657 Results Found

Algal blooms pose a serious threat not only to the lake ecosystem of Lake Bosten but also by negatively impacting its rapidly developing fisheries and tourism industries. This study focuses on Lake Bosten as the research area and utilizes multi-sourc...

Stand age is a significant factor when investigating forest resource management. How to obtain age data at a sub-compartment level on a large regional scale conveniently and in real time has become an urgent scientific challenge in forestry research....

This study examines the intricate relationship between water resource dynamics and drought indices in the Yinchuan Plain, China, by integrating multi-source remote sensing data with advanced deep learning techniques. Using data from 2002 to 2022, we...

Carbon sequestration and oxygen release (CSOR) are core regulating functions of terrestrial ecosystems. However, regional assessments often fail to (i) separate scale-driven high supply from per-area efficiency, (ii) detect structural instability and...

In this study, using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC (vegetation, wetlands and others only), we studied spatial and areal inconsistencies in the three most recent multi-resource land cover products in a complex mou...

As data relay satellites (DRSs) play an increasingly important supporting role in remote sensing missions, efficient coordination across space–ground multiresources becomes a significant problem. Owing to the implementation problem of the centr...

High spatial resolution soil moisture (SM) data are crucial in agricultural applications, river-basin management, and understanding hydrological processes. Merging multi-resource observations is one of the ways to improve the accuracy of high spatial...

The Permanently Shadowed Regions (PSRs) of the lunar south pole have never been directly sampled. To explore and discover lunar resources, the Chinese lunar south pole exploration mission is scheduled to land in direct sunlight near the PSR, where sa...

Geothermal energy is an eco-friendly, renewable source of underground thermal energy that exists in the interior of the earth. By tapping into these formations, fluids can be channeled to heat the rock formations above, resulting in a significantly h...

Research into global water resources is challenged by the lack of ground-based hydrometric stations and limited data sharing. It is difficult to collect good quality, long-term information about river discharges in ungauged regions. Herein, an approa...

The Iter 34 (Antonine Itinerary XXXIV) is the name of the Roman road that crosses the province of Álava from west to east. Since no specific path was officially recognized before our study, the remains of the road did not benefit from heritage...

With the development and popularization of remote sensing earth observation technology and the remote sensing satellite system, the problems of insufficient proactiveness, relevance and timeliness of large-scale remote sensing supporting services are...

The ghost city phenomenon is a serious problem resulting from the rapid urbanization process in China. Estimation of the ghost city rate (GCR) can provide information about vacant dwellings. This paper developed a methodology to quantitatively evalua...

As the number and variety of remote sensing satellites continue to grow, user demands are becoming increasingly complex and diverse. Concurrently, there is an escalating requirement for timeliness in satellite observations, thereby augmenting the com...

Advances in remote inventory and analysis of forest resources during the last decade have reached a level to be now considered as a crucial complement, if not a surrogate, to the long-existing field-based methods. This is mostly reflected in not only...

Gold is a vital strategic resource for many countries. The Laozhaiwan area is an important gold resource base in Yunnan Province and even nationwide. Conducting mineral resource exploration in this region to increase gold reserves is of great signifi...

This paper proposed a new remote sensing observation capability evaluation model (RSOCE) based on analytic hierarchy process to quantitatively evaluate the capability of multi-satellite cooperative remote sensing observation. The analytic hierarchica...

It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means...

Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sens...

This paper proposes an adaptive multi-threshold image segmentation method named IBKA-OTSU to address the limitations of existing deep learning-based image segmentation methods, particularly their heavy reliance on large-scale annotated datasets and h...

Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water, and carbon cycles. Remote sensing...

Black soil is a precious soil resource, yet it is severely affected by gully erosion, which is one of the most serious manifestations of land degradation. The determination of the location and shape of gullies is crucial for the work of gully erosion...

Detecting small objects in high-resolution remote sensing images presents persistent challenges due to their limited pixel coverage, complex backgrounds, and dense spatial distribution. These difficulties are further exacerbated by the increasing res...

The acquisition of massive remote sensing data makes it possible to deeply fuse remote sensing and artificial intelligence (AI). The mobility and cost advantages of new sensing platforms in the Internet of Things (IoT) make them ideal for continuous...

Remote sensing image object detection holds significant research value in resources and the environment. Nevertheless, complex background information and considerable size differences between objects in remote sensing images make it challenging. This...

Semantic segmentation of remote sensing images is an important technique for spatial analysis and geocomputation. It has important applications in the fields of military reconnaissance, urban planning, resource utilization and environmental monitorin...

Snow contributes to regional and global water budgets, and is of critical importance to water resources management and our society. Along with advancement in remote sensing tools and techniques to retrieve snowfall, verification and refinement of the...

Evapotranspiration (ET) plays an important role in coupling the global energy, water, and biogeochemical cycles and explains ecosystem responses to global environmental change. However, quantifying and mapping the spatiotemporal distribution of ET ac...

Due to the inherent inter-class similarity and class imbalance of remote sensing images, it is difficult to obtain effective results in single-source semantic segmentation. We consider applying multi-modal data to the task of the semantic segmentatio...

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,...

Remote sensing visual grounding, a pivotal technology bridging natural language and high-resolution remote sensing images, holds significant application value in disaster monitoring, urban planning, and related fields. However, it faces critical chal...

Early crop planting area estimation is crucial for achieving effective government resource allocation, optimizing resource distribution planning, and preparation related to food security. Utilizing remote sensing images during the crop growth period...

Forest volume is an important information for assessing the economic value and carbon sequestration capacity of forest resources and serves as a key indicator for energy flow and biodiversity. Although remote sensing technology is applied to estimate...

Efficient and accurate semantic segmentation is the key technique for automatic remote sensing image analysis. While there have been many segmentation methods based on traditional hand-craft feature extractors, it is still challenging to process high...

Predicting freshwater resources is a major concern in West Africa, where large parts of the population depend on rain-fed subsistence agriculture. However, a steady decline in the availability of in-situ measurements of climatic and hydrologic variab...

Although deep learning-based methods for semantic segmentation have achieved prominent performance in the general image domain, semantic segmentation for high-resolution remote sensing images remains highly challenging. One challenge is the large ima...

Considering the complexity of landslide hazards, their manual investigation lacks efficiency and is time-consuming, especially in high-altitude plateau areas. Therefore, extracting landslide information using remote sensing technology has great advan...

Change detection is an important technique that identifies areas of change by comparing images of the same location taken at different times, and it is widely used in urban expansion monitoring, resource exploration, land use detection, and post-disa...

Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detectio...

In the American West, wildfires and earthquakes are increasingly threatening the archaeological, historical, and tribal resources that define the collective identity and connection with the past for millions of Americans. The loss of said resources d...

High-resolution snow depth monitoring is a crucial foundation for precise disaster early warning and optimal water resource management. Traditional snow depth estimation methods mainly rely on passive microwave remote sensing data, but due to their l...

A lightweight YOLOv8 variant, CIMB-YOLOv8, is proposed to address challenges in remote sensing object detection, such as complex backgrounds and multi-scale targets. The method enhances detection accuracy while reducing computational costs through tw...

Fuel Moisture Content (FMC) is a critical indicator for assessing forest fire risk and formulating early warning strategies, as its spatiotemporal dynamics directly influence the accuracy of fire danger rating. To improve the accuracy of forest FMC e...

Remote calibration is an advanced methodology that leverages electricity meters, intelligent detection, and computing technologies to enhance calibration efficiency and precision significantly. However, current research predominantly focuses on isola...

Change detection (CD) in high-resolution remote sensing imagery remains challenging due to the complex nature of objects and varying spectral characteristics across different times and locations. Convolutional neural networks (CNNs) have shown promis...

More and more attention has been paid to farmland water conservancy project (FWCP) maintenance in China, which can reallocate water resources in a more rational and efficient manner. Compared with the traditional survey such as field survey, FWCP mai...

Forests are essential for global environmental well-being because of their rich provision of ecosystem services and regulating factors. Global forests are under increasing pressure from climate change, resource extraction, and anthropologically-drive...

In recent years, non-grain production of cultivated land (NGPCL) has become increasingly prominent in China, seriously affecting food production and threatening the country’s food security. However, there is a lack of large-scale and high-preci...

Accurate urban land use classification is vital for urban planning, resource allocation, and sustainable management. Traditional remote sensing methods struggle with fine-grained classification and spatial structure identification, while socio-econom...

Evapotranspiration (ET) is a critical component of the water and energy balances, and the number of remote sensing-based ET products and estimation methods has increased in recent years. Various aspects of remote sensing of ET are reported in 11 pape...