The current use of remote-sensing data in peat, soil, land-cover and crop inventories in Scotland

1983 ◽  
Vol 309 (1508) ◽  
pp. 271-281 ◽  
Keyword(s):  
Remote Sensing ◽  
Peat Soil ◽  
European Space Agency ◽  
Remote Sensing Data ◽  
Vegetation Mapping ◽  
Soil Survey ◽  
Crop Monitoring ◽  
Sensing Data ◽  
Space Agency ◽  
Natural Resource Surveys

The remote-sensing methodology developed, at the Macaulay Institute, for natural resource surveys is introduced and some recent mapping and environmental monitoring projects are reviewed. These include peat resource and peatland vegetation mapping in Lewis and North Harris, crop monitoring in Kincardineshire and landcover mapping in the Buchan Area of Grampian Region, NE Scotland. The current use of remote-sensing data by the Peat Survey Section and the Soil Survey Department is reviewed for peat, soil and vegetation mapping. The principal current projects, which include the D.A.F.S. Bracken Survey of Scotland, the AGRISPINE Experiment for the U.K. National Remote Sensing Centre at R.A.E. Farnborough and the SAR 580 Experiment for the European Space Agency, are discussed.

scholarly journals Application of multi-temporal Sentinel-1 SAR data for yield estimation of rice crops in An Giang, Vietnam

2022 ◽  
Vol 964 (1) ◽  
pp. 012007
Author(s):  
Hoang Phi Phung ◽  
Lam Dao Nguyen ◽  
Nguyen Van Anh Vu ◽  
Nguyen Kim Thanh ◽  
Le Van Trung
Keyword(s):  
Remote Sensing ◽  
Rice Yield ◽  
European Space Agency ◽  
Mekong Delta ◽  
Remote Sensing Data ◽  
Radar Remote Sensing ◽  
Sensing Data ◽  
Space Agency ◽  
Potential Applications ◽  
Multi Temporal

Abstract Rice is one of the main agricultural crops and plays an important role in food security. Therefore, it is essential to propose a method for monitoring the distribution of rice yield. Radar remote sensing data sources provide a sustainable solution for rice monitoring challenges in the countries located in the tropical monsoon region like Vietnam. The SAR (Synthetic Aperture Radar) remote sensing data from the Sentinel-1 satellite provided by the European Space Agency (ESA) is free of charge, has a large coverage and high spatial-temporal resolution. In this paper, rice growing areas in the An Giang province of Vietnam Mekong Delta were analyzed, which demonstrates the potential applications of multi-temporal data and proposes a method to estimate rice yield for agricultural management. The analysis results showed that in 2018 the Winter-Spring rice crop has the highest yield, and the Autumn-Winter crop has the lowest yield. Accurate and timely estimation of rice yield and production can provide important information in terms of spatial distribution and seasonal yield for government and decision-makers in policy making related to import and export.

Riparian Vegetation Mapping for Hydraulic Roughness Estimation Using Very High Resolution Remote Sensing Data Fusion

2010 ◽  
Vol 136 (11) ◽  
pp. 855-867 ◽  
Author(s):  
Giovanni Forzieri ◽  
Gabriele Moser ◽  
Enrique R. Vivoni ◽  
Fabio Castelli ◽  
Francesco Canovaro
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Data Fusion ◽  
Riparian Vegetation ◽  
Remote Sensing Data ◽  
Vegetation Mapping ◽  
Hydraulic Roughness ◽  
Sensing Data ◽  
Very High

scholarly journals Application of Remote Sensing, GIS, and GPS Technology on Environment and Earth's Natural Resources Management An Introduction

2007 ◽  
Vol 6 (1) ◽  
pp. 96-117
Author(s):  
N. Nandini ◽  
Aboud S. Jumbe ◽  
Sucharita Tandon ◽  
Sunita N.
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Crop Monitoring ◽  
Sensing Data ◽  
Data Generator ◽  
Information Updates ◽  
Thematic Information ◽  
Meteorological Satellite

Remote sensing data have been used to derive thematic information of various natural resources and environment.The type and level of information extracted depends on the expertise of the analyst and what he/she is looking for in the data.An application in remote sensing is the practical use to which a series of aerial satellite images are put. The application of remote sensing or earth observation techniques to atmospheric, Earth and environmental sciences can vary according to the final user's requirements.The utilization of remote sensing data can be broadly classified into three categories as a baseline data generator for a variety of environmental resources; as a tool to monitor change detection, Environmental monitoring, and for mapping purposes. Different environmental applications require different frequencies of information updates for monitoring to be effective. Environment phenomena such as weather systems, natural hazards, and other rarely extreme events such as tsunamis; pollution or oceanographic events are very dynamic and rapidly develop over minutes and hours. Therefore for satellite data to be useful in their analysis imaging frequency and data delivery has to be atleast several times a day. At present only low spatial resolution meteorological satellite data can meet this need. Other applications such as crop monitoring require better spatial detail but rates of change occur only over a matter of weeks and therefore image updates need not be more frequent than weekly or monthly. This data can be processed, refined, and managed with the use of advanced tools such as Geographic Information System(GIS) and Geographic Positioning System(GPS).

scholarly journals Urban Classification Using Multi-temporal Sentinel-1 Data Based On Coherence Characteristics

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Le Minh Hang ◽  
Tran Anh Tuan
Keyword(s):  
Remote Sensing ◽  
European Space Agency ◽  
Remote Sensing Data ◽  
Image Data ◽  
Development Planning ◽  
Optical Remote Sensing ◽  
Satellite Mission ◽  
Sar Images ◽  
Sensing Data ◽  
Polarization Image

Classification urban features plays an important part in monitoring and development planning of the area. Optical remote sensing data is currently used in study land use/land cover. However, optical remote sensing data are affected by clouds and weather. Hence, it is difficult to update information. Sentinel-1 is the satellite mission which conducted by the European Space Agency (ESA). Sentinel-1 is composed of two satellites, Sentinel-1A and Sentinel-1B which carried C-band Synthetic Aperture Radar (SAR) instrument, 10m spatial resolution and provided free of charge. SAR images, which is an active microwave data, is not affected by weather, day and night. In this article, the authors present the experimental results of using coherence technique of two SAR images acquised at different times to classify urban features. The classification accuracy by using VV and VH polarization images were respectively 89% and 93%. VH polarization image data used in classification urban feature is better than VV polarization image.

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