Detection of change in vegetation cover using multi-spectral and multi-temporal information for district Sargodha, Pakistan
Bibliographic Data
| ID | 8019438 |
|---|---|
| Authors | Farooq Ahmad (0000-0003-3842-2535, University of the Punjab Lahore, Pakistan, corresponding author) |
| Year | 2012 |
| Volume | 24 |
| Issue | 3 |
| Pages | 557-571 |
| Publication date | 2012-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sociedade & natureza (JOURNAL) |
| Journal identifiers | ISSN: 0103-1570 • E-ISSN: 1982-4513 |
| Publisher | EDUFU (PUBLISHER • BR) |
| DOI | 10.1590/s1982-45132012000300014 |
| OpenAlex | W2065043725 |
| SciELO | S1982-45132012000300014 |
| Language | EN |
| Citations received | 1 |
| References cited | 35 |
Detection of change is the measure of the distinct data framework and thematic change information that can direct to more tangible insights into underlying process involving land cover and landuse changes. Monitoring the locations and distributions of land cover changes is important for establishing links between policy decisions, regulatory actions and subsequent landuse activities. Change detection is the process that helps in determining the changes associated with landuse and land cover properties with reference to geo-registered multi-temporal remote sensing information. It assists in identifying change between two or more dates that is uncharacterized of normal variation. After image to image registrations, the normalized difference vegetation index (NDVI), the transformed normalized difference vegetation index (TNDVI), the enhanced vegetation index (EVI) and the soil-adjusted vegetation index (SAVI) values were derived from Landsat ETM+ dataset and an image differencing algorithm was applied to detect changes. This paper presents an application of the use of multi-temporal Landsat ETM+ images and multi-spectral MODIS (Terra) EVI/NDVI time-series vegetation phenology metrics for the District Sargodha. The results can be utilized as a temporal land use change model for Punjab province of Pakistan to quantify the extent and nature of change and assist in future prediction studies. This will support environmental planning to develop sustainable landuse practices
Ancillary data · Cartography · Change detection · Climate change · Enhanced vegetation index · Geography · Index (typography · Land cover · Land use · Land use, land-use change and forestry · Normalized Difference Vegetation Index · Physical geography · Remote sensing · Satellite imagery · Thematic map · Thematic Mapper · Vegetation (pathology · Vegetation Index · Computer Science · Ecology · Environmental Science · Land Use and Ecosystem Services · Remote Sensing in Agriculture · Remote-Sensing Image Classification
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |