Combining Accuracy Assessment of Land-Cover Maps With Environmental Monitoring Programs

Many investigators use global land cover (GLC) maps for different purposes, such as an input for global climate models. The current GLC maps used for such purposes are based on different remote sensing data, methodologies and legends. Consequently, comparison of GLC maps is difficult and information about their relative utility is limited. The objective of this study is to analyse and compare the thematic accuracies of GLC maps (i.e., IGBP-DISCover, UMD, MODIS, GLC2000 and SYNMAP) at 1 km resolutions by (a) re-analysing the GLC2000 reference dataset, (b) applying a generalized GLC legend and (c) comparing their thematic accuracies at different homogeneity levels. The accuracy assessment was based on the GLC2000 reference dataset with 1253 samples that were visually interpreted. The legends of the GLC maps and the reference datasets were harmonized into 11 general land cover classes. There results show that the map accuracy estimates vary up to 10-16% depending on the homogeneity of the reference point (HRP) for all the GLC maps. An increase of the HRP resulted in higher overall accuracies but reduced accuracy confidence for the GLC maps due to less number of accountable samples. The overall accuracy of the SYNMAP was the highest at any HRP level followed by the GLC2000. The overall accuracies of the maps also varied by up to 10% depending on the definition of agreement between the reference and map categories in heterogeneous landscape. A careful consideration of heterogeneous landscape is therefore recommended for future accuracy assessments of land cover maps.

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Assessing the impacts of human uncertainty in the accuracy assessment of land-cover maps using linguistic scales and fuzzy intervals

International Journal of Remote Sensing ◽

10.1080/01431161.2015.1043034 ◽

2015 ◽

Vol 36 (10) ◽

pp. 2524-2547 ◽

Cited By ~ 1

Author(s):

Pedro Sarmento ◽

Cidália C. Fonte ◽

Joel Dinis ◽

Stephen V. Stehman ◽

Mário Caetano

Keyword(s):

Land Cover ◽

Accuracy Assessment ◽

Land Cover Maps

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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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AREA ESTIMATION OF MULTI-TEMPORAL GLOBAL IMPERVIOUS LAND COVER BASED ON STRATIFIED RANDOM SAMPLING

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

10.5194/isprs-archives-xliii-b4-2020-103-2020 ◽

2020 ◽

Vol XLIII-B4-2020 ◽

pp. 103-108

Author(s):

Y. Gong ◽

H. Xie ◽

X. Tong ◽

Y. Jin ◽

X. Xv ◽

...

Keyword(s):

Land Cover ◽

Random Sampling ◽

Accuracy Assessment ◽

Time Interval ◽

Stratified Random Sampling ◽

Regional Environment ◽

Area Estimation ◽

Research On Evaluation ◽

Multi Temporal ◽

Land Cover Maps

Abstract. Estimating area of impervious land cover is the most useful and one of the ecological assessment indexes of urban and regional environment. Global land cover maps are inevitably misclassified, which affects the quality and application of the data. Statistical approach for assessing the accuracy is critical to understand the global change information and area estimation is usually based on sample data with a probability-based estimator. However, research on evaluation of multi-temporal global impervious land cover maps has not been implemented. In this study, spatial characteristics of the data are considered to assess the thematic map accuracy with a two-stage stratified random sampling plan. The first stage of stratification is determined by the global urban ecoregion and the second one is determined by land cover classes. Additionally, sample size of both map stage and pixel stage are calculated using a probability sampling model. A response design is constructed for a per-pixel accuracy assessment and blind interpretation is implemented using sample pixels and its surrounding area. Our method is applied to the multi-temporal global impervious land cover maps between 2000 and 2010 with a time interval of 5 years and the estimated area in different epoch are listed in detail. The main contribution of our research is illustrating the details for calculating the proportion area of impervious land cover and corresponding confidence intervals based on the reference classification. The experimental results show that the increasing area of the impervious surface according to the sample unit shows good agreement with the urbanization and descriptive accuracy assessments by user’s, producer’s and overall accuracy are shown respectively.

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A note on procedures used for accuracy assessment in land cover maps derived from AVHRR data

International Journal of Remote Sensing ◽

10.1080/014311600210434 ◽

2000 ◽

Vol 21 (5) ◽

pp. 1073-1077 ◽

Cited By ~ 69

Author(s):

M. A. Friedl ◽

C. Woodcock ◽

S. Gopal ◽

D. Muchoney ◽

A. H. Strahler ◽

...

Keyword(s):

Land Cover ◽

Accuracy Assessment ◽

Avhrr Data ◽

Land Cover Maps

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EXTENDING ACCURACY ASSESSMENT PROCEDURES OF GLOBAL COVERAGE LAND COVER MAPS THROUGH SPATIAL ASSOCIATION ANALYSIS

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

10.5194/isprs-archives-xlii-2-w13-1601-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 1601-1607

Author(s):

D. Oxoli ◽

G. Bratic ◽

H. Wu ◽

M. A. Brovelli

Keyword(s):

Land Cover ◽

Spatial Patterns ◽

Accuracy Assessment ◽

Confusion Matrix ◽

Spatial Association ◽

Visual Exploration ◽

Assessment Procedure ◽

Lombardy Region ◽

Land Cover Map ◽

Land Cover Maps

<p><strong>Abstract.</strong> High-resolution land cover maps are in high demand for many environmental applications. Yet, the information they provide is uncertain unless the accuracy of these maps is known. Therefore, accuracy assessment should be an integral part of land cover map production as a way of ensuring reliable products. The traditional accuracy metrics like Overall Accuracy and Producer’s and User’s accuracies &ndash; based on the confusion matrix &ndash; are useful to understand global accuracy of the map, but they do not provide insight into the possible nature or source of the errors. The idea behind this work is to complement traditional accuracy metrics with the analysis of error spatial patterns. The aim is to discover errors underlying features which can be later employed to improve the traditional accuracy assessment. The designed procedure is applied to the accuracy assessment of the GlobeLand30 global land cover map for the Lombardy Region (Northern Italy) by means of comparison with the DUSAF regional land cover map. Traditional accuracy assessment quantified the classification accuracies of the map. Indeed, critical errors were pointed out and further analyses on their spatial patterns were performed by means of the Moran’s I indicator. Additionally, visual exploration of the spatial patterns was performed. This allowed describing possible sources of errors. Both software and analysis strategies were described in detail to facilitate future improvement and replication of the procedure. The results of the exploratory experiments are critically discussed in relation to the benefits that they potentially introduce into the traditional accuracy assessment procedure.</p>

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