In this study, we demonstrate the ability of a new operational system to detect forest loss at a large scale accurately and in a timely manner. We produced forest loss maps every week over Vietnam, Cambodia, and Laos (>750,000 km2 in total) using...
We introduce and test a new method to detect annual forest cover loss from time series estimates of percent tree cover. Our approach is founded on two realistic assumptions: (1) land cover disturbances are rare events over large geographic areas that...
Intense, large-scale forest fires are damaging and very challenging to control. Locations, where various types of fire behavior occur, vary depending on environmental factors. According to the burning site of forest fires and the degree of damage, th...
This paper aims to develop a new methodology for monitoring forest disturbances and regrowth using ALOS PALSAR data in tropical regions. In the study, forest disturbances and regrowth were assessed between 2007 and 2010 in Vietnam, Cambodia and Lao P...
Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fi...
Forest fires, intensified by climate change, threaten tropical ecosystems by accelerating biodiversity loss, releasing carbon emissions, and altering hydrological cycles. Continuous detection of fire-induced forest loss is therefore critical. However...
To solve the problem of the poor performance of a flame detection algorithm in a complex forest background, such as poor detection performance, insensitivity to small targets, and excessive computational load, there is an urgent need for a lightweigh...
Fractional Forest cover holds significance in characterizing the ecological condition of forests and serves as a crucial input parameter for climate and hydrological models. This research introduces a novel approach for generating a 250 m fractional...
Fire is a concern for the sustainability of dry forests such as those of the Mediterranean region, especially under warming climate and high human use. We used data derived from Landsat and MODIS sensors to assess forest changes in the Talassemtane N...
The fight against deforestation and forest degradation is now a major challenge for the preservation of global forest ecosystems. The remote sensing forest monitoring methods that are currently deployed are not always adapted to the Ivorian context b...
China has implemented a series of forestry law, policies, regulations, and afforestation projects since the 1970s. However, their impacts on the spatial and temporal patterns of forests have not been fully assessed yet. The lack of an accurate, high-...
This study assesses ALOS-2/PALSAR-2 (ALOS2) polarimetric images for detecting forest volume losses due to selective logging in a region in the Brazilian Amazon. Two logging-intensive areas, APU 2016, and APU 2017, were studied. ALOS2 imagery attribut...
The precise spatially explicit data on land cover and land use changes is one of the essential variables for enhancing the quantification of greenhouse gas emissions and removals, which is relevant for meeting the goal of the European economy and soc...
Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss...
Effective detection of electricity theft is essential to maintain power system reliability. With the development of smart grids, traditional electricity theft detection technologies have become ineffective to deal with the increasingly complex data o...
Dynamic detection of forest change is the fundamental method of monitoring forest resources and an essential means of preserving the accuracy and timeliness of forest land resource data. This study focuses on a deep learning-based method for dynamic...
The timing, location, intensity, and drivers of forest disturbance and recovery are crucial for developing effective management strategies and policies for forest conservation and ecosystem resilience. Although many algorithms and improvement methods...
Fire use for land management is widespread in natural tropical and plantation forests, causing major environmental and economic damage. Recent studies combining active fire alerts with annual forest-cover loss information identified fire-related fore...
The dry lowland and mangrove forests of Kutai National Park (KNP) in Indonesia provide invaluable ecosystem services to local human populations (>200,000 in number), serve as immense carbon sinks to recapture anthropogenic emissions, and safeguard...
Identifying areas of forest loss is a fundamental aspect of sustainable forest management. Global Forest Change (GFC) datasets developed by Hansen et al. (in Science 342:850–853, 2013) are publicly available, but the accuracy of these datasets...
The commitment by over 100 governments covering over 90% of the world’s forests at the COP26 in Glasgow to end deforestation by 2030 requires more effective forest monitoring systems. The near real-time (NRT) change detection of forest cover lo...
Disease and detection is crucial for the protection of forest growth, reproduction, and biodiversity. Traditional detection methods face challenges such as limited coverage, excessive time and resource consumption, and poor accuracy, diminishing the...
We present a flexible methodology to identify forest loss in synthetic aperture radar (SAR) L-band ALOS/PALSAR images. Instead of single pixel analysis, we generate spatial segments (i.e., superpixels) based on local image statistics to track homogen...
Logging, including selective and illegal activities, is widespread, affecting the carbon cycle and the biodiversity of tropical forests. However, automated approaches using very high resolution (VHR) satellite data (≤1 m spatial resolution) to acc...
Tropical dry forest is one of the most threatened ecosystems, and it is disappearing at an alarming rate. Shifting cultivation is commonly cited as a driver of tropical dry forest loss, although it helps to maintain the forest coverage but with less...
Forest fires are major forestry disasters that cause loss of forest resources, forest ecosystem safety, and personal injury. It is often difficult for current forest fire detection models to achieve high detection accuracy on both large and small tar...
Forest degradation is a major issue in ecosystem monitoring, and to take reformative measures, it is important to detect, map, and quantify the losses of forests. Synthetic Aperture Radar (SAR) time-series data have the potential to detect forest los...
The Norway spruce is one of the most important tree species in Europe. This tree species has been put under considerable pressure due to the ongoing impacts of climate change. Meanwhile, frequent droughts and pest outbreaks are reported as the main r...
Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known p...
A forest wildlife detection algorithm based on an improved YOLOv5s network model is proposed to advance forest wildlife monitoring and improve detection accuracy in complex forest environments. This research utilizes a data set from the Hunan Hupings...
Land use change from forests to grazing lands is one of the important sources of greenhouse gas emissions in many parts of the tropics. The objective of this study was to analyze the extent of soil organic carbon (SOC) loss from the conversion of nat...
Selective logging is a major cause of forest degradation in the tropics, but its precise scale, location and timing are not known as wide-area, automated remote sensing methods are not yet available at this scale. This limits the abilities of governm...
Forest fire smoke detection based on deep learning has been widely studied. Labeling the smoke image is a necessity when building datasets of target detection and semantic segmentation. The uncertainty in labeling the forest fire smoke pixels caused...
While the methods for monitoring deforestation are relatively well established, there is still no compromise on those for forest degradation. We propose here a systematic review on studies about forest degradation in the Congo Basin. Our analysis foc...
Forest fires present a significant challenge to ecosystems, particularly due to factors like tree cover that complicate fire detection tasks. While fire detection technologies, like YOLO, are widely used in forest protection, capturing diverse and co...
Forest cover change is critical in the regulation of global and regional climate change through the alteration of biophysical features across the Earth’s surface. The accurate assessment of forest cover change can improve our understanding of i...
In 2016, in response to forest loss, the Myanmar government banned logging operations for 1 year throughout the entire country and for 10 years in specific regions. However, it is unclear whether this measure will effectively reduce forest loss, beca...
Loss of forest cover and derived effects on forest ecosystems services has led to the establishment of land management policies and forest monitoring systems, and consequently to the demand for accurate and multitemporal data on forest extent and str...
At COP26, the Glasgow Leaders Declaration committed to ending deforestation by 2030. Implementing deforestation-free supply chains is of growing importance to importers and exporters but challenging due to the complexity of supply chains for agricult...
Tropical forests play a key role in the global carbon and hydrological cycles, maintaining biological diversity, slowing climate change, and supporting the global economy and local livelihoods. Yet, rapidly growing populations are driving continued d...
Forest fire detection from videos or images is vital to forest firefighting. Most deep learning based approaches rely on converging image loss, which ignores the content from different fire scenes. In fact, complex content of images always has higher...
The frequent occurrence of forest fires causes irreparable damage to the environment and the economy. Therefore, the accurate detection of forest fires is particularly important. Due to the various shapes and textures of flames and the large variatio...
The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing...
To reduce the loss induced by forest fires, it is very important to detect the forest fire smoke in real time so that early and timely warning can be issued. Machine vision and image processing technology is widely used for detecting forest fire smok...
Rainwater-induced soil erosion occurring in the forest is a special phenomenon of soil erosion in many red soil areas. Detection of such soil erosion is essential for developing land management to reduce soil loss in areas including southern China an...
The SSL/TLS protocol is widely used in data encryption transmission. Aiming at the problem of detecting SSL/TLS-encrypted malicious traffic with small-scale and unbalanced training data, a deep-forest-based detection method called DF-IDS is proposed...
Spatio-temporal information on process-based forest loss is essential for a wide range of applications. Despite remote sensing being the only feasible means of monitoring forest change at regional or greater scales, there is no retrospectively availa...
The threat of forest fires to human life and property causes significant damage to human society. Early signs, such as small fires and smoke, are often difficult to detect. As a consequence, early detection of smoke and fires is crucial. Traditional...
Wind damage is one of the major factors affecting forest ecosystem sustainability, especially in the coastal region. Typhoon Lekima is among the top five most devastating typhoons in China and caused economic losses totaling over USD 8 billion in Zhe...
With climate change, extreme storms are expected to occur more frequently. These storms can cause severe forest damage, provoking direct and indirect economic losses for forestry. To minimize economic losses, the windthrow areas need to be detected f...
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