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頁籤選單縮合
題名 | 高解析影像應用於土地利用分類之探討=Land Cover and Land Use Classification Using High Spatial Resolution Images |
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作者姓名(中文) | 蕭國鑫; 劉治中; 劉進金; 何心瑜; 黃英婷; | 書刊名 | 航測及遙測學刊 |
卷期 | 13:4 2008.12[民97.12] |
頁次 | 頁261-271 |
分類號 | 440.98 |
關鍵詞 | 空載光達; 人工編修; 過濾; Remote sensing; GIS; Classification; |
語文 | 中文(Chinese) |
中文摘要 | 本研究採用航空照片與高解析衛星影像進行國土利用之第三級分類,並搭配外業調查評估影像分類精度。分類中之航空照片結合立體像對與正射照片,直接在螢幕上判釋與數化地物類別,衛星影像則以監督式及非監督式分類方式為之。初步結果顯示,航空照片判釋國土利用調查之土地利用第三級分類,對於農地、林地、水利與交通用地之全體精度在97~98%之間,人為建物區則難以分辨到第三級分類;衛星影像適合分辨林地與水利用地之第一或第二級分類,分類精度為60~75%,但對於第三級分類別,則需輔以GIS資料及結合多時期影像,方可達到較高的分類精度;對於人為建物之第三級分類,航空照片與衛星資料均無法明確分辨。另以多時期衛星影像結合農作坵塊資料,單獨判釋桃園地區2006年二期稻作之第三級分類水稻類別,全體精度達96.47%,但生產者與使用者精度為73.38%與74.23%,仍低於平均精度之85.76%;因此,若水稻類別的辨識若能再結合種植頻率分析,則分類精度應還有再提昇的空間。 |
英文摘要 | High spatial resolution images applied in this study include digital orthophotos of 0.5m grid and pan-sharpened SPOT images of 2.5m grid. A land-cove/land-use classification scheme upto level 3 is adopted, with randomly-sampled field checks for accuracy verification. Manual interpretation with the assistance of on-screen tool-kit is adopted for the discrimination of various land-cover/land-use types on orthophotos. Whereas automatic classifications both supervised and unsupervised approaches are applied for satellite images. Preliminary results show that aerial photographs give an accuracy of 97~98% for agriculture, forestry, hydraulic and telecommunication land units. Satisfied results of level 3 of building up areas can never been achieved solely by photo-interpretation. For satellite classification, an accuracy of 60~75% can be achieved for level 1 and level 2 for the forestry and hydraulic land units. If the classes of level 3 are to be achieved, more ancillary information from GIS data-base should be incorporated. Level 3 can not be attained using satellite images. Multi-temporal images with complementary GIS polygons of field parcels can give rice parcels an overall accuracy of 96.47%. Whereas, the average accuracy (85.76%) is higher than the produce’s accuracy (73.38%) and user’s accuracy (74.23%). It is concluded that temporal plant histogram information is helpful and critical for the classification of agriculture lands. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。