scholarly journals Long-Term Monitoring of Transformation from Pastoral to Agricultural Land Use Using Time-Series Landsat Data in the Feija Basin (Southeast Morocco)

2019 ◽  
Vol 3 (3) ◽  
pp. 525-538 ◽  
Author(s):  
Atman Ait Lamqadem ◽  
Hafid Saber ◽  
Biswajeet Pradhan
Keyword(s):  
Land Use ◽  
Time Series ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Landsat Data ◽  
Long Term Monitoring ◽  
Term Monitoring

Long-term monitoring of citrus orchard dynamics using time-series Landsat data: a case study in southern China

2018 ◽  
Vol 39 (22) ◽  
pp. 8271-8292 ◽  
Author(s):  
Hanzeyu Xu ◽  
Shuhua Qi ◽  
Peng Gong ◽  
Chong Liu ◽  
Junbang Wang
Keyword(s):  
Time Series ◽  
Southern China ◽  
Landsat Data ◽  
Citrus Orchard ◽  
Long Term Monitoring ◽  
Term Monitoring

scholarly journals Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring

2018 ◽  
Vol 7 (10) ◽  
pp. 405 ◽  
Author(s):  
Urška Kanjir ◽  
Nataša Đurić ◽  
Tatjana Veljanovski
Keyword(s):  
Land Use ◽  
Time Series ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Land Use Control ◽  
Sentinel 2

The European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and comparability of CAP results in different Member States. In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that correspond to land use anomaly observations in the assessment of agricultural parcel management activities. We focus on identifying certain signs of ineligible (inconsistent) use in permanent meadows and crop fields in one growing season, and in particular those that can be associated with time-defined greenness (vegetation vigor). Depending on the requirements of the BFAST Monitor method and currently time-limited Sentinel-2 dataset for the reliable anomaly study, we introduce customized procedures to support and verify the BFAST Monitor anomaly detection results using the analysis of NDVI (Normalized Difference Vegetation Index) object-based temporal profiles and time-series standard deviation output, where geographical objects of interest are parcels of particular land use. The validation of land use candidate anomalies in view of land use ineligibilities was performed with the information on declared land annual use and field controls, as obtained in the framework of subsidy granting in Slovenia. The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness. As such it can already be introduced to help the process of agricultural land use control within certain CAP activities in the preparation and adaptation phase.

scholarly journals Long-term monitoring programme of the hydrological variability in the Mediterranean Sea: a first overview of the HYDROCHANGES network

Ocean Science ◽  
2013 ◽  
Vol 9 (2) ◽  
pp. 301-324 ◽  
Author(s):  
K. Schroeder ◽  
C. Millot ◽  
L. Bengara ◽  
S. Ben Ismail ◽  
M. Bensi ◽  
...  
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Sampling Interval ◽  
Global Changes ◽  
Hydrological Variability ◽  
Long Term Monitoring ◽  
The Mediterranean ◽  
Set Up ◽  
Term Monitoring

Abstract. The long-term monitoring of basic hydrological parameters (temperature and salinity), collected as time series with adequate temporal resolution (i.e. with a sampling interval allowing the resolution of all important timescales) in key places of the Mediterranean Sea (straits and channels, zones of dense water formation, deep parts of the basins), constitute a priority in the context of global changes. This led CIESM (The Mediterranean Science Commission) to support, since 2002, the HYDROCHANGES programme (http//www.ciesm.org/marine/programs/hydrochanges.htm), a network of autonomous conductivity, temperature, and depth (CTD) sensors, deployed on mainly short and easily manageable subsurface moorings, within the core of a certain water mass. The HYDROCHANGES strategy is twofold and develops on different scales. To get information about long-term changes of hydrological characteristics, long time series are needed. But before these series are long enough they allow the detection of links between them at shorter timescales that may provide extremely valuable information about the functioning of the Mediterranean Sea. The aim of this paper is to present the history of the programme and the current set-up of the network (monitored sites, involved groups) as well as to provide for the first time an overview of all the time series collected under the HYDROCHANGES umbrella, discussing the results obtained thanks to the programme.

Long-Term Monitoring of Australian Land Cover Change Using Landsat Data: Development, Implementation, and Operation

2016 ◽  
pp. 229-244 ◽  
Author(s):  
Peter Caccetta ◽  
Suzanne Furby ◽  
Jeremy Wallace ◽  
Xiaoliang Wu ◽  
Gary Richards ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Landsat Data ◽  
Long Term Monitoring ◽  
Term Monitoring

EMC Analysis by Land Use Types based on Long-term Monitoring of Nonpoint Source Pollution in Geum River Basin

2013 ◽  
Vol 13 (6) ◽  
pp. 411-422
Author(s):  
Jung Ho Lee ◽  
Yang Ho Song ◽  
Dongho Kim ◽  
Suyoung Park ◽  
Jiyeon Kim ◽  
...  
Keyword(s):  
Land Use ◽  
River Basin ◽  
Nonpoint Source Pollution ◽  
Nonpoint Source ◽  
Land Use Types ◽  
Long Term Monitoring ◽  
Term Monitoring

scholarly journals Classifying multiyear agricultural land use data from Mato Grosso using time-series MODIS vegetation index data

2013 ◽  
Vol 130 ◽  
pp. 39-50 ◽  
Author(s):  
J. Christopher Brown ◽  
Jude H. Kastens ◽  
Alexandre Camargo Coutinho ◽  
Daniel de Castro Victoria ◽  
Christopher R. Bishop
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Mato Grosso ◽  
Index Data

scholarly journals USING LANDSAT 8 IMAGE TIME SERIES FOR CROP MAPPING IN A REGION OF CERRADO, BRAZIL

2016 ◽  
Vol XLI-B8 ◽  
pp. 845-850 ◽  
Author(s):  
H. Bendini ◽  
I. D. Sanches ◽  
T. S. Körting ◽  
L. M. G. Fonseca ◽  
A. J. B. Luiz ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Vegetation Indices ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Land Use Classification ◽  
Crop Mapping ◽  
Phenological Metrics

The objective of this research is to classify agricultural land use in a region of the Cerrado (Brazilian Savanna) biome using a time series of Enhanced Vegetation Index (EVI) from Landsat 8 OLI. Phenological metrics extracted from EVI time series, a Random Forest algorithm and data mining techniques are used in the process of classification. The area of study is a region in the Cerrado in a region of the municipality of Casa Branca, São Paulo state, Brazil. The results are encouraging and demonstrate the potential of phenological parameters obtained from time series of OLI vegetation indices for agricultural land use classification.

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