草业学报
草業學報
초업학보
PRATACULTURAL SCIENCE
2014年
6期
20-27
,共8页
陈祖刚%巴图娜存%徐芝英%胡云锋
陳祖剛%巴圖娜存%徐芝英%鬍雲鋒
진조강%파도나존%서지영%호운봉
数字照相%草地%覆盖度%方法%精度
數字照相%草地%覆蓋度%方法%精度
수자조상%초지%복개도%방법%정도
digital photos%grass land%coverage%method%precision
草地植被盖度是表征生态系统植被生长状况及环境质量的重要参数。在草地植物群落野外调查中，可以利用数码相机拍摄草地样方照片，而后在室内利用图像处理软件进行自动或半自动的植被盖度测量。随着移动智能设备（如 iPhone／iPAD 或各类 Android Phone／PAD）的快速发展和普及，野外实时获取草地样方照片，同步计算草地植被盖度，并与有关遥感反演参数产品作校验对比分析，将成为未来地学移动测量和研究的重要方向。本研究在总结梳理既有利用数码相机识别植被盖度方法的基础上，设计了低覆盖、中低覆盖、中等覆盖、中高覆盖、高覆盖5种不同植被盖度情景，以及从早上6：00到下午6：00、每隔2 h 一次、全天共7次不同光照环境下的照相方案。继而以 Photoshop 人工勾勒和测算方法为基准，选择 RGB 阈值法、RGB 决策树法、HSV 判别法3种自动测量方法开展对比研究。测量结果的对比分析表明，草地盖度变化对 RGB 阈值法和 HSV 判别法的盖度识别精度无明显规律性影响，RGB 决策树的盖度识别精度随着草地盖度的增加而增加；光照强度越强，RGB 阈值法和 HSV 判别法对同一草地样方估算的盖度值越小，RGB 决策树法估算的盖度值随光照强度的变化没有固定的规律。总体上讲，RGB阈值法和 HSV 判别法的识别精度较高，RGB 决策树法误判率较高，但后者可以识别出非绿色的植物茎、花朵。最后提出了在现有绿色植被像元识别方法的基础上，结合边缘检查算法等图形像素的统计学特征分析方法，能进一步提高草地植被盖度测量的准确率。
草地植被蓋度是錶徵生態繫統植被生長狀況及環境質量的重要參數。在草地植物群落野外調查中，可以利用數碼相機拍攝草地樣方照片，而後在室內利用圖像處理軟件進行自動或半自動的植被蓋度測量。隨著移動智能設備（如 iPhone／iPAD 或各類 Android Phone／PAD）的快速髮展和普及，野外實時穫取草地樣方照片，同步計算草地植被蓋度，併與有關遙感反縯參數產品作校驗對比分析，將成為未來地學移動測量和研究的重要方嚮。本研究在總結梳理既有利用數碼相機識彆植被蓋度方法的基礎上，設計瞭低覆蓋、中低覆蓋、中等覆蓋、中高覆蓋、高覆蓋5種不同植被蓋度情景，以及從早上6：00到下午6：00、每隔2 h 一次、全天共7次不同光照環境下的照相方案。繼而以 Photoshop 人工勾勒和測算方法為基準，選擇 RGB 閾值法、RGB 決策樹法、HSV 判彆法3種自動測量方法開展對比研究。測量結果的對比分析錶明，草地蓋度變化對 RGB 閾值法和 HSV 判彆法的蓋度識彆精度無明顯規律性影響，RGB 決策樹的蓋度識彆精度隨著草地蓋度的增加而增加；光照彊度越彊，RGB 閾值法和 HSV 判彆法對同一草地樣方估算的蓋度值越小，RGB 決策樹法估算的蓋度值隨光照彊度的變化沒有固定的規律。總體上講，RGB閾值法和 HSV 判彆法的識彆精度較高，RGB 決策樹法誤判率較高，但後者可以識彆齣非綠色的植物莖、花朵。最後提齣瞭在現有綠色植被像元識彆方法的基礎上，結閤邊緣檢查算法等圖形像素的統計學特徵分析方法，能進一步提高草地植被蓋度測量的準確率。
초지식피개도시표정생태계통식피생장상황급배경질량적중요삼수。재초지식물군락야외조사중，가이이용수마상궤박섭초지양방조편，이후재실내이용도상처리연건진행자동혹반자동적식피개도측량。수착이동지능설비（여 iPhone／iPAD 혹각류 Android Phone／PAD）적쾌속발전화보급，야외실시획취초지양방조편，동보계산초지식피개도，병여유관요감반연삼수산품작교험대비분석，장성위미래지학이동측량화연구적중요방향。본연구재총결소리기유이용수마상궤식별식피개도방법적기출상，설계료저복개、중저복개、중등복개、중고복개、고복개5충불동식피개도정경，이급종조상6：00도하오6：00、매격2 h 일차、전천공7차불동광조배경하적조상방안。계이이 Photoshop 인공구륵화측산방법위기준，선택 RGB 역치법、RGB 결책수법、HSV 판별법3충자동측량방법개전대비연구。측량결과적대비분석표명，초지개도변화대 RGB 역치법화 HSV 판별법적개도식별정도무명현규률성영향，RGB 결책수적개도식별정도수착초지개도적증가이증가；광조강도월강，RGB 역치법화 HSV 판별법대동일초지양방고산적개도치월소，RGB 결책수법고산적개도치수광조강도적변화몰유고정적규률。총체상강，RGB역치법화 HSV 판별법적식별정도교고，RGB 결책수법오판솔교고，단후자가이식별출비록색적식물경、화타。최후제출료재현유록색식피상원식별방법적기출상，결합변연검사산법등도형상소적통계학특정분석방법，능진일보제고초지식피개도측량적준학솔。
Grassland vegetation coverage is an important parameter for characterizing vegetation condition in ec-ological research.With the popularization of digital devices,such as digital cameras,vegetation coverage can be measured in automatic or semi-automatic ways by analyzing the digital photographs using image processing platforms.Moreover,the rapid development and popularity of smart mobile devices (such as the iPhone/iPad) means that there is an opportunity to investigate the use of these devices for real-time collection,processing and analyzing of data such as vegetation cover.Five quadrats with different vegetation cover were selected and measured in different lighting conditions.Photographs were taken every 2 h from 6 AM to 6 PM.The RGB threshold value method,RGB decision tree method and HSV discriminant method were selected for calculating vegetation cover.When light intensity was constant,vegetation cover had no effect on the measurement preci-sion of the RGB threshold value method and the HSV discriminant method,but greatly influenced the meas-urement precision of the RGB decision tree method.The RGB threshold value method and the HSV discrimi-nant method were influenced by light condition;when light intensity increased cover estimates declined.How-ever,there did not appear to be a good relationship between light intensity and cover estimates for the RGB threshold value method.Overall,the measurement precision of the RGB threshold value and HSV discriminant methods were higher than the RGB decision tree method but the latter could identify plant stems and flowers that were not green.Using the current green plant pixel identification methods combined with improved statis-tical analysis methods such as algorithms able to examine edge pixels further improvement of the precision of this technique could be achieved.
