空載光達掃描(Airborne Laser Scanning)具有一定的穿透能力，因此被廣泛運用在獲取地形資訊上，所蒐集到之點雲透過處理後可分類出僅含地表面資訊之地面點，並通過對地面點進行插值來計算數值高程模型(Digital elevation model)，本研究選擇克利金方法來解決此問題，該方法考慮最佳線性無偏估計(Best Linear Unbiased Estimation)，也假設空間中的數據具有一定之相關性，其相關性與數據的空間分布及距離有關，不過目前使用者們大多只關注克利金估計值的成果，也就是以內插產製之數值高程模型，但事實上克利金方法還有另一個輸出成果，克利金變異數，可量化克利金估計值的準確性，藉由此克利金變異數能夠解決空載光達DEM品質估計缺乏量化方式的問題。
本研究中隨機選擇了100筆台灣空載光達資料作為數據集，涵蓋了山區及丘陵地，且因隨機選擇，這100筆資料的地面植被覆蓋程度大不相同，地面點數量及分布也大相逕庭。因此在這些資料中建立了以10公尺為區間，從直徑10公尺到50公尺的圓形空洞，來模擬被植被覆蓋之區域，並測試克利金方法對點雲數據的適應性，而結果顯示，在搜尋了較多鄰近點或是空洞較小的情況，克利金變異數的數值會顯著下降，代表著納入更多數據進行計算使得克利金估計值的結果更為準確。而後，為了在加速運算時間與精度之間取得平衡而將點雲資料進行降取樣，使用均質化方法將點雲密度分別降成每個邊長為1公尺之網格至多含有5、4、3、2、1、0.5、0.25、0.1、0.05個觀測點之點雲資料，結果顯示，當密度降為每1平方公尺1點時，仍能與原始數據擁有相近的克利金變異數值。最後，將成果應用到實務情況，並同時以視覺化與量化的方式呈現，其結果與研究中的多項實驗擁有相同的數據呈現模式，因此證明本研究提出之理論有望於成為空載光達產製數值高程模型誤差準確性的品質評估指標。

Airborne laser scanning (ALS) is widely utilized to produce digital elevation models (DEM) owing to its capability to penetrate through tree canopies. DEM is derived from ALS data by interpolating ground points. Kriging is popular for interpolating ALS DEM. Although kriging is commonly used, few people pay attention to the fact that kriging can also output kriging variance which quantifies the accuracy of kriging estimation. Thus, it is reasonable to use kriging variance to quantify the accuracy of the interpolation procedure of ALS-DEM. In this study, we selected 100 Taiwan ALS dataset of mountainous and hilly terrains and create different sizes of voids to test the feasibility of kriging variance. As expected, smaller voids and more ground points resulted in lower value of kriging variance. The decrease in kriging variance becomes less pronounced as more and more points are included. Next, to accelerate the calculating progress, we test on downsample point cloud data into small sizes. Using homogenization to decrease the density from 5 points per square meter gradually decreased to 0.05 points per square meter. The results showed that when we use 1 or even fewer point in per square meter, it can also achieve similar accuracy compared to the original data. Furthermore, we applied the findings from our study to real-world examples, demonstrating the practical applicability of our tested results. This suggests that our study has implications for quantifying accuracy of interpolation procedure of ALS-DEM).

郭麟霂，多時序光達成果資料品質比較，內政部105年度空間測繪應用計畫成果發表會暨移動製圖技術防救災應用論壇，(2016)
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