It is well known that land cover errors are typically spatially and temporally auto-correlated and can have a distinct spatial distribution. There may be serious consequences in land cover change analysis when the pattern and degree of spatial variation of change accuracy is not understood. This paper explores accuracy measures extracted from the transition matrices for a rural and urban setting. Intensity analysis is used to describe the minimum hypothetical error in imperfect land cover change maps at landscape level. Total land cover change is partitioned into quantity, exchange and shift disagreement based on size and intensity. Multiple resolution analysis quantifies the distances over which exchange and shift disagreement can be measured. Local, geographically weighted transition matrices are constructed to generate spatially explicit measures of change and error. The rural study area exhibited 21% change for each of two transition periods with hypothetical map error from gains (losses) amounting to 9% (5%) for the first and 8% (5%) for the second transition. Thirty two percent change was measured over a single transition in the urban setting. Hypothetical error from gain and loss was found to be 15% and 12% respectively. Allocation disagreement, based on the sum of exchange and shift components, comprised more than 50% of the measured change, predominantly due to high gain commission and omission errors involving a large dormant class. Spatially explicit allocation disagreement from the urban geographically weighted change budget modelled 18% allocation disagreement with probability higher than 0.6, in agreement with the global figure of 20%. Local disagreement in the rural catchment with a probability of greater than 0.6 agreed with the global statistics derived. Local allocation disagreement with a probability of 0.9 and higher only occurred in 1% of the study areas. It was found that at coarser resolutions, quantity disagreement provides the total change in the landscape. The study highlights the potential of local transition measures to complement global statistics extracted from the transition matrix in determining allocation as well as map error in land cover maps.

众所周知，土地覆盖误差通常在空间和时间上是自动相关的，并且可以具有独特的空间分布。如果不了解变化精度的空间变化的模式和程度，则可能会对土地覆被变化分析产生严重的影响。本文探讨了从农村和城市环境的过渡矩阵中提取的准确性测度。强度分析用于描述景观水平不完善的土地覆被变化图中的最小假设误差。土地总覆盖变化根据数量和强度分为数量，交换和转移分歧。多分辨率分析量化了可以测量交换和换档分歧的距离。本地，构建地理加权的转换矩阵以生成空间明晰的变化和误差度量。农村研究区在两个过渡期中的每一个都表现出21％的变化，其中收益的假设地图误差（损失），第一笔损失为9％（5％），第一笔损失为8％（5％））进行第二次转换。在城市环境中的一次过渡中测得32％的变化。发现来自收益和损失的假设误差分别为15％和12％。基于交换和班次总和的分配分歧占所测变化的50％以上，主要是由于涉及大量休眠类别的高收益佣金和遗漏错误。与城市地理加权变更预算中的空间显式分配差异模型化，以18％的分配差异为模型，概率高于0.6，与20％的全球数字一致。农村地区流域的局部分歧可能大于0.6，这与导出的全球统计数据一致。仅在研究区域的1％中发生了0.9或更高概率的本地分配分歧。人们发现，在较粗的分辨率下，数量上的分歧提供了景观的总体变化。这项研究强调了地方过渡措施的潜力，可以补充从过渡矩阵中提取的全球统计数据，从而确定土地覆被图中的分配以及地图误差。