The precisely extraction of construction areas in remote sensing images can play an important role in territorial planning, land use management, urban environments and disaster reduction. In this article, we propose a method for extracting construction areas using Gaofen-1 panchromatic remote sensing images by adopting the improved Pantex<sup></sup> (a procedure for the calculation of texture-derived built-up presence index) and unsupervised classification. First of all, texture cooccurrence measures of 10 different directions and displacements are calculated. In this step, we improve the built-up presence index that we use the windows size of 21*21 to calculate the GLCM contrast measure instead of 9*9 according to the spatial resolution of Gaofen-1 panchromatic image. Then we use the intersection operator “MIN” to combine the 10 different anisotropic GLCM contrast measure to generate the final built-up presence index result. At last, we use the unsupervised classification method to classify the Pantex result into two classes and the one with larger cluster center is the construction area class. Confusion matrix of Beijing-Tianjin-Hebei region experiment shows that this method can effectively and accurately extract the construction areas in Gaofen-1 panchromatic images with the overall accuracy of more than 92%.
Satellite telemetry is the vital indicators to estimate the performance of the satellite. The telemetry data, the threshold
range and the variation tendency collected during the whole operational life of the satellite, can guide and evaluate the
subsequent design of the satellite in the future. The rotational parts on the satellite (e.g. solar arrays, antennas and
oscillating mirrors) affect collecting the solar energy and the other functions of the satellite. Visualization telemetries
(pictures, video) are captured to interpret the status of the satellite qualitatively in real time as an important supplement
for troubleshooting. The mature technology of commercial off-the-shelf (COTS) products have obvious advantages in
terms of the design of construction, electronics, interfaces and image processing. Also considering the weight, power
consumption, and cost, it can be directly used in our application or can be adopted for secondary development. In this
paper, characteristic simulations of solar arrays radiation in orbit are presented, and a suitable camera module of certain
commercial smartphone is adopted after the precise calculation and the product selection process. Considering the
advantages of the COTS devices, which can solve both the fundamental and complicated satellite problems, this
technique proposed is innovative to the project implementation in the future.
At present, there are two types of method to detect ships in SAR images. One is a direct detection type, detecting ships
directly. The other is an indirect detection type. That is, it firstly detects ship wakes, and then seeks ships around wakes.
The two types all effect by speckle noise. In order to improve the accuracy of ship detection and get accurate ship and
ship wakes parameters, such as ship length, ship width, ship area, the angle of ship wakes and ship outline from SAR
images, it is extremely necessary to remove speckle noise in SAR images before data used in various SAR images ship
detection. The use of speckle noise reduction filter depends on the specification for a particular application. Some
common filters are widely used in speckle noise reduction, such as the mean filter, the median filter, the lee filter, the
enhanced lee filter, the Kuan filter, the frost filter, the enhanced frost filter and gamma filter, but these filters represent
some disadvantages in SAR image ship detection because of the various types of ship. Therefore, a mathematical
function known as the wavelet transform and multi-resolution analysis were used to localize an SAR ocean image into
different frequency components or useful subbands, and effectively reduce the speckle in the subbands according to the
local statistics within the bands. Finally, the analysis of the statistical results are presented, which demonstrates the
advantages and disadvantages of using wavelet shrinkage techniques over standard speckle filters.