Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

Damen, M. C. J.

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Multivolume work

Persistent identifier:: 856342815

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856342815

Language:: English

Additional Notes:: Volume 1-3 erschienen von 1986-1988

Editor:: Damen, M. C. J.

Document type:: Multivolume work

Volume

Persistent identifier:: 856343064

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Scope:: XV, 547 Seiten

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856343064

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Damen, M. C. J.

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: 4 Renewable resources in rural areas: Vegetation, forestry, agriculture, soil survey, land and water use. Chairman: J. Besenicar, Liaisons: M. Molenaar, Th. A. de Boer

Document type:: Multivolume work

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Chapter

Title:: Assessment of TM thermal infrared band contribution in land cover/land use multispectral classification. José A. Valdes Altamira, Marion F. Baumgardner, Carlos R. Valenzuela

Document type:: Multivolume work

Structure type:: Chapter

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 Assessment of TM thermal infrared band contribution in land cover/land use multispectral classification José A.Valdes Altamira ICI, Mexico Marion F. Baumgardner Purdue University, Laboratory for Applications of Remote Sensing, West Lafayette, Ind, USA Carlos R.Valenzuela ITC, Enschede, Netherlands ABSTRACT :. Thermal data from Landsat 4 TM were used in conjunction with the six reflective TM bands to assess the contribution of the thermal band in eight multispectral classifications using four different data sets. Despite its coarse resolution and differences in radiometric measurements, the thermal data provided an additional informational plane in the generation of Principal Components. This informational plane did not appear when the thermal band was excluded from the linear transformation. The use of all seven TM bands for cluster statistics generation provided greater statistically separability between pairs of spectral classes than when only reflective bands were used. Classification with subsets of selected bands gave better results than classification performed without the use of the thermal band for statistics generation. Classifications with Principal Components reduced the number of spectrally separable classes, but with a significant reduction in computer time. The present paper is an abbreviated version of a Master of Science thesis (Valdés, 1984) , as part of the LIQDA NASA contract NAS5-26859 conducted by LARS/Purdue University. 1 INTRODUCTION Thematic Mapper sensor era started with the launch of Landsat 4, the first of the second generation of Land) sat satellites. This sensor has better spatial reso-~ lution than the earlier Multispectral Scanner onboard Landsats 1,2 £ 3 (30 m -vs- 80m), seven spectral bands instead of four, and four the number of Quanti zation levels (256 -vs- 64). The T.M. also has a band in the thermal infrared re gion of the spectrum, this band differs from the re flective bands in its spatial resolution (120 m) and the type of electromagnetic measurements. This band has not been used often by the scientific community either in the experiments with T.M. simulators or in the first analysis conducted by NASA on the Landsat Image Data Quality Analysis. The hypothesis of this study is that the use of the T.M. thermal infreres band in conjunction with the six reflective bands will provide better discrimina tion of agricultural and urban features than does classifications with the six reflective bands only. The hypothesis can be expressed as: Ho = P(7 TM bands) ^P(6 TM reflective bands) HI = P(7 TM bands) ^rP(6 TM reflective bands) Where P = goodness of classification. Principal Components analysis (data compression tech nique) was also performed to evaluate the contribu- ~ tion of each band to the informational content of the T.M. data. 2 LITERATURE REVIEW 2.1 Agricultural mapping with remote sensing data The specialized literaure in remote sensing contains many examples of the detection and quantification of crops using techniques of digital analysis. Many of these applications are considered either experimental systems (Bauer', et al. ,1971 ;Bauer, 1977; Valdes ,1981) or quasi-operational systems (McDonald and Hall,1978) The results of some of these experiments show diffe rent degrees of accuracy in the identification and quantification of crop resources. However, all these results demonstrate a great potential for surveying crops due to the characteristics of.the data obtained by the Landsat sensors, and the computer processing, for monitoring the vegetative resources in large geo .graphic areas. There is a great amount of documentation available related to the physiological, physical and spectral behavior of vegetation. These must be considered in understanding how solar energy interacts with the ve getation and in order to interpret data from multi spectral sensors. In 1963 , Hoffer and Johannsen working with different vegetative species (com, soybeans and 3 timber spe cies) , found that the spectral response of all those species have the same typical vegetation curve. They also found significant differences in the response — at certain wavelengths, mainly in the visible and near infrared portions of the spectrum. To discriminate crop species by means of remote sen sing, several factors related to the cultural practi_ ces for each crop must be considered, such as plant and row spacing, geometric arrangement of the plants, fertilization and irrigation practices, and growth cycles. The differences in reflectance wich allows us to discriminate between vegetative species, are due to the characteristics of the leaves and canopies of different species. All these internal and external factors influence the optical properties of the leves and canopies. The spectral patterns sensed by the scan ners represent the integration of all of them. 2.2 Thermal and environmental effects of incoming solar energy In order to interpret remote. sensing data of vegeta tion, it is important to comprehend the interaction of the plant with its environment. A plant is exposed to electromagnetic radiation from its surroundings, such as soil, rocks, plants, sun, sky, clouds and atmosphere. All objects above.absolute zero radite energy by virtue of their tempreature and emittance. At temperatures normally exhibited by objects at or near the earths surface, this radiation is almost en tirely in the infrared wavelength region from 4 urn to 100 urn approximately (Swain and Davis, 1978), Plants in stress caused by insects, diseases, physio logical disorders, nutrient deficiency and adverse en vironmental effects suffer detectable temperature and or emittance changes (Kumar and Silva, 1973). Several authors have presented the potential use of thermal change detection on plants in order to evalua te stress causal agents. Clum (1926) and Curtis (19357)

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