How do you keep your remote sensing skills updated and relevant in a fast-changing field?

Pour suivre les tendances en télédétection : - je suis abonné à un journal scientifique qui m'envoie les derniers articles sur la télédétection. - je participe à des webinaies et à des ateliers à distance avec l'UNOOSA (branche de l'ONU en charge des affaires spatiales). - je suis abonné à des Newsletters au sujet de la télédétection

Staying informed on the cutting edge of remote sensing is crucial for me. By reading academic papers that interest me, particularly those in MDPI's dedicated "Remote Sensing" journal, often sparks new ideas and reveals innovative technologies and methodologies. Furthermore, connecting and brainstorming with professional and sharing challenges leads to collaborative breakthroughs and new ideas. Engaging with proffesional communities ang social media groups not only exposes me to diverse perspectives but also fosters collaborative opportunities to tackle complex remote sensing problems. Finally, I find it valueable testing new technologies on existing projects.

To stay updated and relevant in remote sensing, attend workshops, engage in online learning, collaborate with experts, read research papers, contribute to open-source projects, apply skills to real-world projects, and participate in professional networks

Another way is to look for small projects or create ones ourselves and post the results of these projects online and invite reviews. I have noted that many experienced experts revert with more efficient ways to address the same project or similar ones. Regards

Keeping up with the latest industry trends in remote sensing is essential for professionals to stay informed about emerging technologies and methodologies. This continuous learning approach ensures that remote sensing skills remain relevant and adaptable in a rapidly changing field.For instance, staying updated on the latest trends in hyperspectral imaging or machine learning applications in remote sensing can equip professionals with valuable skills. This knowledge may lead to the integration of advanced techniques for more accurate land cover classification, enhancing the practical utility of remote sensing technologies in environmental monitoring or agricultural assessments.

1. Siga newsletters, hashtags, páginas de empresas e pessoas que falem das novidades do setor. 2. Estude sobre as tendências de mercado e o que será mais demandado nos próximos anos. 3. Devido à vastid?o de aplica??es do sensoriamento remoto, defina uma linha de atua??o para buscar conhecimentos. 4. Estude e treine, mas sem esquecer que novas áreas demandam um aprofundamento teórico, além do técnico, para que você n?o se torne um apertador de bot?es.

Practicing with data is instrumental in keeping remote sensing skills updated and relevant in a fast-changing field. Hands-on experience with diverse datasets helps professionals adapt to evolving technologies, refine their analysis techniques, and understand the practical applications of new tools. For example, regularly working with high-resolution satellite imagery and applying state-of-the-art image processing algorithms can enhance a remote sensing specialist's ability to extract meaningful information, contributing to advancements in fields such as urban planning or disaster response.

Another way to keep your remote sensing skills updated and relevant is to contribute to the community while practicing with real-world data and scenarios. Engage in forums, discussion groups, and collaborative projects to share knowledge and learn from others. Consider publishing research papers or technical articles to disseminate insights and findings. Additionally, mentor aspiring remote sensing enthusiasts or volunteer for initiatives aimed at leveraging remote sensing for social good. By actively contributing to the remote sensing community, you not only enhance your expertise but also foster a culture of collaboration and innovation in the field.

Staying at the forefront of remote sensing requires a proactive approach to continuous learning. I consistently upskill by exploring the latest tools, such as Google Earth Engine, and advanced Python libraries. In addition, I engage with the GIS community on platforms like LinkedIn to exchange insights and gather expert feedback. Networking with industry professionals allows me to stay informed on emerging trends and innovations. I also prioritize hands-on experience through workshops, webinars, and certifications to reinforce my knowledge and ensure my skills remain cutting-edge.

New satellites are being put online all the time. Try processing some new raw data, before it is available in Google Earth Engine (easy mode). That will force you to learn everything- metadata parsing, atmospheric correction, georeferencing, terrain, pixel de-artifacts, and data management. For example, the LISS-4 data is a leap forward compared to Sentinel 2 in some ways, but it hasn't been fully evaluated for larger-scale use. I'd highly recommend downloading some data and try harmonizing it with other global datasets.

Staying updated in remote sensing requires continuous learning of new tools and technologies. With advancements in cloud computing platforms like Google Earth Engine and AI-driven image processing tools, it's crucial to stay proficient with emerging software. Regularly exploring open-source tools such as QGIS, Python libraries like rasterio and geopandas, and machine learning frameworks for geospatial data helps maintain a competitive edge. Learning these new tools not only enhances your analytical capabilities but also keeps you adaptable to the evolving demands of the remote sensing industry.

MathWorks has furnished a comprehensive hyperspectral imaging library replete with an array of functions and tools tailored for hyperspectral image processing and visualization. Within this library, you can seamlessly employ these functions to engage in tasks such as reading, writing, and manipulating hyperspectral data acquired through hyperspectral imaging sensors, accommodating various file formats. The library is equipped with a rich suite of algorithms designed to cater to diverse needs in hyperspectral analysis. For a user-friendly experience, MathWorks has also introduced the Hyperspectral Viewer app.

Learning new tools is crucial for keeping remote sensing skills current in a fast-changing field. As technology advances, staying informed about and proficient in the latest software and hardware ensures that professionals can effectively process, analyze, and interpret remote sensing data. For instance, acquiring proficiency in using advanced Geographic Information System (GIS) platforms like ArcGIS Pro or open-source tools like QGIS can significantly enhance a remote sensing specialist's ability to handle complex spatial data, facilitating applications in land use planning or environmental monitoring.

A third avenue to enhance your remote sensing skills is by actively contributing to the remote sensing community while learning new tools and software. Share your knowledge and experiences with others in forums, discussion groups, and collaborative projects. Consider creating tutorials or documentation to help fellow practitioners navigate these tools and software more effectively. Additionally, participate in open-source projects or volunteer initiatives aimed at advancing remote sensing techniques and applications. By contributing to the community, you not only reinforce your own understanding but also foster a culture of collaboration and knowledge-sharing within the remote sensing community.

Not many people are talking about front-end tools. Many of the ways people use RS are flat. When you get into app development for remote sensing, you find that there are many libraries that run natively in the browser, like turf.js, which runs in leaflet. It's not super easy, but you can create something to play with the data in actual real-time. ArcGIS Living Atlas and online dashboards and apps are another (paid) but real-time way to explore remote sensing data. Temporal visualizations with voxels and layers are another way to blow your mind- you'll never look at remote sensing data the same way again.

A fourth strategy to enhance your remote sensing skills is by actively contributing to collaborative efforts within the remote sensing community. Engage with networks, associations, groups, and clubs dedicated to remote sensing topics and activities. Participate in hackathons, meetups, events, and initiatives that unite remote sensing enthusiasts and experts from diverse backgrounds. Contribute to group projects, share insights and resources, and offer support to fellow practitioners. By collaborating with others, you not only deepen your understanding of remote sensing but also foster meaningful connections and enrich the collective knowledge of the community.

Volunteer to OSGEO. Start a local chapter. There are a ton of awesome projects, like Opticks- an image processing application that you can write your own extension to. Also, you can join mailing lists like DSSAT (an open-source soil modeling simulation software). The model/sim folks seem to always have tons of new research going on, events, and people you can connect with.

The best way to learn and improve on one's skill set is to engage experts in your work. Seeking for feedback helps create an environment for learning to the individual. This can be done in different ways such as writing blogs, sharing articles and on a personal level by sending works to experts for feedback. LinkedIn has created an atmosphere where works from individuals are given the needful attention through the comments. People share their views and suggestions as comments. They really help the individual and guide them on the needful paths.

A fifth avenue to enhance your remote sensing skills is by actively seeking feedback from peers, mentors, supervisors, clients, and users. Request constructive criticism, suggestions, recommendations, or testimonials on your remote sensing projects, products, or services. Utilize online platforms like GitHub, Stack Overflow, Reddit, and LinkedIn to showcase your work and engage with other users and experts, fostering discussion and feedback. By actively seeking feedback, you can identify areas for improvement, capitalize on your strengths, and refine your remote sensing skills and performance. Additionally, leveraging feedback facilitates continuous learning and growth within the remote sensing field.

Start working on a paper (whitepaper, journal article, blog, magazine piece- whatever). Other academic researchers are almost always interested in collaborating on a paper. The rigorous format, presentation of concepts, and process of writing itself will teach you a lot about what gaps you may want to fill in your training, and where your strengths and weaknesses lie as a practitioner.

This is the Ultimate! There's no better time to wait and start by trying right away. Experts attain such level because the want to know more and learn more. Inquisitive is a key part of the journey and comes with so many benefits. You learn, unlearn and relearn throughout the journey because you're curious. Personally I learn a lot through being inquisitive. It is not an easy way to choose but worth it! You do not rust in the game but always polish your ideas and embrace new methods.

This tip is HIGHLY underrated!! Remote sensing spills out into EVERY industry. I find that researching how remote sensing as a tool is being used in disparate industries to be a great way to keep my skills fresh. Fit for purpose sensors are constantly being deployed and connecting them to workflows in other industries is a fun mental challenge.

Na minha vis?o, uma das melhores maneiras de aperfei?oar e manter suas habilidades em sensoriamento remoto é através da curiosidade e da busca constante por conhecimento. O sensoriamento remoto pode ser aplicado de diversas formas a um mesmo produto. Explorar novas maneiras de aplica??o, encontrar diferentes solu??es e até mesmo combinar essas solu??es para resolver um determinado problema sempre ajudará a maximizar seu conhecimento. Além disso, é essencial buscar pesquisas e artigos recentes para estar sempre atualizado com novos processos e formas inovadoras de utilizar o sensoriamento remoto. A curiosidade e o aprendizado contínuo s?o fundamentais para o desenvolvimento nesta área.

In today's world of AI, it is easier than ever to *start* a project in remote sensing. Last year, I solo developed an ambitious project incorporating Google Earth Engine, an easy-to-use GUI, and client-side real-time raster analysis. Only by diving in, did I realize how over my head I was. Front-end mapping is not easy, and real-time is darn near impossible! In summary, I don't think AI will replace programmers any time soon- you still need to read, understand, and make the right decisions, otherwise, you'll end up with a mess. Your strongest asset is your creativity and ability to change paradigms and perspectives. After time, you'll learn to do it yourself and it'll be faster and better. Keep trying impossible things- it's worth it.