A flowline map of glaciated Canada based on remote sensing dataThis paper is accompanied by a large foldout map entitled A flowline map of glaciated Canada based on remote sensing data (see pocket on back cover).

The map A flowline map of glaciated Canada based on remote sensing data presents flowlines for the former Laurentide and Cordilleran ice sheets based on flow indicators derived from aggregated, flow-parallel landforms — drumlins and crag and tails, fluting, sinuous ridges and furrows, and rises. An extensive review introduces the concepts and evolution of flowline mapping at continental-ice-sheet and regional scales, emphasizing the use of new remote sensing data. Coherent, glaciologically plausible sets of flowlines mapped as flow tracts reflect large-scale flow structure in the paleo-ice sheets and demarcate fields of flow-parallel bedforms. In addition to flow reconstruction, mapped distributions of fields of glacial terrain types — hummocky terrain, Rogen terrain, and bedrock-dominant terrain — increase our power to interpret flowlines and, in turn, give evidence on the genesis of these terrains. End moraines and eskers also aid map interpretation. Landsat 7 Enhanced Thematic Mapper+ (ETM+) satellite images and Shuttle Radar Topography Mission (SRTM) hill shades provide the basic information for this flowline mapping in a Geographical Information System (ArcMap). Information on the Flowline Map allows us to develop conceptual models of ice sheets and to appreciate regional constraints on applications in mineral exploration, in aggregate and groundwater discovery and assessment, in soil and landform genesis, and in glaciology, paleoclimatology, and paleoceanography.

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Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-1125-2011 ◽

2011 ◽

Vol 8 (1) ◽

pp. 1125-1159

Author(s):

J. Cristóbal ◽

R. Poyatos ◽

M. Ninyerola ◽

P. Llorens ◽

X. Pons

Keyword(s):

Remote Sensing ◽

Estimation Error ◽

Remote Sensing Data ◽

Geographical Information ◽

Climate Modelling ◽

Mountain Area ◽

Flow Measurements ◽

Sensing Data ◽

Landsat 7 ◽

Landsat 5 Tm

Abstract. Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (TERRA/AQUA MODIS and Landsat-5 TM/Landsat-7 ETM+) and combining three different approaches to calculate the B parameter. We then compared these estimates with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, with a mean RMSE value of about 0.6 mm day−1 and an estimation error of ±30%. The poor agreement obtained using MODIS data reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and therefore further research is necessary on this issue.

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Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area

Hydrology and Earth System Sciences ◽

10.5194/hess-15-1563-2011 ◽

2011 ◽

Vol 15 (5) ◽

pp. 1563-1575 ◽

Cited By ~ 14

Author(s):

J. Cristóbal ◽

R. Poyatos ◽

M. Ninyerola ◽

P. Llorens ◽

X. Pons

Keyword(s):

Remote Sensing ◽

Estimation Error ◽

Remote Sensing Data ◽

Geographical Information ◽

Climate Modelling ◽

Mountain Area ◽

Flow Measurements ◽

Sensing Data ◽

Landsat 7 ◽

Landsat 5 Tm

Abstract. Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS-based climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (Landsat-7 ETM+, Landsat-5 TM and TERRA/AQUA MODIS, with a spatial resolution of 60, 120 and 1000 m, respectively) and combining three different approaches to calculate the B parameter, which represents an average bulk conductance for the daily-integrated sensible heat flux. We then compared these estimates with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, R2 test of 0.89, with a mean RMSE value of about 0.6 mm day−1 and an estimation error of ±30 %. The poor agreement obtained using TERRA/AQUA MODIS, with a mean RMSE value of 1.8 and 2.4 mm day−1 and an estimation error of about ±57 and 50 %, respectively. This reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and therefore further research is necessary on this issue. Finally, implementing regional GIS-based climate models as inputs in ETd retrieval have has provided good results, making possible to compute ETd at regional scales.

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REGIONAL GEOLGICAL MAPPING IN TROPICAL ENVIRONMENTS USING LANDSAT TM AND SRTM REMOTE SENSING DATA

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-ii-2-w2-93-2015 ◽

2015 ◽

Vol II-2/W2 ◽

pp. 93-98

Author(s):

A. Beiranvand Pour ◽

M. Hashim

Keyword(s):

Remote Sensing ◽

Mineral Exploration ◽

Remote Sensing Data ◽

Shuttle Radar Topography Mission ◽

Peninsular Malaysia ◽

Landsat Tm ◽

Sensing Data ◽

Tropical Environments ◽

Geological Maps ◽

Srtm Data

Landsat Thematic Mapper (TM) and Shuttle Radar Topography Mission (SRTM) data were used to produce geological maps in tropical environments. Lineament, lithology and landform maps were produced for all states in peninsular Malaysia in this study. Kedah, Perak and Terengganu states have been selected as case studies to demonstrate the results of the data and techniques used. Directional filtering technique was applied to Landsat TM bands 4, 5 and 3 for lineament mapping. The lithology map was produced using Landsat TM bands combination consist of bands 4, 3 and 2. Digital elevation model and landform map were produced using SRTM data in 3 Dimension (3D) and 2 Dimension (2D) perspective views, respectively. The produced geological maps and the remote sensing data and methods applied in this study are mostly appropriate for hazard risk mapping applications and mineral exploration projects in the peninsular Malaysia and tropical environments.

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Estimation of PM10 Distribution using Landsat 7 ETM+ Remote Sensing Data

International Journal of Advanced Remote Sensing and GIS ◽

10.23953/cloud.ijarsg.284 ◽

2017 ◽

Vol 6 (1) ◽

pp. 2246-2252 ◽

Cited By ~ 4

Author(s):

Ajay Roy ◽

◽

Anjali Jivani ◽

Bhuvan Parekh ◽

◽

...

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Sensing Data ◽

Landsat 7

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Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas

10.3390/books978-3-0365-1265-5 ◽

2021 ◽

Keyword(s):

Remote Sensing ◽

Environmental Monitoring ◽

Mineral Exploration ◽

Remote Sensing Data ◽

Hyperspectral Remote Sensing ◽

Sensing Data

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LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes

Remote Sensing of Environment ◽

10.1016/j.rse.2018.11.036 ◽

2019 ◽

Vol 221 ◽

pp. 695-706 ◽

Cited By ~ 12

Author(s):

Jianbo Qi ◽

Donghui Xie ◽

Tiangang Yin ◽

Guangjian Yan ◽

Jean-Philippe Gastellu-Etchegorry ◽

...

Keyword(s):

Remote Sensing ◽

Large Scale ◽

Remote Sensing Data ◽

Image Simulation ◽

Simulation Framework ◽

Sensing Data

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Risk management support through India Remote Sensing Satellites

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-1-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 1-6

Author(s):

N. Aparna ◽

A. V. Ramani ◽

R. Nagaraja

Keyword(s):

Remote Sensing ◽

Risk Management ◽

Satellite Data ◽

Global Climate ◽

Remote Sensing Data ◽

Temporal Variations ◽

Geographical Information ◽

Indian Remote Sensing ◽

Management Support ◽

Sensing Data

Remote Sensing along with Geographical Information System (GIS) has been proven as a very important tools for the monitoring of the Earth resources and the detection of its temporal variations. A variety of operational National applications in the fields of Crop yield estimation , flood monitoring, forest fire detection, landslide and land cover variations were shown in the last 25 years using the Remote Sensing data. The technology has proven very useful for risk management like by mapping of flood inundated areas identifying of escape routes and for identifying the locations of temporary housing or a-posteriori evaluation of damaged areas etc. The demand and need for Remote Sensing satellite data for such applications has increased tremendously. This can be attributed to the technology adaptation and also the happening of disasters due to the global climate changes or the urbanization. However, the real-time utilization of remote sensing data for emergency situations is still a difficult task because of the lack of a dedicated system (constellation) of satellites providing a day-to-day revisit of any area on the globe. The need of the day is to provide satellite data with the shortest delay. Tasking the satellite to product dissemination to the user is to be done in few hours. Indian Remote Sensing satellites with a range of resolutions from 1 km to 1 m has been supporting disasters both National & International. In this paper, an attempt has been made to describe the expected performance and limitations of the Indian Remote Sensing Satellites available for risk management applications, as well as an analysis of future systems Cartosat-2D, 2E ,Resourcesat-2R &RISAT-1A. This paper also attempts to describe the criteria of satellite selection for programming for the purpose of risk management with a special emphasis on planning RISAT-1(SAR sensor).

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