應用Google Earth Engine與影像分類技術於巴拉圭查科地區進行森林砍伐評估

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馬莉亞(Maria Leticia Cardozo Torres) 查詢紙本館藏

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國際永續發展碩士在職專班

論文名稱

應用Google Earth Engine與影像分類技術於巴拉圭查科地區進行森林砍伐評估
(Deforestation Assessment in the Paraguayan Chaco using Google Earth Engine)

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摘要(中)

森林作為生物多樣性的資源庫，能為野生動物提供棲息地，有利固碳，並緩解氣候溫室效應。近年來，人類活動是造成森林砍筏的主要因素。本研究的目的是通過雲端的Google Earth Engine（GEE）平台，進行衛星影像整合及分析，對南美洲巴拉圭查科的森林砍伐問題進行評估。本研究直接透過GEE平台上收集、整合2013年和2017年二年期查科地區的多幅Landsat衛星影像，利用隨機森林分類器(Random Forest Classifier)進行監督式影像分類，將研究區不同類型之土地覆蓋類別進行區分，用以後了解此二年期間森林砍伐之空間分布並評估森林覆蓋率變化的狀況。
利用GEE平台獲得的分類結果經檢核點驗證後得到：2013年分類總體正確度(overall accuracy)為0.86，2017年為0.87。結果表明利用GEE平台不僅可進行快速、有效影像整合，亦可產出可靠的影像分類圖資。
研究結果顯示2013年森林覆蓋面積為172,861.85平方公里，2017年為163,875.54平方公里;也就是說此四年內的森林覆蓋面積損失達到了8,986.31平方公里。另外檢視查克地區的森林砍伐狀況，發現砍伐的地區去有明顯幾何矩形特徵，反映了大規模的植生移除以及重型機械的使用。透過文獻分析已知查科地區森林砍伐的主要驅動力是牛牧場，而本研究發現森林砍伐的持續發生與巴拉圭肉類出口量的持續增加情形相吻合，本研究並預期此森林砍伐的問題很可能會持續發生，乃是基於巴拉圭政府當前之政策目標為在2020年前將持續增加其牛肉的產量。從森林砍伐的分布位置發現，森來砍伐事實上在國家森林保護區內蔓延，並威脅者當地原住民社區的土地和和文化，顯示了巴拉圭國家法律的禁制在這些地區實屬有限。

摘要(英)

Forests act as a reservoir of biodiversity, shelter to wildlife, carbon sinks, and mitigates climate change. Despite their importance, they have been threatened by human activities, which is the main driver of deforestation. The objectives of this study are the assessment and analysis of deforestation in the Paraguayan Chaco, South America, by means of satellite image classification and analysis through the cloud-based Google Earth Engine (GEE) platform.
Landsat images from the years of 2013 and 2017 were classified by a pixel-based supervised Random Forest Classifier. The classification results from different land-cover in the study area were then use to assess the deforestation, which expose a forest cover loss, in 2013 the forest cover was 172,862 km2 and 163,875.5 km2 in 2017; this revealed a cover loss of 8,986.3 km2 in 4 years. Furthermore, the classification results obtained in GEE platform were validated with validation points, the classification overall accuracy obtained was 0.86 for 2013 and 0.87 for 2017. The results indicate that GEE perform a rapid image processing and it is an effective reliable platform for deforestation assessment within the Chaco area.
The results shown that the deforestation process leaves geometry rectangular features in the land surface and they are easily visualized, this suggests that there is a large scale clearing and heavy machinery is use. The main driver of deforestation in the Chaco is cattle ranching, and the results of this study indicate that the deforestation in continue advancing. During the years of study, Paraguay increase the amount of meat exportation, situating the country within the top 10 major countries worldwide exporter of meat, and this coincide with the increase of deforestation in the Chaco, this problem is likely to continue, because Paraguay set a country goal of reaching more cattle heads by 2020.
Moreover, the results revealed that the deforestation process was spread within and in the buffer zones of the national forest protected areas, this suggest that there is lack of compliance with law were it stated that the protected areas are forbidden to use for economic purposes. Indigenous communities were also affected by the deforestation in the study period, threatening their home land and heritage.

關鍵字(中)

★ 森林砍伐
★ Google Earth Engine
★ 巴拉圭查克地區
★ Landsat
★ 隨機森林分類器

關鍵字(英)

★ Deforestation
★ Google Earth Engine
★ Paraguayan Chaco
★ Landsat
★ Random Forest Classifier

論文目次

1. Introduction 1
2. Literature Review 5
2.1 Deforestation 5
2.1.1 Deforestation in the Chaco 14
2.2 Google Earth Engine 10
2.2.1 Google Earth Engine studies 12
3. Study area 16
3.1 Location 16
3.2 Biodiversity 17
3.3 Protected areas 20
4. Data Acquisition 22
4.1 Satellite imagery 22
4.2 GIS data 26
5. Methods 29
5.1 General Flowchart 29
5.2 Image classification 30
5.3 Accuracy assessment 35
5.4 Deforestation assessment 37
6. Results and Discussions 39
6.1 Image classification and accuracy assessment 39
6.2 Deforestation Assessment 44
6.3 Deforestation, protected areas and indigenous communities 50
6.3.1 Protected areas 50
6.3.2 Indigenous communities 56
7. Conclusions 58
References 59

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指導教授

姜壽浩(Shou-Hao Chiang)

審核日期

2019-8-22

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