls, big-box stores, universities, transit stations, and other public spaces (including underground facilities). Google encourages owners of public facilities to submit floor plans of their buildings in order to add them to the service.  Map users can view different floors of a building or subway station by clicking on a level selector that is displayed near any structures which are mapped on multiple levels.
My Maps Edit
My Maps is a feature in Google Maps launched in April 2007 that enables users to create custom maps for personal use or sharing. Users can add points, lines, shapes, notes and images on top of Google Maps using a WYSIWYG editor.  An Android app for My Maps, initially released in March 2013 under the name Google Maps Engine Lite, is also available.  
Google Local Guides Edit
Google Local Guides is a volunteer program launched by Google Maps to enable its users to contribute to Google Maps. Sometimes it provides them additional perks and benefits for the work. The program is partially a successor to Google Map Maker as features from the former program became integrated into the website and app. 
The program consists of adding reviews, photos, basic information, videos and correcting information such as wheelchair accessibility.  
Earth Timelapse, released in April 2021, is a program in which users can see how the earth has been changed in the last 37 years. They combined the 15 million satellite images (roughly ten quadrillion pixels) to create the 35 global cloud-free Images for this program. 
The version of Google Street View for classic Google Maps required Adobe Flash.  In October 2011, Google announced MapsGL, a WebGL version of Maps with better renderings and smoother transitions.  Indoor maps uses JPG, .PNG, .PDF, .BMP, or .GIF, for floor plans. 
Users who are logged into a Google Account can save locations so that they are overlaid on the map with various colored "pins" whenever they browse the application. These "Saved places" can be organised into user named lists and shared with other users. One default list "Starred places" also automatically creates a record in another Google product, Google Bookmarks.
Map data and imagery Edit
The Google Maps terms and conditions  state that usage of material from Google Maps is regulated by Google Terms of Service  and some additional restrictions. Google has either purchased local map data from established companies, or has entered into lease agreements to use copyrighted map data.  The owner of the copyright is listed at the bottom of zoomed maps. For example, street maps in Japan are leased from Zenrin. Street maps in China are leased from AutoNavi.  Russian street maps are leased from Geocentre Consulting and Tele Atlas. Data for North Korea is sourced from the companion project Google Map Maker.
Street map overlays, in some areas, may not match up precisely with the corresponding satellite images. The street data may be entirely erroneous, or simply out of date: "The biggest challenge is the currency of data, the authenticity of data," said Google Earth representative Brian McClendon. As a result, in March 2008 Google added a feature to edit the locations of houses and businesses.  
Restrictions have been placed on Google Maps through the apparent censoring of locations deemed potential security threats. In some cases the area of redaction is for specific buildings, but in other cases, such as Washington, D.C.,  the restriction is to use outdated imagery.
Google Maps API Edit
Google Maps API, now called Google Maps Platform, hosts about 17 of different APIs, which are themed under the following categories Maps, Places and Routes. 
The Google Maps API is free for commercial use, provided that the site on which it is being used is publicly accessible and does not charge for access, and is not generating more than 25,000 map accesses a day.   Sites that do not meet these requirements can purchase the Google Maps API for Business. 
As of 21 June 2018, Google increased the prices of the Maps API and requires a billing profile. [ citation needed ]
Google Maps in China Edit
Due to restrictions on geographic data in China, Google Maps must partner with a Chinese digital map provider in order to legally show Chinese map data. Since 2006, this partner has been AutoNavi. 
Within China, the State Council mandates that all maps of China use the GCJ-02 coordinate system, which is offset from the WGS-84 system used in most of the world. google.cn/maps (formerly Google Ditu) uses the GCJ-02 system for both its street maps  and satellite imagery.  google.com/maps also uses GCJ-02 data for the street map, but uses WGS-84 coordinates for satellite imagery,  causing the so-called China GPS shift problem.
Frontier alignments also present some differences between google.cn/maps and google.com/maps. On the latter, sections of the Chinese border with India and Pakistan are shown with dotted lines, indicating areas or frontiers in dispute. However, google.cn shows the Chinese frontier strictly according to Chinese claims with no dotted lines indicating the border with India and Pakistan. For example, the South Tibet region claimed by China but administered by India as a large part of Arunachal Pradesh is shown inside the Chinese frontier by google.cn, with Indian highways ending abruptly at the Chinese claim line. Google.cn also shows Taiwan and the South China Sea Islands as part of China. Google Ditu's street map coverage of Taiwan no longer omits major state organs, such as the Presidential Palace, the five Yuans, and the Supreme Court. 
Feature-wise, google.cn/maps does not feature My Maps. On the other hand, while google.cn displays virtually all text in Chinese, google.com/maps displays most text (user-selectable real text as well as those on map) in English. This behavior of displaying English text is not consistent but intermittent – sometimes it is in English, sometimes it is in Chinese. The criteria for choosing which language is displayed are not known publicly.
Google Latitude Edit
Google Latitude was a feature from Google that lets users share their physical locations with other people. This service was based on Google Maps, specifically on mobile devices. There was an iGoogle widget for desktops and laptops as well.  Some concerns were expressed about the privacy issues raised by the use of the service. On August 9, 2013, this service was discontinued,  and on March 22, 2017, Google incorporated the features from Latitude into the Google Maps app. 
Google Map Maker Edit
In areas where Google Map Maker was available, for example, much of Asia, Africa, Latin America and Europe as well as the United States and Canada, anyone who logged into their Google account could directly improve the map by fixing incorrect driving directions, adding biking trails, or adding a missing building or road. General map errors in Australia, Austria, Belgium, Denmark, France, Liechtenstein, Netherlands, New Zealand, Norway, South Africa, Switzerland, and the United States could be reported using the Report a Problem link in Google Maps and would be updated by Google.  For areas where Google used Tele Atlas data, map errors could be reported using Tele Atlas map insight. 
If imagery was missing, outdated, misaligned, or generally incorrect, one could notify Google through their contact request form. 
In November 2016, Google announced the discontinuation of Google Map Maker as of March 2017. 
Google Maps is available as a mobile app for the Android and iOS mobile operating systems. The Android app was first released in September 2008,   though the GPS-localization feature had been in testing on cellphones since 2007.    Up until iOS 6, the built-in maps application on the iOS operating system was powered by Google Maps. However, with the announcement of iOS 6 in June 2012, Apple announced that they had created their own Apple Maps mapping service,  which officially replaced Google Maps when iOS 6 was released on September 19, 2012.  However, at launch, Apple Maps received significant criticism from users due to inaccuracies, errors and bugs.   One day later, The Guardian reported that Google was preparing its own Google Maps app,  which was released on December 12, 2012.   Within only two days, the application had been downloaded over ten million times. 
The Google Maps apps for iOS and Android have many of the same features, including turn-by-turn navigation, street view, and public transit information.   Turn-by-turn navigation was originally announced by Google as a separate beta testing app exclusive to Android 2.0 devices in October 2009.   The original standalone iOS version did not support the iPad,  but tablet support was added with version 2.0 in July 2013.  An update in June 2012 for Android devices added support for offline access to downloaded maps of certain regions,   a feature that was eventually released for iOS devices, and made more robust on Android, in May 2014.  
At the end of 2015 Google Maps announced its new offline functionality,  but with various limitations – downloaded area cannot exceed 120,000 square kilometres   and require a considerable amount of storage space.  In January 2017, Google added a feature exclusively to Android that will, in some U.S. cities, indicate the level of difficulty in finding available parking spots,  and on both Android and iOS, the app can, as of an April 2017 update, remember where users parked.   In August 2017, Google Maps for Android was updated with new functionality to actively help the user in finding parking lots and garages close to a destination.  In December 2017, Google added a new two-wheeler mode to its Android app, designed for users in India, allowing for more accessibility in traffic conditions.   In 2019 the android version introduced the new feature called live view that allows to view directions directly on the road thanks to augmented reality  Google Maps won the 2020 Webby Award for Best User Interface in the category Apps, Mobile & Voice.  In March 2021, Google added a feature in which user can draw missing roads. 
USA Today welcomed the application back to iOS, saying: "The reemergence in the middle of the night of a Google Maps app for the iPhone is like the return of an old friend. Only your friend, who'd gone missing for three months, comes back looking better than ever."  Jason Parker of CNET, calling it "the king of maps", said, "With its iOS Maps app, Google sets the standard for what mobile navigation should be and more."  Bree Fowler of the Associated Press compared Google's and Apple's map applications, saying: "The one clear advantage that Apple has is style. Like Apple devices, the maps are clean and clear and have a fun, pretty element to them, especially in 3-D. But when it comes down to depth and information, Google still reigns superior and will no doubt be welcomed back by its fans."  Gizmodo gave it a ranking of 4.5 stars, stating: "Maps Done Right".  According to The New York Times, Google "admits that it's [iOS app is] even better than Google Maps for Android phones, which has accommodated its evolving feature set mainly by piling on menus". 
However, Google Maps' location tracking is widely regarded as a threat to users' privacy, with Dylan Tweney of VentureBeat writing in August 2014 that "Google is probably logging your location, step by step, via Google Maps", and linked users to Google's location history map, which "lets you see the path you've traced for any given day that your smartphone has been running Google Maps". Tweney then provided instructions on how to disable location history.  The history tracking was also noticed, and recommended disabled, by editors at CNET  and TechCrunch.  Additionally, Quartz reported in April 2014 that a "sneaky new privacy change" would have an effect on the majority of iOS users. The privacy change, an update to the Gmail iOS app that "now supports sign-in across Google iOS apps, including Maps, Drive, YouTube and Chrome", meant that Google would be able to identify users' actions across its different apps. 
The Android version of the app surpassed 5 billion installations in March 2019. 
Go version Edit
Google Maps Go, a version of the app designed for lower-end devices, was released in beta in January 2018.  By September 2018, the app had over 10 million installations. 
In 2005 the Australian Nuclear Science and Technology Organisation (ANSTO) complained about the potential for terrorists to use the satellite images in planning attacks, with specific reference to the Lucas Heights nuclear reactor however, the Australian Federal government did not support the organization's concern. At the time of the ANSTO complaint, Google had colored over some areas for security (mostly in the US), such as the rooftop of the White House and several other Washington, D.C., US buildings.   
In October 2010, Nicaraguan military commander Edén Pastora stationed Nicaraguan troops on the Isla Calero (in the delta of the San Juan River), justifying his action on the border delineation given by Google Maps. Google has since updated its data which it found to be incorrect. 
On January 27, 2014, documents leaked by Edward Snowden revealed that the NSA and the GCHQ intercepted Google Maps queries made on smartphones, and used them to locate the users making these queries. One leaked document, dating to 2008, stated that "[i]t effectively means that anyone using Google Maps on a smartphone is working in support of a GCHQ system." 
In February 2020, Simon Weckert used 99 cell phones to fake a Google Maps traffic jam. 
In the most simple terms, Google Earth is a digital map, which shows detailed, high-quality information gathered from satellite images of the Earth. One able to see different views in 3D, from various angles and perspectives. The program can be downloaded for free on a mobile or a computer and covers around 98% of the world, and one can see cities and landscapes from various angles.
What is Google Earth for?
Google Earth uses satellite images, aerial photography, GIS data, and represents the information in a 3D globe. One can zoom into any portion of the earth to get a view from various angles. This fascinating software allows for anyone sitting in one continent, to be able to see even the most minuscule feature in an entirely different part of the Earth. Features like Street View, Night Sky, Flight Simulator, are interesting to navigate. Google Earth basically offers a 3D view of the world, to the most minute details, so one can virtually travel the globe, without having to step out at all.
What are the key features to watch out for?
The 3D Building Model is one of the best and most interesting features of Google Earth. One can see different monuments and prominent buildings from different angles. So if you feel like visiting the Statue of Liberty and cannot for some reason, Google Earth 3D provides a pretty comprehensive and granular view into the monument.
Google Earth features stories and places that one can explore through the program. Pictures of the places lead you to the location, which you can zoom in and navigate with the click of a button. Some of the most beautiful pictures and imagery of the places give you a fantastic online tour.
Google Earth is linked to Maps, which can help find the distance and navigation from your location to the desired destination. While Google Earth gives you the zoomed view of the destination of interest, so even before arriving at a particular destination, you can see how it looks like. In the recent versions of the application, Street View is also integrated into the software, for a more drilled down view of localities and areas.
The Voyager feature shows the Google Stories and virtual tours of various natural and man-made wonders of the world. Information about iconic monuments, amazing satellite images, and a collation of the most breath-taking places on Earth.
The application works on both Android and iOS systems and works on any Windows or Mac operating systems. Easy to download and run.
What are the alternatives to Google Earth?
Google Earth, although a really unique program with state-of-the-art features and imagery, does have able competitors like Google Earth Pro, Google Maps, NASA World Wind, Arcgis, Street View, Cesium, Gis, QGis, etc. The biggest difference between Google Earth and Google Earth Pro is the quality of images that one has access to, to be able to download and print.
Google Maps is a more functional, mapping application, that tracks real-time information about routes, traffic, detours, time is taken from one place to another. While Google Earth shows images from the world, Google Maps tracks real-time information to navigate from one place to the other, and serve entirely different functions. Google Earth is a more experiential program, while Google Maps is purely functional.
NASA WorldWind is an open-source virtual globe, which was first developed by NASA. Since this is open source, developers use it to manipulate and analyze data. Google Earth has also introduced Projects (which is only accessible from a desktop application), for deeper involvement with programmers and developers. Again, the usage is slightly different for WorldWind and Google Earth. While Google Earth is more experiential, for travel and images, NASA WorldWind is more inclined towards building programs for developers using WorldWind as the basis.
Other programs like Arcgis, Street View, Cesium, Gis, QGis, and others, do not have the resource or knowledge base of Google, to be able to compete entirely. By the sheer volume of data captured and applied, Google Earth is a superior application for 3D imagery and navigation of the Earth.
Best things about Google Earth?
Google Earth offers a unique opportunity to be able to navigate any part of the globe, by simply clicking a button. It is easy to use, fairly intuitive, offers a map view and a street view, is interactive, and gives interesting suggestions to zoom into. If one gets deeper into it, it’s a black hole for time, as it really lets you explore the world. The coexistence with Google Maps also makes navigating easy. For researchers and travelers, Google Earth provides a great perspective into viewing the world as it is. The precise data ensures minuscule details to be seen clearly, and it is an excellent tool to experience some of the most amazing structures of the world.
Worst things about Google Earth?
There are privacy issues that the program is facing, with some countries and sensitive military zones blanked out on the program. One can literally zoom into the house that one lives in, so it does pose the question of privacy. Features like Projects are only accessible through the desktop, which can be slightly limiting. Apart from the experiential factor, Google Earth lacks any obvious functional application like say a Google Maps does. It also does not have real-time data, like Google Maps, so it might show some outdated images as well.
What’s our verdict?
Google Earth quite literally opens up the world to users on a smartphone, laptop, or tablet. The sheer volume of information about the features of the world is fascinating to explore, and for researchers, writers, travel enthusiasts, explorers, the program is a real boon. It’s easy to use the application, with simple features, and an intuitive interface. The multiple views and tools allow for easy exploration of various sites. However, the first thing you probably will be zooming into is your own house, and be completely taken by how good the picture quality is!
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Download Microsoft .NET Framework 4.7.x all packages Offline installer
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NET Framework (pronounced as "dot net") is a software framework developed by Microsoft that runs primarily on Microsoft Windows. It includes a large class library named as Framework Class Library (FCL) and provides language interoperability (each language can use code written in other languages) across several programming languages. Programs written for .NET Framework execute in a software environment (in contrast to a hardware environment) named the Common Language Runtime (CLR). The CLR is an application virtual machine that provides services such as security, memory management, and exception handling. As such, computer code written using .NET Framework is called "managed code". FCL and CLR together constitute the .NET Framework.
The Microsoft .NET Framework 4.7.1 is a highly compatible, in-place update to the Microsoft .NET Framework 4, 4.5, 4.5.1, 4.5.2, 4.6, 4.6.1, 4.6.2, and 4.7. The offline package can be used in situations where the web installer cannot be used due to lack of internet connectivity.