Recent developments of 30 m global land characterization datasets （e.g., land cover, vegetation continues field） represent the finest spatial resolution inputs for global scale studies. Here, we present results from...Recent developments of 30 m global land characterization datasets （e.g., land cover, vegetation continues field） represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover map- ping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC （Finer Resolution Observa- tion and Monitoring-Global Land Cover） and FROM-GLC-seg （Segmentation）, with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area （NL-ISA） and MODIS urban extent （MODIS-urban）, to produce an improved 30 m global land cover map-FROM-GLC-agg （Aggregation）. It was pos-processed using additional coarse res- olution datasets （i.e., MCD12Q1, GlobCover2009, MOD44W etc.） to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion ag- gregation approaches were employed to create a multi-resolution hierarchy （i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km） of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map （at 30 m） and the three maps subse- quently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required.展开更多
A technically transparent and freely available reference sample set for validation of global land cover mapping was recently established to assess the accuracies of land cover maps with multiple resolutions.This sampl...A technically transparent and freely available reference sample set for validation of global land cover mapping was recently established to assess the accuracies of land cover maps with multiple resolutions.This sample set can be used to estimate areas because of its equal-area hexagon-based sampling design.The capabilities of these sample set-based area estimates for cropland were investigated in this paper.A 30-m cropland map for China was consolidated using three thematic maps(cropland,forest and wetland maps)to reduce confusion between cropland and forest/wetland.We compared three area estimation methods using the sample set and the 30 m cropland map.The methods investigated were:(1)pixel counting from a complete coverage map,(2)direct estimation from reference samples,and(3)model-assisted estimation combining the map with samples.Our results indicated that all three methods produced generally consistent estimates which agreed with cropland area measured from an independent national land use dataset.Areas estimated from the reference sample set were less biased by comparing with a National Land Use Dataset of China(NLUD-C).This study indicates that the reference sample set can be used as an alternative source to estimate areas over large regions.展开更多
基金supported by the National High-tech R&D Program of China(Grant No.2009AA12200101)the National Natural Science Foundation of China(Grant No.41301445)+1 种基金an Open Fund from the State Key Laboratory of Remote Sensing Science(Grant No.OFSLRSS201202)a research grant from Tsinghua University(Grant No.2012Z02287)
文摘Recent developments of 30 m global land characterization datasets （e.g., land cover, vegetation continues field） represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover map- ping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC （Finer Resolution Observa- tion and Monitoring-Global Land Cover） and FROM-GLC-seg （Segmentation）, with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area （NL-ISA） and MODIS urban extent （MODIS-urban）, to produce an improved 30 m global land cover map-FROM-GLC-agg （Aggregation）. It was pos-processed using additional coarse res- olution datasets （i.e., MCD12Q1, GlobCover2009, MOD44W etc.） to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion ag- gregation approaches were employed to create a multi-resolution hierarchy （i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km） of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map （at 30 m） and the three maps subse- quently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required.
基金supported by the National Natural Science Foundation of China(Grant No.41301445)a research grant from Tsinghua University(Grant No.20151080351)
文摘A technically transparent and freely available reference sample set for validation of global land cover mapping was recently established to assess the accuracies of land cover maps with multiple resolutions.This sample set can be used to estimate areas because of its equal-area hexagon-based sampling design.The capabilities of these sample set-based area estimates for cropland were investigated in this paper.A 30-m cropland map for China was consolidated using three thematic maps(cropland,forest and wetland maps)to reduce confusion between cropland and forest/wetland.We compared three area estimation methods using the sample set and the 30 m cropland map.The methods investigated were:(1)pixel counting from a complete coverage map,(2)direct estimation from reference samples,and(3)model-assisted estimation combining the map with samples.Our results indicated that all three methods produced generally consistent estimates which agreed with cropland area measured from an independent national land use dataset.Areas estimated from the reference sample set were less biased by comparing with a National Land Use Dataset of China(NLUD-C).This study indicates that the reference sample set can be used as an alternative source to estimate areas over large regions.
