Denis Frischmann’s Post

🌿 #DataScience #EnvironmentalConservation #GIS #GoogleEarthEngine Excited to share a solution I developed using Google Earth Engine for Species Distribution Modeling (SDM)! 🌎 📊 What we built: I developed a complete script to analyze the distribution of the Cedro tree (Cedrela) in Brazil, combining: Bioclimatic data from WorldClim Terrain information from SRTM Tree cover data from MODIS Species occurrence records 🔧 Key technical aspects: Spatial Pre-processing: Removal of duplicates using a 10km grid Territorial mask for Brazil Normalization of environmental data Multivariate Analysis: PCA (Principal Component Analysis) for dimensionality reduction Selection of the most relevant principal components Correlation analysis between variables using Spearman Visualization: Elevation maps Tree cover Principal components Correlation matrix between variables 🎯 Key benefits: Reduction of sampling bias Computational optimization Better interpretability of results Clear visualization of spatial patterns 💡 Why does this matter? This type of analysis is crucial for: Species conservation Protected area planning Understanding climate change impacts Sustainable forest management 🤝 I'm sharing this because I believe in the importance of merging technology with environmental conservation. The code is available for anyone interested in exploring and adapting it for other species. Interested in learning more about how data science can help in biodiversity conservation? Let’s talk! https://lnkd.in/d8Fr7xsr #Biodiversity #EnvironmentalGeoprocessing #Conservation #DataScience #GIS #RemoteSensing #GoogleEarthEngine

🚀 Breaking new ground in biodiversity data with NaturaConnect! 🌿 I’m excited to share that our colleagues from CNRS, Wilfried Thuiller and Sara Si-Moussi, have released a game-changing dataset as part of the NaturaConnect project on the GEO BON Essential Biodiversity Variables Data Portal! This dataset delivers predictive models for over 1,200 terrestrial vertebrate species across Europe, mapped at a 1 km resolution using powerful machine learning techniques. 🌐📈 Not only is this dataset published under a CC BY 4.0 license, but we are also providing a DOI (Digital Object Identifier) to make sure the dataset is easily citable and traceable. This reinforces the F.A.I.R. (Findable, Accessible, Interoperable, Reusable) principles, making it simpler for researchers to locate, use, and cite the data in their work. 📊📚 This level of openness and accessibility is a massive step forward in fostering collaboration and transparency in biodiversity science. It’s a significant milestone for the NaturaConnect project and the entire research community across Europe! 💡🔍 A big shoutout to the CNRS team for pushing the envelope and helping us evolve our systems to support cutting-edge biodiversity monitoring and open science. 🌱✨ 💥 Explore the dataset on the GEO BON portal, and see how it’s driving forward sustainable and transparent research practices! 🌍 https://lnkd.in/eqhdxsTr #BiodiversityInnovation #GEOEBVs #MachineLearning #NaturaConnect #iDiv #EssentialBiodiversityVariables #OpenScience #CCBY4 #DOI #FAIRData #ConservationTech #DataDrivenScience #SustainableResearch #DataCube #ScienceInAction

🌍🔍 Understanding Species Distribution Modeling (SDM) with Google Earth Engine! Species Distribution Modeling (SDM) is a game-changing tool in conservation biology. It helps us map where species like Cedrela fissilis 🌳 can potentially thrive, based on environmental conditions such as climate, land cover, and soil attributes. By linking species presence data to environmental variables, we can estimate the current distribution of a species and even predict future shifts due to climate change or habitat loss. 🌡️🌿 One of the most exciting aspects of SDM is how platforms like Google Earth Engine (GEE) make large-scale modeling more accessible than ever. With GEE, conservationists can access vast environmental datasets, apply machine learning algorithms, and process models rapidly — all from a cloud-based platform. 🚀🌐 In the research led by Dr. Ramiro D. Crego (Crego et al., 2022), SDM was implemented using GEE's JavaScript Code Editor, showcasing how powerful and efficient this tool is for species conservation! 🖥️✨ Using SDM, we can visualize the distribution of Cedrela fissilis, a species crucial to many ecosystems, and assess the areas where conservation efforts should be prioritized. 🗺️🌱 This model not only helps us understand where this species currently exists but also where it could exist if environmental conditions change. This is key for shaping strategies to protect biodiversity in the face of global challenges. 🌎🛡️ Check out this distribution map of Cedrela fissilis below! 👇 #SpeciesDistributionModeling #SDM #Conservation #GoogleEarthEngine #GEE #CedrelaFissilis #Biodiversity #MachineLearning #Ecology #ClimateChange #ConservationTech #DrRamiroCrego #SaveOurSpecies

iNaturalist observations are now available within ESRI's Living Atlas! This integration is a massive leap forward for biodiversity and environmental monitoring, providing access to an incredible repository of citizen science data. Why is this a game-changer? Researchers, conservationists, and environmental planners can easily incorporate rich, user-generated biodiversity data into their GIS workflows. This means better insights, more informed decision-making, and enhanced environmental stewardship. Key Benefits: • Comprehensive Data: Access millions of verified observations of plants and animals, contributed by a global community of citizen scientists. • Enhanced Analysis: Use ArcGIS tools to analyze trends, monitor changes, and plan conservation efforts more effectively. • Interactive Mapping: Create interactive maps that showcase biodiversity patterns and engage stakeholders with visually compelling data. The project I'm currently leading for mapping riparian zones in South Africa can significantly benefit from a tool like this. Integrating iNaturalist observations into workflows will undoubtedly increase our chances to monitor and protect our crucial ecosystems. full announcement here: https://lnkd.in/dRJPKvb5 #GIS #Biodiversity #EnvironmentalScience #CitizenScience #ArcGIS #iNaturalist #Conservation #DataIntegration #Sustainability #ESRI

We have just unveiled our latest data and analytics tool, the Online Reporting for Biodiversity (ORB) tool: https://orb.abmi.ca/areas The ORB tool, officially launched today, provides a user-friendly platform for generating biodiversity and land cover reports for different areas in the province, including natural regions, watershed boundaries, and municipalities or counties. These reports include interactive graphs, maps, and tables, covering human footprint, wetland area, biodiversity intactness, as well as other general information. "We're excited to introduce the ORB tool, which is in direct response to the needs of our data users," said Katherine Maxcy, Reporting and Analytics Lead. "With this tool, we aim to make land cover and biodiversity data more accessible for the wide range of partners and collaborators involved in land use planning and stewardship activities in Alberta." Key highlights of the ORB tool include its intuitive interface, tailored reports based on user-selected areas of interest, and its ability to present data in an easy-to-digest format. Additionally, the tool will be regularly updated with new features and data to ensure its relevance and usefulness over time. Users are encouraged to explore the ORB tool and share it with their networks. Watch a video tour demonstrating how to use the tool on our YouTube Channel: https://lnkd.in/d5uypB2k Financial support for the development of the ORB tool generously provided by the Government of Alberta.

UK pioneers geospatial tech for biodiversity improvements Geographic Information System (GIS) technology is revolutionising the processes required for delivering biodiversity mandates and improvements — and the UK is setting the bar. https://lnkd.in/eDQxVg_Y

🌍 Exciting Milestone: Completed Course on Using Spatial Data for Biodiversity! I’m thrilled to share that I have recently completed a comprehensive course on Using Spatial Data for Biodiversity! In a world where conservation efforts and biodiversity management are more crucial than ever, understanding how to leverage spatial data is key to making informed decisions and driving impactful change. This course has been an enlightening journey, equipping me with valuable skills and insights to enhance our approach to preserving the natural world. Here are a few highlights from my learning experience: Advanced Spatial Analysis: Gained hands-on experience with UN Biodiversity Lab, GIS tools and techniques to analyze and visualize spatial data, which is vital for understanding habitat distributions and species movement patterns. Biodiversity Mapping: Learned how to create detailed maps that illustrate biodiversity hotspots and track changes in species diversity over time, providing crucial information for conservation planning. Data Integration: Explored methods for integrating diverse datasets to build comprehensive models that aid in predicting ecological changes and assessing the impacts of environmental policies. Real-World Applications: Delved into case studies and real-world scenarios where spatial data has been used to tackle pressing environmental issues, reinforcing the practical applications of the skills acquired. This course has not only deepened my understanding of spatial data but also strengthened my commitment to contributing to biodiversity conservation efforts. I am excited to apply these new skills to future projects and collaborate with like-minded professionals in the field. A big thank you to UNITED NATION DEVELOPMENT PROGRAMME(LEARNING FOR NATURE) for delivering such an informative and inspiring course. I look forward to the opportunities that lie ahead and to continuing the journey of learning and growth in this vital field. #Biodiversity #SpatialData #UNBiodiversityLab #GIS #Conservation #UNDP #Learningfornature

Why is it so hard to actually measure ecosystem condition with field data? But first, if you are wondering why direct measurement is important... 💡 Ecological survey data are required to verify that potential impacts (e.g. measured with remote sensing or pressure-impact modelling) translate into actual impacts and to ensure maximum level of accuracy. Ecologists regularly collect biodiversity state data and a number of companies of varying sizes are improving measurement approaches such as eDNA, drones, camera traps, eco-acoustics, etc. (see The Biodiversity Footprint Intelligence Company (BioInt)'s overview of their strengths and weaknesses, link in comments). So why is it difficult to measure ecosystem condition, and more specifically composition? Companies measuring the state of nature on their direct operations and supply chains face two main difficulties: 1️⃣ Species occurrence is not enough, abundances are necessary: most approaches can only tell if a species has been spotted, but cannot provide individual counts (i.e. how many individual of each species the ecosystem hosts) 2️⃣ Undisturbed densities are also required, and that raises one very tricky question: what would be the undisturbed habitat in the location assessed? But more practically, it also reveals the lack of databases listing undisturbed densities. I have focused on difficulties but what about solutions? How can ecosystem condition be directly measured in practice? 🔦The AFD case study with the MSA metric A proof of concept was developed using the MSA metric, providing partial solutions to these questions (4 page summary). A standardised protocol to measure ecosystem condition with field data is still lacking though. Read more about the AFD case study and the challenges and uses of measuring ecosystem composition in my newsletter (link in comments). 💬 What do you think about recent publications using eDNA and machine learning to assess ecosystem condition? PS: this a summer repost, hope you are or have been enjoying holidays in contact with nature! I'll be back to new content in September.

𝗡𝘂𝗿𝘁𝘂𝗿𝗶𝗻𝗴 𝗡𝗮𝘁𝘂𝗿𝗲: 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗚𝗜𝗦 𝗮𝗻𝗱 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗠𝗮𝗽𝗽𝗶𝗻𝗴 𝗶𝗻 𝗔𝘂𝘀𝘁𝗿𝗮𝗹𝗶𝗮 Australia's rich biodiversity and diverse ecosystems provide invaluable services that sustain life, regulate climate, and support human well-being. Ecosystem services mapping, powered by artificial intelligence (AI) within Geographic Information Systems (GIS), plays a pivotal role in understanding, quantifying, and conserving these essential services. In this blog post, we explore the synergies between AI and GIS for ecosystem services mapping, focusing on key services such as carbon sequestration, water purification, and biodiversity conservation in the Australian context. 📗Read full post here on my GIS blog 🔗https://lnkd.in/eb3e4uKa ❤️Subscribe for regular GIS Tips and Articles 🔗https://lnkd.in/gzzHS_Rt

🌍 Advancing Biodiversity Data with NaturaConnect! 🌿 #NaturaConnect partners from CNRS recently published a groundbreaking dataset on the GEO BON Essential Biodiversity Variables (EBV) Data Portal. This release features predictive models for over 1,200 terrestrial vertebrate species across Europe, each mapped at a one square kilometre resolution through advanced ensemble machine learning techniques. 📊 🔍Key highlights of the dataset: 1. High-Resolution Mapping: Each model delivers data at a fine-grained 1 km² scale, offering unprecedented detail. 2. Enhanced Precision and Transparency: The ensemble approach, combined with additional metrics, provides clearer insights into prediction uncertainties, adding reliability to the data. 3. Commitment to Openness: This dataset adheres to F.A.I.R. principles (Findable, Accessible, Interoperable, Reusable), facilitating ease of access, use, and citation for the broader research community. This milestone represents a significant step forward for the NaturaConnect project, enhancing the GEO BON EBV portal’s capacity and fostering collaboration across Europe’s biodiversity research efforts. Congratulations to the CNRS team for their dedication to advancing open science and sustainable research practices in biodiversity. To explore the dataset and learn more about how it supports transparency and innovation in biodiversity monitoring, visit the GEO BON portal. 🔗 Access the dataset here: https://buff.ly/48DFq09 #HorizonEU #EssentialBiodiversityVariables