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Thin cirrus clouds can reduce land surface long-wave transmission and re-emit energy at a colder temperature and thus making it difficult to estimate downwelling surface longwave radiation (DSLR) from satellite data. In this study, a simulation database is established in terms of radiances observed at the top of the atmosphere (TOA), cloud optical thickness (COT), atmosphere water vapor content (WVC)...
The vast amount of data acquired by current high resolution Earth observation satellites implies some technical challenges to be faced. Google Earth Engine (GEE) platform provides a framework for the development of algorithms and products built over this data in an easy and scalable manner. In this paper, we take advantage of the GEE platform capabilities to exploit the wealth of information in the...
Mapping activities of urban land change is important for human activity to Earth's dynamic change. To get the detailed information on urban development maps in large area, dense training samples are needed in different area and specific season, which is cost-consuming. To overcome this issue, we provide a transfer learning method based on deep information to extract urban areas in all season and different...
An effective monitoring and analysis of ecosystems requires developing new tools and knowledge. In this paper, we propose an approach for detecting land-cover changes using satellite Image Time Series. This approach represents each image by spectral indices and then extracts local features of these representations. Next, a clustering technique (e.g., k-means) is applied to the extracted features,...
Wetland classification has always been a challenging task among remote sensing experts. Typically, wetland classes have low accuracies regardless of the applied dataset, as they have many spectral and ecological similarities. In this paper, a method is developed particularly effective for distinguishing spectrally similar classes such as wetlands. In this method, feature selection and object-based...
Spectral built-up indices are considered promising to map impervious surface area (ISA) distribution at regional and global scales due to their easy implementation, parameter-free and convenience in practical applications. The objective of this study is to explore and compare the potential of different impervious surface indices for mapping urban area from Landsat imagery. By sharpening a thermal-band...
Light scattering models of snow are very important for remote sensing of snow. Many previous models have used unrealistic assumptions about the snow particle shape and microstructure. In this paper, a new model is proposed, wherein a bicontinuous medium is used to simulate the snow microstructure, and geometric optics theory is used in combination with the Monte Carlo method to simulate the scattering...
In the last decade, Persistent Scatterer Interferometry (PSI) and SAR tomography (TomoSAR) have been used for reconstructing the elevation profile of a scene, starting from a set of co-registered Synthetic Aperture Radar (SAR) images. The possible advantage of TomoSAR over classical interferometric methods consists in the potential capability of improving the detection of single scatterers presenting...
Advanced spaceborne thermal emission radiometer (ASTER) has been used to obtain global digital elevation models (DEMs) that cover all over the world using along-track stereovision; however, the coupling of nadir- and backward-observation is not free from some occlusion areas. Moreover, DEMs derived from optical stereovision suffer from voids due to clouds and shadows. Therefore, stereo pairs obtained...
Mangrove forests constitute an important coastal ecosystem, which provides valuable ecosystem services such as coastal erosion protection, water filtration and shelters for a wide variety of plants and animals. Remote sensing satellite imagery provides valuable information for mangrove mapping and monitoring. In this study, we use high resolution images from SPOT-5, Landsat-7 and Landsat-8 satellites...
Evapotranspiration (ET) is one of the most significant components in the water and heat transfer between land and atmosphere. This paper develops an improved constant evaporative fraction (EF) method through a theoretical derivation to improve the upscaling of remote sensing instantaneous latent heat flux (LE) to daily scale. Preliminary results show that our improved constant EF upscaling method...
Agriculture is one of the key areas where Remote Sensing (RS) techniques can be efficiently implemented for solving wide range of tasks (crop mapping, crop monitoring, crop yield forecasting etc.) on regular basis. Sentinel mission represents really new opportunities in agricultural domain — free of charge for non-commercial use satellite images with 10–20 m spatial resolution, 5-day revisit frequency...
Extreme climate events are projected to increase under the context of global warming associated with the increase in greenhouse gas emissions. In particular, coastal regions which are also characterized with significant urbanization will be vulnerable to the extreme events, such as severe typhoon. Timely assessment and accurate information on the extent and severity of the damage caused by extreme...
Land surface temperature is an important driving force in the exchange of water, heat, and even CO2 at the surface-atmosphere interface in the desert regions. The rapid and continuous measurements of land surface temperature are meaningful to the ecological and environmental researches. A physically based single-frequency and double-polarization algorithm for retrieving land surface temperature is...
With the assumption that spectral characteristics of coastal band (Band 1) and blue band (Band 2) of Landsat-8 were similar in a cloud-free area, an algorithm to detect thin clouds was derived. The assumption and algorithm was evaluated using Landsat-8 data of p14/r36 acquired on 1 April 2014. First, the assumed spectral similarity of Bands 1 and 2 was validated in the cloud-free area. The similarity...
We present a novel technique that allows us to detect, map and quantify changes on the Earth's surface in three-dimensions that occur at time scales of a few seconds. This rapid change detection capability is a byproduct of the development of a multichannel airborne lidar system that scans the target surface at three different times in a single aircraft pass. Results, capabilities, limitations and...
We developed a simple algorithm for detecting hot spots using Sentinel-2A data, modifying a method for Landsat 8 data. The empirical hot spot detection equation was developed using apparent spectral reflectances at band 8a (0.87 μm) and band 12 (2.2 μm). Due to the improved spatial resolution, false detections often occur in inclined flat surfaces, such as roofs and solar panels. To avoid such false...
Presented are an overview of wetland processes related to atmospheric methane and terrestrial water storage, and a review remote sensing methods for wetland observations. Beyond known pathways of methane emission from wetlands, other pathways related to subterranean pressures from rising groundwater level and from subsurface transport flux in the aquifer are hypothesized. In synergy with current capabilities...
Disturbance and regrowth are vital processes in determining the roles of forest ecosystem in carbon and biogeochemical cycles. The vegetation change tracker (VCT) algorithm derives the spectral disturbance magnitude based on the time series observations. While these spectral disturbance magnitudes are indicative of physical changes in tree cover or biomass, their quantitative relationships have yet...
Medium resolution remote sensing data such as Landsat imagery and its analysis are heavily affected by the mixed pixel problem especially in regions of heterogeneous, spatially dispersed land cover such as peri-urban environments. However, this data is often the only available temporally consistent data source for multi-temporal applications that cover time periods prior to 2000. For this reason,...
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