Results 31 to 40 of about 17,569,314 (273)
A normalized difference vegetation index (NDVI) time-series of idle agriculture lands: A preliminary study [PDF]
, 2011 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.
Vaiphasa, T. +12 more
core +1 more source
, 2022 we create a well-annotated SCD dataset, Landsat-SCD with unprecedented time series and change types in complex scenarios. The Landsat-SCD dataset provides 10 change types with much more fine change information than is previously available in the context
Yuan Panli (12698189)
core +1 more source
Science of Landsat Analysis Ready Data
Remote Sensing, 2019 The free and open policy of Landsat data in 2008 completely changed the way that Landsat data was analyzed and used, particularly for applications such as time series analysis.
Zhe Zhu
doaj +1 more source
Mapping Brazilian savanna vegetation gradients with Landsat time series
International Journal of Applied Earth Observation and Geoinformation, 2016 Abstract Global change has tremendous impacts on savanna systems around the world. Processes related to climate change or agricultural expansion threaten the ecosystem’s state, function and the services it provides. A prominent example is the Brazilian Cerrado that has an extent of around 2 million km2 and features high biodiversity with many endemic
Marcel Schwieder +5 more
openaire +2 more sources
Sub-annual tropical forest disturbance monitoring using harmonized Landsat and Sentinel-2 data
International Journal of Applied Earth Observations and Geoinformation, 2021 Accurate sub-annual detection of forest disturbance provides timely baseline information for understanding forest change and dynamics to support the development of sustainable forest management strategies.
Na Chen +4 more
doaj +1 more source
Thick cloud removal in Landsat images based on autoregression of Landsat time-series data
Remote Sensing of Environment, 2020 Abstract Thick-cloud contamination causes serious missing data in Landsat images, which substantially limits applications of these images. To remove thick clouds from Landsat data, the most popular methods employ auxiliary data such as a cloud-free image of the same area acquired on another date (referred to as the “reference image”).
Ruyin Cao +4 more
openaire +2 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 A long time-series land surface temperature (LST) product is useful for ecological and environmental studies. However, current LST products cannot provide a global coverage at a fine spatial resolution (~100 m) over a long period (>30 years).
Mengmeng Wang +8 more
doaj +1 more source
MAPPING DISTURBANCE DYNAMICS IN WET SCLEROPHYLL FORESTS USING TIME SERIES LANDSAT [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these ...
A. Haywood +3 more
doaj +1 more source
Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study [PDF]
Remote Sensing, 2018 Quarry sites result from human activity, which includes the removal of original vegetation and the overlying soil to dig out stones for building use. Therefore, the dynamics of the quarry area provide a unique view of human mining activities. Actually, the topographic changes caused by mining activities are also a result of the development of the local
Haoteng Zhao +6 more
openaire +3 more sources
Remote Sensing, 2021 Fine-resolution satellite imagery is needed for characterizing dry-season phenology in tropical forests since many tropical forests are very spatially heterogeneous due to their diverse species and environmental background.
Xiaolin Zhu +8 more
doaj +1 more source