Showing papers in "International Journal of Remote Sensing in 2019"
TL;DR: For many years, crop type classification and monitoring has been an important data source for agricultural monitoring and food security assessment studies as discussed by the authors, and reliable and accurate crop classification maps are an important source of information.
Abstract: Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring...
105 citations
TL;DR: This study develops a scale robust CNN structure to improve the segmentation accuracy of building data from high-resolution aerial and satellite images and introduces a combined data augmentation and relative radiometric calibration method for multi-source building extraction.
Abstract: Identifying buildings from remote sensing imagery has been a challenge due to uncertainties from remote sensing imagery and variations in building structure and texture. In this study, we develop a...
98 citations
TL;DR: A long short-term memory (LSTM) recurrent neural network (RNN) model is built to take advantage of the temporal pattern of crops across image time series to improve the accuracy and reduce the complexity of land cover maps.
Abstract: Land cover maps are significant in assisting agricultural decision making. However, the existing workflow of producing land cover maps is very complicated and the result accuracy is ambiguous. This...
97 citations
TL;DR: The superpixel extraction via SEEDS method was found to be the optimal superpixel segmentation approach for CNN classification, and the scale effect on CNN classification accuracy was investigated by comparing the four super pixel segmentation methods.
Abstract: Pixel-based convolutional neural network (CNN) has demonstrated good performance in the classification of very high resolution images (VHRI) from which abstract deep features are extracted. However...
96 citations
TL;DR: In this paper, the number of oil palm trees in a plantation area is important to predict the yield of palm oil, manage the yield, and manage the management of the plantations.
Abstract: Oil palm trees are important economic crops in tropical areas. Accurate knowledge of the number of oil palm trees in a plantation area is important to predict the yield of palm oil, manage ...
85 citations
TL;DR: A deep learning approach is used to predict and count oil palms in satellite imagery by utilizing two different convolution neural networks to detect young and mature oil palm separately and uses GIS during data processing and result storage process.
Abstract: Detection and counting of oil palm are important in oil palm plantation management. In this article, we use a deep learning approach to predict and count oil palms in satellite imagery. Previous oi...
84 citations
TL;DR: The animals of the rainforest canopies are often endangered by deforestation or hunting but are difficult to survey and study because of the inaccessibility of the treetops, combined with the visual ca...
Abstract: Animals of the rainforest canopies are often endangered by deforestation or hunting but are difficult to survey and study because of the inaccessibility of the treetops, combined with the visual ca...
71 citations
TL;DR: In mountainous areas, land surface temperature exhibits a high spatial heterogeneity due to the influences from the changes in surface topographic factors (elevation, aspect, and slope), vege...
Abstract: In mountainous areas, land surface temperature (LST) exhibits a high spatial heterogeneity due to the influences from the changes in surface topographic factors (elevation, aspect, and slope), vege...
65 citations
TL;DR: In this article, the first comparison of Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) in identifying soil salinity using soil physiochemical, spectral, and spectral properties is presented.
Abstract: This study presents the first comparison of Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) in identifying soil salinity using soil physiochemical, spectral, s...
64 citations
TL;DR: The Thermal Infrared Sensor (TIRS) on board the Landsat 8 is an important parameter in the climatological, hydrological, ecological, and meteorological studies.
Abstract: Land-surface temperature (LST) is an important parameter in the climatological, hydrological, ecological, and meteorological studies. The Thermal Infrared Sensor (TIRS) on board the Landsat 8 is a ...
64 citations
TL;DR: The proliferation of relatively affordable off-the-shelf drones offers great opportunities for wildlife monitoring and conservation as discussed by the authors, and the recent reduction in the cost of thermal infrared can be attributed to this.
Abstract: The proliferation of relatively affordable off-the-shelf drones offers great opportunities for wildlife monitoring and conservation. Similarly the recent reduction in the cost of thermal infrared c...
TL;DR: Deep convolutional neural network denoiser prior is integrated into unidirectional variation model, named as UV-DCNN, to simultaneously destripe and denoise optical remote sensing images, which can be efficiently solved by the alternating minimization optimization method.
Abstract: Stripe and random noise are two different degradation phenomena commonly co-existing in optical remote sensing images, which are often modelled as inverse problems, respectively. When solvi...
TL;DR: In this paper, the vegetation fraction (VF) monitoring in a specific area is a very important parameter for precision agriculture and high-cost flights on aeroplanes and satellite imagery were used.
Abstract: The vegetation fraction (VF) monitoring in a specific area is a very important parameter for precision agriculture. Until a few years ago, high-cost flights on aeroplanes and satellite imagery were...
TL;DR: The experimental result shows that the classification performance using SSFPCA and SFPCA outperforms that of using conventional PCA, SPC a, SSPCA, FPCA, Super PCA and using the entire original dataset without employing any feature reduction.
Abstract: The remote sensing hyperspectral images (HSIs) usually comprise many important information of the land covers capturing through a set of hundreds of narrow and contiguous spectral wavelength bands....
TL;DR: In this article, one of the most promising methods for monitoring affected areas, which has a negative impact on soil productivity and agricultural fields, has been proposed, is the use of soil salinity monitoring.
Abstract: Soil salinity is a major environmental threat, which has a negative impact on soil productivity and agricultural fields. One of the most promising methods for monitoring affected areas, which has s...
TL;DR: In this article, Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and s...
Abstract: Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and s...
TL;DR: In this paper, the ability of the Sentinel-2A satellite to estimate the severity of fire severity maps has been evaluated for planning, managing, and rehabilitation after wildfire events, and the results showed that accurate, reliable, and timely burn severity maps are necessary for planning and managing wildfire management.
Abstract: Accurate, reliable, and timely burn severity maps are necessary for planning, managing and rehabilitation after wildfires. This study aimed at assessing the ability of the Sentinel-2A satellite to ...
TL;DR: In this article, the linear band model and the log-transformed band ratio model were compared in two study areas of the Irish coast with different morphological and environmental conditions, and the linear model fitted better than the LRT model providing coefficient of determination values, R2, between 0.83 and 0.88 for the five images considered in the study.
Abstract: Bathymetry estimated from optical satellite imagery has been increasingly implemented as an alternative to traditional bathymetric survey techniques. The availability of new sensors such as Sentinel-2 with improved spatial and temporal resolution, in comparison with previous optical sensors, offers innovative capabilities for bathymetry derivation. This study presents an assessment of the fit between satellite data and the underlying models in the most widely used empirical algorithms: the linear band model and the log-transformed band ratio model using Sentinel-2A data. Both models were tested in two study areas of the Irish coast with different morphological and environmental conditions. Results showed that the linear band model fitted better than the log-transformed band ratio model providing coefficient of determination values, R2, between 0.83 and 0.88 (0 m–10 m) for the five images considered in the study. The closest fit was found in the depth range 2 m–6 m. Atmospheric correction, bottom type influence, and water column conditions proved to be key factors in the bathymetric derivation using these satellite datasets.
TL;DR: The UAVs represent one of the most important innovation technologies of the last years; the progress made in the field of sensors has allowed to equip the UAV with vario...
Abstract: The unmanned aerial vehicles (UAVs) represent one of the most important innovation technologies of the last years; the progress made in the field of sensors has allowed to equip the UAVs with vario...
TL;DR: The vast size of oil palm plantations has led to lightweight unmanned aerial vehicles (UAVs) being identified as cost effective tools to generate inventories for improved planta... as discussed by the authors.
Abstract: The vast size of oil palm (Elaeis guineensis) plantations has led to lightweight unmanned aerial vehicles (UAVs) being identified as cost effective tools to generate inventories for improved planta...
TL;DR: In this article, the spatial and temporal extents of permanent and temporary bodies of surface water are monitored for various applications such as water resource management, climate modelling, and biodiv...
Abstract: Monitoring the spatial and temporal extents of permanent and temporary bodies of surface water is important for various applications such as water resource management, climate modelling, and biodiv...
TL;DR: Salinization of soil is one of the most important environmental issues in arid and semi-arid areas, and agricultural production and ecological development have been profoundly influenced by this issue as mentioned in this paper.
Abstract: Salinization of soil is one of the most important environmental issues in arid and semi-arid areas. Accordingly, agricultural production and ecological development have been profoundly influenced i...
TL;DR: The 6-day repeatability of the Sentinel-1 constellation allows building up an interferometric stack with unprecedented velocity as discussed by the authors, which allows for easily updatable hot-spot analyses, frequently repeated following the u...
Abstract: The 6-days repeatability of Sentinel-1 constellation allows building up an interferometric stack with unprecedented velocity. Easily updatable hot-spot analyses, frequently repeated following the u...
TL;DR: In this article, the authors used remote sensing approaches using statistical models to scale up grassland above-ground biomass from the sample scale to the regional scale, and found that remote sensing could be the most effective means for scaling up grass land above ground biomass (AGB).
Abstract: Remote sensing could be the most effective means for scaling up grassland above-ground biomass (AGB) from the sample scale to the regional scale. Remote sensing approaches using statistical models ...
TL;DR: In this paper, an approach for estimating the soil moisture content (SMC) in arid environment in Tunisia is presented, which is very important in countries characterized by arid and semi-arid climate.
Abstract: In this paper, an approach for estimating the soil moisture content (SMC) in arid environment in Tunisia is presented. In countries characterized by arid and semi-arid climate, it is very important...
TL;DR: Step-by-step guidance for classifier training, model selection, and map production with supervised learning model selection is provided and the optimal classifiers and their associated polynomial degree of input features and hyperparameters vary for the two image datasets that were tested.
Abstract: Remote sensing scientists are increasingly adopting machine learning classifiers for land cover and land use (LCLU) mapping, but model selection, a critical step of the machine learning classificat...
TL;DR: In this article, the authors developed a robust methodology to estimate pasture biomass across the huge land surface of Mongolia (1.56 × 106 km2) using high-resolution Landsat 8 satellite data calibrations.
Abstract: The aim of this study was to develop a robust methodology to estimate pasture biomass across the huge land surface of Mongolia (1.56 × 106 km2) using high-resolution Landsat 8 satellite data calibr...
TL;DR: In this article, the authors assessed the Dianchi Lake watershed as a case study area to illustrate the characteristics and patterns of the watershed in a high spatial and temporal resolution, and assessed the long-term impervious surface area (ISA) patterns and characteristics.
Abstract: Chinese urbanization has drawn widespread attention since the 21st century. Understanding urban expansion at a watershed scale including cities of different sizes is important for improving our current knowledge of the urban extent and its impact on the hydrological cycle, water management, surface energy balances, and biodiversity. Impervious surface area (ISA) can be used as a synthesized quantifiable index to reflect the intensity of natural ecosystems changing into urban ecosystems. It is important to understand ISA patterns and characteristics, which requires long-term impervious surface data at a high spatial and temporal resolution. Previous methods of ISA estimation mainly focused on the spectral differences between ISA and other land covers, and most studies were inclined to use one or a few images without fully considering the long time series of the temporal domain of the reflective data on remote-sensing images. This assessed the Dianchi Lake watershed as a case study area to illustrat...
TL;DR: Combining optical and polarimetric synthetic aperture radar (PolSAR) earth observations offers a complementary data set with a significant number of spectral, textural, and polar-imetric features as mentioned in this paper.
Abstract: Combining optical and polarimetric synthetic aperture radar (PolSAR) earth observations offers a complementary data set with a significant number of spectral, textural, and polarimetric features fo...
TL;DR: In this paper, the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) is used to estimate near-surface soil moisture from Signal-to-Noise Ratio (S...
Abstract: Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) is a new remote-sensing technique, and it can be used to estimate near-surface soil moisture from Signal-to-Noise Ratio (S...