找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Geomorphic Risk Reduction Using Geospatial Methods and Tools; Raju Sarkar,Sunil Saha,Rajib Shaw Book 2024 The Editor(s) (if applicable) an

[復(fù)制鏈接]
查看: 34439|回復(fù): 57
樓主
發(fā)表于 2025-3-21 17:14:34 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools
編輯Raju Sarkar,Sunil Saha,Rajib Shaw
視頻videohttp://file.papertrans.cn/384/383865/383865.mp4
概述Highlights scientific methods to reduce the geomorphic hazard impact of different regions.Provides a pathway towards the management of different geomorphic hazards risk.Applies advanced machine learni
叢書名稱Disaster Risk Reduction
圖書封面Titlebook: Geomorphic Risk Reduction Using Geospatial Methods and Tools;  Raju Sarkar,Sunil Saha,Rajib Shaw Book 2024 The Editor(s) (if applicable) an
描述This book explores the use of advanced geospatial techniques in geomorphic hazards modelling and risk reduction. It also compares the accuracy of traditional statistical methods and advanced machine learning methods and addresses the different ways to reduce the impact of geomorphic hazards..In recent years with the development of human infrastructures, geomorphic hazards are gradually increasing, which include landslides, flood and soil erosion, among others. They cause huge loss of human property and lives. Especially in mountainous, coastal, arid and semi-arid regions, these natural hazards are the main barriers for economic development. Furthermore, human pressure and specific human actions such as deforestation, inappropriate land use and farming have increased the danger of natural disasters and degraded the natural environment, making it more difficult for environmental planners and policymakers to develop appropriate long-term sustainability plans. The most challenging task is to develop a sophisticated approach for continuous inspection and resolution of environmental problems for researchers and scientists. However, in the past several decades, geospatial technology has u
出版日期Book 2024
關(guān)鍵詞Geomorphic hazard; Machine learning technique; Satellite image; Resilience process; Risk reduction techn
版次1
doihttps://doi.org/10.1007/978-981-99-7707-9
isbn_softcover978-981-99-7709-3
isbn_ebook978-981-99-7707-9Series ISSN 2196-4106 Series E-ISSN 2196-4114
issn_series 2196-4106
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools影響因子(影響力)




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools影響因子(影響力)學(xué)科排名




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools網(wǎng)絡(luò)公開度




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools被引頻次




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools被引頻次學(xué)科排名




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools年度引用




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools年度引用學(xué)科排名




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools讀者反饋




書目名稱Geomorphic Risk Reduction Using Geospatial Methods and Tools讀者反饋學(xué)科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

0票 0.00%

Better Implies Difficulty

 

1票 100.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 20:41:22 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:31:49 | 只看該作者
Artificial Neural Network Ensemble with General Linear Model for Modeling the Landslide Susceptibiliare highly susceptible to landslide. In the present study ensemble of ANN, general linear model (GLM), and ensemble ANN-GLM machine learning methods were applied for producing the landslide susceptibility maps (LSMs) of the Mirik region. A total of 373 landslide locations and twelve landslide condit
地板
發(fā)表于 2025-3-22 07:50:58 | 只看該作者
An Advanced Hybrid Machine Learning Technique for Assessing the Susceptibility to Landslides in the ble NBT-RTF, Naive Bayes tree (NBT), and rotation forest (RTF). For landslide susceptibility modelling, 189 landslide sites and 12 landslide conditioning factors (LCFs) were gathered. Multi-collinearity analysis was done among the LCFs to determine the best LCFs to use. The metrics utilized to asses
5#
發(fā)表于 2025-3-22 12:36:51 | 只看該作者
6#
發(fā)表于 2025-3-22 16:36:35 | 只看該作者
7#
發(fā)表于 2025-3-22 17:57:06 | 只看該作者
An Ensemble of J48 Decision Tree with AdaBoost and Bagging for Flood Susceptibility Mapping in the So limit its destructive effects, proper planning, cope up ideas, and mitigation strategies are required. So the present study deals with the preparation of flood susceptibility mapping in the Sundarban region of West Bengal, India. The study prepares a flood inventory map and also identifies the col
8#
發(fā)表于 2025-3-22 23:46:40 | 只看該作者
9#
發(fā)表于 2025-3-23 04:38:51 | 只看該作者
Quantitative Assessment of Interferometric Synthetic Aperture Radar (INSAR) for Landslide Monitoring-surface ground motion in deep-seated landslides. We also consider the uncertainties that may arise out of using a remote sensing tool to track ground motion, as opposed to traditional boreholes, and how InSAR can be used to understand this?uncertainty.?The landslide case study of interest in this w
10#
發(fā)表于 2025-3-23 08:19:44 | 只看該作者
Geospatial Study of River Shifting and Erosion–Deposition Phenomenon Along a Selected Stretch of Riva. Measurement of braiding index (>1.5) and sinuosity (<1.5) with the aim of analyzing river morphometric parameters along with river shifting related with erosion–deposition for sinuosity throughout the study time duration indicate that the river has a braiding and straight or sinuous nature. Islan
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-15 20:07
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
五指山市| 略阳县| 定日县| 桂阳县| 澄迈县| 柳河县| 辽中县| 屯留县| 长春市| 彩票| 青龙| 盐源县| 贡嘎县| 来宾市| 孟州市| 临海市| 都安| 新河县| 惠来县| 保德县| 吉安县| 尉犁县| 方城县| 鹤庆县| 赞皇县| 尖扎县| 柘城县| 横峰县| 杂多县| 房山区| 建始县| 潞西市| 乃东县| 息烽县| 沽源县| 游戏| 洛扎县| 曲阜市| 沅陵县| 乌拉特后旗| 额济纳旗|