GeoAI dengan Python
Panduan Praktis untuk AI Geospasial Open Source
Satelit menangkap volume citra yang sangat besar setiap hari, tetapi mengubah piksel menjadi wawasan memerlukan AI. Buku ini mengajarkan Anda untuk membangun, melatih, dan menerapkan model deep learning pada citra satelit nyata menggunakan Python dan alat open source, dengan 23 bab berisi kode yang dapat dijalankan sekarang juga. Semua contoh kode tersedia gratis di https://book.opengeoai.org.
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About the Book
Pelajari cara menerapkan deep learning dan AI pada citra satelit, foto udara, dan data geospasial menggunakan Python. Panduan praktis ini membawa Anda dari pengunduhan data penginderaan jauh hingga pelatihan dan evaluasi model deep learning, semuanya menggunakan alat open source.
Apa yang akan Anda pelajari- Menyiapkan lingkungan GeoAI lengkap dengan Python, PyTorch, dan akselerasi GPU
- Mengunduh citra satelit dari Microsoft Planetary Computer dan portal data terbuka
- Membuat peta interaktif dan menyiapkan dataset pelatihan dari citra satelit berukuran besar
- Melatih dan mengevaluasi model untuk tujuh tugas inti AI geospasial: pengenalan gambar, deteksi objek, segmentasi semantik, segmentasi instans, translasi gambar, deteksi perubahan, dan regresi tingkat piksel
- Menerapkan model fondasi, termasuk Segment Anything Model (SAM), model visi-bahasa, dan embedding satelit, pada masalah observasi Bumi di dunia nyata
- Menjalankan alur kerja AI di QGIS tanpa menulis kode menggunakan plugin untuk segmentasi pohon, deteksi air, dan lainnya
- 23 bab dengan contoh kode yang dapat dijalankan, disusun dalam lima bagian: Dasar-Dasar, Akuisisi dan Persiapan Data, Tugas Inti AI, Model Fondasi, dan Plugin QGIS
- Semua contoh menggunakan citra satelit nyata dengan PyTorch, torchgeo, segment-geospatial, leafmap, dan geoai
- Semua kode dan dataset tersedia secara gratis di GitHub dan Source Cooperative untuk memastikan reproduksibilitas penuh
Profesional GIS, ilmuwan penginderaan jauh, ilmuwan data, dan mahasiswa yang ingin menerapkan AI pada data geospasial menggunakan Python dan alat open source.
Author
About the Author
Dr. Qiusheng Wu is an Associate Professor at the University of Tennessee and an Amazon Scholar. His research focuses on geospatial data science, with an emphasis on using open-source Python tools and cloud computing to study environmental change. He is the creator of several widely-used Python packages, including geemap, leafmap, and geoai, and is dedicated to advancing geospatial analysis and visualization. Dr. Wu's work is a cornerstone of the open-source geospatial community, and he brings his deep expertise to this book, guiding you through the process of learning and mastering geospatial programming with Python.
Episode 318
An Interview with Qiusheng Wu
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