Showing papers in "International Journal of Applied Earth Observation and Geoinformation in 2018"

TL;DR: A systematic and overarching review of different spatial and temporal factors affecting the UHI effect is provided and discusses the findings in policy terms and provides directions for future research.

TL;DR: It is concluded that the multi-temporal crop type classification efficiently mitigates negative effects observed when using single-date acquisition within sub-optimal temporal windows.

TL;DR: It is necessary to place GCPs around the edge of the study area to minimize planimetry errors and to create a stratified distribution inside theStudy area with a density of around 0.5–1 GCP × ha−1 to minimize altimetryerrors.

TL;DR: Evaluated UAS/SfM for multitemporal 3D crop modelling and developed and assessed a methodology for estimating plant height data from point clouds generated using SfM, showing a potential path to reducing laborious manual height measurement and enhancing plant research programs through UAS and S fM.

TL;DR: The results not only indicate land use change, but also demonstrate the advantage of utilizing Google Earth Engine and the public archive database in its platform to track and monitor this change over time.

TL;DR: The results of this study show that the estimation of LAI and LCC by numerical inversion of the PROSAIL model can be improved when multi-angular observations are introduced, however, for the potato crop, PRosAIL inversion for measured data only showed moderate accuracy and slight improvements.

TL;DR: The experiences and achievements of China’s mangrove conservation efforts presented in this study will facilitate the development of applicable coastal management strategies globally, especially in developing countries.

TL;DR: A new approach exploiting satellite soil moisture observations for quantifying the amount of water applied for irrigation is developed, with satisfactory performance from satellite data with retrieval errors lower than ∼0.04 m³/m³ and revisit times shorter than 3 days.

TL;DR: This study shows for the first time how land use and land cover classifications in cloud-prone monsoon regions with small-scale agriculture and multiple cropping patterns can be improved by combining Sentinel-1 and Sentinel-2 data.

TL;DR: An efficient mapping method to monitor bare soil areas, which are indicative of land degradation in the case of the Northeast of Brazil, using Normalized Difference Vegetation Index images, indicated that the degraded areas increased in the period of the study.

TL;DR: A new approach to identify crop types and cropping patterns in the state of Mato Grosso, Brazil and indicates that the proposed approach is promising for mapping large-scale croplands, their crops patterns and crop types.

TL;DR: This work compares two types of satellite-based maps for evaluating fire damage in a large wildfire located in Sierra de Gata (central-western Spain) on 6–11 August 2015 and shows that Landsat based burn severity maps presented an adequate assessment of the damage grade and its spatial distribution in wildfire emergency response.

TL;DR: The sensitivity analysis underlines the robustness of the proposed approach for rapid flood mapping and its integration into the fully-connected conditional random field model to remove the ambiguities of the saliency-guided GGMM.

TL;DR: Overall accuracy and F-score for OOA methods outperformed pixel-based unsupervised classification methods in both landslide and non-landslide classes and indicates that the OOA is able to identify the majority of landslides with a few false positive when compared to pixel- based unsuper supervised classification.

TL;DR: This study developed a strategy for inter- and intra-row weed detection in early season maize fields from aerial visual imagery using the Hough transform algorithm and a semi-automatic Object-Based Image Analysis procedure combined with feature selection techniques to classify soil, weeds and maize.

TL;DR: This research used as inputs 2001–2012 daily reflectance from MOD09GQ/MOD09GA products and 16-day composite VIs from the MOD13Q1 dataset to find the best VI/TS combination to estimate start- of-season (SOS) and end-of- season (EOS) dates across 50 temperate deciduous forests.

TL;DR: UHI intensity between “urban” and “rural/urban low density” (“vegetation”) areas for 1984–1999 and 2000–2015 was established and confirmed by both parametric and non-parametric tests at 1% significance level.

TL;DR: The estimated rice production for the three rice growing seasons 2015 correlates well with data at the district level collected from the province statistics offices with R2s of 0.93 for the Winter–Spring, 0.86 for the Summer–Autumn and 0.87 for the Autumn–Winter season.

TL;DR: Wang et al. as discussed by the authors proposed a new Multi-Band Water Index (MBWI) for Landsat 8 Operational Land Imager (OLI) images by maximizing the spectral difference between water and non-water surfaces using pure pixels.

TL;DR: The research has shown that combining optical and SAR data does not guarantee improvement compared with using single data source for urban land cover classification, depending on the selection of appropriate fusion levels and fusion methods.

TL;DR: A new methodology for retrieving surface soil moisture (SSM) under conditions of partial vegetation cover based on the synergy between Sentinel-1 Synthetic Aperture Radar (SAR) and Landsat Operational Land Image (OLI) data is presented.

TL;DR: An automatic method to identify tree stems, and estimate tree heights and diameters from terrestrial laser scanning (TLS) data based on the isolation and vertical continuity of the stems showed robustness to the presence of steep or irregular terrain, the absence of low vegetation and artifacts at breast height, the indistinct use of individual or multiple scans, and tree density in the plot.

TL;DR: The C6 MODIS LST products were validated using a radiance-based (R-based) method and are in good agreement with the R-based LST values, with bias and root mean square error (RMSE) values of less than 1 K for all sites during the daytime and night-time.

TL;DR: The performance of multiple regression models built for N quantification with and without including the airborne-retrieved SIF was compared with the performance of models built with plant traits estimated by model inversion, and also with standard approaches based on single spectral indices.

TL;DR: The early detection of bark beetle green attacks is investigated by examining foliar biochemical and spectral properties (400–2000 nm) and whether bark beetle infestation affects the estimation accuracy of foliar biochemicals.

TL;DR: The conclusions are that time-series of high spatial resolution UAV images can be acquired in a flexible and easy way, the individual images can nowadays be processed in a straightforward way into suitable products i.e. OrthoMosaics and DEMs which are valuable products for land administrators having a responsibility to survey and monitor rivers and control them.

TL;DR: A case study of an epithermal system located in southern Peru is presented, aimed at the characterization of mineral assemblies for discriminating potential high sulfidationEpithermal targets, using hyperspectral imagery integrated with petrography, XRD and magnetic data.

TL;DR: Evaluating the capability of existing satellite synthetic aperture radar with multispectral data to estimate forest canopy height over five study sites across two biomes in North America suggests that a biome level model developed from several study sites can be used as a reliable estimator of biome-level forest structure from existing satellite imagery.

TL;DR: This work was made possible by EPSRC (UK) Award 1636878, with iCase sponsorship from the National Physical Laboratory and additional funding from Laing O’Rourke.