Global detection and analysis of coastline associated rainfall using an objective pattern recognition technique

Coastally associated rainfall is a common feature especially in tropical and subtropical regions. However, it has been difficult to quantify the contribution of coastal rainfall features to the overall local rainfall. We develop a novel technique to objectively identify precipitation associated with land-sea interaction and apply it to satellite based rainfall estimates. The Maritime Continent, the Bight of Panama, Madagascar and the Mediterranean are found to be regions where land-sea interactions plays a crucial role in the formation of precipitation. In these regions $\approx$ 40% to 60% of the total rainfall can be related to coastline effects. Due to its importance for the climate system, the Maritime Continent is a particular region of interest with high overall amounts of rainfall and large fractions resulting from land-sea interactions throughout the year. To demonstrate the utility of our identification method we investigate the influence of several modes of variability, such as the Madden-Julian-Oscillation and the El Ni\~no Southern Oscillation, on coastal rainfall behavior. The results suggest that during large scale suppressed convective conditions coastal effects tend modulate the rainfall over the Maritime Continent leading to enhanced rainfall over land regions compared to the surrounding oceans. We propose that the novel objective dataset of coastally influenced precipitation can be used in a variety of ways, such as to inform cumulus parametrization or as an additional tool for evaluating the simulation of coastal precipitation within weather and climate models

A mixed system of interpretation: neural networks/expert-system applied to aerial images

In this paper, we propose a complete system of analysis of images, which includes the whole sequence of treatments front the low level until the interpretation ŀ It uses neural networks as well as a rule-based system ŀ We show that the implementation of an expert-system gives useful information for the conception of the neural nets ŀ The mixed realisation allows us to use at best the specificities of each approach ŀ We also show how to make a neural network learn locally contradictory configurations.Dans cet article, nous proposons un système complet d'analyse d'images comprenant toute la chaîne de traitements depuis le bas-niveau jusqu'à l'interprétation. Il utilise à la fois un réseau de neurones et un système à base de règles. Nous montrons que la mise en oeuvre d'un système-expert fournit des informations précieuses pour la conception des réseaux. La réalisation mixte permet d'utiliser au mieux les spécificités de chacune des approches. Nous montrons également comment faire apprendre des configurations localement contradictoires à un réseau de neurone

Similarity Searching in Large Image Databases

We propose a method to handle approximate searching by image content in large image databases. Image content is represented by attributed relational graphs holding features of objects and relationships between objects. The method relies on the assumption that a fixed number of ``labeled'' or ``expected'' objects (e.g., ``heart'', ``lungs'' etc.) are common in all images of a given application domain in addition to a variable number of ``unexpected'' or ``unlabeled'' objects (e.g., ``tumor'', ``hematoma'' etc.). The method can answer queries by example such as ``{\em find all X-rays that are similar to Smith's X-ray}''. The stored images are mapped to points in a multidimensional space and are indexed using state-of-the-art database methods (R-trees). The proposed method has several desirable properties: (a) Database search is approximate so that all images up to a pre-specified degree of similarity (tolerance) are retrieved, (b) it has no ``false dismissals'' (i.e., all images qualifying query selection criteria are retrieved) and (c) it scales-up well as the database grows. We implemented the method and ran experiments on a database of synthetic (but realistic) medical images. The experiments showed that our method significantly outperforms sequential scanning by up to an order of magnitude. (Also cross-referenced as UMIACS-TR-94-134

Earth Resources: A continuing bibliography with indexes, issue 36

This bibliography lists 576 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System between October 1 and December 31, 1982. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

An Analytical Framework for Assessing the Efficacy of Small Satellites in Performing Novel Imaging Missions

In the last two decades, small satellites have opened up the use of space to groups other than governments and large corporations, allowing for increased participation and experimentation. This democratization of space was primarily enabled by two factors: improved technology and reduced launch costs. Improved technology allowed the miniaturization of components and reduced overall cost meaning many of the capabilities of larger satellites could be replicated at a fraction of the cost. In addition, new launcher systems that could host many small satellites as ride-shares on manifested vehicles lowered launch costs and simplified the process of getting a satellite into orbit. The potential of these smaller satellites to replace or augment existing systems has led to a flood of potential satellite and mission concepts, often with little rigorous study of whether the proposed satellite or mission is achievable or necessary. This work proposes an analytical framework to aid system designers in evaluating the ability of an existing concept or small satellite to perform a particular imaging mission, either replacing or augmenting existing capabilities. This framework was developed and then refined by application to the problem of using small satellites to perform a wide area search mission – a mission not possible with existing imaging satellites, but one that would add to current capabilities. Requirements for a wide area search mission were developed, along with a list of factors that would affect image quality and system performance. Two existing small satellite concepts were evaluated for use by examining image quality from the systems, selecting an algorithm to perform the search function automatically, and then assessing mission feasibility by applying the algorithm to simulated imagery. Finally, a notional constellation design was developed to assess the number of satellites required to perform the mission. It was found that a constellation of 480 CubeSats producing 4 m spatial resolution panchromatic imagery and employing an on-board processing algorithm would be sufficient to perform a wide area search mission