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Remote Sensing of Environment
Scopus
ISSN 0034-4257 · Elsevier BV · 60 artikel di indeks
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Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar
Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeated measurements of these data allow for the observation of deforestation or degradation of existing forests, natural forest…
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Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on individual urban environments (e.g., single cities or regions). Yet these AI models tend to meet the performance bottleneck…
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Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission
NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level…
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Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review
Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to…
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Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model
Leaf area index (LAI) is a terrestrial essential climate variable that is required in a variety of ecosystem and climate models. The Global LAnd Surface Satellite (GLASS) LAI product has been widely used, but its current version (V5) from Moderate Resolution Imaging Spectroradiometer (MODIS) data…
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Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2
Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical…
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Fifty years of Landsat science and impacts
Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed…
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World Settlement Footprint 3D - A first three-dimensional survey of the global building stock
Settlements, and in particular cities, are at the center of key future challenges related to global change and sustainable development. Widely used indicators to assess the efficiency and sustainability of settlement development are the compactness and density of the built-up area. However, at…
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Evaluating global and regional land warming trends in the past decades with both MODIS and ERA5-Land land surface temperature data
Global surface temperature has been setting new record highs in the recent decades, imposing increasing environmental challenges for societies and ecosystems worldwide. Global warming rates of the 20th century have been documented by a number of studies, nevertheless, the warming rates in the most…
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Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3
Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance…
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NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms
The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared…
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Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends
Light detection and ranging (lidar) data acquired from airborne or spaceborne platforms have revolutionized measurement and mapping of forest attributes. Airborne data are often either acquired using multiple overlapped flight lines to provide complete coverage of an area of interest, or using…
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ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters
Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric…
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Satellite remote sensing of active fires: History and current status, applications and future requirements
Landscape fire is a widespread, somewhat unpredictable phenomena that plays an important part in Earth's biogeochemical cycling. In many biomes worldwide fire also provides multiple ecological benefits, but in certain circumstances can also pose a risk to life and infrastructure, lead to net…
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Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks
During the last two decades, forest monitoring and inventory systems have moved from field surveys to remote sensing-based methods. These methods tend to focus on economically significant components of forests, thus leaving out many factors vital for forest biodiversity, such as the occurrence of…