scholarly journals Land Cover Classification Based on Fused Data from GF-1 and MODIS NDVI Time Series

2016 ◽  
Vol 8 (9) ◽  
pp. 741 ◽  
Author(s):  
Fanjie Kong ◽  
Xiaobing Li ◽  
Hong Wang ◽  
Dengfeng Xie ◽  
Xiang Li ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Land Cover Classification ◽  
Modis Ndvi ◽  
Ndvi Time Series

scholarly journals Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset

2016 ◽  
Vol 8 (6) ◽  
pp. 495 ◽  
Author(s):  
Lili Xu ◽  
Baolin Li ◽  
Yecheng Yuan ◽  
Xizhang Gao ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Land Cover Changes ◽  
Modis Ndvi ◽  
Time Series Dataset ◽  
Different Types ◽  
Ndvi Time Series

scholarly journals Detecting Land Cover Change Using an Extended Kalman Filter on MODIS NDVI Time-Series Data

2011 ◽  
Vol 8 (3) ◽  
pp. 507-511 ◽  
Author(s):  
W. Kleynhans ◽  
J. C. Olivier ◽  
K. J. Wessels ◽  
B. P. Salmon ◽  
F. van den Bergh ◽  
...  
Keyword(s):  
Time Series ◽  
Kalman Filter ◽  
Land Cover ◽  
Land Cover Change ◽  
Extended Kalman Filter ◽  
Time Series Data ◽  
Series Data ◽  
Modis Ndvi ◽  
Ndvi Time Series

scholarly journals Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

2011 ◽  
Vol 8 (11) ◽  
pp. 3359-3373 ◽  
Author(s):  
C. Höpfner ◽  
D. Scherer
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Vegetation Dynamics ◽  
Time Series Data ◽  
Series Data ◽  
Land Cover Types ◽  
Modis Ndvi ◽  
Ndvi Time Series ◽  
Western Morocco ◽  
North Western

Abstract. Vegetation phenology as well as the current variability and dynamics of vegetation and land cover, including its climatic and human drivers, are examined in a region in north-western Morocco that is nearly 22 700 km2 big. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 is utilised. The data have a spatial resolution of 250 m and were acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The presented approach allows to compose and to analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that the high temporal resolution of 16 d is sufficient for (a) determining local land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000) and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types (i.e. areas that did not change their land cover type) show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared with stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km2. Statistically significant inter-annual trends in vegetation dynamics during the last decade could however not be discovered. A sequence of correlations was respectively carried out to extract the most important periods of rainfall responsible for the production of green biomass and for the extent of land cover types. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85) on an intra-annual time scale to NDVI percentiles (50 %) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI values. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover, as well as prediction methods of land cover change, can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco. It especially offers a quick access when estimating the extent of agricultural lands.

scholarly journals Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

2011 ◽  
Vol 8 (2) ◽  
pp. 3953-3998 ◽  
Author(s):  
C. Höpfner ◽  
D. Scherer
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Vegetation Dynamics ◽  
Time Series Data ◽  
Series Data ◽  
Land Cover Types ◽  
Modis Ndvi ◽  
Ndvi Time Series ◽  
Western Morocco ◽  
North Western

Abstract. Vegetation phenology as well as current variability and dynamics of vegetation and land cover including its climatic and human drivers are examined in a region in north-western Morocco of nearly 22 700 km2. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 with a spatial resolution of 250 m and acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is utilised. The presented approach allows to compose and analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that high temporal resolution of 16 d is sufficient (a) for determining land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000), and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared to the stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km2. However, statistically significant inter-annual trends in vegetation dynamics during the last decade could not be discovered. A sequence of correlations was done to extract the most important period of rainfall for production of green biomass and for the extent of land cover types, respectively. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85) at intra-annual time scale to NDVI percentiles (50%) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI in 16 d steps. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover as well as prediction methods of land cover change can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco offering a fast access especially for estimating the extent of agricultural lands.

scholarly journals Land Cover Classification of an Area Susceptible to Landslides Using Random Forest and NDVI Time Series Data

2020 ◽  
Author(s):  
Tatiana Dias Tardelli Uehara ◽  
Anderson Reis Soares ◽  
Renata Pacheco Quevedo ◽  
Thales Sehn Korting ◽  
Leila Maria Garcia Fonseca ◽  
...  
Keyword(s):  
Time Series ◽  
Random Forest ◽  
Land Cover ◽  
Time Series Data ◽  
Land Cover Classification ◽  
Series Data ◽  
Ndvi Time Series

scholarly journals Land Cover Classification of Landsat Data with Phenological Features Extracted from Time Series MODIS NDVI Data

2014 ◽  
Vol 6 (11) ◽  
pp. 11518-11532 ◽  
Author(s):  
Kun Jia ◽  
Shunlin Liang ◽  
Xiangqin Wei ◽  
Yunjun Yao ◽  
Yingru Su ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Land Cover Classification ◽  
Landsat Data ◽  
Modis Ndvi
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