全球氣溫溫暖化加上都市中大量的人造鋪面所導致的都市熱島現象，已使得現今的都市之中變得越來越熱，而溫度越高又增加空調能源的使用加劇二氧化碳的排放，形成一個惡性的升溫循環。突破以往對於都市熱環境移動量測或採取單一中央氣象局溫度等溫濕度氣候量測方法，本研究架設高密度地面氣溫測量網(HiSAN, The application of a high-density street-level air temperature observation network)在台南市架設102個距離地面2米的溫度量測站，藉以得到實際都市之中的空氣溫度，且因量測網為長期的實測架設，所以本研究取得全年各102測站的各自空氣溫度及濕度藉以有更大量的數據探討都市之中的熱環境。將得到之數據採用環域分析法，計算以溫度測量站為中心之環域內的土地使用與土地覆蓋對熱環境所造成之影響，同時量化溫度測站周邊的發展狀況。
研究結果顯示，台南區域的都市熱環境會因為地理特徵及都市發展因子等兩種不同型態的因子所影響，且依照季節及時段的不同而有不同的影響。在地理特徵的部份，因為沿海城市全日的氣候狀況會強烈受到離海的距離的影響，導致日夜間熱島的影響變化的不同，在日間熱島區域會集中於內陸區域而到夜間則會變化至沿海區域；在都市發展因子的部分，都市中的道路及建築等不透水層不管在日間或是夜間皆是強烈影響都市升溫的主要原因，而對於植栽及水體等透水層則會因為日夜間的變化而有不同影響，在日間水體的降溫效果較植栽好，而夜間則是綠地的降溫效果較好。
依據上述分析之結果針對都市設計提出規劃建議，本研究依照使用目地之使用時段分為主要為日間使用和夜間使用的兩個部分，並針對空調耗用最大的夏季進行降溫調適策略的制定，在使用目地的使用時段若為日間使用時，在地理位置的選擇上可以以沿海區域為設置之考量，使氣候背景相較於內陸為較低溫之區域，因水體在日間的降溫效果較綠地好，在使用目地的周遭設置大面積的水域，即可創造出較低溫之使用目地；而在夜間的住宅等使用在規劃的建議上，在地理位置則會建議設置於較內陸的區域，而在透水鋪面的設置則會建議使用以綠地為主水池為輔的規劃設計。

During the rapid urbanization process. The air temperature in urban area is increasing year by year. Owing to the different urban built environment will affect the micro climate, it is important to quantify urbanization level and thermal environment. Therefore, this study applies satellite image and urban basic map to get land use and land cover. And utilized the High density street-level air temperature observation network (HiSAN) to solving the issue mention above.
The result shows, the distance from the sea is a parameter that is important for temperature. There is higher temperature farther away from the sea in the day time but there is lower in the night time. Urban development factors will have different effects due to different times. In summer day, high ratio water area is the better way to cool down which can reduce 1 degree temperature. In summer night, high ratio green area is the better way to cool down. Therefore, the temperature prediction formula is set according to different seasons which is divided into four seasons and day and night. These formulas can predict the temperature of each place through the weather bureau data.

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