scholarly journals China's land cover and land use change from 1700 to 2005: Estimations from high-resolution satellite data and historical archives

2010 ◽  
Vol 24 (3) ◽  
pp. n/a-n/a ◽  
Author(s):  
Mingliang Liu ◽  
Hanqin Tian
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Satellite Data ◽  
Historical Archives

Generating long-term high-resolution land-use change datasets for regional climate modeling in CORDEX domains

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Diana Rechid ◽  
Vanessa Reinhart ◽  
Christina Asmus ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Local Scale ◽  
Modeling Studies

<p>Land-use and land cover (LULC) are continuously changing due to environmental changes and anthropogenic activities. Many observational and modeling studies show that LULC changes are important drivers altering land surface feedbacks and land-atmosphere exchange processes that have substantial impact on climate on the regional and local scale. Yet, most long-term regional climate modeling studies do not account for these changes. Therefore, within the WCRP CORDEX Flagship Pilot Study LUCAS (Land Use Change Across Scales) a new workflow was developed to generate high-resolution annual land cover change time series based on past reconstructions and future projections. First, the high-resolution global land cover dataset ESA-CCI LC (~300 m resolution) is aggregated and converted to a 0.1° resolution, fractional plant functional type (PFT) dataset. Second, the land use change information from the land-use harmonized dataset (LUH2), provided at 0.25° resolution as input for CMIP6 experiments, is translated into PFT changes employing a newly developed land use translator (LUT). The new LUT was first applied to the EURO-CORDEX domain. The resulting LULC maps for past and future - the LUCAS LUC dataset - can be applied as land use forcing to the next generation RCM simulations for downscaling CMIP6 by the EURO-CORDEX community and in the framework of FPS LUCAS. The dataset includes land cover and land management practices changes important for the regional and local scale such as urbanization and irrigation. The LUCAS LUC workflow is applied to further CORDEX domains, such as Australasia and North America. The resulting past and future land cover changes will be presented, and challenges regarding the application of the new workflow to different regions will be addressed. In addition, issues related to the implementation of the dataset into different RCMs will be discussed.</p>

scholarly journals REMOTE SENSING APPLICATIONS IN THE FRAME OF “URBAN GEOLOGY” PROJECT

2017 ◽  
Vol 43 (3) ◽  
pp. 1486
Author(s):  
K. Nikolakopoulos ◽  
P. Tsompos
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Image Analysis ◽  
High Resolution ◽  
Land Use Change ◽  
Satellite Data ◽  
Urban Geology ◽  
Sensing Applications ◽  
Remote Sensing Applications ◽  
Very High

In the frame of the “Urban Geology” project of IGME a lot of remote sensing applications were carried out: DSMs creation and accuracy verification, orthorectification of very high resolution satellite data, data fusion, multitemporal and multisensor image analysis, land cover and land use change detection e.t.c. The applications that took place in the pilot case of Nafplio are presented in this study

scholarly journals Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA using multi-satellite data fusion

2016 ◽  
Author(s):  
Yun Yang ◽  
Martha C. Anderson ◽  
Feng Gao ◽  
Christopher R. Hain ◽  
Kathryn A. Semmens ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
North Carolina ◽  
Land Use Change ◽  
Land Cover ◽  
Water Use ◽  
Satellite Data ◽  
Fusion System ◽  
Time Step ◽  
Heterogeneous Landscapes

Abstract. As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal resolution of satellite data, combined with the effects of cloud contamination, constrain the amount of detail that a single satellite can provide. In this study, we describe an application of a multi-sensor ET data fusion system over a mixed forested/agricultural landscape in North Carolina, USA during the growing season of 2013. The fusion system ingests ET estimates from a Two-Source Energy Balance (TSEB) model applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms: hourly geostationary satellite data at 4-km resolution, daily 1-km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), and bi-weekly Landsat thermal data sharpened to 30-m. These multiple datastreams are combined using the Spatial-Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30-m resolution to investigate seasonal water use behavior at the level of individual forest stands and land cover patches. A new method, also exploiting the STARFM algorithm, is used to fill gaps in the Landsat ET retrievals due to cloud cover and/or the scan-line corrector (SLC) failure on Landsat 7. The retrieved daily ET timeseries agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation (20 year old) loblolly pine stand, and US-NC3 located in a recently clear cut and replanted field site. Root mean square errors (RMSE) for NC2 and NC3 were 0.99 mm d-1 and 1.02 mm d-1, respectively, with mean absolute errors of approximately 29 % at the daily time step, 12 % at the monthly time step, and 3 % over the full study period at two flux tower sites. Analyses of water use patterns over the plantation indicate increasing seasonal ET with stand age for young to mid-rotation stands up to 20 years, but little dependence on age for older stands. An accounting of consumptive water use by major land cover classes representative of the modeling domain is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components obtained with the TSEB. The study provides new insights about the effects of forest management and land use change on hydrological water balance, and the method developed has the potential to be used to routinely monitor hydrology and water use over heterogeneous landscapes using thermal remote sensing data.

scholarly journals OBJECT ORIENTED CLASSIFICATION AND FEATURE EXTRACTION FOR PARTS OF EAST DELHI USING HYBRID APPROACH

2018 ◽  
Vol XLII-5 ◽  
pp. 749-754
Author(s):  
P. Kumar ◽  
S. Ravindranath ◽  
K. G. Raj
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Cover ◽  
Satellite Data ◽  
Urban Land ◽  
Urban Land Use ◽  
Data Sets ◽  
Land Use Land Cover ◽  
Master Plans ◽  
Very High

<p><strong>Abstract.</strong> Rapid urbanization of Indian cities requires a focused attention with respect to preparation of Master Plans of cities. Urban land use/land cover from very high resolution satellite data sets is an important input for the preparation of the master plans of the cities along with extraction of transportation network, infrastructure details etc. Conventional classifiers, which are pixel based do not yield reasonably accurate urban land use/land cover classification of very high resolution satellite data (usually merged images of Panchromatic &amp;amp; Multispectral). Object Based Image Classification techniques are being used to generate urban land use maps with ease which is GIS compatible while using very high resolution satellite data sets. In this study, Object Based Image Analysis (OBIA) has been used to create broad level urban Land Use / Land Cover (LU/LC) map using high resolution ResourceSat-2 LISS-4 and Cartosat-1 pan-sharpened image on the study area covering parts of East Delhi City. Spectral indices, geometric parameters and statistical textural methods were used to create algorithms and rule sets for feature classification. A LU/LC map of the study area comprising of 4 major LU/LC classes with its main focus on separation of barren areas from built up areas has been attempted. The overall accuracy of the result obtained is estimated to be approximately 70%.</p>

scholarly journals Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion

2017 ◽  
Vol 21 (2) ◽  
pp. 1017-1037 ◽  
Author(s):  
Yun Yang ◽  
Martha C. Anderson ◽  
Feng Gao ◽  
Christopher R. Hain ◽  
Kathryn A. Semmens ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
North Carolina ◽  
Land Use Change ◽  
Land Cover ◽  
Data Fusion ◽  
Water Use ◽  
Satellite Data ◽  
Fusion System ◽  
Time Step

Abstract. As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal resolution of satellite data, combined with the effects of cloud contamination, constrain the amount of detail that a single satellite can provide. In this study, we describe an application of a multi-sensor ET data fusion system over a mixed forested/agricultural landscape in North Carolina, USA, during the growing season of 2013. The fusion system ingests ET estimates from the Two-Source Energy Balance Model (TSEB) applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms: hourly geostationary satellite data at 4 km resolution, daily 1 km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) and biweekly Landsat thermal data sharpened to 30 m. These multiple ET data streams are combined using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30 m resolution to investigate seasonal water use behavior at the level of individual forest stands and land cover patches. A new method, also exploiting the STARFM algorithm, is used to fill gaps in the Landsat ET retrievals due to cloud cover and/or the scan-line corrector (SLC) failure on Landsat 7. The retrieved daily ET time series agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation (20-year-old) loblolly pine stand and US-NC3 located in a recently clear-cut and replanted field site. Root mean square errors (RMSEs) for NC2 and NC3 were 0.99 and 1.02 mm day−1, respectively, with mean absolute errors of approximately 29 % at the daily time step, 12 % at the monthly time step and 0.7 % over the full study period at the two flux tower sites. Analyses of water use patterns over the plantation indicate increasing seasonal ET with stand age for young to mid-rotation stands up to 20 years, but little dependence on age for older stands. An accounting of consumptive water use by major land cover classes representative of the modeling domain is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components obtained with the TSEB. The study provides new insights about the effects of management and land use change on water yield over forested landscapes.

scholarly journals High-resolution land-use land-cover change data for regional climate modelling applications over Europe – Part 2: Historical and future changes

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Vanessa Reinhart ◽  
Diana Rechid ◽  
Nathalie de Noblet-Ducoudré ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Changes ◽  
Regional Climate ◽  
Climate Modelling ◽  
Historical Changes ◽  
The Impact

Abstract. Anthropogenic land-use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently extensively investigated within the WCRP CORDEX Flagship Pilot Study (FPS) LUCAS – "Land Use and Climate Across Scales" using an ensemble of different Regional Climate Models (RCMs) coupled with diverse Land Surface Models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM-LSM simulations. To account for these needs, we generated the LUCAS LUC Version 1.0 at 0.1° resolution for Europe Hoffmann et al. (2021b,c). The plant functional type distribution for the year 2015 (i.e. LANDMATE PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details about the conversion method based on a cross-walking procedure and the evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (submitted). Subsequently, we applied the land-use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25° resolution as input for CMIP6 experiments, to derive realistic LULC distribution at high spatial resolution and at annual timesteps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a Land Use Translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to remotely-sensed PFT time series. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the Coupled Modelling Intercomparison Project Phase 6 (CMIP6). The resulting LULCC maps can be applied as land use forcing to the next generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions world-wide.

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