Soil Mapping in Chongwe, Zambia by Digital Analysis of Landsat Data
- Chizumba Shepande
- Marvin Bauer
- Jay Bell
- Victor Shitumbanuma
Abstract
Designing a methodology for mapping and studying soils in a quick and inexpensive way is critical especially in developing countries like Zambia, which lack detailed soil surveys. Therefore, this study was conducted to determine the potential of Landsat 7 ETM+ data (Enhanced Thematic Mapper plus) in mapping soils in Chongwe, a semi-arid region in Zambia. In addition, the study attempted to establish how accurate spectral soil maps produced by digital analysis of Landsat data can be and how such maps compared with field observation data. Also, in situations where there was poor agreement between Landsat data and field observation data, possible causes of such discrepancies where determined.
A soil inventory of the Chongwe region of Zambia was prepared using computer-aided digital analysis of two Landsat 7 ETM+ satellite images acquired in the dry and rainy seasons to investigate the hypothesis that there is a relationship between Landsat spectral reflectance and certain soil types and that this relationship can be used to map soils with reasonable accuracy.
The study revealed that digital analysis of Landsat 7 ETM images has the capacity to map and delineate soil patterns with reasonable accuracy, especially when acquired during the dry season when there are long periods of cloud free skies, low soil moisture and minimal vegetation cover. The overall agreement between the Landsat classification and reference data was 72%, indicating a definite relationship between Landsat imagery and soil types.
In terms of soilscape boundary delineation, the Landsat derived map was had a higher level of agreement with field observations than the conventional soil map. In addition, the study showed that overall, upland areas have a better agreement with Landsat spectral data compared to lowland areas, probably due to the diverse origin of sediments and low spatial extent of most landforms in lowland areas.
- Full Text: PDF
- DOI:10.5539/jas.v8n9p152
Journal Metrics
- h-index: 67
- i10-index: 839
- WJCI (2022): 1.220
- WJCI Impact Factor: 0.263
Index
- AGRICOLA
- AGRIS
- BASE (Bielefeld Academic Search Engine)
- Berkeley Library
- CAB Abstracts
- CiteFactor
- CiteSeerx
- CNKI Scholar
- Copyright Clearance Center
- CrossRef
- DESY Publication Database
- DTU Library
- EBSCOhost
- EconPapers
- Elektronische Zeitschriftenbibliothek (EZB)
- EuroPub Database
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- Google Scholar
- Harvard Library
- IDEAS
- Index Copernicus
- Jisc Library Hub Discover
- JournalTOCs
- KindCongress
- LIVIVO (ZB MED)
- LOCKSS
- Max Planck Institutes
- Mendeley
- MIAR
- Mir@bel
- NLM Catalog PubMed
- Norwegian Centre for Research Data (NSD)
- OAJI
- Open J-Gate
- OUCI
- PKP Open Archives Harvester
- Polska Bibliografia Naukowa
- Qualis/CAPES
- RefSeek
- RePEc
- ROAD
- ScienceOpen
- Scilit
- SCiNiTO
- Semantic Scholar
- SHERPA/RoMEO
- Southwest-German Union Catalogue
- Standard Periodical Directory
- Stanford Libraries
- SUDOC
- Technische Informationsbibliothek (TIB)
- Trove
- UCR Library
- Ulrich's
- UniCat
- Universe Digital Library
- WorldCat
- WorldWideScience
- WRLC Catalog
- Zeitschriften Daten Bank (ZDB)
Contact
- Anne BrownEditorial Assistant
- jas@ccsenet.org