Question

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For daytime analysis, daytime surface temperature distribution across different land use types was studied through comparison of land usage with the Singapore thermal satellite image taken by Landsat 7 ETM+ thermal band on 11 October 2002 at 11.09AM. The thermal image has nine spectral bands, as shown in Fig. 2.
The eighth band is a 15 m resolution panchromatic image, and bands 1–5 and 7 contain 30 m resolution within the visible and infrared spectrum. Band six consists out of a low and high gain 60 m resolution thermal band (8–12 mm). An approximate surface temperature could be extracted from the later. The extraction of the temperature data from the high-gain band was used as it had a less stripped texture and a wider range of recorded values digital number (DN) values. The technique developed by the Landsat Scientific team (2006) was chosen for the conversion. With the image processing software ENVI, the thermal image ‘‘L71125059_05920021011_B62’’, which is the high-gain band six of the Landsat 7 ETM+ data, calculations on each pixel were performed.
The Master Plan 2003 land use map was used to extract the land use in a supervised classification. This was done by a supervised Mahalanobis Distance classification, followed by a majority/minority analysis to clean up the data—furthermore, the data underwent several clumped and sieved processes. Only the seven major land use types were then further analyzed with the thermal image. Other land use types were either to small or were due to contextual reasons cannot be processed, e.g. military areas have dense jungle as well as airfields and buildings.
A green, red, and near infrared (NIR) band of a 20 m resolution SPOT image of Singapore was used to classify either human built structures (roads, airports, buildings) or vegetation (parks, natural grass sport fields, jungle).

For night time analysis, two methods were used to analyse the night time ambient temperature distribution across different land use types. Firstly, the land use map was prepared from Master Plan 2003 using the polygon in ArcMap. Then night time ambient temperature data were plotted in point form from the study of Wong (2004) using ArcMap. Descriptive summary and 3D graph representation of night time ambient temperature were generated using ArcMap and ArcScene after over lapping land use and temperature map.

Answer 1

白天分析，白天表面温度分布在不同的土地利用类型进行了研究，通过比较，土地使用与新加坡热卫星图像采取的Landsat 7号卫星ETM +热带2002年10月11在上午11时09分。热图像9谱带所示，图。 2 。

第八届带15米的分辨率全色图像，并带1月5日和7号决议包含30米内的可见光和红外光谱。六级组成了一个低和高增益60米决议热波段（ 8-12毫米） 。近似表面温度可提取的更新。提取的温度数据从高增益波段，因为它使用了较少剥夺纹理和更广泛的记录值的数字号码（ DN ）的价值。这项技术开发的大地的科研团队（ 2006年）被选定为转换。随着图像处理软件环境，该热像'' L71125059_05920021011_B62 '' ，这是高增益带六个Landsat 7号卫星ETM +数据，计算每个像素进行。

总体规划2003年的土地使用地图被用来提取的土地利用监督分类。这是由一个监督马氏距离分类，其次是多数/少数分析清理数据此外，经历了几个成群数据和筛选过程。只有七个主要土地利用类型，然后进一步分析了热成像。其他土地利用类型或者小或者是由于内容原因无法处理，例如：军事领域的丛林，以及机场和建筑物。

绿色，红色和近红外（近红外）带了20米的分辨率SPOT卫星影像的新加坡是用来区分不是人类建造结构（公路，机场，建筑物）或植被（公园，体育领域的天然草地，丛林） 。

夜的时间分析，两种方法用于分析夜间环境温度分布在不同的土地利用类型。首先，土地使用地图准备从2003年总计划中使用的多边形ArcMap 。然后夜间环境温度数据，绘制表格，点的研究黄（ 2004 ）利用ArcMap 。概要叙述和三维图形的代表性夜间环境温度生成使用ArcMap和ArcScene经过研磨土地使用和温度图。