Latest Remote Sensing & Geospatial Research Papers
The newest Remote Sensing & Geospatial papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Remote Sensing & Geospatial so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.
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- The Governance of Satellite Communications and Remote Sensing in Africa: Youth Perspectives and Intergenerational JusticeAbraham Kuol Nyuon · Zenodo (CERN European Organ... · Sep 17, 2026
This article examines The Governance of Satellite Communications and Remote Sensing in Africa: Youth Perspectives and Intergenerational Justice with a focused emphasis on Rwanda within the field of Law. It is structured as a conference pape…
- The Governance of Satellite Communications and Remote Sensing in Africa: Youth Perspectives and Intergenerational JusticeAbraham Kuol Nyuon · Zenodo (CERN European Organ... · Sep 17, 2026
This article examines The Governance of Satellite Communications and Remote Sensing in Africa: Youth Perspectives and Intergenerational Justice with a focused emphasis on Rwanda within the field of Law. It is structured as a conference pape…
- Evaluating Communal Grazing Reserve Efficacy for Rangeland Biomass Restoration in Afar, Ethiopia: An Integrated Remote Sensing and Field AssessmentMekonnen Assefa, Mohammed, Hanan, Tadesse Gebre, Selamawit Tesfaye · Zenodo (CERN European Organ... · Aug 23, 2026
{ "background": "Communal grazing reserves are a key rangeland management strategy in arid and semi-arid pastoral systems of the Horn of Africa, yet empirical evidence of their efficacy for biomass restoration remains limited and contested.…
- Evaluating Communal Grazing Reserve Efficacy for Rangeland Biomass Restoration in Afar, Ethiopia: An Integrated Remote Sensing and Field AssessmentMekonnen Assefa, Mohammed, Hanan, Tadesse Gebre, Selamawit Tesfaye · Zenodo (CERN European Organ... · Aug 23, 2026
{ "background": "Communal grazing reserves are a key rangeland management strategy in arid and semi-arid pastoral systems of the Horn of Africa, yet empirical evidence of their efficacy for biomass restoration remains limited and contested.…
- Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?Qiwei Ma, Chunping Qiu, Xinjun Cheng, Xiaoyu Zhang et al. · arXiv · Jul 22, 2026
The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU), enabling natural-language interaction with remote sensing imagery. However, a systema…
- RS-RIE-Bench: Benchmarking Reasoning-Guided Remote Sensing Image EditingZihan Qin, Boao Xu, Zhao Dong, Yingping Sun et al. · arXiv · Jul 22, 2026
Remote sensing image editing aims to modify remote sensing images according to natural language instructions while preserving geographic rules and sensor observation characteristics. Existing benchmarks mainly target natural images or gener…
- RIM: A Retrieval-In-Matching Framework for Cross-Domain Global Visual Localization of UAVsXin Li, Siyuan Duan, Shang Wang, Zhimin Mao et al. · arXiv · Jul 22, 2026
Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisition-time and imaging-platform differences between UAV and reference imagery induce substa…
- DAPGNet: Dynamic Adaptive Physics-Guided Graph Diffusion Network for Hyperspectral Image ClassificationPengkun Wang, Weijia Cao, Ning Wang, Xiaofei Yang · arXiv · Jul 16, 2026
Hyperspectral image (HSI) classification requires reliable pixel-relation modeling under spectral variability, mixed pixels, and heterogeneous boundaries. Existing graph-based HSI classifiers usually construct graph topology from spatial pr…
- Domain-Incremental Remote Sensing Change Detection via Difference-Guided Adaptation and Frequency-Decoupled DistillationDaifeng Peng, Yaning Li, Haiyan Guan · arXiv · Jul 14, 2026
Remote sensing change detection (RSCD) models are prone to catastrophic forgetting when incrementally adapted to new domains. Existing domain-incremental learning (DIL) methods mainly preserve image-level representations but often overlook …
- Promptable Concept Segmentation from Above: Evaluating SAM 3's Zero-Shot and One-Shot Capabilities in Remote SensingMohammad Dabaja, Turgay Celik · arXiv · Jul 10, 2026
The deployment of large-scale foundation models, such as the Segment Anything Model 3 (SAM 3), promises a transition toward open-vocabulary, training-free computer vision. However, their capacity to generalize out-of-distribution to the com…
- MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM AdaptationJiaju Han, Ma Yaqi, Yahui Chai, Xuemeng Sun et al. · arXiv · Jul 7, 2026
Infrared remote-sensing imagery captures intensity structure, object-background contrast, and illumination-invariant cues often invisible in RGB imagery. Yet, most remote-sensing vision-language resources and models focus on visible-band se…
- AirflowAttack: Thermal-Airflow Adversarial Perturbations against Infrared Remote-Sensing Vision-Language ModelsCong Su, Jiaju Han, Xuemeng Sun, Chengyin Hu et al. · arXiv · Jul 7, 2026
Vision-language models (VLMs) are increasingly deployed on infrared (IR) remote sensing imagery in security-critical settings, yet their adversarial robustness remains unexamined. We present AirflowAttack, to our knowledge the first adversa…
- Interpretation-Oriented Cloud Removal via Observation-Anchored Residual Flow with Geo-Contextual AlignmentZiyao Wang, Maonan Wang, Yucheng He, Xianping Ma et al. · arXiv · Jul 2, 2026
Cloud removal (CR) is essential for optical remote sensing, serving as a prerequisite for reliable downstream interpretation, such as semantic segmentation and change detection. However, existing CR approaches often prioritize visual realis…
- GeoSearcher: Anchor-Guided Progressive Reasoning for Remote Sensing Visual Grounding with Process SupervisionDianyu Wang, Yidan Zhang, Peirong Zhang, Xuyang Li et al. · arXiv · Jul 1, 2026
Recent multimodal large language models (MLLMs) have shown strong cross-modal understanding and coordinate generation abilities in visual grounding. However, transferring these abilities to remote sensing visual grounding (RSVG) remains cha…
- High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative DespecklingDavid Ma, Jeremy Feinstein, Shreya Pandit, Arkaprabha Ganguli et al. · arXiv · Jun 29, 2026
Reliable high-resolution flood extent mapping from satellite imagery remains constrained by limited data fidelity and sensor-specific artifacts. Multispectral optical imagery is degraded by clouds, shadows, and urban confounders, while synt…
- RSICCLLM: A Multimodal Large Language Model for Remote Sensing Image Change CaptioningYelin Wang, Zijia Song, Shuo Ye, Chuanguang Yang et al. · arXiv · Jun 26, 2026
Remote Sensing Image Change Captioning (RSICC) aims to describe changes between bi-temporal remote sensing images and holds significant research and application value. However, most existing methods rely on conventional deep learning archit…
- EO-WM: A Physically Informed World Model for Probabilistic Earth Observation ForecastingJunwei Luo, Shuai Yuan, Zhenya Yang, Yansheng Li et al. · arXiv · Jun 25, 2026
Earth Observation (EO) forecasting aims to predict future Earth surface dynamics from satellite observations under changing meteorological conditions. In this paper, we view this task as a partially observed, weather-driven world modeling p…
- FunPiQ: A New Benchmark for Pixel-Level Quality Assessment in Fundus ImagesPengwei Wang, José Morano, Virginia Mares, Hrvoje Bogunović · arXiv · Jun 24, 2026
Color fundus photography (CFP) is the most common ophthalmic imaging modality for large-scale screening. However, it is highly susceptible to degradations, making robust fundus image quality assessment (FIQA) crucial. The criteria for what …
- Counting Trees from Satellite Imagery with Noisy SupervisionDimitri Gominski, Maurice Mugabowindekwe, Qiue Xu, Xiaowei Tong et al. · arXiv · Jun 23, 2026
Counting individual trees is a fundamental task for environmental monitoring, yet remains largely unexplored with satellite imagery. At these resolutions, isolated trees may still be identifiable, but crown boundaries become ambiguous in de…
- AerialFusionMapNet: Online HD Map Construction with Aerial-Onboard BEV FusionDaniel Lengerer, Mathias Pechinger, Klaus Bogenberger, Carsten Markgraf · arXiv · Jun 23, 2026
High-resolution aerial imagery has recently emerged as a complementary modality for automated driving perception and has shown potential to improve birds-eye-view (BEV) scene understanding when fused with onboard sensors. Prior work demonst…
- Hedgementation = Hedgerow Segmentation: A Remote Sensing BenchmarkNathan Senyard, Salem Hamdani, Astrid Zhang, Derek Wang et al. · arXiv · Jun 22, 2026
We propose Hedgementation: a new benchmark to evaluate machine learning models for hedgerow mapping from remote sensing data at country scale and 10m$^2$ spatial resolution. We combine and harmonize multiple remote sensing data products and…
- AwakeForest: An Interactive Geospatial Platform for Large-Scale Forest ImagerySuraj Prasai, Kangning Cui, Rongkun Zhu, Sarra Alqahtani et al. · arXiv · Jun 22, 2026
Forest imagery analysis often involves multiple tightly coupled vision tasks, which must be performed under substantial variation in geographic regions, sensors, and acquisition conditions. However, practitioners often lack a unified tool t…
- PCFootprint: A Large-Scale Dataset and Benchmark for Vectorized Building Footprint Extraction from Aerial LiDAR Point CloudsHaoyuan Shen, Kuihao Wang, Ruisheng Wang, Yujun Liu · arXiv · Jun 18, 2026
Building footprint extraction is a fundamental task in photogrammetry, remote sensing, and computer vision. Recent image-based methods have achieved remarkable progress in extracting vectorized footprints from high-resolution optical imager…
- A Unified Framework for Efficient Remote Sensing Visual Question Answering: Adapting Dual, Hybrid, and Encoder-Decoder ArchitecturesTimothy Agboada, Shikha Chandel, Yadav Raj Ghimire, Leila Hashemi-Beni · arXiv · Jun 17, 2026
Visual Question Answering (VQA) in the Remote Sensing (RS) domain presents unique challenges due to the high resolution, multi scale object distribution, and semantic complexity of aerial imagery. While general domain Foundation Models have…
- Neural Tree Reconstruction for the Open Forest ObservatoryMarissa Ramirez de Chanlatte, Arjun Rewari, Trevor Darrell, Derek J. N. Young · arXiv · Jun 16, 2026
The Open Forest Observatory (OFO) is a collaboration across universities and other partners to make low-cost forest mapping accessible to ecologists, land managers, and the general public. The OFO is building both a database of geospatial f…
- FusionRS: A Large-Scale RGB-Infrared Remote Sensing Dataset for Dual-Modal Vision-Language Foundation ModelsJiaju Han, Ben Zhang, Xuemeng Sun, Qike Zhang et al. · arXiv · Jun 15, 2026
Remote sensing vision-language models have advanced Earth observation understanding, but most existing work remains centered on RGB imagery, leaving the complementary information in infrared data underexplored. Infrared images provide disti…
- A Lightweight Fiducial-Based Pipeline for 3D Hyperspectral Mapping of ex-vivo Lumpectomy SpecimensAnna Bicchi, Alberto Rota, Leonardo Passoni, Nicola Ancellotti et al. · arXiv · Jun 12, 2026
Hyperspectral Imaging (HSI) is a promising modality for intraoperative assessment of resection margins in Breast-Conserving Surgery (BCS), but its clinical translation requires aligning the inherently 2D spectral information onto the 3D sha…
- SemDINO: A DINOv3-Driven Network for Cross-Temporal Semantic Alignment in Change DetectionXinyu Tong, Meihua Zhou, Jinxiao Sun, Yingjie Tang et al. · arXiv · Jun 8, 2026
Semantic change detection (SCD) aims to simultaneously locate land-cover changes and identify semantic categories before and after transition. However, existing methods suffer from insufficient cross-temporal alignment, weak multi-scale rep…
- Beyond Backscatter: InSAR coherence from detected SAR imagesFrancescopaolo Sica, Andrea Pulella, Michael Schmitt · arXiv · Jun 5, 2026
In this work, we propose a deep learning framework for coherence regression directly from detected SAR images, without the need for accurate coregistration. A Residual U-Net is trained using coherence maps derived from precisely coregistere…
- In-Context Multiple Instance LearningAlexander Möllers, Marvin Sextro, Julius Hense, Gabriel Dernbach et al. · arXiv · Jun 4, 2026
Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied in fields ranging from computational pathology to satellite imagery. Nevertheless, existi…