Evaluation of Landsat TM vegetation indices for estimating vegetation cover on semi-arid rangelands: a case study from Australia

2009 ◽  
Vol 35 (5) ◽  
pp. 435-446 ◽  
Author(s):  
Yun Chen ◽  
David Gillieson
Keyword(s):  
Vegetation Cover ◽  
Vegetation Indices ◽  
Landsat Tm ◽  
Arid Rangelands ◽  
Semi Arid

Assessing the performance of remotely sensed landscape function indices in semi-arid rangelands of Iran

2017 ◽  
Vol 39 (3) ◽  
pp. 253 ◽  
Author(s):  
F. Jafari ◽  
R. Jafari ◽  
H. Bashari
Keyword(s):  
Structural Properties ◽  
Vegetation Cover ◽  
Function Analysis ◽  
Remotely Sensed ◽  
Rangeland Management ◽  
Landscape Function ◽  
Structural And Functional Properties ◽  
Basin Scale ◽  
Arid Rangelands ◽  
Semi Arid

Appropriate rangeland management requires rangeland function analysis at broad scales. This study aimed to examine the potential of remotely sensed function indices extracted from Landsat data to evaluate the function of semi-arid rangelands in central Iran at the sub-basin scale. Three replicate 30-m transects were randomly placed in the dominant slope direction of 14 selected sub-basins. Various structural properties of vegetation (e.g. number and size of vegetation patches and interpatch lengths) and soil surface were scored based on the landscape function analysis (LFA) procedure. The obtained structural and function indices of the LFA, as well as field percent vegetation cover, were compared with the perpendicular distance vegetation index and remotely sensed function indices including proximity, lacunarity, leakiness index, and weighted mean patch size (WMPS). Remotely sensed function indices were found to be capable of discriminating rangeland landscapes with different conditions. Results showed that the structural properties of vegetation considered in the LFA could also be obtained through WMPS and proximity indices (R >0.76; P < 0.01). All indices, except for lacunarity, had significant correlations with percent vegetation cover and the strongest correlation was observed between WMPS and proximity. Our findings highlight the usefulness and efficiency of function indices derived from satellite data in the estimation of structural and functional properties of rangeland landscapes at the sub-basin scale.

Sensitivity of Landsat 7 & 8-derived vegetation indices on semi-arid rangelands of southwestern Uzbekistan

2020 ◽  
pp. 1-16 ◽  
Author(s):  
Toshpulot F. Rajabov ◽  
R. Douglas Ramsey ◽  
Bakhtiyor K. Mardonov ◽  
Muhtor G. Nasirov ◽  
Tashkhanim Rakhimova ◽  
...  
Keyword(s):  
Vegetation Indices ◽  
Landsat 7 ◽  
Arid Rangelands ◽  
Semi Arid

scholarly journals Determination of best sediment estimation model in semi-arid rangelands by using small reservoirs dams sedimentation(case study: daremorid watershed in kerman province)

2019 ◽  
Vol 9 (18) ◽  
pp. 233-240
Author(s):  
peyman madanchi ◽  
محمود عرب خدری ◽  
Mahmood Habibnejad Roshan ◽  
◽  
◽  
...  
Keyword(s):  
Estimation Model ◽  
Small Reservoirs ◽  
Arid Rangelands ◽  
Semi Arid

scholarly journals Remote Sensing of Bush Encroachment on Commercial Cattle Farms in Semi-Arid Rangelands in Namibia

2011 ◽  
pp. 327-343
Author(s):  
Matthias Schröter ◽  
Oliver Jakoby ◽  
Roland Olbrich ◽  
Marcus Eichhorn ◽  
Stefan Baumgärtner
Keyword(s):  
Remote Sensing ◽  
Expert Knowledge ◽  
Accuracy Assessment ◽  
Vegetation Indices ◽  
Ground Truth ◽  
Aerial Photographs ◽  
Bush Encroachment ◽  
Arid Rangelands ◽  
Cattle Farms ◽  
Semi Arid

Bush encroachment is one of the most extensive changes in land cover in semi-arid rangelands and an urgent problem for cattle farming, rapidly reducing the productivity of the rangeland. Despite the severity of these consequences, a complete and accurate assessment of bush encroached areas is still missing at large. This study aims at assessing bush encroachment on commercial cattle farms in central Namibia by employing remote sensing methods to distinguish between areas covered by bush and open rangeland. The authors use different classification techniques and vegetation indices to characterize the nature of vegetation cover. Their analysis shows that results are sensitive to specific classifications of indices. As an accuracy assessment could not be run on these results the authors could not analyze which classification approximates real bush encroachment best. Hence, this study highlights the need for further analysis. Ground truth data, in the form of field mappings, high resolution aerial photographs or local expert knowledge are needed to gain further insights and produce reliable results.

scholarly journals Detecção de Mudança da Vegetação de Caatinga (Change Detection of Vegetation Caatinga)

2013 ◽  
Vol 5 (6) ◽  
pp. 1473 ◽  
Author(s):  
Paulo Roberto Megna Francisco ◽  
Iêde De Brito Chaves ◽  
Lúcia Helena Garófalo Chaves ◽  
Eduardo Rodrigues Viana de Lima
Keyword(s):  
Change Detection ◽  
River Basin ◽  
Vegetation Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Dry Period ◽  
Caatinga Biome ◽  
Semi Arid

A caatinga é um bioma de grande diversidade que cobre a maior parte da área de clima semiárido brasileiro. Várias técnicas já foram utilizadas com o objetivo de determinar quantitativamente e qualitativamente o estado da vegetação a partir de imagens de satélite e índices de vegetação foram desenvolvidos para auxiliar no mapeamento da vegetação e otimizar os parâmetros presentes nas medidas multiespectrais utilizadas com esse fim. Este trabalho teve como objetivo mapear a vegetação da caatinga, e selecionar um índice de vegetação usando o IBVL para validação dos resultados e detectar mudanças ocorridas. Concluiu-se que o melhor índice que se correlaciona com a cobertura vegetal da caatinga foi o Normalized Difference Vegetation Index, do período seco, e que a metodologia utilizada mostrou-se eficiente para caracterização, classificação e separação em 9 classes. A maior recuperação ocorreu em áreas de drenagem e em declividade mais acentuada. A classe detectada de não mudança ocorreu em áreas de menor cobertura vegetal e de solos propensos à erosão. Estimou-se que 38,71% da área da bacia do rio Taperoá esteja em processo de desertificação.Palavras-chave: Semiárido, Geoprocessamento, Degradação. Change Detection of Vegetation Caatinga ABSTRACTThe caatinga biome is a large diversity that covers most of the area of Brazilian semi-arid climate. Several techniques have been used in order to determine quantitatively and qualitatively the state of vegetation from satellite images and vegetation indices were developed to assist in vegetation mapping and optimizing the parameters present in the multispectral measurements used for this purpose. This study aimed to map the vegetation of the caatinga, and select a vegetation index using IBVL to validate the results and detect changes. It was concluded that the best index that correlates with the vegetation of the caatinga was the Normalized Difference Vegetation Index, the dry period, and that the methodology used was efficient for characterization, classification and separation into nine classes. The best recovery occurred in areas of drainage and steeper slope. The class detected no change occurred in areas with less vegetation cover and soils prone to erosion. It was estimated that 20.21% of the area of the river basin Taperoá is in an advanced process of desertification.Keywords: Semiarid, Geoprocessing, Degradation.

The application of Landsat image data to rangeland assessment and monitoring: An example from South Australia.

1983 ◽  
Vol 5 (2) ◽  
pp. 63 ◽  
Author(s):  
RD Graetz ◽  
MR Gentle ◽  
RP Pech ◽  
JF O'Callaghan ◽  
G Drewien
Keyword(s):  
Vegetation Indices ◽  
South Australia ◽  
Image Data ◽  
Rangeland Management ◽  
Landsat Image ◽  
Landsat Data ◽  
Individual Property ◽  
Resource Information ◽  
Arid Rangelands ◽  
Semi Arid

The potential of Landsat image data to assess and monitor an area of semi-arid rangelands in South Australia is demonstrated. The project is a cooperative ongoing one between CSIRO and a future operational user of Landsat, the South Australian Pastoral Board, and it has as its long-term aim the development of a Land Image-Based Resource Information System (LIBRIS) for rangeland management. Three separate stages of the project are described. The fist is the integration of tenure maps with Landsat image data to permit a useful analysis and interrogation of the combined Landsat data sets. The second is the derivation of vegetation indices from Landsat data that are applicable to the semi-arid rangelands. Indices of 'cover' and of 'greenness' have been derived, but this report concen- trates on the cover index only for it can be related to soil erosion hazard/landscape stability and, as such, it represents a simple, robust vegetation-related index derived directly from Landsat. Lastly this index is used to map both cover and trend (changes in cover). Cover changes over the period 1973-1980 are detected and reported for a test region of 8300 km2. With the integration of tenure boundaries the interrogation, mapping and reporting at the individual property level is demonstrable.

Sign in / Sign up

Export Citation Format

Share Document