Forest type maps require periodic revision, yet field inspection of every stand is impractical. This study tested whether stand-level disagreement between a Sentinel-2 U-Net classifier and the Republic of Korea’s forest type map could support s...
Up-to-date information about the type and spatial distribution of forests is an essential element in both sustainable forest management and environmental monitoring and modelling. The OpenStreetMap (OSM) database contains vast amounts of spatial info...
Forests play a vital role in combating gradual developmental deficiencies and balancing regional ecosystems, yet they are constantly disturbed by man-made or natural events. Therefore, developing a timely and accurate forest disturbance detection str...
Indigenous forests cover 24% of New Zealand and provide valuable ecosystem services. However, a national map of forest types, that is, physiognomic types, which would benefit conservation management, does not currently exist at an appropriate level o...
This paper presents a meticulous exploration of advanced machine learning techniques for precise forest type classification using multi-temporal remote sensing data within a woodland environment. The study comprehensively evaluates a diverse range of...
Aboveground biomass (AGB) mapping using spaceborne LiDAR data and multi-sensor images is essential for efficient carbon monitoring and climate change mitigation actions in heterogeneous forests. The optimal predictors of remote sensing-based AGB vary...
Among the land use–land cover products, tree cover maps are essential tools for assessing forest functionality and ecosystem services, and implementing sustainable forest management. By combining open-source and ancillary high-resolution cartog...
This study investigates the mapping of forest community types for the entire state of West Virginia, United States, using Global Land Analysis and Discovery (GLAD) Phenology Metrics, Analysis Ready Data (ARD) derived from Landsat time series data, an...
In order to accommodate foreseen climate change in European forests, the following are recommended: (i) to increase the number of tree species and the structural diversity; (ii) to replace unsuitable species by native broadleaved tree species, and (i...
Accurate measurement of the tree height and canopy cover density is important for forest biomass and management. Recently, Light Detection and Ranging (LIDAR) and Unmanned Aerial Vehicle (UAV) images have been used to estimate the tree height and can...
The knowledge of tree species distribution at a national scale provides benefits for forest management practices and decision making for site-adapted tree species selection. An accurate assignment of tree species in relation to their location allows...
Long-term forest landscape change in mountainous rural areas reflects interactions among land-use pressure, forest structure and human activities. This study had two primary objectives: (i) to quantify 53 years of change in forest extent, stand struc...
Crop area extent estimates and crop type maps provide crucial information for agricultural monitoring and management. Remote sensing imagery in general and, more specifically, high temporal and high spatial resolution data as the ones which will be a...
Knowledge about crop type distribution is valuable information for effective management of agricultural productivity, food security estimation, and natural resources protection. Algorithms for automatic crop type detection have great potential to pos...
Timely and accurate crop type mapping is a critical prerequisite for the estimation of water availability and environmental carrying capacity. This research proposed a method to integrate time series Sentinel-1 (S1) and Sentinel-2 (S2) data for crop...
Ecosystem maps are foundational tools that support multi-disciplinary study design and applications including wildlife habitat assessment, monitoring and Earth-system modeling. Here, we present continuous-field cover maps for tundra plant functional...
Accurate crop-type mapping is essential for agricultural monitoring, but pixel-based products often suffer from within-field fragmentation, boundary noise, and limited consistency with field management units. This study developed a parcel-constrained...
Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time seri...
Predictive vegetation mapping is an essential tool for managing and conserving high conservation-value forests. Cool temperate rainforests (Rainforest) and cool temperate mixed forests (Mixed Forest, i.e., rainforest spp. overtopped by large remnant...
Monitoring forests is important for measuring overall success of the 2030 Agenda because forests play an essential role in meeting many Sustainable Development Goals (SDG), especially SDG 15. Our study evaluates the contribution of three satellite da...
There are a limited number of studies addressing the forest status, its extent, location, type and composition over a larger area at the regional or national levels. The dense time series and a wide swath of Sentinel-2 data are a good basis for fores...
The comprehensive application of spectral, spatial, and temporal (SST) features derived from remote sensing images is a significant technique for classifying and mapping forest types. Facing limitations in the availability of detailed forest type ide...
We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique f...
Accurate and comparable annual mapping is critical to understanding changing vegetation distribution and informing land use planning and management. A U-Net convolutional neural network (CNN) model was used to map natural vegetation and forest types...
Accurate and up-to-date information is essential for environmental monitoring, particularly in regions characterized by complex topography and heterogeneous landscapes. This study presents a multisource remote sensing–based approach for forest...
Fine-scale mapping of forest types is a prerequisite for accurately assessing forest biomass, biodiversity, ecosystem service values, and carbon budgets. Shihe County, located within an ecotone transitioning from subtropical to temperate monsoon clim...
Research Highlights: In this study, we classified natural forest into four forest types using time-series multi-source remotely sensed data through a proposed semi-supervised model developed and validated for mapping forest types and assessing forest...
In Alaska the current wildfire fuel map products were generated from low spatial (30 m) and spectral resolution (11 bands) Landsat 8 satellite imagery which resulted in map products that not only lack the granularity but also have insufficient accura...
Priority habitat types (HTs) within the Natura 2000 network are of the highest importance for conservation in Europe. However, they often occur in smaller areas and their conservation status is not well understood. One such HT is that of the Tilio&nd...
A natural reserve’s forest is an important base for promoting natural education, scientific research, biodiversity conservation and carbon accounting. Dynamic monitoring of the forest type and forest aboveground biomass (AGB) in a nature reserv...
This paper discusses the potential of using infrared remote sensing data to determine geocryological conditions in the northern part of the Yenisei Ridge in Russia. Landsat-8 thermal infrared images and land surface data were used for our analysis. T...
Dramatic forest dynamics strongly influence pressure mitigation from the increasing population and climate changes of an urban landscape. Effectively monitoring landscapes in a spatiotemporally consistent manner, satellite remote sensing has emerged...
High-resolution crop type mapping is of importance for site-specific agricultural management and food security in smallholder farming regions, but is challenging due to limited data availability and the need for image-based algorithms. In this paper,...
High temporal and spatial resolution optical image time series have been proven efficient for crop type mapping at the end of the agricultural season. However, due to cloud cover and image availability, crop identification earlier in the season is di...
Ontology-driven Geographic Object-Based Image Analysis (O-GEOBIA) contributes to the identification of meaningful objects. In fusing data from multiple sensors, the number of feature variables is increased and object identification becomes a challeng...
Accurate information about forest type and distribution is critical for many scientific applications. It is possible to make a forest type map from the satellite data in a cost effective way. However, forest type mapping over a large and mountainous...
Forest inventory mapping is used worldwide to describe forests at a large spatial scale via the delimitation of portions of the landscape that are structurally homogeneous. Consequently, there is a significant amount of descriptive forest data in for...
The constellation of two Sentinel-1 satellites provides an unprecedented coverage of Synthetic Aperture Radar (SAR) data at high spatial (20 m) and temporal (2 to 6 days over Europe) resolution. The availability of dense time series enables the analy...
Tropical rainforests are complex mosaics of different forests types, each with its own biodiversity and structure. Efforts to characterize and map diversity and composition of tropical forests are vital at both local and larger scales in order to imp...
Forest disturbance detection is of great significance for understanding forest dynamics. The Landsat-based detection of the Trends in Disturbance and Recovery (LandTrendr) algorithm is widely used for forest disturbance mapping. However, there are st...
Although wall-to-wall, accurate, and up-to-date forest composition maps at the stand level are a fundamental input for many applications, ranging from global environmental issues to local forest management planning, countrywide mapping approaches on...
As one of the world’s major forestry countries, accurate forest-type maps in China are of great importance for the monitoring and management of forestry resources. Classifying and mapping forest types on a large scale across the country is chal...
Human activities have both positive and negative impacts on forests, altering the extent and composition of various forest vegetation types, and increasing uncertainty in ecological management. A detailed understanding of the historical distribution...
Precise information on forest canopy height (FCH) is critical for forest carbon stocks estimation and management, but mapping continuous FCH with satellite data at regional scale is still a challenge. By fusing ICESat-2, Sentinel-1/2 images and ancil...
Forest disturbance mapping plays an important role in furthering our understanding of forest dynamics. The Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr) algorithm is widely used in forest disturbance mapping. However, it...
Urban forests are more about people than trees. The positivist approach faces many obstacles in analyzing current urban forest-related issues; thus, this study adopted semantic differences and cognitive map approaches to evaluate the subjective prefe...
The expansion of plantation poses new challenges for mapping forest, especially in mountainous regions. Using multi-source data, this study explored the capability of the random forest (RF) algorithm for the extraction and mapping of five forest type...
Efficient methodologies for mapping forest types in complicated mountain areas are essential for the implementation of sustainable forest management practices and monitoring. Existing solutions dedicated to forest-type mapping are primarily focused o...
Unaffected by cloud cover and solar illumination, synthetic aperture radar (SAR) images coupled with quad-polarimetric techniques have significant potential for mapping forest aboveground biomass (AGB) in the mountains of southern China. To improve t...
Forest recovery from past disturbance is an integral process of ecosystem carbon cycles, and remote sensing provides an effective tool for tracking forest disturbance and recovery over large areas. Although the disturbance products (tracking the conv...
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