Jet Propulsion Laboratory

About: Jet Propulsion Laboratory is a facility organization based out in La Cañada Flintridge, California, United States. It is known for research contribution in the topics: Mars Exploration Program & Telescope. The organization has 8801 authors who have published 14333 publications receiving 548163 citations. The organization is also known as: JPL & NASA JPL.

The landing of the NEAR-Shoemaker spacecraft on asteroid 433 Eros

Abstract: The NEAR-Shoemaker spacecraft was designed to provide a comprehensive characterization of the S-type asteroid 433 Eros (refs 1,2,3), an irregularly shaped body with approximate dimensions of 34 x 13 x 13 km Following the completion of its year-long investigation, the mission was terminated with a controlled descent to its surface, in order to provide extremely high resolution images Here we report the results of the descent on 12 February 2001, during which 70 images were obtained The landing area is marked by a paucity of small craters and an abundance of 'ejecta blocks' The properties and distribution of ejecta blocks are discussed in a companion paper The last sequence of images reveals a transition from the blocky surface to a smooth area, which we interpret as a 'pond' Properties of the 'ponds' are discussed in a second companion paper The closest image, from an altitude of 129 m, shows the interior of a 100-m-diameter crater at 1-cm resolution

Measuring constraint-set utility for partitional clustering algorithms

Abstract: Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves performance, with respect to the true data labels. However, in most of these experiments, results are averaged over different randomly chosen constraint sets, thereby masking interesting properties of individual sets. We demonstrate that constraint sets vary significantly in how useful they are for constrained clustering; some constraint sets can actually decrease algorithm performance. We create two quantitative measures, informativeness and coherence, that can be used to identify useful constraint sets. We show that these measures can also help explain differences in performance for four particular constrained clustering algorithms.

Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements

Abstract: The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 m3 m−3 or better. The ubRMSE for L4_SM surface (root zone) soil moisture is 0.038 m3 m−3 (0.030 m3 m−3) at the 9-km scale and 0.035 m3 m−3 (0.026 m3 m−3) at the 36-km scale. The L4_SM estimates improve (significantly at the 5% level for surface soil moisture) over model-only estimates, which do not benefit from the assimilation of SMAP brightness temperature observations and have a 9-km surface (root zone) ubRMSE of 0.042 m3 m−3 (0.032 m3 m−3). Time series correlations exhibit similar relative performance. The sparse network results corroborate these findings over a greater variety of climate and land cover conditions.