Characterizing Global Land Cover Type and Seasonal Land Cover Dynamics at Moderate Spatial Resolution With MODIS Data

AbstractGlobal land cover data are widely used in weather, climate, and hydrometeorological models. The Collection 5.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) product is found to have a substantial amount of interannual variability, with 40% of land pixels showing land cover change one or more times during 2001–10. This affects the global distribution of vegetation if any one year or many years of data are used, for example, to parameterize land processes in regional and global models. In this paper, a value-added global 0.5-km land cover climatology (a single representative map for 2001–10) is developed by weighting each land cover type by its corresponding confidence score for each year and using the highest-weighted land cover type in each pixel in the 2001–10 MODIS data. The climatology is validated by comparing it with the System for Terrestrial Ecosystem Parameterization database as well as additional pixels that are identified from the Google Earth proprietary software database. When compared with the data of any individual year, this climatology does not substantially alter the overall global frequencies of most land cover classes but does affect the global distribution of many land cover classes. In addition, it is validated as well as or better than the MODIS data for individual years. Also, it is based on higher-quality data and is validated better than the Global Land Cover Characteristics database, which is based on 1 year of Advanced Very High Resolution Radiometer data and represents a widely used first-generation global product.

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REVIEW OF HIGH-RESOLUTION GLOBAL LAND COVER

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b4-2021-175-2021 ◽

2021 ◽

Vol XLIII-B4-2021 ◽

pp. 175-182

Author(s):

G. Bratic ◽

A. Vavassori ◽

M. A. Brovelli

Keyword(s):

High Resolution ◽

Land Cover ◽

Spatial Resolution ◽

Accuracy Assessment ◽

General Information ◽

Tree Canopy ◽

Global Land Cover ◽

Tree Canopy Cover ◽

Global Land ◽

Land Cover Maps

Abstract. The land cover detection on our planet at high spatial resolution has a key role in many scientific and operational applications, such as climate modeling, natural resources management, biodiversity studies, urbanization analyses and spatial demography. Thanks to the progresses in Remote Sensing, accurate and high-resolution land cover maps have been developed over the last years, aiming at detecting the spatial resolution of different types of surfaces. In this paper we propose a review of the high-resolution global land cover products developed through Earth Observation technologies. A series of general information regarding imagery and data used to produce the map, the procedures employed for the map development and for the map accuracy assessment have been provided for every dataset. The land cover maps described in this paper concern the global distribution of settlements (Global Urban Footprint, Global Human Settlement Built-Up, World Settlement Footprint), water (Global Surface Water), forests (Forest/Non-forest, Tree canopy cover), and a two land cover maps describing world in 10 generic classes (GlobeLand30 and Finer Resolution Observation and Monitoring of Global Land Cover). The advantages and shortcomings of these maps and of the methods employed to produce them are summarized and compared in the conclusions.

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Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada

Remote Sensing ◽

10.3390/rs11192286 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2286

Author(s):

Libo Wang ◽

Paul Bartlett ◽

Darren Pouliot ◽

Ed Chan ◽

Céline Lamarche ◽

...

Keyword(s):

Land Cover ◽

Spatial Resolution ◽

Land Surface ◽

Forest Cover ◽

Reference Sample ◽

Tree Cover ◽

Initial Surface ◽

Forest Cover Change ◽

Global Land Cover ◽

Global Land

Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated. This study assesses the applicability of the Climate Change Initiative (CCI) LC product for use in the Canadian Land Surface Scheme (CLASS) through comparison with finer resolution datasets over Canada, assisted with reference sample data and a vegetation continuous field tree cover fraction dataset. The results show that in comparison with the finer resolution maps over Canada, the 300 m CCI product provides much improved LC distribution over that from the 1 km GLC2000 dataset currently used to provide initial surface conditions in CLASS. However, the CCI dataset appears to overestimate needleleaf forest cover especially in the taiga-tundra transition zone of northwestern Canada. This may have partly resulted from limited availability of clear sky MEdium Resolution Imaging Spectrometer (MERIS) images used to generate the CCI classification maps due to the long snow cover season in Canada. In addition, changes based on the CCI time series are not always consistent with those from the MODIS or a Landsat-based forest cover change dataset, especially prior to 2003 when only coarse spatial resolution satellite data were available for change detection in the CCI product. It will be helpful for application in global simulations to determine whether these results also apply to other regions with similar landscapes, such as Eurasia. Nevertheless, the detailed LC classes and finer spatial resolution in the CCI dataset provide an improved reference map for use in land surface models in Canada. The results also suggest that uncertainties in the current cross-walking tables are a major source of the often large differences in the plant functional types (PFT) maps, and should be an area of focus in future work.

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Recent global land cover dynamics and implications for soil erosion and carbon losses from deforestation

Anthropocene ◽

10.1016/j.ancene.2021.100291 ◽

2021 ◽

pp. 100291

Author(s):

Xiangping Hu ◽

Jan Sandstad Næss ◽

Cristina Maria Iordan ◽

Bo Huang ◽

Wenwu Zhao ◽

...

Keyword(s):

Soil Erosion ◽

Land Cover ◽

Global Land Cover ◽

Land Cover Dynamics ◽

Global Land ◽

Carbon Losses

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Effective UV surface albedo of seasonally snow-covered lands

Atmospheric Chemistry and Physics ◽

10.5194/acp-7-2759-2007 ◽

2007 ◽

Vol 7 (10) ◽

pp. 2759-2764 ◽

Cited By ~ 20

Author(s):

A. Tanskanen ◽

T. Manninen

Keyword(s):

Land Cover ◽

Snow Cover ◽

Surface Albedo ◽

Land Cover Type ◽

University Of Maryland ◽

Cover Type ◽

Global Land Cover ◽

Reflectivity Data ◽

The University ◽

Classification Product

Abstract. At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.

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Effective UV surface albedo of seasonally snow-covered lands

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-7-2873-2007 ◽

2007 ◽

Vol 7 (1) ◽

pp. 2873-2891

Author(s):

A. Tanskanen ◽

T. Manninen

Keyword(s):

Land Cover ◽

Snow Cover ◽

Surface Albedo ◽

Land Cover Type ◽

University Of Maryland ◽

Cover Type ◽

Global Land Cover ◽

Reflectivity Data ◽

The University ◽

Classification Product

Abstract. At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.

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