Estimation of rice grain yield from dual-polarization Radarsat-2 SAR data by integrating a rice canopy scattering model and a genetic algorithm

Fast and accurate estimation of rice yield plays a role in forecasting rice productivity for ensuring regional or national food security. Microwave synthetic aperture radar (SAR) data has been proved to have a great potential for rice monitoring and parameters retrieval. In this study, a rice canopy scattering model (RCSM) was revised and then was applied to simulate the backscatter of rice canopy. The combination of RCSM and genetic algorithm (GA) was proposed for retrieving two important rice parameters relating to grain yield, ear length and ear number density, from a C-band, dual-polarization (HH and HV) Radarsat-2 SAR data. The stability of retrieved results of GA inversion was also evaluated by changing various parameter configurations.Results show that RCSM can effectively simulate backscattering coefficients of rice canopy at HH and HV mode with an error of <1 dB. Reasonable selection of GA’s parameters is essential for stability and efficiency of rice parameter retrieval. Two rice parameters are retrieved by the proposed RCSM-GA technology with better accuracy. The rice ear length are estimated with error of <1.5 cm, and ear number density with error of <23 #/m². Rice grain yields are effectively estimated and mapped by the retrieved ear length and number density via a simple yield regression equation. This study further illustrates the capability of C-band Radarsat-2 SAR data on retrieval of rice ear parameters and the practicability of radar remote sensing technology for operational yield estimation.     

水稻遥感动力估产模拟初探

将遥感手段和动力估产模型相结合，即通过ＮＯＡＡ卫星获得有效绿度模式；通过绿度－叶面积关系式，估算水稻群体叶面积指数；依据水稻生物量分配规律及环境条件对其影响，估算水稻各器官的干重，取得了较好的模拟效果。     

气候变暖对中国水稻生产可能影响的研究

利用随机天气模型,将大气环流模式预测的气候情景与水稻模式相链接,研究了气候变暖对中国水稻生产的可能影响。结果表明,大气中ＣＯ２浓度加倍,中国水稻主产区适宜水稻生长的日数将延长６～１１ｄ,积温增加２２０～３３０℃·ｄ。积温的相对增长率由南向北呈增长趋势。水稻产量形成期低温天气出现频率将减少,而高温天气出现的频率增加。若品种与播种、移栽期不变,水稻产量将下降;而若通过改变品种使作物生育期基本保持目前的状况,减产幅度将比品种不变时明显偏小,部分地区还有可能增产。     

水稻冠层光谱反射特性的动态变化研究

通过对早稻整个生长期内冠层反射光谱特性动态变化的系统研究表明:①在整个水稻生长期内,水稻冠层反射光谱的比值植被指数(RVI)值呈有规律的变化,在抽穗前,随移栽后天数增加,RVI值也逐渐增大,至抽穗前达到最大值;而抽穗后,则随着移栽后天数的增加,RVI值逐渐下降,至收割前降至最低值;②积温与RVI之间存在着较密切的关系,通过对不同生育期积温与RVI之间进行的线性回归分析表明,在抽穗前,积温与RVI值之间呈极显著正相关;而抽穗后,积温与RVI之间呈极显著的负相关。在遥感估产中,这种水稻冠层反射光谱特性的变化对于校正生育期的估产偏差和提高估产精度可能有重要意义。     

广东省水稻旱灾的评价及防旱抗旱对策

根据广东省水稻旱灾实况，提出了水稻旱情和干旱灾情没的评价指标，分析了广东省解放后历年旱，晚稻旱情和灾情及分布和变化规律，并针对本省的自然条件和灌溉现状提出了防旱抗旱措施。     

贵州省水稻实时农业气候综合评价方法研究

利用1979～1991年贵州水稻气象与物候观测等资料和数理统计分析方法，研究了水稻实时农业气候综合评价方法。应用该方法对贵州省水稻产量年景进行了验证，结果表明该方法对水稻生产具有较高的实用价值。     

水稻障碍型冷害损失评估及预测动态模型研究

在分析东北水稻生殖生长关键期低温生理反应的基础上,建立了计算日冷积温(时积温)及其与空壳率关系的模式和敏感期内每日水稻敏感群体数量比率分布标准化模式,进而建立了水稻在生殖生长关键期内因低温影响而导致空壳率及减产率评估、预测模式。该模式可较精确地计算出逐日低温导致的空壳率及减产率,可比成熟期提前25 d左右进行冷害评估和损失预测。     

The CERES‐Rice Model‐Based Estimates of Potential Monsoon Season Rainfed Rice Productivity in Bangladesh*

Agricultural practices in Bangladesh are largely dependent on the monsoonal rainfall. Historically, Bangladesh often experiences severe droughts and floods during the monsoon months, with significant crop losses during both extreme conditions. This article provides a quantitative assessment of potential monsoon‐season aman rice for four transplanting dates: 1 June, 1 July, 15 July, and 15 August. A crop‐growth simulation model, the CERES‐Rice, is applied to sixteen locations representing major rice‐growing regions of Bangladesh to determine baseline yield estimates for four transplanting dates. The applications were conducted for 1975 through 1987. Average potential yield in Bangladesh is 6,907, 5,039, 3,637, and 1,762 kg ha^?1 for the above transplanting dates, respectively. In other words, Bangladesh would obtain 27 percent, 48 percent, and 75 percent less yield for 1 July, 15 July, and 15 August transplanting, respectively, than for 1 June transplanting. Potential yield vulnerability is the least for 1 June transplanting (up to 5 percent) and the highest (up to 66 percent) for 15 July transplanting date. The model applications show that regional variations exist for potential yield and yield vulnerability for a particular transplanting date. In addition, response of yield and vulnerability for a region changes with transplanting dates.     

Analysing spatial–temporal changes in rice cultivation practices in the Senegal River Valley using MODIS time-series and the PhenoRice algorithm

In this study we used the PhenoRice algorithm to track recent variations of rice cultivation practices along the Senegal River Valley. Time series of MODIS imagery with 250 m spatial resolution and a nominal 8-days frequency were used as input for the algorithm to map the spatial and temporal variations of rice cultivated area and of several important phenological metrics (e.g., crop establishment and harvesting dates, length of season) for the 2003–2016 period in both the dry and the wet rice cultivation seasons. Comparison between PhenoRice results and ancillary and field data available for the Senegal part of the study area showed that the algorithm is able to track the interannual variations of rice cultivated area, despite the total detected rice area being consistently underestimated. PhenoRice estimates of crop establishment and harvesting dates resulted accurate when compared with field observations available for two sub-regions for a period of 10 years, and thus allow assessing interannual variability and tracking changes in agronomic practices. An analysis of interannual trends of rice growing practices based on PhenoRice results highlighted a clear shift of rice cultivation from the wet to the dry season starting approximately from 2008. The shift was found to be particularly evident in the delta part of the SRV. Additionally, a statistically significant trend was revealed starting 2006 towards a longer dry season (r² = 0.81; Slope = 1.24 days y⁻¹) and a shorter wet season (r² = 0.65; Slope = 0.53 days y⁻¹). These findings are in agreement with expert knowledge of changes ongoing in the area. In particular the shorter wet season is attributed to shortage of labor and equipment leading to a delay in completion of harvesting operations in the dry season, which led to the adoption of short-duration rice varieties by farmers in the wet season to avoid risk of yield losses due to climatic constraints. Aforementioned results highlight the usefulness of the PhenoRice algorithm for providing insights about recent variations in rice cultivation practices over large areas in developing countries, where high-quality up to date information about changes in agricultural practices are often lacking.     

南方丘陵地区水稻种植面积遥感信息提取的试验

以浙江省为试验区, 针对水稻种植面积遥感信息提取的业务化运行问题, 进行了以下试验:(1) 以传统的单象元统计分类识别方法为分类器, 在地理信息系统支持下, 提取丘陵地区大范围水稻种植面积信息的可行性; (2) 在遥感资料的基础上, 结合地形数据综合提取水稻种植面积专题信息的可行性和有效性; (3) 混合象元分解方法在丘陵地区的有效性和适用性.结果表明, 用最大似然法提取大范围水稻种植面积信息的精度可满足业务化运行的要求; 模糊监督分类有较高的分类精度和较好的稳定性, 具有较强的适应性; 坡度数据作为遥感影像分类的辅助数据层, 可以有效地提高丘陵地区水稻种植面积信息的提取精度, 还可以提高分类的稳定性和空间位置精度.