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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISSN 2194-9042 · Copernicus Publications · 4.546 artikel di indeks
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Deformation Monitoring and Prediction of Open-pit Mine Slope Based on GBInSAR Technology and LSTM Neural Network
High-precision and real-time deformation monitoring of open-pit mine slopes provides reliable data support for slope safety early warning and governance, which is directly related to the production efficiency of open-pit mines and the safety of personnel and property. Compared with traditional…
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Conservation Index for lentic ecosystems for an urban coastal wetland in south-central Chile - Rocuant Andalien
Wetlands are ecosystems of great importance worldwide. Global change puts pressure on these ecosystems, contributing to their degradation. Population growth and urban development are among the main problems affecting wetlands located in these areas. Therefore, this manuscript focuses on measuring…
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Ionospheric Scintillation in Brazil: Analysis and Its Impact on GNSS Loss of Lock
This study analyses the ionospheric scintillations over the Brazilian territory, focusing on their magnitude, seasonality, and impact on Global Navigation Satellite Systems (GNSS) signal quality, specifically GPS (Global Positioning System), GLONASS (Global’naya Navigatsionnaya Sputnikovaya Sistema…
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Human detection with YOLO for last-mile delivery applications using UAVs
Low-cost alternative solutions have advanced last-mile delivery, with Unmanned Aerial Vehicles (UAVs) emerging as a promising option for logistics tasks. However, as UAV operations increasingly occur in densely crowded urban areas, safety concerns - especially for people nearby - have intensified…
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Forecasting Trinidad's Evolving Flood Future: A Susceptibility Mapping Approach with Long-Term Rainfall Projections (2010-2100)
Global International Panel on Climate Change (IPCC) models highlight increasing incidence and intensity of rainfall events due to climate change in the Caribbean. However, more granular regional models are needed to guide sector-specific actions. This paper addresses this data gap by using recent…
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Confidence Indicator for Fire Event Alerts Based on Geostationary Remote Sensing in Brazil and ACTO Countries
This work presents a methodology for anticipating the emergence of fire events using hot spot products. It is based on the high temporal resolution and ultra-real-time availability of data from the ABI sensor of the geostationary satellites GOES-16 and GOES-19. The scope involves predicting the…
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Integration of UAV-GNSS-GIS Technologies in a University Extension Project for Religious Cemetery Management: A Case Study at Martin Luther Church (Ibirama - Brazil)
This paper presents a university extension project to improve the spatial documentation of the Martin Luther Church cemetery in Ibirama, Brazil. This was achieved by integrating Unmanned Aerial Vehicle (UAV) photogrammetry, high-precision Global Navigation Satellite System (GNSS) surveying, and…
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APPPOLO: A Brazilian Processing Software for Multi-GNSS Precise Point Positioning
This paper presents the development and evaluation of a Brazilian software for Precise Point Positioning (PPP) using multiple Global Navigation Satellite Systems (GNSS). The tool, named APPPOLO (Advanced Precise Point Positioning software for Optimized Localization), was designed to support…
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Convolutional Neural Network (CNN) Architecture for Detecting Fusarium wilt in Banana Crops Using UAV-Based Multispectral Imaging
Banana crops are highly susceptible to Fusarium wilt, a disease that can cause significant crop losses if not detected early. This study aimed to develop a classification model to detect Fusarium-infected banana plants using multispectral images. The dataset consisted of labeled images categorized…
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Accuracy of Reconstruction with Short baseline from a Single-frame Multispectral Camera
Close-range acquisition of multispectral images is becoming widespread in many applications, such as forestry and agriculture monitoring. However, some challenges still need to be addressed, such as the co-registration of the spectral bands generated with multi-lens cameras. Depth variations can…
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Characterization of Brazilian impact structures based on interpretations of Sentinel-1 C-band dual-polarization (VV and VH) data
The known Brazilian impact structures are characterized using C-band Synthetic Aperture Radar (SAR) images from the Sentinel-1 satellites. After acquiring the dual-polarization (VV and VH) Ground Range Detected Dataset from a public repository, we applied standard processing techniques, including…
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Urban Morphology and Infrastructure Patterns: A LiDAR-Based 3D Cluster Analysis Using Verticalization as a Proxy
This study analyzes urban verticalization and socio-spatial patterns in Belo Horizonte using LiDAR-derived building heights and infrastructure indicators. A normalized Digital Surface Model (nDSM) was generated from LiDAR data to map vertical structures with high spatial accuracy. Self-Organizing…
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Mass balance estimation on the Zongo glacier, Bolivia, using a semi-distributed conceptual model (SCM)
The mass balance of a glacier is used to quantify the accumulation and melting processes, which affect its mass. With this information, it is possible to infer the variation in water reserves, which will support decision-making based on the supply and demand of water. The objective of this work is…
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Applicability of Radio Occultation Data for Atmospheric Temperature Estimation over the São Francisco River Basin
Accurate atmospheric profiling is essential for understanding climate dynamics and improving weather forecasting, particularly in data-scarce regions. This study evaluates the performance of the Radio Occultation (RO) technique - using data from the Constellation Observing System for Meteorology…
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High-Accuracy Corridor Mapping Without GCPs: Assessing Precisions of DSMs Generated from UAS Photogrammetry with On-Site Pre-Calibration
High-resolution Digital Surface Models (DSMs) are crucial for diverse geospatial analyses and UAS photogrammetry offers a cost-effective option for DSM acquisition. However, corridor mapping, due to its linear geometry, challenges the extraction of 3D information without relying on Ground Control…
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Mapping with Words: Integrating Large Language Models into Geospatial Practice
For decades, the focus of geospatial artificial intelligence (AI) has been on imagery and data, with linguistic interfaces remaining unexplored. This study presents a systematic review of research applying Large Language Models (LLMs) to Cartography and GIScience. We analysed 54 peer-reviewed…
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GIS mapping of Allochthonous Marine Litter across the Brazilian Amazon Coast
The Amazon coast is vulnerable to solid waste pollution, which can lead to the degradation of its ecosystems and affect its biodiversity. The debris that reaches this coast has different origins and sources, with international waste coming from other countries through mainly sea-based sources…
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MLP-Based Classification of Multispectral Point Clouds for Digital Agriculture
High-resolution monitoring of individual plants is crucial for improving decision-making processes in precision agriculture, particularly when it comes to assessing development, nutrition, and health status. Deep Convolutional Neural Networks (DCNNs) have proven to be highly effective in…
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Spectral Index for classifying glacier debris distribution and thickness using Multispectral UAV imagery: A case study at Juncal Norte Glacier, Central Andes of Chile
Understanding of debris-covered glaciers is crucial for predicting melt dynamics in high-mountain regions. Juncal Norte Glacier, located on the northwestern slope of Nevado Juncal in central Chile, has experienced a marked retreat—losing 22% of its surface area between 1955 and 2022. As it recedes…
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Discriminative Spectral Regions for Detecting Huanglongbing in Citrus Plants through Statistical Analysis
This study aims to characterize the spectral reflectance of healthy and huanglongbing (HLB)-infected citrus individuals at both the leaf and plant levels using a statistical approach. Our main contribution is to assess the extent to which hyperspectral measurements can differentiate disease status…
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