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International journal of applied earth observation and geoinformation
International Institute for Aerospace Survey and Earth Sciences
International journal of applied earth observation and geoinformation

International Institute for Aerospace Survey and Earth Sciences

1569-8432

International journal of applied earth observation and geoinformation/Journal International journal of applied earth observation and geoinformationISTPSCIAHCI
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    Multi-temporal RADARSAT-2 polarimetric SAR for maize mapping supported by segmentations from high-resolution optical image

    Shuai, GuanyuanZhang, JinshuiBasso, BrunoPan, Yaozhong...
    15页
    查看更多>>摘要：Due to its ability to penetrate the cloud, Synthetic Aperture Radar (SAR) has been a great resource for crop mapping. Previous research has verified the applicability of SAR imagery in object-oriented crop classification, however, speckle noise limits the generation of optimal segmentation. This paper proposed an innovative SARbased maize mapping method supported by optical image, Gaofen-1 PMS, based segmentation, named as parcel based SAR classification assisted by optical imagery-based segmentation (os-PSC). Polarimetric decomposition was applied to extract polarimetric parameters from multi-temporal RADARSAT-2 data. One Gaofen-1 image was then used for parcel extraction, which was the basic unit for SAR image analysis. The final step was a multistep classification for final maize mapping including: the potential maize mask extraction, pure/mixed maize parcel division and an integrated maize map production. Results showed that the overall accuracy of the os-PSC method was 89.1%, higher than those of pixel-level classification and SAR-based segmentation methods. The comparison between optical- and SAR-based segmentation demonstrated that optical-based segmentation would be better at representing maize field boundaries than the SAR-based segmentation. Moreover, the parcel- and pixel-level integrated classification will be suitable for many agricultural systems with small landownership where inter-cropping is common. Through integrating advantages of the SAR and optical data, os-PSC shows promising potentials for crop mapping.
      原文链接:
    • NSTL
    • Elsevier

    Detection of geothermal anomalies using Landsat 8 TIRS data in Tulu Moye geothermal prospect, Main Ethiopian Rift

    Darge, Yosef MengistuHailu, Binyam TesfawMuluneh, Ameha AtnafuKidane, Tesfaye...
    11页
    查看更多>>摘要：Despite the high geothermal potential of the Main Ethiopian Rift (MER), risks associated with the industry and the difficulty of identifying possible targets using ground surveys alone continue to impede the development of geothermal power diligence in Ethiopia. In this paper, we investigate the geothermal potential of the Tulu Moye prospect area in the MER using Landsat 8, which is an important and cost-effective method of detecting geothermal anomalies. Data with a path/row of 168/054 were obtained from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared (TIR) sensors for October 17, 2014. Based on radiometric calibration, atmospheric correction (with the 6S model) and an NDVI-based threshold method for calculating land surface emissivity, a split-window algorithm was applied to retrieve the land surface temperature (LST) of the study area. Results show LST values ranging from 292.2 to 315.8 K, with the highest values found in barren lands. A comparison of LST between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 shows a maximum difference of 1.47 K. Anomalous areas were also discovered, where LST was about 3-9 K higher than the background area. We identified seven of these as areas of high geothermal activity in the Tulu Moye prospective geothermal area. Auxiliary data and overlay analysis tools eliminated any non-geothermal influences. The research reveals that the distribution of highy prospective geothermal areas is consistent with the development and distribution of faults in the study area. Magmatism is the thermal source and faults provide conduits for the heat to flow from earth's interior to the surface, facilitating the presence of geothermal anomalies. Finally, TIR remote sensing methods prove to be a robust and cost-effective technique for detecting LST anomalies in the geologically active area of MER. Moreover, combining TIR remote sensing with knowledge of the structural geology of the area and geothermal mechanisms is an efficient approach to detecting geothermal areas.
      原文链接:
    • NSTL
    • Elsevier

    Integrating geotechnical and SAR data for the monitoring of underground works in the Madrid urban area: Application of the Persistent Scatterer Interferometry technique

    Jesus Garcia, AdrianMarchamalo, MiguelMartinez, RubenGonzalez-Rodrigo, Beatriz...
    10页
    查看更多>>摘要：The Differential Interferometric Synthetic Aperture Radar (DInSAR) is a powerful deformation control technique for civil engineering applications. However, the performance definition and limitations of the technique in tunneling works are far from being standardized. This work presents a thorough validation effort of the applicability of the Persistent Scatterer Interferometry (PSI) technique to the Madrid's M-30 tunneling works. A set of 26 Envisat images, covering from August 2003 to April 2008, were processed with two PSI techniques and the results were validated with on-ground measurements from leveling benchmarks and strips. The comparison of the deformations of more than 1500 control points has led to a global deformation difference of 2.6 mm RMS and 3.5 mm RMS with a coverage of the area of interest with persistent scatterers of 65% and 34% for the two PSI algorithms used. The limitations of the PSI technique when using SAR missions with low revisit time were shown. PSI has proven the potential to complement on ground monitoring techniques in tunneling works as soon as the limitations are overcome.
      原文链接:
    • NSTL
    • Elsevier

    Human expertise in the interpretation of remote sensing data: A cognitive task analysis of forest disturbance attribution

    White, A. Raechel
    8页
    查看更多>>摘要：The visual analysis of remote sensing imagery is useful for the extraction of information not readily available through automated image analysis. Previous studies have shown that the replication of human reasoning about image content is difficult due to human creativity and mental flexibility. Development of automated image analysis programs continues; however, geovisual analytics suggests that it may be more beneficial to design symbiotic computer-human interpretation systems. It is imperative to understand the experiences, knowledge, and cognitive processes that image interpreters rely on. Cognitive Task Analysis (CTA) is a methodological framework developed from Cognitive Systems Engineering (CSE) where expert users are studied with the goals of explicating their needs, wants, and cognitive abilities for dealing with complex technological systems. Here we report the results of a CTA process carried out with users of a geovisual analytic tool to support forest disturbance detection and signification. These results suggest that different facets of the cognitive processes undertaken by users are not always explicit, and differences in the participant's attentiveness to their mental processes vary greatly. Despite these differences and pathways to their final interpretations, participants were able to successfully come to similar judgments as for their peers.
      原文链接:
    • NSTL
    • Elsevier

    Full year crop monitoring and separability assessment with fully-polarimetric L-band UAVSAR: A case study in the Sacramento Valley, California

    Li, HuapengZhang, CeZhang, ShuqingAtkinson, Peter M....
    12页
    查看更多>>摘要：Spatial and temporal information on plant and soil conditions is needed urgently for monitoring of crop productivity. Remote sensing has been considered as an effective means for crop growth monitoring due to its timely updating and complete coverage. In this paper, we explored the potential of L-band fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data for crop monitoring and classification. The study site was located in the Sacramento Valley, in California where the cropping system is relatively diverse. Full season polarimetric signatures, as well as scattering mechanisms, for several crops, including almond, walnut, alfalfa, winter wheat, corn, sunflower, and tomato, were analyzed with linear polarizations (HH, HV, and VV) and polarimetric decomposition (Cloude-Pottier and Freeman-Durden) parameters, respectively. The separability amongst crop types was assessed across a full calendar year based on both linear polarizations and decomposition parameters. The unique structure-related polarimetric signature of each crop was provided by multitemporal UAVSAR data with a fine temporal resolution. Permanent tree crops (almond and walnut) and alfalfa demonstrated stable radar backscattering values across the growing season, whereas winter wheat and summer crops (corn, sunflower, and tomato) presented drastically different patterns, with rapid increase from the emergence stage to the peak biomass stage, followed by a significant decrease during the senescence stage. In general, the polarimetric signature was heterogeneous during June and October, while homogeneous during March-to-May and July-to-August. The scattering mechanisms depend heavily upon crop type and phenological stage. The primary scattering mechanism for tree crops was volume scattering (> 40%), while surface scattering (> 40%) dominated for alfalfa and winter wheat, although double-bounce scattering (> 30%) was notable for alfalfa during March-to-September. Surface scattering was also dominant (> 40%) for summer crops across the growing season except for sunflower and tomato during June and corn during July-to-October when volume scattering (> 40%) was the primary scattering mechanism. Crops were better discriminated with decomposition parameters than with linear polarizations, and the greatest separability occurred during the peak biomass stage (July-August). All crop types were completely separable from the others when simultaneously using UAVSAR data spanning the whole growing season. The results demonstrate the feasibility of L-band SAR for crop monitoring and classification, without the need for optical data, and should serve as a guideline for future research.
      原文链接:
    • NSTL
    • Elsevier

    The worsening impacts of land reclamation assessed with Sentinel-1: The Rize (Turkey) test case

    Erten, EsraRossi, Cristian
    8页
    查看更多>>摘要：Massive amounts of land are being reclaimed to build airports, new cities, ports, and highways. Hundreds of kilometers are added each year, as coastlines are extended further out to the sea. In this paper, this urbanization approach is monitored by Persistent Scatterer Interferometry (PSI) technique with Sentinel-1 SAR data. The study aims to explore this technology in order to support local authorities to detect and evaluate subtle terrain displacements. For this purpose, a large 3-years Sentinel-1 stack composed by 92 images acquired between 07/01/2015 to 27/01/2018 is employed and stacking techniques are chosen to assess ground motion. The test site of this study, Rize, Turkey, has been declared at high risk of collapse and radical solutions such as the relocation of the entire city in another area are been taken into consideration. A media fact-checking approach, i.e. evaluating national and international press releases on the test site, is considered for the paper and this work presents many findings in different areas of the city. For instance, alerts are confirmed by inspecting several buildings reported by the press. Critical infrastructures are monitored as well. Portions of the harbor show high displacement rates, up to 1 cm/year, proving reported warnings. Rural villages belonging to the same municipality are also investigated and a mountainous village affected by landslide is considered in the study. Sentinel-1 is demonstrated to be a suitable system to detect and monitor small changes or buildings and infrastructures for these scenarios. These changes may be highly indicative of imminent damage which can lead to the loss of the structural integrity and subsequent failure of the structure in the long-term. In Rize, only a few known motion-criticalstructures are monitored daily with in-situ technologies. SAR interferometry can assist to save expensive inspection and monitoring services, especially in highly critical cases such as the one studied in this paper.
      原文链接:
    • NSTL
    • Elsevier

    Mapping forest aboveground biomass in the reforested Buffelsdraai landfill site using texture combinations computed from SPOT-6 pan-sharpened imagery

    Hlatshwayo, Sizwe ThamsanqaMutanga, OnisimoLottering, Romano T.Kiala, Zolo...
    13页
    查看更多>>摘要：Developing models for estimating aboveground biomass (AGB) in naturally growing forests is critical for climate change modelling. AGB models developed using satellite imagery varies with study area, depending on the complexity of vegetation and landscape structure, which affects the upwelling radiance. We assessed the potential of SPOT-6 imagery in predicting AGB of trees planted at different time periods, using image texture combinations. Image texture variables were computed from the SPOT6 pan-sharpened image data, which is characterised by a 1.5 m spatial resolution. In addition, we incorporated the minimal variance technique to select the optimum window sizes that best captures AGB variation in our study area. The results showed that image texture was able to detect AGB for both mature and young trees, however, models detecting mature trees were more superior, with accuracies of R-2 = 0.70 and 0.25 for 2009-2011 and 2011-2013 plantation phases, respectively. In addition, our results showed that the three band texture ratios yielded the highest accuracy (R-2 = 0.88 and RMSE = 54.54 kg m(-2)) compared to two texture (R-2 = 0.85 and RMSE = 60.65 kg m(-2)) and single texture band combinations (R-2 = 0.64 and RMSE = 94.13 kg m(-2)). A frequency analysis was also run to determine which bands appeared more frequently in the selected texture band models. The frequency analysis revealed that both the red and green bands appeared more frequently on the selected texture band variables, indicating that they were more sensitive to the variation of AGB in our study area. The results showed high variation in AGB within the Buffelsdraai reforestation site, especially due to varying tree plantation phases as well as topography. In essence, the study demonstrated the possibility of image texture combinations computed from the SPOT-6 image in estimating AGB.
      原文链接:
    • NSTL
    • Elsevier

    Quad and compact multitemporal C-band PolSAR observations for crop characterization and monitoring

    Homayouni, S.McNairn, H.Hosseini, M.Jiao, X....
    10页
    查看更多>>摘要：Monitoring crop condition using optical satellite indices has a legacy of several decades. Early warning of variances in crop production is vital in mitigating regional and global food insecurity. Adoption of optical vegetation indices for this purpose is widespread, yet cloud cover impedes the acquisition of these data. Although early research using scatterometers and aircraft hinted at the sensitivity of Synthetic Aperture Radar (SAR) responses to crop development, the implementation of satellite SAR observations in operational crop condition monitoring is limited. In the research presented here, volume-to-surface (V/S) scattering ratios derived from C band RADARSAT-2 quad and simulated compact polarimetric (QP and CP) imagery are assessed for their potential to monitor crop growth. Both V/S ratios were strongly correlated with optical vegetation indices, including the widely adopted Normalized Difference and Soil Adjusted Vegetation Indices. The changes in the ratio of volume to surface scattering were correlated with variations in crop biomass. The results support the potential of a SAR scattering ratio for crop condition monitoring. In particular, encouraging results were reported for compact polarimetry, a mode that can be implemented to deliver broader swath coverage conducive to regional and national monitoring.
      原文链接:
    • NSTL
    • Elsevier

    Impact of the spatial resolution on the energy balance components on an open-canopy olive orchard

    Ramirez-Cuesta, J. M.Allen, R. G.Zarco-Tejada, P. J.Kilic, A....
    15页
    查看更多>>摘要：The recent technical improvements in the sensors used to acquire images from land surfaces has made possible to assess the performance of the energy balance models using unprecedented spatial resolutions. Thus, the objective of this work is to evaluate the response of the different energy balance components obtained from METRIC model as a function of the input pixel size. Very high spatial resolution airborne images (approximate to 50 cm) on three dates over olive orchards were used to aggregate different spatial resolutions, ranging from 5 m to 1 km. This study represents the first time that METRIC model has been run with such high spatial resolution imagery in heterogeneous agricultural systems, evaluating the effects caused by its aggregation into coarser pixel sizes. Net radiation and Soil heat flux showed a near insensitive behavior to spatial resolution changes, reflecting that the emissivity and albedo respond linearly to pixel aggregation. However, greater discrepancies were obtained for sensible (up to 17%) and latent (up to 23%) heat fluxes at spatial resolutions coarser than 30 x 30 m due to the aggregation of non-linear components, and to the inclusion of non-agricultural areas in such aggregation. Results obtained confirm the good performance of METRIC model when used with high spatial resolution imagery, whereas they warn of some major errors in crop evapotranspiration estimation when medium or large scales are used.
      原文链接:
    • NSTL
    • Elsevier

    Detection of spatio-temporal evolutions on multi-annual satellite image time series: A clustering based approach

    Ienco, DinoOse, KenjiTeisseire, MaguelonneKhiali, Lynda...
    17页
    查看更多>>摘要：The expansion of satellite technologies makes remote sensing data abundantly available. While the access to such data is no longer an issue, the analysis of this kind of data is still challenging and time consuming. In this paper, we present an object-oriented methodology designed to handle multi-annual Satellite Image Time Series (SITS). This method has the objective to automatically analyse a SITS to depict and characterize the dynamic of the areas (the way that the land cover of the areas evolve over time). First, it identifies the spatio-temporal entities (reference objects) to be tracked. Second, the evolution of such entities is described by means of a graph structure and finally it groups together spatio-temporal entities that evolve similarly. The analysis were performed on three study areas to highlight inter (among the study areas) and intra (inside a study area) similarity by following the evolution of the underlying phenomena. The analysis demonstrate the benefits of our methodology. Moreover, we also stress how an expert can exploit the extracted knowledge to pinpoint relevant landscape evolutions in the multi-annual time series and how to make connections among different study areas.
      原文链接:
    • NSTL
    • Elsevier