Comparative Study on Cloud Parameter Estimation Among GOSAT/CAI, MODIS, CALIPSO/CALIOP and Landsat-8/OLI with Laser Radar: Lidar as Truth Data

Abstract

 A comparative study on cloud parameter estimation among GOSAT/CAI, MODIS, CALIPSO/CALIOP and Landsat-8/OLI is carried out using Laser Radar: Lidar as a truth data. Optical depth, size distribution, as well as cirrus type of clouds are cloud parameters. In particular, cirrus cloud detection is tough issue. 1.38 µm channel is required for its detection. Although MODIS and Landsat-8/OLI have such channel, the other mission instruments, CAI and CALIPSO/CALIOP do not have such channel. As a truth data of cloud parameter, ground based Lidar is used in this comparative study. From the Lidar, backscattered echo signal and depolarization coefficient are obtained as a function of altitude. Therefore, cloud type, vertical profile can be derived from the Lidar data. CALIPSO/CALIOP is satellite based Lidar which allows observation of clouds from space. Although the directions of laser light emissions between CALIPSO/CALIOP and the ground based Lidar are different, their principles are same. Therefore, it is expected that CALIPSO/CALIOP data derived cloud parameters are similar to the ground based Lidar data derived cloud parameters. The experimental results show the aforementioned facts and are useful for improvement of cloud parameter estimation accuracy with several sensor data combinations.

Authors and Affiliations

Kohei Arai, Masanori Sakashita, Hiroshi Okumura, Shuji Kawakami, Kei Shiomi, Hirofumi Ohyama

Keywords

Related Articles

 Brainstorming Versus Arguments Structuring in Online Forums

 We characterize electronic discussion forums as being of one of the following two types: Brainstorming Forums and Arguments Structuring Forums. In this work we analyze and classify the types of threading models occ...

 Diagrammatic Language for Artificial Intelligence: Representation of Things that Flow

 This paper utilizes a diagrammatic language for expressing certain philosophical notions, such as possible worlds, beliefs, and propositions. The focus is on a diagrammatic representation that depicts “things” to s...

Image Prediction Method with Nonlinear Control Lines Derived from Kriging Method with Extracted Feature Points Based on Morphing

Method for image prediction with nonlinear control lines which are derived from extracted feature points from the previously acquired imagery data based on Kriging method and morphing method is proposed. Through comparis...

 Comparative Analysis of Improved Cuckoo Search(ICS) Algorithm and Artificial Bee Colony (ABC) Algorithm on Continuous Optimization Problems

 This work is related on two well-known algorithm, Improved Cuckoo Search and Artificial Bee Colony Algorithm which are inspired from nature. Improved Cuckoo Search (ICS) algorithm is based on Lévy flight and behavi...

 A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

 Quantitative multilevel association rules mining is a central field to realize motivating associations among data components with multiple levels abstractions. The problem of expanding procedures to handle quantita...

Download PDF file
  • EP ID EP112336
  • DOI 10.14569/IJARAI.2016.050504
  • Views 128
  • Downloads 0

How To Cite

Kohei Arai, Masanori Sakashita, Hiroshi Okumura, Shuji Kawakami, Kei Shiomi, Hirofumi Ohyama (2016).  Comparative Study on Cloud Parameter Estimation Among GOSAT/CAI, MODIS, CALIPSO/CALIOP and Landsat-8/OLI with Laser Radar: Lidar as Truth Data. International Journal of Advanced Research in Artificial Intelligence(IJARAI), 5(5), 21-29. https://europub.co.uk/articles/-A-112336