Inversion of organic matter content in wetland soil based on Landsat 8 remote sensing image-Reference-Cited by-同舟云学术

Inversion of organic matter content in wetland soil based on Landsat 8 remote sensing image

Published:2019-10 Issue: Volume:64 Page:102645
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Zhai Maotong

Funder

National Natural Science Foundation of China

Jiangxi Outstanding Youth Science Fund

Jiangxi Provincial Department of Education Science and Technology Project

Jiangxi University of Finance and Economics 2018 Graduate Innovation Special Fund Project

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference29 articles.

1. Selection of Landsat8 image classification bands based on MLC–RFE;Liu;J. Indian Soc. Remote Sens.,2019

2. Evaluate the capability of LANDSAT8 operational land imager for shoreline change detection/inland water studies;Pervez;ISPRS – Int. Arch. Photogramm., Remote Sens. Spatial Inf. Sci.,2017

3. Adaptability evaluation of different fusion methods on ZY-3 and Landsat8 images;Liu;Remote Sens. Land Resour.,2014

4. Extraction on crops planting structure based on multi-temporal Landsat8 OLI images;Liu;Remote Sens. Technol. Appl.,2015

5. A practical trial of landslide detection from single-temporal Landsat8 images using contour-based proposals and random forest: a case study of national Nepal;Fang;Landslides,2017

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