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Due to the almost hemispheric observational scope of the Moon-based Earth observations, the effects of sampling time interval on the image offsets of the observed points are fundamentally different from the cases of traditional satellite-based platforms. Sampling time intervals will affect the offsets in the full-disc image, while the magnitude of the image offsets is dependent on the spatial resolution. Hence, their relationships merit further investigation. To this end, a novel method to determine the image coordinates based on radius-angle pair expression is proposed. The offsets of the observed points between two adjacent samplings can be calculated and the effects of the sampling time interval on the offsets can be analysed. We found that the magnitude of the image offsets in the x-axis direction is approximately two times larger than that in y-axis direction under the same sampling time interval and the effects of the sampling time interval is related to the observed point's latitude. Further, based on the fact that the maximum offsets occur at the Earth's equator, the detailed calculation of the shortest sampling time interval taken to exceed 1-pixel offset corresponding to different spatial resolutions is carried out. The results described herein can provide guidance for designing sensors for Moon-based Earth observations. [ABSTRACT FROM AUTHOR]

There are increasing concerns about the Arctic region and the Antarctic region, which are known as indicators of the global change. To conduct research on the global change issue, especially for the two-polar regions of the Earth, the long-term continuous Earth observations are required. However, the existing Earth observation systems lack the ability to meet this need. In this paper, we propose to use the Moon as an Earth observation platform. This Moon-based platform could have large spatial coverage and long temporal duration. In addition, the site selection is a complex issue for the Moon-based platform because of the vast space on the Moon surface. We research this problem by placing the sensor at four potential sites on the Moon, respectively – the North Pole, the South Pole, the Sinus Iridum area and the Mare Nectaris area. Furthermore, the latitude and longitude of nadir point, the time length, the observation duration and the time length during a single observation duration of the four sites are calculated. Analyses are conducted to compare some observation performances of the four sites. Finally, we found that the latitude variation of the nadir point has an impact on the time window and the observation duration. If the sensor is placed at the polar regions of the Moon, there will be an 18.6-year period between the two adjacent longest observation duration. Thus, we give the next best time window to observe the two-polar regions of the Earth, when the sensor is placed at the polar region of the Moon. If the sensor is placed at the lower latitude regions of the Moon, there will be a 9.3-year period between the two adjacent longest observation duration. Moreover, on account of the observation duration and the time length during a single observation duration, the sites with relative low latitudes on the Moon are good choices. [ABSTRACT FROM AUTHOR]

As a new concept platform for Earth observation, a Moon-based platform has the advantages of large-scale, constant and long-term dynamic Earth observations that can meet the needs of conducting systematic research on the Earth. However, a Moon-based platform has particular differences from space-borne and air-borne platforms because of its long distance from the Earth and the vast expanses of the Moon. In this article, we present three contributions. First, we propose a formula to describe the relative position of the Moon-based platform and Earth observation target. Second, we establish an observation geometry model and discuss three key observation parameters that are vital to the observation scope and coverage calculation. Third, a new observation scope and coverage analysis method is established in order to demonstrate that a suitable Moon-based Earth observation platform site can be located in the full observation region. We establish a geometric model for a Moon-based platform based on the Earth orientation parameters and Jet Propulsion Laboratory (JPL) ephemerides. Then, three key parameters including the visibility of the Earth from the Moon, nadir point, and Earth viewing angle are calculated using the proposed model. These parameters determine the observation scope and coverage of the Earth. The Earth-facing hemisphere of the Moon is divided into four regions, including the full observation region and the incomplete observation regions. Compared with the selenocentric case, during orbital periods, the maximum nadir point’s latitudinal and longitudinal difference in terms of placing sensors on the Moon surface is about 0.3°, the maximum viewing angle difference of the Earth is about 0.005°, and the maximum angular difference of the Moon-based platform and the Sun is about 0.24°. Thus, the maximum coverage difference is about 0.1%, so that placing sensors on the full observation region would result in better Earth observation performance. [ABSTRACT FROM AUTHOR]

Due to the lack of accuracy in the navigation system, airborne repeat-pass synthetic aperture radar (SAR) interferometry (InSAR) suffers residual motion errors (RMEs). Previously, we proposed the multisquint technique with point targets (MTPT) to estimate the errors, but its implementation needs improvement and its accuracy has not been assessed by real airborne repeat-pass InSAR data. In this article, the modified MTPT is introduced first. The modification is mainly embodied in two aspects: automatic target selection and noise removing. Because the multisquint (MS) technique is also capable of estimating the RMEs in SAR interferogram and its accuracy has been verified to be high, here it is used as a comparison. In addition, from the viewpoint of MTPT, MS can be understood from another perspective. Using real X-band airborne repeat-pass SAR data, the performance of MTPT is evaluated. The experiment shows that MTPT is able to achieve high accuracy when a large number of point targets are distributed in the observed scene. The limitations of MTPT are also discussed at the end of this article. [ABSTRACT FROM PUBLISHER]

In the retrieval of forest canopy attributes using a geometric-optical model, the spectral scene reflectance of each component should be known as prior knowledge. Generally, these reflectances were acquired by a foregone survey using an analytical spectral device. This article purposed to retrieve the forest structure parameters using light detection and ranging (LiDAR) data, and used a linear spectrum decomposition model to determine the reflectances of the spectral scene components, which are regarded as prior knowledge in the retrieval of forest canopy cover and effective plant area index (PAIe) using a simplified Li–Strahler geometric-optical model based on a Satellites Pour l'Observation de la Terre 5 (SPOT-5) high-resolution geometry (HRG) image. The airborne LiDAR data are first used to retrieve the forest structure parameters and then the proportion of the SPOT pixel not covered by crown or shadow Kg of each pixel in the sample was calculated, which was used to extract the reflectances of the spectral scene components by a linear spectrum decomposition model. Finally, the forest canopy cover and PAIe are retrieved by the geometric-optical model. As the acquired time of SPOT-5 image and measured data has a discrepancy of about 2 months, the retrieved result of forest canopy cover needs a further validation. The relatively high value of R 2 between the retrieval result of PAIe and the measurements indicates the efficiency of our methods. [ABSTRACT FROM PUBLISHER]

Based on the triangulated irregular network (TIN) model, barycentric coordinates and random points, a new method was developed for more accurate characterization of 3D shape signatures of buildings using Light Detection and Ranging (LiDAR) data and Geographic Information System (GIS). The new method was applied to four simulated building models with flat, pent, gable and hip roofs to test the detection of changes in 3D building shapes in a post-earthquake scenario: (1) a three-storey building model becomes two-storey after losing the first floor; (2) a severe damage of a two-storey building model; and (3) a total collapse of a two-storey building model. The new method was then applied to real LiDAR data from four buildings in Harris County, TX, USA. All the changes in 3D shapes of the models and real buildings were successfully detected using 3D shape signatures. Sensitivity analyses were carried out to test the influence of LiDAR point density and new points in TIN triangles on 3D shape signatures. The results suggest that LiDAR point density of 0.5 point m−2 or higher can generate stable 3D shape signatures of buildings, and that the density of the new points in TIN triangles does not affect 3D shape signatures significantly. Built upon the new method and results, a framework was proposed for an automated assessment of post-earthquake building damage using geospatial data. A flowchart was presented to provide more details of the framework, and the advantages and limitations of the framework were also discussed. It is expected that the framework can be effectively applied to post-earthquake building damage assessment and other disaster scenarios that involve major changes in 3D building shapes. [ABSTRACT FROM AUTHOR]