Showing papers in "Remote Sensing of Environment in 2016"

TL;DR: The Landsat 8 Operational Land Imager (OLI) atmospheric correction algorithm is developed using the Second Simulation of the Satellite Signal in the Solar Spectrum Vectorial (6SV) model, refined to take advantage of the narrow OLI spectral bands, improved radiometric resolution and signal-to-noise.

TL;DR: Improvements made to the fire detection algorithm and swath-level product that were implemented as part of the Collection 6 land-product reprocessing, which commenced in May 2015, indicated targeted improvements in the performance of the collection 6 activeFire detection algorithm compared to Collection 5, with reduced omission errors over large fires, and reduced false alarm rates in tropical ecosystems.

TL;DR: In this paper, the authors compared the top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified.

TL;DR: It is recommended that future research efforts focus stronger on the causal understanding of why tree species classification approaches work under certain conditions or – maybe even more important - why they do not work in other cases as this might require more complex field acquisitions than those typically used in the reviewed studies.

TL;DR: The aim of this paper is to report the current status of the global USGS Landsat archive, document the existing and anticipated contributions of LGAC to the archive, and characterize the current acquisitions of Lands at-7 and Landsat-8.

TL;DR: The results indicated that the Landsat 8, GEE, and improved PPPM algorithm can effectively support the yearly mapping of paddy rice in NE Asia and has a high accuracy with the producer (user) accuracy of 73% (92%), based on the validation using very high resolution images and intensive field photos.

TL;DR: A new spatiotemporal data fusion method that uses simple principles and needs only one fine-resolution image as input has the potential to increase the availability of high-resolution time-series data that can support studies of rapid land surface dynamics.

TL;DR: A statistical meta-analysis of the past 15 years of research on supervised per-pixel image classification revealed that inclusion of texture information yielded the greatest improvement in overall accuracy of land-cover classification with an average increase of 12.1%.

TL;DR: This work aims at demonstrating the ability of state-of-the-art classifiers, such as Random Forests (RF) or Support Vector Machines (SVM), to classify HR-SITS, and selecting the best feature set used as input data in order to establish the classifier accuracy over large areas.

TL;DR: In this paper, the authors compared the accuracy of seven water index methods for classifying water in 30m resolution Landsat TM/ETM+/OLI imagery from eastern Australia.

TL;DR: A water detection algorithm was used based on a decision tree classifier, and a comparison methodology using a logistic regression was used to map the presence of surface water across the entire continent from every observation of 27 years of satellite imagery as mentioned in this paper.

TL;DR: In this paper, the effects of landscape composition and spatial configuration on the urban thermal environment were investigated using correlation analysis and piecewise linear regression, and the authors found that the urban heat island (UHI) was much more significant in summer than in spring, autumn and winter.

TL;DR: In this paper, a case study of the Atlanta metropolitan area was used to illustrate the relationship between land use and land cover (LULC) patterns and thermal characteristic has long been studied for examining the impact of urbanization on urban thermal environment.

TL;DR: In this article, the Airborne Snow Observatory (ASO) used a coupled imaging spectrometer and scanning lidar, combined with distributed snow modeling, developed for the measurement of snow spectral albedo/broadband albedos and snow depth/SWE.

TL;DR: In this paper, a random forest (RF) regression approach was used to increase the spatial resolution of LST maps from 1.1 km to 250 m. The approach was tested for a complex landscape in the Eastern Mediterranean, the Jordan River Region, with LST fields from aggregated Landsat-7 ETM+ and MODIS (MODIS/Terra LST product MOD11A1) data; as reference at the finer scale, they used Landsat 7 derived LST data.

TL;DR: In this article, the authors derived NDVI end for 91.2% of the non-water, non-snow land area of Canada and Alaska using the peak-summer Landsat surface reflectance data of 19842012.

TL;DR: In this article, a small, unpiloted aerial system was used to acquire aerial photographs and processing theses using structure-from-motion (SfM) photogrammetry.

TL;DR: This is the first review work, exclusively dedicated to highlight UAV as a remote sensing platform in glaciology, and examines polar and alpine applications of UAV and their future prospects in separate sections and presents an extensive reference list for the readers.

TL;DR: Wu et al. as discussed by the authors employed multi-temporal and multi-sensor fusion methods for a long-term and fine-scale summer SUHI analysis of the city of Wuhan in China.

TL;DR: In this article, the authors report on the maturation of optical satellite-image-based ice velocity mapping over the ice sheets and large glacierized areas, enabled by the high radiometric resolution and internal geometric accuracy of Landsat 8's Operational Land Imager (OLI).

TL;DR: In this article, a new set of global 8-day composite 1-km resolution gross primary production (GPP) and evapotranspiration (ET) remote sensing products from 2000 to 2015, using a simplified process-based model, the Breathing Earth System Simulator (BESS).

TL;DR: Based on a time series of remotely sensed PM 2.5 concentrations, this paper analyzed the spatiotemporal patterns of this crucial pollutant in China from 1999 to 2011 using trend analysis and standard deviation ellipse analysis, and carried out a health risk assessment of human exposure to PM 2.

TL;DR: In this paper, the authors review recent advances based on repeat lidar collections and analysis of LRI data to highlight novel applications of lidar remote sensing beyond 3D, and outline the potential and current challenges of time and LRI information from lidar sensors to expand the scope of research applications.

TL;DR: In this paper, a generalized approach is developed to provide consistent view angle corrections across the Landsat archive, which is not applicable for generation of Landsat surface albedo, which requires a full characterization of the surface bidirectional reflectance distribution function (BRDF), or for correction to a constant solar illumination angle across a wide range of sun angles.

TL;DR: In this paper, the Soil Water Deficit Index (SWDI) was calculated using the SMOS L2 soil moisture series in the REMEDHUS (Soil Moisture Measurement Stations Network) area (Spain) during the period 2010-2014.

TL;DR: In this paper, the authors study correlations for the period 2003-2013 between yield estimates for major crops grown in Brazil and the Evaporative Stress Index (ESI) -an indicator of agricultural drought that describes anomalies in the actual/reference evapotranspiration (ET) ratio, retrieved using remotely sensed inputs of land surface temperature (LST) and leaf area index (LAI).

TL;DR: In this paper, a global evaluation of different SMOS soil moisture (SM) products (SMOS-L2, SMOSL3, and SMOS-NN) was performed comparing products with those of model simulations and other satellites.

TL;DR: In this paper, the Simple Algorithm For Yield (SAFY) model is combined with high-resolution remote sensing data from several sensors: Formosat-2, SPOT4-Take5, Landsat-8 and Deimos-1.

TL;DR: In this paper, the authors evaluate the utility of a multi-scale system for monitoring ET as applied over two vineyard sites near Lodi, California during the 2013 growing season, leading into the drought in early 2014.

TL;DR: In this article, a post-classification methodology was proposed to characterize the change in impervious surface cover (ISC) as a continuous field in space and time, and applied to a series of ISC maps of the Washington DC-Baltimore metropolitan region.