Sub-pixel Area Calculation Methods for Estimating Irrigated Areas.
Sub-pixel Area Calculation Methods for Estimating Irrigated Areas.
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DOI：
10.3390/s7112519
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发表时间：
2007-10-31
期刊：
影响因子：
--
通讯作者：
Pandey S
中科院分区：
文献类型：
--
作者：
Thenkabailc PS;Biradar CM;Noojipady P;Cai X;Dheeravath V;Li Y;Velpuri M;Gumma M;Pandey S
本文的目标是开发并演示根据粗分辨率卫星传感器数据计算子像素区域 (SPA) 的实用方法。使用以下方法对这些方法进行了测试和验证：(a) 主要基于 AVHRR 数据的 10 公里分辨率的全球灌溉面积地图 (GIAM)，以及 (b) 主要基于 MODIS 数据的 500 米印度灌溉面积地图。通过将全像素灌溉面积 (FPIA) 乘以灌溉面积分数 (IAF) 来估计粗分辨率卫星传感器数据的亚像素灌溉面积 (SPIA)。提出了三种 IAF 计算方法：(a) Google Earth Estimate (IAF-GEE)； (b) 高分辨率图像（IAF-HRI）； (c) 子像素分解技术（IAF-SPDT）。 IAF-GEE 涉及使用 Google 地球中亚米级至 4 米超高分辨率图像 (VHRI) 的“放大视图”，并帮助确定可灌溉总面积 (TAAI) 或不考虑灌溉强度或季节性的净灌溉面积。 IAF-HRI 是一种众所周知的方法，它使用较高分辨率的数据来确定较粗分辨率图像的 SPA。 IAF-SPDT 是一种独特且创新的方法，其中 SPA 是根据红色波段与近红外波段光谱反射率的二维亮度-绿色-湿度 (BGW) 特征空间图中某类每个像素的精确位置来确定的。使用 GIAM 的 IAF-SPDT 计算出的 SPIA 与使用众所周知的 IAF-HRI 计算出的 SPIA 的误差在 2% 以内。此外，两种方法的分数显着相关。 IAF-HRI 和 IAF-SPDT 有助于确定考虑强度或季节性的年化灌溉面积或总灌溉面积 (AIA)（例如，第一季、第二季和连续全年作物的面积总和）。与使用 10 公里和 500 米数据得出的 FPIA 相比，SPIA 与 SPIA 相比，基于全国人口普查的前 40 个灌溉国家的灌溉面积（约占全球灌溉面积的 90%）的相关性明显更好（并且不确定性和误差更小）。 SPIA 更接近实际面积，而 FPIA 严重高估了面积。该研究清楚地证明了子像素区域相对于全像素区域的价值和重要性，并提出了 3 种创新的计算方法。
The goal of this paper was to develop and demonstrate practical methods for computing sub-pixel areas (SPAs) from coarse-resolution satellite sensor data. The methods were tested and verified using: (a) global irrigated area map (GIAM) at 10-km resolution based, primarily, on AVHRR data, and (b) irrigated area map for India at 500-m based, primarily, on MODIS data. The sub-pixel irrigated areas (SPIAs) from coarse-resolution satellite sensor data were estimated by multiplying the full pixel irrigated areas (FPIAs) with irrigated area fractions (IAFs). Three methods were presented for IAF computation: (a) Google Earth Estimate (IAF-GEE); (b) High resolution imagery (IAF-HRI); and (c) Sub-pixel de-composition technique (IAF-SPDT). The IAF-GEE involved the use of “zoom-in-views” of sub-meter to 4-meter very high resolution imagery (VHRI) from Google Earth and helped determine total area available for irrigation (TAAI) or net irrigated areas that does not consider intensity or seasonality of irrigation. The IAF-HRI is a well known method that uses finer-resolution data to determine SPAs of the coarser-resolution imagery. The IAF-SPDT is a unique and innovative method wherein SPAs are determined based on the precise location of every pixel of a class in 2-dimensional brightness-greenness-wetness (BGW) feature-space plot of red band versus near-infrared band spectral reflectivity. The SPIAs computed using IAF-SPDT for the GIAM was within 2 % of the SPIA computed using well known IAF-HRI. Further the fractions from the 2 methods were significantly correlated. The IAF-HRI and IAF-SPDT help to determine annualized or gross irrigated areas (AIA) that does consider intensity or seasonality (e.g., sum of areas from season 1, season 2, and continuous year-round crops). The national census based irrigated areas for the top 40 irrigated nations (which covers about 90% of global irrigation) was significantly better related (and had lesser uncertainties and errors) when compared to SPIAs than FPIAs derived using 10-km and 500-m data. The SPIAs were closer to actual areas whereas FPIAs grossly over-estimate areas. The research clearly demonstrated the value and the importance of sub-pixel areas as opposed to full pixel areas and presented 3 innovative methods for computing the same.
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