42,155 Results Found

The editors of the Remote Sensing office would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...]

The publisher and editors of the Remote Sensing would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2013 for Remote Sensing. [...]

The editors of Remote Sensing would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2015. [...]

The editors of Remote Sensing would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...]

Peer review is an essential part in the publication process, ensuring that Remote Sensing maintains high quality standards for its published papers.[...]

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Remote Sensing maintains its standards for the high quality of its published papers [...]

Guest Editors help invite many high-quality papers for Remote Sensing[...]

Peer review is an essential part of the publication process, ensuring that Remote Sensing maintains the high standard of its published papers[...]

Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC). The VRPC aims to improve remote sensing products...

The academician Xiaowen Li devoted much of his life to pursuing fundamental research in remote sensing. A pioneer in the geometric-optical modeling of vegetation canopies, his work is held in high regard by the international remote sensing community....

Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of a...

Reliable image classification results are crucial for the application of remote sensing images, but the reliability of image classification has received less attention. In particular, the inherent uncertainty of remote sensing images has been disrega...

Environmental remote sensing has faced increasing satellite data availability, advanced algorithms for thematic analysis, and novel concepts of ground truth. For that reason, contents and concepts of learning and teaching remote sensing are constantl...

Oceans/Seas are important components of Earth that are affected by global warming and climate change. Recent studies have indicated that the deeper oceans are responsible for climate variability by changing the Earth’s ecosystem; therefore, assessing...

With the rapid development of satellite remote sensing technology, the size of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus beco...

Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 y...

Remote sensing image scene classification is one of the most challenging problems in understanding high-resolution remote sensing images. Deep learning techniques, especially the convolutional neural network (CNN), have improved the performance of re...

A hydrological model is a useful tool to study the effects of human activities and climate change on hydrology. Accordingly, the performance of hydrological modeling is vitally significant for hydrologic predictions. In watersheds with intense human...

Mass remote sensing data management and processing is currently one of the most important topics. In this study, we introduce ScienceEarth, a cluster-based data processing framework. The aim of ScienceEarth is to store, manage, and process large-scal...

Advanced remote sensing technology has provided spatially distributed variables for estimating land–ocean heat fluxes, allowing for practical applications in drought monitoring, water resources management, and climate assessment. This Special I...

The accurate detection of collapsed buildings is of great significance for post-disaster rescue and reconstruction. High-resolution optical images are important data sources for identifying collapsed buildings, and the identification accuracy mainly...

Bibliometric analysis based on the Science Citation Index Expanded published by Thomson Scientific was carried out to identify the research status and future trends of remote sensing (RS) during 2010–2015. The analysis revealed the institutional, nat...

Paddy rice is a staple food of three billion people in the world. Timely and accurate estimation of the paddy rice planting area and paddy rice yield can provide valuable information for the government, planners and decision makers to formulate polic...

Driven by the urgent demand of remote sensing big data management and knowledge discovery, large-scale remote sensing image retrieval (LSRSIR) has attracted more and more attention. As is well known, hashing learning has played an important role in c...

With the development of remote sensing technologies, the volume of remote sensing data is growing dramatically, making efficient management and retrieval of large-scale remote sensing images increasingly important. Recently, deep hashing for content-...

Total phosphorus (TP) concentration is one of the indicators for surface water quality evaluation. In this study, an indirect algorithm was proposed to retrieve TP concentration. This algorithm retrieves the TP concentration in urban waters based on...

As a fundamental and important task in remote sensing, remote sensing image scene understanding (RSISU) has attracted tremendous research interest in recent years. RSISU includes the following sub-tasks: remote sensing image scene classification, rem...

High-resolution remote sensing image segmentation is a mature application in many industrial-level image applications and it also has military and civil applications. The scene analysis needs to be automated as much as possible with high-resolution r...

To meet the demand for increasing global food production while using limited water resources, crop water stress must be improved in agriculture. Remote-sensing-based plant stress indicators have the benefits of high spatial resolutions, a cheap cost,...

The Remote Sensing Editorial Office wishes to make the following erratum to this paper [1]. [...]

Deep learning technology has achieved great success in the field of remote sensing processing. However, the lack of tools for making deep learning samples with remote sensing images is a problem, so researchers have to rely on a small amount of exist...

Looting of archaeological sites is illegal and considered a major anthropogenic threat for cultural heritage, entailing undesirable and irreversible damage at several levels, such as landscape disturbance, heritage destruction, and adverse social imp...

Integrated and intelligent in situ observations are important for the remote sensing monitoring of dynamic water environments. To meet the field investigation requirements of ocean color remote sensing, we developed a water color remote sensing-orien...

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]

High-quality academic publishing is built on rigorous peer review [...]

The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not.[...]

Rigorous peer-reviews are the basis of high-quality academic publishing [...]

Handling multiple scales efficiently is one avenue for processing big remote sensing imagery data. Unfortunately, imagery is also affected by the infamous modifiable areal unit problem, which creates unpredictable errors at different scales. We devel...

Covering the full texts of all papers published in MDPI’s Remote Sensing between 2009 and 2021, in-depth scientometric analyses were conducted. Trends in publications show an increase in the overall number of papers. A relative increase in pape...

As a core resource of traditional Chinese medicine (TCM), medicinal plants are conventionally monitored and assessed using high-cost, low-efficiency methods. Remote sensing offers an efficient technical alternative for large-scale and dynamic evaluat...

With the advent of new satellite technology, the radiative energy exchanges between Sun, Earth, and space may now be quantified accurately. Nevertheless, much less is known about the magnitude of the energy flows within the climate system and at the...

Deep learning is an important research method in the remote sensing field. However, samples of remote sensing images are relatively few in real life, and those with markers are scarce. Many neural networks represented by Generative Adversarial Networ...

With the arrival of the big data era in Earth observation, the remote sensing communities have accumulated a large amount of invaluable and irreplaceable data for global monitoring. These massive remote sensing data have enabled large-area and long-t...

Water body extraction techniques from remotely sensed images are crucial in water resources distribution studies, climate change studies and other work. The traditional remote sensing water body extraction has the problems of low accuracy and being t...

With the degradation of the environment and the acceleration of urbanization, urban residential land has been undergoing rapid changes and has attracted great attention worldwide. Meanwhile, the quantitative evaluation of the suitability of urban res...

3D pose estimation is always an active but challenging task for object detection in remote sensing images. In this paper, we present a new algorithm for predicting an object’s 3D pose in remote sensing images, called Anchor Points Prediction (A...

The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring vegetation status, as accurate and reliable NDVI time series are crucial for understanding the relationship between environmental conditions, vegetation health, and produ...

Remote sensing image clustering is a challenging task considering its intrinsic complexity. Recently, by combining the spectral and spatial information of the remote sensing data, the clustering performance can be dramatically enhanced, termed as Spe...

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, mon...

Recently, locust outbreaks around the world have destroyed agricultural and natural vegetation and caused massive damage endangering food security. Unusual heavy rainfalls in habitats of the desert locust (Schistocerca gregaria) and lack of monitorin...