衛星多元影像資料於地物分類與災害監測之應用（I）; Landcover Classification and Disaster Monitoring Using Satellite Multi-Sensing Images (I)

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Title:	衛星多元影像資料於地物分類與災害監測之應用（I）;Landcover Classification and Disaster Monitoring Using Satellite Multi-Sensing Images (I)
Authors:	陳錕山;劉振榮
Contributors:	太空及遙測研究中心
Keywords:	林業類;農業環境保護
Date:	2004-12-01
Issue Date:	2010-11-30 16:03:37 (UTC+8)
Publisher:	行政院農業委員會
Abstract:	一、整合SAR及INSAR資料與技術於地物分類及災害監測(4/4)：本計畫擬整合不同衛星、不同入射角、不同偏極多樣化雷達系統監測，利用角反射器(Corner Reflector, CR)與主動式輻射校正器(Active Radar Calibrator, ARC)精進雷達影像之幾何精度與輻射校正，並建立各項數據及程序來因應不同衛載雷達系統在幾何精度精進程序與訊號校正之程序，對於未來在農業災害方面進行精確雷達觀測需求。對於在農業災害防治方面，各項實驗數據資料庫之建立不僅僅能更精確的選定所須之衛載SAR，更可經由資料庫的資訊了解所需各衛載SAR之輻射極化方式，並依程序執行相關工作進而提供在農業災害方面最有效正確之即時資訊。若要提供準確迅速而無誤的農業災害知訊，除了先前對不同衛星、不同觀測角、不同輻射極化方式需做資料匯整以利查訊外，在衛載雷達資料的獲取與前期處理資料的程序建立方面更為重要，若建立一連貫良好無誤的災害處理應變程序的話，不僅可提供詳細完整的災區知訊，對於即時或長久之監測方面，更可有效率的提供相關權責單位做處理。二、遙測資料在台灣地區植被分類之研究及應用(4/4)：本計畫之主要目標為應用目前的衛星資料與遙測技術估算大至台灣全島，小至局部森林地區的資訊，預期於短時間內提供台灣地區森林之面積、偵測地區性森林之變遷、甚至辨識區分森林之種類等潛能，除在經濟效益與時效性上有相當程度的改善外，亦提供了目前偵(監)測森林異常變化之最佳利器。本年度的目標在於完成植被指數資料庫的建立及使用此資料庫推估台灣森林地區的變化情形。 (一) 建立不同衛星資料(AVHRR、SPOT HRV與VI、MODIS)估算植被指數的方法。 (二) 建立不同植被指數計算(NDVI、AFRI、AVRI)方法及比較其在台灣地區使用上的優劣。 (三) 台灣地區森林面積變異計算監測模式之建立。 (四) 瞭解衛星資料在森林分類的能力。 (五) 建立台灣地區各月份，各季節公里級的植被指數資料庫。 I. Integration of SAR and InSAR Data and Techniques for Landcover Classification and Disaster Monitoring (4/4): This proposal intends to establish a database search by using data from different satellites and their various incidence angles and multi-polarization information. By using high geometric accuracy and radiometric calibration of radar images from Corner Reflector, CR and Active Radar Calibrator, ARC, in addition, by establishing various data for the use of different SAR systems in the improvement of geometric accuracy and signal calibration, radar monitor in future agricultural disaster is going to be more effective. The establishment of various laboratory data not only can help in choosing the right spaceborn SAR, but also it helps in understanding its radiometric polarization. This provides the most effective, accurate, and immediate information for agricultural disaster. In order to provide accurate information on agricultural disaster, the acquisition of spaceborn radar data and the establishment of preprocessing procedure are far more important than tidying up data from different satellites and their various incidence angles and polarization information as mentioned earlier. If a disastrous-response procedure can be correctly established, it not only can provide complete information on disastrous area but also can provide information on immediate and long-term monitor for the related institutions. II. Using Remote sensing Data for Vegetation Classification and Applications in Taiwan Area (4/4): Project objectives: Conventional means of estimating the area and growth of forestlands and farmlands in Taiwan has not only been expensive, but also time-consuming. This has been especially difficult as the area of Taiwan is narrowly shaped, and the terrain and land cover is both considered complex. Therefore, the main goal of this project is to develop methods that are suitable in the estimation and monitoring of the forests around Taiwan through the utilization of remote sensing technology. The project hopes to assess the applicability of using satellite data in forest classifications and crop yield estimations, and if possible, develop the technology into a real-time basis. As more attention is being paid on the global emission of CO<sub>2</sub>, new rules have been implemented regarding the amount each country can release, which depends primarily on the area of forestland a country owns. If we can keep a close eye on the changes of our forests, we can be in accordance with the emission protocols, and perhaps even obtain some profit. This would be of tremendous help to the development and application of Taiwan's forest resources. Project structure: In order to obtain the goals mentioned above, the primary task for this year will include the collection of satellite data that provide extensive coverage from AVHRR and SPOT-4 VI, and also high-resolution images from SPOT HRV. With the acquired data, there are three aspects to achieve: (1) Determination and correction of the influence on the vegetation index from different satellite observational angles. (2) Assessment of the forest land calculations, and conducting improvements of the models used. (3) Testing and analysis of satellite data in forestland classification and crop land estimation. Anticipated results: (1) The completion of a vegetation index database for each respective month and season of Taiwan. (2) The development and improvement of models in forest land estimation and changes. (3) Understanding how the terrain affects remote sensing retrievals of the vegetation index. In addition, obtaining analytical results made on forestland classifications and cropland assessments, which can be used for future researches. 研究期間：9301 ~ 9312
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Center for Space and Remote Sensing Research ] Research Project

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