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A Process for Assessing Wooded Plant Cover by Remote Sensing
The ability to map the extent of wooded vegetation cover over large areas using remote sensing is important for managing and assessing rangelands. Currently, applied techniques are inadequate because they 1) do not directly measure the amount of land covered by woody plants and rely on low-resolutio...
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Published in: | Rangeland ecology & management 2005-03, Vol.58 (2), p.184-190 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The ability to map the extent of wooded vegetation cover over large areas using remote sensing is important for managing and assessing rangelands. Currently, applied techniques are inadequate because they 1) do not directly measure the amount of land covered by woody plants and rely on low-resolution images, 2) require considerable training-area data to train a classifier, and 3) describe only a limited number of land cover types. This paper presents an innovative methodology for creating a land-cover map that requires little to no traditional, training-area data collection before classification. The procedure combines both high-resolution aerial photography (resampled to 2.5-m pixels) and lower-resolution satellite imagery (30-m pixels) to produce a detailed and easily producible data set. The resulting data set also categorizes regions into a wide variety of land cover types in addition to differing levels of wooded cover. This new methodology was applied to the Upper Guadalupe River watershed in Texas, which is composed of varying amounts of brush cover between herbaceous range and dense cover. Validation by comparison to aerial imagery demonstrated a 74.4% success rate for all land cover classes. Validation was also performed by ground survey for several brush-covered points and showed a 90.0% success rate. As a result of the ground survey, modifications to the methodology were recommended to reduce classification errors and improve the process.
La capacidad de mapear la cantidad de cobertura de vegetación leñosa en grandes áreas usando sensores remotos es importante para manejar y evaluar los pastizales. Las técnicas actualmente aplicadas son inadecuadas porque ellas 1) no miden directamente la cantidad de terreno cubierto por plantas leñosas y se basan en imágenes de baja resolución, 2) se requiere considerable entrenamiento datos de área para entrenar al clasificador, y 3) describen solo un número limitado de tipos de cobertura del terreno. Este artículo presenta una metodología innovadora para crear mapas de cobertura del terreno que requiere de poco a nada de entrenamiento tradicional en la colección de datos de área antes de la clasificación. El procedimiento combina tanto fotografía aérea de alta resolución (remuestrada a 2.5-m pixeles) e imágenes de satélite de baja resolución (30-m pixeles) para producir un juego de datos detallado y fácilmente de producir. El juego de datos resultante también categoriza regiones dentro de una amplia variedad |
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ISSN: | 1550-7424 1551-5028 |
DOI: | 10.2111/1551-5028(2005)58<184:APFAWP>2.0.CO;2 |