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Remote Sensing of Environment

Resumen/Descripción – provisto por la editorial en inglés

Remote Sensing of Environment serves the remote sensing community with the publication of results on theory, science, applications and technology of remote sensing of Earth resources and environment. Thoroughly interdisciplinary, this journal publishes on terrestrial, oceanic, and atmospheric sensing. The emphasis of the journal is on biophysical and quantitative approaches to remote sensing at local to global scales. Areas of interest include, but are not necessarily restricted to:
– Agriculture, forestry and range
– Biophysical-spectral models
– Ecology
– Earth and environmental science
– Geography and land information
– Geology and geoscience
– Hydrology and water resources
– Image processing and analysis
– Atmospheric science and meteorology
– Oceanography
– Sensor systems and spectral-radiometric measurements

In addition to original research papers, comprehensive review articles are welcome. Brief papers containing significant new data or techniques may be published as Short Communications.

Palabras clave – provistas por la editorial

No disponibles.

Disponibilidad

Institución detectada	Período	Navegá	Descargá	Solicitá
No detectada	desde mar. 1969 / hasta dic. 2023	ScienceDirect

Información

Tipo de recurso:

revistas

ISSN impreso

0034-4257

ISSN electrónico

1879-0704

Editor responsable

Elsevier

País de edición

Países Bajos

Fecha de publicación

1969-

Cobertura temática

Ingenieria ambiental

Tabla de contenidos

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doi: 10.1016/j.rse.2017.09.013

Big Remotely Sensed Data: tools, applications and experiences

F. Casu; M. Manunta; P.S. Agram; R.E. Crippen

Palabras clave: Computers in Earth Sciences; Soil Science; Geology.

Pp. 1-2

doi: 10.1016/j.rse.2018.02.055

High-resolution multi-temporal mapping of global urban land using Landsat images based on the Google Earth Engine Platform

Xiaoping Liu; Guohua Hu; Yimin Chen; Xia Li; Xiaocong Xu; Shaoying Li; Fengsong Pei; Shaojian Wang

Palabras clave: Computers in Earth Sciences; Soil Science; Geology.

Pp. 227-239

doi: 10.1016/j.rse.2018.11.005

The ATL08 land and vegetation product for the ICESat-2 Mission

Amy Neuenschwander; Katherine Pitts

Palabras clave: Computers in Earth Sciences; Geology; Soil Science.

Pp. 247-259

doi: 10.1016/j.rse.2019.04.016

Smallholder maize area and yield mapping at national scales with Google Earth Engine

Zhenong Jin; George Azzari; Calum You; Stefania Di Tommaso; Stephen Aston; Marshall Burke; David B. Lobell

Palabras clave: Computers in Earth Sciences; Soil Science; Geology.

Pp. 115-128

doi: 10.1016/j.rse.2019.111347

Country-wide high-resolution vegetation height mapping with Sentinel-2

Nico Lang; Konrad Schindler; Jan Dirk Wegner

Palabras clave: Computers in Earth Sciences; Geology; Soil Science.

Pp. 111347

doi: 10.1016/j.rse.2019.111400

Mapping three decades of annual irrigation across the US High Plains Aquifer using Landsat and Google Earth Engine

Jillian M. Deines; Anthony D. Kendall; Morgan A. Crowley; Jeremy Rapp; Jeffrey A. Cardille; David W. Hyndman

Palabras clave: Computers in Earth Sciences; Soil Science; Geology.

Pp. 111400

doi: 10.1016/j.rse.2019.111624

Mapping cropping intensity in China using time series Landsat and Sentinel-2 images and Google Earth Engine

Luo Liu; Xiangming Xiao; Yuanwei Qin; Jie Wang; Xinliang Xu; Yueming Hu; Zhi Qiao

Palabras clave: Computers in Earth Sciences; Soil Science; Geology.

Pp. 111624

doi: 10.1016/j.rse.2020.112165

Mapping global forest canopy height through integration of GEDI and Landsat data

Peter Potapov; Xinyuan Li; Andres Hernandez-Serna; Alexandra Tyukavina; Matthew C. Hansen; Anil Kommareddy; Amy Pickens; Svetlana Turubanova; Hao Tang; Carlos Edibaldo Silva; John Armston; Ralph Dubayah; J. Bryan Blair; Michelle Hofton

Palabras clave: Computers in Earth Sciences; Geology; Soil Science.

Pp. 112165

doi: 10.1016/j.rse.2021.112474

Not all DEMs are equal: An evaluation of six globally available 30 m resolution DEMs with geodetic benchmarks and LiDAR in Mexico

J.J. Carrera-Hernández

Palabras clave: Computers in Earth Sciences; Geology; Soil Science.

Pp. 112474

doi: 10.1016/j.rse.2021.112715

New insights in glaciers characterization by differential diagnosis integrating GPR and remote sensing techniques: A case study for the Eastern Gran Zebrù glacier (Central Alps)

E. Forte; I. Santin; S. Ponti; R.R. Colucci; P. Gutgesell; M. Guglielmin

Palabras clave: Computers in Earth Sciences; Geology; Soil Science.

Pp. 112715