We introduce a new large-scale dataset for the advancement of object detection techniques and overhead object detection research. This satellite imagery dataset enables research progress pertaining to four key computer vision frontiers.We utilize a novel process for geospatial category detection and bounding box annotation with three stages of quality control. Our data is collected from WorldVi...

The impact of a rapidly changing climate on the biosphere is an urgent area of research for mitigation policy and management. Plant phenology is a sensitive indicator of climate change and regulates the seasonality of carbon, water, and energy fluxes between the land surface and the climate system, making it an important tool for studying biosphere–atmosphere interactions. To monitor plant phen...

Solar irradiance data are crucial to PV system performance analysis. Although lightmeters (or pyranometers) have been applied in utility-level solar farms, they are not economically feasible for commercial/residential-level solar sites. Publicly accessible data, such as meteorological satellite imagery, are potentially an ideal source to meet the emerging demand. This research applied satellite...

Clustering is an unsupervised classification that aims to classify an image into homogeneous regions. We have proposed a hierarchical content based image clustering algorithm to automatically cluster the remote sensing satellite image. The performance evaluation of this algorithm is done with reference to the LISS 4 sensor imagery of IRS-P6 satellite. Centroid of the clusters is uniformly distr...

QuickBird satellite imagery, provided by DigitalGlobe Inc., has the highest resolution, among the satellite imaging systems that are commercially available. The QuickBird imaging system simultaneously collects 67-72 centimeter resolution stereo panchromatic and 2.44-2.88 meter resolution multispectral images. In this research, a QuickBird stereo pair of basic imagery product that was taken over...

Monte Carlo Ray Tracing: MCRT based adjacency effect and nonlinear mixture pixel model is proposed for remote sensing satellite imagery data analysis. Through simulation and actual visible to near infrared radiometer onboard spaceborne data utilizing experiment, the proposed model is confirmed and validated. Therefore, influences due to adjacency effect and nonlinearity of mixed pixel can be ta...

In this article an attempt for improving an existing method creating DEMs fully automatically from stereoscopic image pairs is presented. Results applying this method to very high resolution (VHR) satellite imagery is shown. The herein discussed “column” algorithm is illustrated in brief and compared to a conventional algorithm frequently used in generating DEMs from satellite line scanner data...

Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use...

Leaf area index (LAI) is an important surface biophysical parameter as an input to many process-oriented ecosystem models. Remote sensing technology provides a practical way to estimate LAI at a large spatial scale, and hence, considerable effort has been expended in developing LAI estimation models from remotely sensed imagery. LAI estimation models were usually formulated using multi-spectral...