東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

How Does Land Cover Classification i...

Reyes, Carlos Sebastian.

FindBook

Google Book

Amazon

博客來

How Does Land Cover Classification in Google Earth Engine Compare with Traditional Methods of Land Cover Classification? What Are the Tradeoffs?

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	How Does Land Cover Classification in Google Earth Engine Compare with Traditional Methods of Land Cover Classification? What Are the Tradeoffs?/
作者:	Reyes, Carlos Sebastian.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	62 p.
附註:	Source: Masters Abstracts International, Volume: 83-01.
Contained By:	Masters Abstracts International83-01.
標題:	Environmental science. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28541005
ISBN:	9798516071966

How Does Land Cover Classification in Google Earth Engine Compare with Traditional Methods of Land Cover Classification? What Are the Tradeoffs?
Reyes, Carlos Sebastian.

How Does Land Cover Classification in Google Earth Engine Compare with Traditional Methods of Land Cover Classification? What Are the Tradeoffs? - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 62 p.

Source: Masters Abstracts International, Volume: 83-01.

Thesis (M.S.)--The University of Texas at El Paso, 2021.

This item must not be sold to any third party vendors.

The project focuses on comparing land cover classification of traditional methods such as ArcGIS with newer ones such as Google Earth Engine (GEE) as well as discussing any potential tradeoffs. Two studies were performed in both platforms, the first involved analyzing land cover change in the Middle Rio Grande (MRG) region of southern New Mexico, far west Texas, and northern Chihuahua, Mexico. The MRG study focused on urban and agricultural change in the region using two different classification methods. The second study focused on creating a post-hurricane damage assessment (PDA) with the goal of developing an automated method of estimating the location and quantity of debris (focusing on trees). Overall, the research shows the pros and cons of each platform as well as which is better given user's overall standing in terms of equipment, prior experience, project size, and time constraints.

ISBN: 9798516071966Subjects--Topical Terms:

677245
Environmental science.
Subjects--Index Terms:

ArcGIS

How Does Land Cover Classification in Google Earth Engine Compare with Traditional Methods of Land Cover Classification? What Are the Tradeoffs?
LDR:02142nmm a2200385 4500 001 2282094
005 20210927083539.5
008 220723s2021 ||||||||||||||||| ||eng d
020 $a 9798516071966
035 $a (MiAaPQ)AAI28541005
035 $a AAI28541005
040 $a MiAaPQ $c MiAaPQ
100 1 $a Reyes, Carlos Sebastian. $3 3560837
245 1 0 $a How Does Land Cover Classification in Google Earth Engine Compare with Traditional Methods of Land Cover Classification? What Are the Tradeoffs?
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 62 p.
500 $a Source: Masters Abstracts International, Volume: 83-01.
500 $a Advisor: Pennington, Deana.
502 $a Thesis (M.S.)--The University of Texas at El Paso, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a The project focuses on comparing land cover classification of traditional methods such as ArcGIS with newer ones such as Google Earth Engine (GEE) as well as discussing any potential tradeoffs. Two studies were performed in both platforms, the first involved analyzing land cover change in the Middle Rio Grande (MRG) region of southern New Mexico, far west Texas, and northern Chihuahua, Mexico. The MRG study focused on urban and agricultural change in the region using two different classification methods. The second study focused on creating a post-hurricane damage assessment (PDA) with the goal of developing an automated method of estimating the location and quantity of debris (focusing on trees). Overall, the research shows the pros and cons of each platform as well as which is better given user's overall standing in terms of equipment, prior experience, project size, and time constraints.
590 $a School code: 0459.
650 4 $a Environmental science. $3 677245
650 4 $a Information technology. $3 532993
650 4 $a Geographic information science. $3 3432445
653 $a ArcGIS
653 $a Classification
653 $a Environmental science
653 $a Google Earth Engine
653 $a Land cover
653 $a Tree detection
690 $a 0768
690 $a 0489
690 $a 0370
710 2 $a The University of Texas at El Paso. $b Environ. Sci. & Eng.. $3 3194056
773 0 $t Masters Abstracts International $g 83-01.
790 $a 0459
791 $a M.S.
792 $a 2021
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28541005