Showing papers in "Remote Sensing of Environment in 2015"

TL;DR: In this article, a new cirrus band was introduced for detecting clouds, especially for thin cirrus clouds, and a new version of the Fmask algorithm was developed for use with Landsat 8 images.

TL;DR: In this paper, the authors evaluated the skill of a new, merged soil moisture product (ECV_SM) that has been developed in the framework of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative projects.

TL;DR: In this article, a special issue on Remote Sensing of Inland Waters comprises 16 articles on freshwater ecosystems around the world ranging from lakes and reservoirs to river systems using optical data from a range of in situ instruments as well as airborne and satellite platforms.

TL;DR: This review has organised the literature by the unit of analysis and the comparison method used to identify change, significantly reducing the conceptual overlap present in previous reviews giving a succinct nomenclature with which to understand and apply change detection workflows.

TL;DR: In this paper, the advancement of airborne LiDAR technology, including data configuration, feature spaces, classification techniques, and radiometric calibration/correction, is reviewed and discussed, with an emphasis on identification of the approach, analysis of pros and cons, investigating the overall accuracy, and how the classification results can serve as an input for different urban environmental analyses.

TL;DR: In this paper, the authors developed a methodology to map active and fallow land using MODIS Normalized Differenced Vegetation Index (NDVI) time series and provided the first European-wide map of the extent of abandoned farmland (cropland and grassland) and recultivation.

TL;DR: In this article, a generalized approach for mapping crop yields with satellite data and test its predictions for yields across more than 17,000 maize fields and 11,000 soybean fields spanning multiple states and years in the Midwestern United States.

TL;DR: In this paper, the effect of aerosol characteristics (e.g., aerosol composition and size distribution) on the AOD-PM2.5 relationship is seldom considered in observation-based methods.

TL;DR: The NASA Hyperspectral InfraRed Imager (HyspIRI) as mentioned in this paper is comprised of a visible to short-wavelength infrared (VSWIR) imaging spectrometer and a thermal infrared (TIR) multispectral imager, together with an Intelligent Payload Module (IPM) for onboard processing and rapid downlink of selected data.

TL;DR: In this paper, a semi-empirical single-band turbidity retrieval algorithm using the near infrared (NIR) band at 859 nm in highly turbid waters is assessed.

TL;DR: In this article, in-situ soil moisture measurements from three networks which represent different climatic and vegetation conditions over the Tibetan Plateau are used to evaluate the skill of seven remotely sensed soil moisture products and one reanalysis soil moisture product in the period of 2002-2012.

TL;DR: In this paper, the authors performed a statistical comparison of the state-of-the-art tropospheric corrections estimated from the MERIS and MODIS spectrometers, a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and new power-law empirical methods.

TL;DR: In this paper, the authors investigated the characteristics of glaciers and their changes through time from a wide range of satellite sensors, such as area, elevation change and surface velocity, and proposed algorithms for product creation and post-processing.

TL;DR: The results of this study indicate that STRUM is more suitable for data fusion applications requiring Landsat-like surface reflectances, such as gap-filling and cloud masking, especially in situations where few high-resolution images are available.

TL;DR: In this article, an area-based approach was proposed to predict wood volume, stem volume, aboveground biomass, and basal area across a wide range of canopy structures, sites and LiDAR characteristics.

TL;DR: In this paper, the authors used Carnegie Airborne Observatory visible-to-shortwave infrared (VSWIR) imaging spectroscopy with light detection and ranging (LiDAR) to assess the foliar traits of Amazonian and Andean tropical forest canopies.

TL;DR: Wang et al. as mentioned in this paper provided a two-stage framework of long-term mapping of urban areas at an annual frequency in Beijing, China, over the period from 1984 to 2013.

TL;DR: In this article, a hybrid inversion method was developed to estimate the LAI values of crops based on PROSAIL simulation datasets, 43 hyperspectral vegetation indices (VIs), including the optimized soil-adjusted vegetation index (OSVAI) and modified triangular vegetation index(MTVI2), were analyzed to identify optimal VIs for estimating LAI.

TL;DR: In this paper, the authors presented a comprehensive assessment of the relationship between far-red SIF retrieved at 760nm (SIF760) and gross primary production (GPP) and its transferability across three structurally and physiologically contrasting ecosystems: perennial grassland, cropland and mixed temperate forest.

TL;DR: In this article, a 3-arc-second water body map (G3WBM) was developed by using an automated algorithm to process multi-temporal Landsat images from the Global Land Survey (GLS) database.

TL;DR: Wang et al. as mentioned in this paper developed an automated, Landsat-based paddy rice mapping (Landsat-RICE) system that uses time series Landsat images and a phenology-based algorithm based on the unique spectral characteristics of paddy Rice during the flooding/transplanting phase.

TL;DR: Aquatic color radiometry remote sensing of coastal and inland water bodies is of great interest to a wide variety of research, management, and commercial entities as well as the general public as mentioned in this paper.

TL;DR: In this article, Vanhellemont et al. presented the use of the high quality SWIR bands of the Operational Land Imager (OLI) on Landsat-8, launched in 2013, to extend their existing turbid water atmospheric correction to extremely turbid waters.

TL;DR: In this article, an integrated protocol is proposed to produce spatially exhaustive annual BAP image composites that are seasonally constrained and free of atmospheric perturbations, which can be used for mapping and monitoring land cover and land cover change.

TL;DR: In this article, the authors apply spectral trend analysis of Landsat Thematic Mapper (TM) and enhanced thematic mapper plus (ETM+) data from 1984 to 2012 to detect, characterize, and attribute forest changes in the province of Saskatchewan, Canada.

TL;DR: In this article, the authors developed an algorithm to simultaneously process data from different Landsat platforms and sensors (TM and ETM+) to map annual forest cover loss and decadal forest cover gain.

TL;DR: In this paper, the authors analyzed the temporal consistency of multi-sensor NDVI time series by analyzing the cooccurrence between breaks in the NDVI and sensor shifts from GIMMS3g (Global Inventory Modeling and Mapping Studies 3rd generation), VIP3 (Vegetation Index and Phenology version 3), LTDR4 (Long Term Data Record version 4) and SPOT-VGT (Systeme Pour l'Observation de la Terre VEGETATION).

TL;DR: In this article, a robust data-driven method to track tropical deforestation and degradation based on Landsat time series data is presented, where change magnitude, calculated based on differences between observed and expected values in a monitoring period, was found to be an essential predictor variable for disturbances.

TL;DR: DBEST as discussed by the authors uses a novel segmentation algorithm which simplifies the trend into linear segments using one of three user-defined parameters: a generalisation-threshold parameter δ, the m largest changes, or a threshold β for the magnitude of changes of interest for detection.

TL;DR: The authors used bagged derision trees to predict the location of surface water cover with an inundation probability map that was generated using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map.