Landsat Spectral Data for Digital Soil Mapping

Boettinger, Janis L.; Ramsey, R. Douglas; Bodily, J.M.; Cole, Nancy; Kienast-Brown, S.; Nield, S. J.; Saunders, Aaron Marc; Stum, Alexander Knell

doi:10.1007/978-1-4020-8592-5_16

Cited by 86 publications

(56 citation statements)

References 5 publications

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“…In India, the forests are being disturbed from pre-independence period until today for various rationales (Stebbing, 1992 2000) reported the usefulness of NDVI to assess the percentage of vegetation cover and opined that higher the NDVI value indicates the rich vegetation density. This technique has also being assisted with Landsat ETM+ data vis-à-vis analysis of other satellite images for digital mapping of forest density (Kumar et al, 2007), soil mapping and different LULC (Boettinger et al, 2008). Primary feature of vegetation viz., light, water and soil conditions are also being affected due to additional deforestation and clear-cut timber harvestation (Kumar et al, 2007;Boettinger et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…This technique has also being assisted with Landsat ETM+ data vis-à-vis analysis of other satellite images for digital mapping of forest density (Kumar et al, 2007), soil mapping and different LULC (Boettinger et al, 2008). Primary feature of vegetation viz., light, water and soil conditions are also being affected due to additional deforestation and clear-cut timber harvestation (Kumar et al, 2007;Boettinger et al, 2008). The present study showed positive discrimination of gradual increment of NDVI value, indicates that anthropogenic pressure increase in time dependent manner, which is reflected at our http://www.aloki.hu • 3).…”

Section: Discussionmentioning

confidence: 99%

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Monitoring and Assessment of Land Use and Land Cover Changes (1977 - 2010) in Kamrup District of Assam, India Using Remote Sensing and Gis Techniques

Kumar¹

2017

Appl Ecol Env Res

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Monitoring and Assessment of Land Use and Land Cover Changes (1977 - 2010) in Kamrup District of Assam, India Using Remote Sensing and Gis Techniques

Kumar¹

2017

Appl Ecol Env Res

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“…Landsat TM images have been used with mixed success to map igneous and metamorphic units (e.g., [11,[13][14][15][16][17]), as well as clastic, carbonate, and evaporitic lithologies (e.g., [18][19][20][21][22]). TM data have been applied with some success in the mapping of prominent zones of mineral alteration such as those marked by the presence of abundant oxides and hydroxides (e.g., [23,24]).…”

Section: Discrimination Of Rock Types Using Multispectral Remote Sensmentioning

confidence: 99%

Landsat-TM-Based Discrimination of Lithological Units Associated with the Purtuniq Ophiolite, Quebec, Canada

Leverington

Moon

2012

Remote Sensing

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Abstract:In order to better constrain the utility of multispectral datasets in the characterization of surface materials, Landsat Thematic Mapper (TM) data were evaluated in the discrimination of geological classes in the Cape Smith Belt of Quebec, a greenstone belt that hosts Early Proterozoic units including those of the Purtuniq ophiolite. Ground-based measurements collected for the study area highlight the importance of chemical alteration in controlling the reflectance properties of key geological classes. The spatial distribution of exposed lithologies in the study area was determined through (1) image classification using a feedforward backpropagation neural network classifier; and (2) generation of fraction images for spectral end members using a linear unmixing algorithm and ground reflectance data. Despite some shortcomings, the database of surface cover generated by the neural network classifier is a useful representation of the spatial distribution of exposed geological materials in the study area, with an overall agreement with ground truth of 87.7%. In contrast, the fraction images generated through unmixing are poor representations of ground truth for several key lithological classes. These results underscore both the considerable utility and marked limitations of Landsat TM data in the mapping of igneous and metamorphic lithologies.

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“…Landsat bands are known for particular applications: band 7 (geology band), band 5 (soil and rock discrimination) and band 3 (discrimination of soil from vegetation) (Boettinger et al, 2008;Campbell, 2002Campbell, , 2009Chen and Campagna, 2009). Band ratios are also known for eliminating shadowing and topographic effects which is suitable for complex terrain.…”

Section: Methodology and Materialsmentioning

confidence: 99%

USING REMOTE SENSING FOR LINEAMENT EXTRACTION IN Al MAGHRABAH AREA - HAJJAH, YEMEN

Al-Nahmi

Alami

Baïdder

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Remote sensing and GIS data have become more and more important for the study of geology, structural geology and extract of lineament which give us an overview of the tectonic events. The main objective of our study is to design a method for extracting and mapping of lineament from Landsat 8_OLI satellite images of the study area. Different processing techniques were used to achieve our objective : MNF Minimum Noise Fraction bands (4,5,6), Color composites (7,5,3), PCA Principal Component Analysis bands (4,5,7), band ratios (7/5,6/4,4/2), directional filters, and image processing applied on the Landsat 8_OLI composite colours. The results of this study indicate that, the area is really affected by several structural trends: N-S, NW-SE, and NE-SW directions. The result of lineament analysis gives us a good interpretation of the main structural geology and tectonic forces.

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Landsat Spectral Data for Digital Soil Mapping

Cited by 86 publications

References 5 publications

Monitoring and Assessment of Land Use and Land Cover Changes (1977 - 2010) in Kamrup District of Assam, India Using Remote Sensing and Gis Techniques

Monitoring and Assessment of Land Use and Land Cover Changes (1977 - 2010) in Kamrup District of Assam, India Using Remote Sensing and Gis Techniques

Landsat-TM-Based Discrimination of Lithological Units Associated with the Purtuniq Ophiolite, Quebec, Canada

USING REMOTE SENSING FOR LINEAMENT EXTRACTION IN Al MAGHRABAH AREA - HAJJAH, YEMEN

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