In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into a time series of Normalized Difference Vegetation Index (NDVI) images before the investigation. It can be visually observed that the NDVI time series of the Idle Agriculture Land (IAL) has the NDVI values closed to zero. In other words, the trend of the NDVI values remains, approximately, unchanged about the zero level for the whole period of the study time. In contrast, the non-idle areas hold a higher level of the NDVI variation. The NDVI valu...
Both agricultural area expansion and intensification are necessary to cope with the growing demand f...
The existence of rural landscape is very significant in balancing the biohysical environment. The ch...
Vegetation seasonality assessment through remote sensing data is crucial to understand ecosystem res...
In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all ...
In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all ...
Normalized difference vegetation index (NDVI) has been widely applied for monitoring vegetation dyna...
The calculation of Normalized Difference Vegetation Indices (NDVI) can be very useful in the generat...
The information on land cover changes is very important in regional spatial planning. Remote sensing...
ABSTRACT: Crop monitoring is an important factor that contributes in any nation’s economy, and thei...
Calculation of vegetation indices, especially Normalized Difference Vegetation Index (NDVI), has bec...
Calculation of vegetation indices, especially Normalized Difference Vegetation Index (NDVI), has b...
AbstractThe normalized difference vegetation index (NDVI) is one of the significant classification m...
The normalized difference vegetation index (NDVI) is one of the significant classification methods w...
This study uses the Normalised Difference Vegetation Index (NDVI) from 1992 to 2019 to examine the s...
Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield...
Both agricultural area expansion and intensification are necessary to cope with the growing demand f...
The existence of rural landscape is very significant in balancing the biohysical environment. The ch...
Vegetation seasonality assessment through remote sensing data is crucial to understand ecosystem res...
In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all ...
In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all ...
Normalized difference vegetation index (NDVI) has been widely applied for monitoring vegetation dyna...
The calculation of Normalized Difference Vegetation Indices (NDVI) can be very useful in the generat...
The information on land cover changes is very important in regional spatial planning. Remote sensing...
ABSTRACT: Crop monitoring is an important factor that contributes in any nation’s economy, and thei...
Calculation of vegetation indices, especially Normalized Difference Vegetation Index (NDVI), has bec...
Calculation of vegetation indices, especially Normalized Difference Vegetation Index (NDVI), has b...
AbstractThe normalized difference vegetation index (NDVI) is one of the significant classification m...
The normalized difference vegetation index (NDVI) is one of the significant classification methods w...
This study uses the Normalised Difference Vegetation Index (NDVI) from 1992 to 2019 to examine the s...
Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield...
Both agricultural area expansion and intensification are necessary to cope with the growing demand f...
The existence of rural landscape is very significant in balancing the biohysical environment. The ch...
Vegetation seasonality assessment through remote sensing data is crucial to understand ecosystem res...