Generating Digital Elevation Models (DEMs) from stereo optical satellite data has been a well-established practice for many years. The typical workflow involves performing Bundle Adjustment (BA) to align the stereo imagery, often supplemented with Ground Control Point (GCP) data for accurate vertical values. However, acquiring high-precision GCPs using geodetic GPS can be costly and time-consuming. In this study, we utilize a GCP-less approach that combines iterative bundle adjustment with an existing DEM for SPOT-7 tri-stereo imagery. The Semi-global matching algorithm is employed as the stereo correlator for all three stereo combinations (Forward-Nadir, Nadir-Backward, Forward-Backward). We also explore four alternative approaches: single BA without GCPs, single BA with 9 GCPs, 9 GCPs only, and single BA without GCPs but with DEM co-registration. To build the DEM, we utilize the SPOT-7 panchromatic band (1.5m) and upscale it by a factor of two to achieve a Ground Sampling Distance of 3 meters. We evaluate the horizontal shift in the x and y directions of the produced DEMs using DEMNAS as the reference. Additionally, the vertical accuracy is assessed using the Root Mean Square Error (RMSE) by comparing the results to a combination of geodetic Independent Control Points (ICPs), Unmanned Aerial Vehicle (UAV) Digital Surface Models (DSMs), and filtered ICESat-2 ATL-08 points as the reference data. Preliminary findings indicate that the GCP-less iterative BA approach outperforms all but one other method on average. The iterative BA method yields average x and y shifts of 1.72 meters and 0.95 meters, respectively. These values are lower than those obtained using single BA (13.01 and 3.27), single BA with 9 GCPs (2.85 and 2.62), and 9 GCPs only (3.94 and 1.00) approaches. The only approach that produces lower shifts is the single BA with DEM co-registration, which results in 0.60m and 0.72m for x and y shifts, respectively.
Topographic Correction (TC) is one of the essential pre-processing methods to reduce the topographic effect in remote sensing data. It is one of the main factors affecting the reflectance value of objects in remote sensing imagery in the rugged topographic area and contributes to quantitative analysis. High-resolution satellite imagery also requires high spatial resolution of the Digital Elevation Model (DEM) as an important requirement in applying TC methods. This study evaluated the performance of five different TC algorithms (i.e., Statistical-Empirical (SE), C-Correction, Minnaert, Gamma, and Sun Canopy Sensor+C (SCS+C) over four hilly to the undulating area with different land-cover characteristics on SPOT-6/7 Multispectral imagery in Sulawesi Island and used the nation-wide DEMNAS as DEM. Visual and statistical evaluations were used to examine the surface reflectance value before and after correction by calculating linear regression and Pearson Correlation (R) between illumination (IL) and reflectance value, and the difference between mean reflectance value of lit and shadowed for vegetated slope. The results showed that the Minnaert, SCS+C, and C-Correction, perform better than other methods. However, Minnaert and SCS+C statistically and visually performed better in all topographic conditions, and C-Correction showed moderate performance. The Gamma method tends to be under-correction but is visually suitable for favorable topographic conditions and poorly illuminated areas in shaded slopes area. In contrast, SE tends to overcorrect all SPOT-6/7.
Topographic correction over mountainous region is an essential preprocessing steps for landuse/landcover extraction from earth observation (EO) satellite data. Until the time of this paper writing, there has not been any publication regarding topographic correction on LAPAN-A3 multispectral data. Topographic correction mainly grouped into two categories: band ratio, and illumination modelling which required ancillary digital elevation model (DEM). This paper aim to evaluate three different DEM source used for topographic correction on LAPAN-A3. These DEMs are Shuttle Radar Topographic Mission (SRTM), ALOS World 3D (AW3D), and nation-wide DEMNAS. The topographic corrections were performed over a subset of forested mountainous region in South Sulawesi, Indonesia. Minnaert correction algorithm was used in all three DEMs and evaluate the results. Performance evaluation were based on visual assessment, as well as spectral homogeneity of the pixel value before and after correction. The spectral homogeneity were calculated based on coefficient variation changes before and after correction. The initial results showed that SRTM produced the best visual appearance, while DEMNAS performed the best in terms of highest reduction in coefficient variation.
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