HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia
Optical imagery can reveal spectral properties of forest canopy, which rarely allows for finding accurate correspondence of canopy features with soils and hydrology. In Amazonia non-floodable swampy forests can not be easily distinguished from non-floodable terra-firme forests using just bidimension...
| Autor principal: | Rennó, Camilo Daleles |
|---|---|
| Outros Autores: | Nobre, Antônio Donato, Cuartas, Luz Adriana, Soares, Joao V., Hodnett, Martin G., Tomasella, J., Waterloo, M. J. |
| Grau: | Artigo |
| Idioma: | English |
| Publicado em: |
Remote Sensing of Environment
2020
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| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/18530 |
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oai:repositorio:1-18530 |
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dspace |
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oai:repositorio:1-18530 HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia Rennó, Camilo Daleles Nobre, Antônio Donato Cuartas, Luz Adriana Soares, Joao V. Hodnett, Martin G. Tomasella, J. Waterloo, M. J. Agricultural Engineering Correlation Methods Drainage Earth Sciences Engineering Geology Forestry Geodetic Satellites Geomorphology Groundwater Hydrogeology Rain Soil Moisture Soils Surveying Topography Underwater Soils Vegetation Water Amazonia Data Sets Descriptor Descriptors Digital Elevation Model (dem) Forest Canopies Land-surface Processes Optical Imagery Physical Principles Rain Forests Shuttle Radar Topographic Mission Soil Water Spectral Data Spectral Properties Strong Correlations Terrain Classification Topographic Data Vegetation Canopies Water Table Depths Tracking Radar Algorithm Canopy Classification Data Set Digital Elevation Model Drainage Imagery Mapping Method Optical Method Rainforest Remote Sensing Swamp Forest Terrain Agriculture Algorithms Correlation Data Drainage Forestry Groundwater Hydrology Mapping Mathematical Models Moisture Optical Instruments Plants Rain Soil Topography Amazonia South America Optical imagery can reveal spectral properties of forest canopy, which rarely allows for finding accurate correspondence of canopy features with soils and hydrology. In Amazonia non-floodable swampy forests can not be easily distinguished from non-floodable terra-firme forests using just bidimensional spectral data. Accurate topographic data are required for the understanding of land surface processes at finer scales. Topographic detail has now become available with the Shuttle Radar Topographic Mission (SRTM) data. This new digital elevation model (DEM) shows the feature-rich relief of lowland rain forests, adding to the ability to map rain forest environments through many quantitative terrain descriptors. In this paper we report on the development of a new quantitative topographic algorithm, called HAND (Height Above the Nearest Drainage), based on SRTM-DEM data. We tested the HAND descriptor for a groundwater, topographic and vegetation dataset from central Amazonia. The application of the HAND descriptor in terrain classification revealed strong correlation between soil water conditions, like classes of water table depth, and topography. This correlation obeys the physical principle of soil draining potential, or relative vertical distance to drainage, which can be detected remotely through the topography of the vegetation canopy found in the SRTM-DEM data. © 2008 Elsevier Inc. All rights reserved. 2020-06-15T22:02:02Z 2020-06-15T22:02:02Z 2008 Artigo https://repositorio.inpa.gov.br/handle/1/18530 10.1016/j.rse.2008.03.018 en Volume 112, Número 9, Pags. 3469-3481 Restrito Remote Sensing of Environment |
| institution |
Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional |
| collection |
INPA-RI |
| language |
English |
| topic |
Agricultural Engineering Correlation Methods Drainage Earth Sciences Engineering Geology Forestry Geodetic Satellites Geomorphology Groundwater Hydrogeology Rain Soil Moisture Soils Surveying Topography Underwater Soils Vegetation Water Amazonia Data Sets Descriptor Descriptors Digital Elevation Model (dem) Forest Canopies Land-surface Processes Optical Imagery Physical Principles Rain Forests Shuttle Radar Topographic Mission Soil Water Spectral Data Spectral Properties Strong Correlations Terrain Classification Topographic Data Vegetation Canopies Water Table Depths Tracking Radar Algorithm Canopy Classification Data Set Digital Elevation Model Drainage Imagery Mapping Method Optical Method Rainforest Remote Sensing Swamp Forest Terrain Agriculture Algorithms Correlation Data Drainage Forestry Groundwater Hydrology Mapping Mathematical Models Moisture Optical Instruments Plants Rain Soil Topography Amazonia South America |
| spellingShingle |
Agricultural Engineering Correlation Methods Drainage Earth Sciences Engineering Geology Forestry Geodetic Satellites Geomorphology Groundwater Hydrogeology Rain Soil Moisture Soils Surveying Topography Underwater Soils Vegetation Water Amazonia Data Sets Descriptor Descriptors Digital Elevation Model (dem) Forest Canopies Land-surface Processes Optical Imagery Physical Principles Rain Forests Shuttle Radar Topographic Mission Soil Water Spectral Data Spectral Properties Strong Correlations Terrain Classification Topographic Data Vegetation Canopies Water Table Depths Tracking Radar Algorithm Canopy Classification Data Set Digital Elevation Model Drainage Imagery Mapping Method Optical Method Rainforest Remote Sensing Swamp Forest Terrain Agriculture Algorithms Correlation Data Drainage Forestry Groundwater Hydrology Mapping Mathematical Models Moisture Optical Instruments Plants Rain Soil Topography Amazonia South America Rennó, Camilo Daleles HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia |
| topic_facet |
Agricultural Engineering Correlation Methods Drainage Earth Sciences Engineering Geology Forestry Geodetic Satellites Geomorphology Groundwater Hydrogeology Rain Soil Moisture Soils Surveying Topography Underwater Soils Vegetation Water Amazonia Data Sets Descriptor Descriptors Digital Elevation Model (dem) Forest Canopies Land-surface Processes Optical Imagery Physical Principles Rain Forests Shuttle Radar Topographic Mission Soil Water Spectral Data Spectral Properties Strong Correlations Terrain Classification Topographic Data Vegetation Canopies Water Table Depths Tracking Radar Algorithm Canopy Classification Data Set Digital Elevation Model Drainage Imagery Mapping Method Optical Method Rainforest Remote Sensing Swamp Forest Terrain Agriculture Algorithms Correlation Data Drainage Forestry Groundwater Hydrology Mapping Mathematical Models Moisture Optical Instruments Plants Rain Soil Topography Amazonia South America |
| description |
Optical imagery can reveal spectral properties of forest canopy, which rarely allows for finding accurate correspondence of canopy features with soils and hydrology. In Amazonia non-floodable swampy forests can not be easily distinguished from non-floodable terra-firme forests using just bidimensional spectral data. Accurate topographic data are required for the understanding of land surface processes at finer scales. Topographic detail has now become available with the Shuttle Radar Topographic Mission (SRTM) data. This new digital elevation model (DEM) shows the feature-rich relief of lowland rain forests, adding to the ability to map rain forest environments through many quantitative terrain descriptors. In this paper we report on the development of a new quantitative topographic algorithm, called HAND (Height Above the Nearest Drainage), based on SRTM-DEM data. We tested the HAND descriptor for a groundwater, topographic and vegetation dataset from central Amazonia. The application of the HAND descriptor in terrain classification revealed strong correlation between soil water conditions, like classes of water table depth, and topography. This correlation obeys the physical principle of soil draining potential, or relative vertical distance to drainage, which can be detected remotely through the topography of the vegetation canopy found in the SRTM-DEM data. © 2008 Elsevier Inc. All rights reserved. |
| format |
Artigo |
| author |
Rennó, Camilo Daleles |
| author2 |
Nobre, Antônio Donato Cuartas, Luz Adriana Soares, Joao V. Hodnett, Martin G. Tomasella, J. Waterloo, M. J. |
| author2Str |
Nobre, Antônio Donato Cuartas, Luz Adriana Soares, Joao V. Hodnett, Martin G. Tomasella, J. Waterloo, M. J. |
| title |
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia |
| title_short |
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia |
| title_full |
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia |
| title_fullStr |
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia |
| title_full_unstemmed |
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia |
| title_sort |
hand, a new terrain descriptor using srtm-dem: mapping terra-firme rainforest environments in amazonia |
| publisher |
Remote Sensing of Environment |
| publishDate |
2020 |
| url |
https://repositorio.inpa.gov.br/handle/1/18530 |
| _version_ |
1787145089117585408 |
| score |
11.653393 |