• Title/Summary/Keyword: Sensing data

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A Numerical Experiment in Assimilating Agricultural Practices in a Mixed Pixel Environment using Genetic Algorithms

  • Honda, Kyoshi;Ines, Amor V.M.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.837-839
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    • 2003
  • Low spatial resolution remote sensing (RS) data (LSRD) are promising in agricultural monitoring activities due to their high temporal resolution, but under such a spatial resolution, mixing in a pixel is a common problem. In this study, a numerical experiment was conducted to explore a mixed pixel problem in agriculture using a combined RSsimulation model SWAP (Soil-Water-Atmosphere -Plant) and a Genetic Algorithm (GA) approach. Results of the experiments showed that it is highly possible to address the mixed pixel problem with LSRD.

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A study on global environmental monitoring by using ADEOS-II GLI data

  • Yamamoto, Hirokazu;Hashimoto, Toshiaki;Mitomi, Yasushi;Yoshioka, Hiroki;Honda, Yoshiaki;Igarashi, Tamotsu
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.482-484
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    • 2003
  • GLI on boarded ADEOS-II satellite allows us to observe vegetation status in the two different resolutions simultaneously, because of thirty 1km resolution channels and six 250m resolution channels. There are four GLI land higher level products from these channels ; those are PGCP (Precise Geometric Correction Parameter), L2A_LC (TOA reflectance), ACLC (atmospheric corrected reflectance), and VGI (NDVI and EVI). This paper shows ADEOS-II GLI land data processing, and some of the latest results.

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FOREST MONITORING PROTOTYPE SYSTEM USING WEB MAPPING TECHNOLOGY

  • Kawahito, Shinobu;Kuroiwa, Kaori;Sobue, Shin-ichi;Ochiai, Osamu
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.793-794
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    • 2003
  • Forest fire monitoring prototype system was developed by National Development Agency of Japan (NASDA) and the Ministry of Agriculture, Forestry and Fisheries of Japan (MAFF) to verify the usefulness of interoperabile system to study new services of Earth observation satellite data distribution for a practical application. In this system, a standard interface of Web based GIS technology, OpenGIS Consortium (OGC) technology, was adopted. This system is also expected to encourage data sharing activities in Digital Asia Network (DAN) as a demonstration system.

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Determination of Flood Hydrograph by Remote Sensing Techniques in a Small Watershed (원격탐사 기법에 의한 소유역의 홍수 수문곡선 결정)

  • 남현옥;박경윤;조성익
    • Korean Journal of Remote Sensing
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    • v.5 no.1
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    • pp.13-27
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    • 1989
  • In recent years satellite data have been increasingly used for the analysis of floodprone areas. This study was carried out to demonstrate the usefulness of repetitive satellite imagery in monitoring flood levels of the Pyungchang watershed. Runoff characteristics parameters were analyzed by Soil Conservation Service(SCS) Runoff Curve Number(RCN) based on Landsat imagery and Digital Terrain Model data. The RCN average within the watershed was calculated from RCN estimates for all the pixels(picture elements) and adjusted by antecedent precipitation conditions. The direct runoff hydrograph was derived from the unit hydrograph using SCS dimensionless unit hydrograph and effective rainfalls estimated by the SCS method. In comparsion of the direct runoff hydrograph with the measured rating curve their peak times differ by one hour and peak discharges differ by 5.9 percents of the discharge from each other. It was shown that repetitive satellite image could be very useful in timely estimating watershed runoffs and evaluating ever-changing surface conditions of a river basin.

Remote Sensing Application for the Mineralized Zone in Ryeongnam Area Using LANDSAT TM Data (III) (LANDSAT TM 자료에 의한 영남지역의 광산대조사 및 응용방법 개발(III))

  • 姜必鍾;智光薰
    • Korean Journal of Remote Sensing
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    • v.5 no.2
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    • pp.91-107
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    • 1989
  • The purpose of this study is to investigate ways to use Landsat TM data for geological mapping and minieralized area detection. The study was carried out in Kyongju-Pohang area where toseki and bentonite mines are distributed. Rock samples of 18 granites, andesites, toseki, betonites, sedimentary rocks and altered rocks in the study area were collected for the study. The radiometric measurtment of the rock samples were carried out with a radiometer in the laboratory and in the field. The Landsat TM bands 2,3,4,5,7 were used for the measurement. The radiometric characteristics of the sample were mainly processed by the principal component analysis. It was found that the pricipal component analysis of the radiometric characteristics of geologic materials is very useful for the detection of the alteration of rocks and grade of mineral contents. It is expected that the technique can be used in the future for the efficient exploration of minerals in this country and abroad.

Efficiency of Superconducting Gravimeter Observations and Future Prospects

  • Neumeyer Juergen
    • Korean Journal of Remote Sensing
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    • v.21 no.1
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    • pp.15-29
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    • 2005
  • Superconducting Gravimeters (SG) are the most sensitive instruments for measuring temporal gravity variations. The gravimeter is an integrating sensor therefore the gravity variations caused by different sources must be separated for studying a special effect by applying different models and data analysis methods. The present reduction methods for gravity variations induced by atmosphere and hydrosphere including the ocean and the detection and determination of the most surface gravity effects are shown. Some examples demonstrate the combination of ground (SG) and space techniques especially the combination of SG with GRACE satellite derived temporal gravity variations. Resulting from the performance of the SG and the applied data analysis methods some proposals are made for future SG applications.

Unsupervised Image Classification using Region-growing Segmentation based on CN-chain

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.20 no.3
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    • pp.215-225
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    • 2004
  • A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The 'local' segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. The 'global' segmentor of the second stage, which has not spatial constraints for merging, clusters the segments resulting from the previous stage, using the conventional agglomerative approach. Using simulation data, the proposed method was compared with another hierarchical clustering technique based on 'mutual closest neighbor.' The experimental results show that the new approach proposed in this study considerably increases in computational efficiency for larger images with a low number of bands. The technique was then applied to classify the land-cover types using the remotely-sensed data acquired from the Korean peninsula.

Region Growing Segmentation with Directional Features

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.26 no.6
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    • pp.731-740
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    • 2010
  • A region merging technique is suggested in this paper for the segmentation of high-spatial resolution imagery. It employs a region growing scheme based on the region adjacency graph (RAG). The proposed algorithm uses directional neighbor-line average feature vectors to improve the quality of segmentation. The feature vector consists of 9 components which includes an observation and 8 directional averages. Each directional average is the average of the pixel values along the neighbor line for a given neighbor line length at each direction. The merging coefficients of the segmentation process use a part of the feature components according to a given merging coefficient order. This study performed the extensive experiments using simulation data and a real high-spatial resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for the object-based analysis of high-spatial resolution images.

Generation of Forest Leaf Area Index (LAI) Map Using Multispectral Satellite Data and Field Measurements

  • Lee, Kyu-Sung;Kim, Sun-Hwa;Park, Yoon-Il;Jang, Ki-Chang
    • Korean Journal of Remote Sensing
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    • v.19 no.5
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    • pp.371-380
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    • 2003
  • The primary objective of this study is to develop a suitable methodology to generate forest leaf area index (LAI) map at regional and local scales. To build empirical models, we collected the LAI values at 30 sample plots over the forest within the kyongan watershed area by the field measurements using an optical instrument. Landsat-7 ETM+ multispectral data obtained at the same growing season with the field LAI measurement were used. Three datasets of remote sensing signal were prepared for analyzing the relationship with the field measured LAI value and they include raw DN, atmospherically corrected reflectance, and topographically corrected reflectance. From the correlation analysis and regression model development, we found that the radiometric correction of topographic effects was very critical step to increase the sensitivity of the multispectral reflectance to LAI. In addition, the empirical model to generate forest LAI map should be separately developed for each of coniferous and deciduous forest.

The Method of Linking Fire Survey Data with Satellite Image-based Fire Data (산불피해대장 정보와 위성영상 기반 산불발생데이터의 연계 방안)

  • Kim, Taehee;Choi, Jinmu
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1125-1137
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    • 2020
  • This study aimed to propose the method of linking satellite image-based forest fire data to supplement the limitation of forest fire survey data that records only the ignition location and area of forest fire. For this purpose, a method was derived to link the fire survey data provided by the Korea Forest Service between January 2012 and December 2019 with MODIS and VIIRS image-based forest fire data. As a result, MODIS and VIIRS-based forest fire data out of 191 wildfires in the forest fire survey data were able to identify 11% and 44% of fire damage area, respectively. An average of 56% of forest damage area was extracted from VIIRS-based forest fire data compared to forest fire areas identified by high-resolution Sentinel-2A satellites. Therefore, for large-scale forest fires, VIIRS wildfire data can be used to compensate for the limitations of forest fire survey data that records only the ignition location and area.