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1.
Spatial differences in drought proneness and intensity of drought caused by differences in cropping patterns and crop growing environments within a district indicate the need for agricultural drought assessment at disaggregated level. The objective of this study is to use moderate resolution satellite images for detailed assessment of the agricultural drought situation at different administrative units (blocks) within a district. Monthly time composite NDVI images derived from moderate resolution AWiFS (60 m) and WiFS (180 m) images from Indian Remote Sensing satellites were analysed along with ground data on rainfall and crop sown areas for the kharif seasons (June – November) of 2002 (drought year), 2004 (early season drought) and 2005 (good monsoon year). The impact of the 2002 meteorological drought on crop area in different blocks of the district was assessed. The amplitude of crop condition variability in a severe drought year (2002) and a good year (2005) was used to map the degree of vulnerability of different blocks in the district to agricultural drought. The impact of early season deficit rainfall in 2004 on the agricultural situation and subsequent recovery of the agricultural situation was clearly shown. Agricultural drought assessment at disaggregated level using moderate resolution images is useful for prioritizing the problem areas within a district to undertake, in season drought management plans, such as alternate cropping strategies, as well as for end of the season drought relief management actions. The availability of ground data on rainfall, cropping pattern, crop calendar, irrigation, soil type etc., is very crucial in order to interpret the seasonal NDVI patterns at disaggregated level for drought assessment. The SWIR band of AWiFS sensor is a potential data source for assessing surface drought at the beginning of the season. 相似文献
2.
土壤湿度信息遥感研究 总被引：3，自引：0，他引：3
土壤湿度是农业生产与应用过程中非常重要的因素,决定农作物的水分供应状况.本文利用MODIS产品数据获取的归一化植被指数(NDVI)和陆面地表温度(Ts)构建Ts-NDVI特征空间,根据温度植被干旱指数(TVDI)的研究原理与方法,对研究区2010年5～8月份土壤湿度分布情况进行遥感监测.结合气象数据与土壤墒情资料对局部... 相似文献
3.
Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area. 相似文献
4.
Comparison of three remotely sensed drought indices for assessing the impact of drought on winter wheat yield 总被引：1，自引：0，他引：1
Jianxi Huang Wen Zhuo Ran Huang Fernando Sedano Wei Su 《International Journal of Digital Earth》2020,13(4):504-526
ABSTRACTAgricultural drought threatens food security. Numerous remote-sensing drought indices have been developed, but their different principles, assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas. Here, we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces, northern China (predominantly rain-fed and irrigated agriculture, respectively): vegetation health index (VHI), temperature vegetation dryness index (TVDI) and drought severity index (DSI). We compared the agreement between these indices and the standardized precipitation index (SPI), soil moisture, winter wheat yield and National Meteorological Drought Monitoring (NMDM) maps. On average, DSI outperformed the other indices, with stronger correlations with SPI and soil moisture. DSI also corresponded better with soil moisture and NMDM maps. The jointing and grain-filling stages of winter wheat are more sensitive to water stress, indicating that winter wheat required more water during these stages. Moreover, the correlations between the drought indices and SPI, soil moisture, and winter wheat yield were generally stronger in Shaanxi province than in Henan province, suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas. 相似文献
5.
基于植被指数和地表温度特征空间的农业干旱监测模型研究综述 总被引：2，自引：0，他引：2
遥感技术是监测区域农业旱情时空变化的主要手段，其反演的植被指数(NDVI)和地表温度(Ts)两个参数可以通过表征绿色植被对干旱胁迫生境的反应揭示土壤水分信息，反映作物受旱状况，但两者单独使用时均存在局限性。而基于植被指数和地表温度的二维特征空间综合了两个参数特有的生理生态意义，不仅可以指示作物受旱时的水热胁迫环境，同时揭示了作物在这种胁迫环境下表现出的症状，可有效提高农业干旱监测的精度和效率。本文在较为详细地阐述植被指数-地表温度特征空间评估农业旱情的原理基础上，综述了这方面有代表性的4个干旱监测模型，初步分析了影响这类模型特征空间的部分非土壤水分因子，并对它们在应用中的优缺点做了评述和总结，为今后此领域研究中需要关注的问题做了展望。 相似文献
6.
This paper reports acreage, yield and production forecasting of wheat crop using remote sensing and agrometeorological data for the 1998–99 rabi season. Wheat crop identification and discrimination using Indian Remote Sensing (IRS) ID LISS III satellite data was carried out by supervised maximum likelihood classification. Three types of wheat crop viz. wheat-1 (high vigour-normal sown), wheat-2 (moderate vigour-late sown) and wheat-3 (low vigour-very late sown) have been identified and discriminated from each other. Before final classification of satellite data spectral separability between classes were evaluated. For yield prediction of wheat crop spectral vegetation indices (RVI and NDVI), agrometeorological parameters (ETmax and TD) and historical crop yield (actual yield) trend analysis based linear and multiple linear regression models were developed. The estimated wheat crop area was 75928.0 ha. for the year 1998–99, which sowed ?2.59% underestimation with land record commissioners estimates. The yield prediction through vegetation index based and vegetation index with agrometeorological indices based models were 1753 kg/ha and 1754 kg/ha, respectively and have shown relative deviation of 0.17% and 0.22%, the production estimates from above models when compared with observed production show relative deviation of ?2.4% and ?2.3% underestimations, respectively. 相似文献
7.
中国农情遥感速报系统 总被引：49，自引：3，他引：49
介绍了中国农情遥感速报系统的建设情况 ,系统内容包括农作物长势监测、农作物种植面积监测、农作物单产预测与粮食产量估算、作物时空结构监测和粮食供需平衡预警等。简要介绍了 1998年以来中国农情遥感速报系统在监测内容与监测范围、监测频率、技术发展以及质量控制与过程检验体系建立等方面的进展 ,并就中国农情遥感速报系统的发展方向提出了展望。 相似文献
8.
微波植被指数在干旱监测中的应用 总被引：3，自引：0，他引：3
在植被覆盖区域,归一化植被指数(NDVI)被广泛地应用于干旱遥感监测。和基于光学遥感的植被指数相比,Shi等提出的微波植被指数MVI(Microwave Vegetation Index)被证实能够反映更多的植被生长信息。本文以MVI为基础,利用MVI代替目前比较成熟的温度植被指数TVDI(Temperature Vegetation Index)中的NDVI,构建温度微波植被干旱指数TMVDI(Temperature Microwave Vegetation Index),发展了一种新的干旱监测方法。本文以2006年夏季四川省发生的百年难遇的干旱为研究对象,将基于TMVDI与TVDI的干旱监测结果进行了对比分析。最后,为评估监测结果的准确性,将遥感监测的结果与基于气象站点降雨观测数据构建的标准降雨指数SPI(Standardized Precipitation Index)的计算结果进行了对比分析。结果表明,利用低频降轨微波辐射计数据计算的T MVDI最适合于进行植被覆盖区域的干旱监测。 相似文献
9.
《地理信息系统科学与遥感》2013,50(3):183-190
Many remote sensing applications are predicated on the fact that there is a known relationship between climate and vegetation dynamics as monitored from space. However, few studies investigate vegetation index variation on individual homogeneous land cover units as they relate to specific climate and environmental influences at the local scale. This study focuses on the relationship between the Palmer Drought Severity Index (PDSI) and different vegetation types through the derivation of vegetation indices from Landsat 7 ETM+ data (NDVI, Tasseled Cap, and SAVI). A series of closely spaced through time images from 1999 to 2002 were selected, classified, and analyzed for an area in northeastern Ohio. Supervised classification of the images allowed us to monitor the response in individual land cover classes to changing climate conditions, and compare these individual changes to those over the entire larger areas. Specifically, the images were compared using linear regression techniques at various time lags to PDSI values for these areas collected by NOAA. Although NDVI is a robust indicator of vegetation greenness and vigor, it may not be the best index to use, depending on the type of vegetation studied and the scale of analysis used. A combination of NDVI and other prominent vegetation indices can be used to detect subtle drought conditions by specifically identifying various time lags between climate condition and vegetation response. 相似文献
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11.
T. N. Hajare N. G. Patil K. S. Verma 《Journal of the Indian Society of Remote Sensing》2008,36(3):267-272
Spectral indices as an indicator of physiological traits affecting safflower yield in relation to soil variability were evaluated
in a two year experiment (1997–1999). Reflectance, biometric and phonological data were collected. Two indices namely normalized
differential vegetation index (NDVI) and ratio of spectral reflectance in infrared region to red region (1R/R) were derived
from radiometric observation. Yield data indicated significant difference in different soils. Temporal NDVI behaviour as a
function of soil type was not prominent especially in early stages of crop growth. However NDVI at 75 days after sowing (DAS)
was found to be relatively better indicator of plant status and yield. IR/R was relatively less effective in indicating the
differential response of crop to soil types. Effect of soil and crop interaction on spectral indices was significant at 75
and 90 DAS, which was attributed to attainment of maximum leaf area and leaf area at these stages of growth. Regression analysis
showed strong positive relationship between NDVI and leaf area, dry matter and yield. IR/R and leaf area had the strongest
and consistent relationship (r = 0.96). A single regression equation accounted for yield variability in the dataset. Thus
possible transformation of NDVI maps (satellite data) to LAI units and consequently applications like yield forecasting was
indicated. Utility of spectra-temporal data as a pointer of plant development status and yield was also demonstrated. 相似文献
12.
Accurately monitoring the temporal, spatial distribution and severity of agricultural drought is an effective means to reduce the farmers’ losses. Based on the concept of the new drought index called VegDRI, this paper established a new method, named the Integrated Surface Drought Index (ISDI). In this method, the Palmer Drought Severity Index (PDSI) was selected as the dependent variable; for the independent variables, 12 different combinations of 14 factors were examined, including the traditional climate-based drought indicators, satellite-derived vegetation indices, and other biophysical variables. The final model was established by fully describing drought properties with the smaller average error (relative error) and larger correlation coefficients. The ISDI can be used not only to monitor the main drought features, including precipitation anomalies and vegetation growth conditions but also to indicate the earth surface thermal and water content properties by incorporating temperature information. Then, the ISDI was used for drought monitoring from 2000 to 2009 in mid-eastern China. The results for 2006 (a typical dry year) demonstrate the effectiveness and capability of the ISDI for monitoring drought on both the large and the local scales. Additionally, the multiyear ISDI monitoring results were compared with the actual drought intensity using the agro-meteorological disaster data recorded at the agro-meteorological sites. The investigation results indicated that the ISDI confers advantages in the accuracy and spatial resolution for monitoring drought and has significant potential for drought identification in China. 相似文献
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14.
Anup K. Prasad Lim Chai Ramesh P. Singh Menas Kafatos 《International Journal of Applied Earth Observation and Geoinformation》2006
Numerous efforts have been made to develop various indices using remote sensing data such as normalized difference vegetation index (NDVI), vegetation condition index (VCI) and temperature condition index (TCI) for mapping and monitoring of drought and assessment of vegetation health and productivity. NDVI, soil moisture, surface temperature and rainfall are valuable sources of information for the estimation and prediction of crop conditions. In the present paper, we have considered NDVI, soil moisture, surface temperature and rainfall data of Iowa state, US, for 19 years for crop yield assessment and prediction using piecewise linear regression method with breakpoint. Crop production environment consists of inherent sources of heterogeneity and their non-linear behavior. A non-linear Quasi-Newton multi-variate optimization method is utilized, which reasonably minimizes inconsistency and errors in yield prediction. 相似文献
15.
Alex O. Onojeghuo George A. Blackburn Qunming Wang Peter M. Atkinson Daniel Kindred Yuxin Miao 《地理信息系统科学与遥感》2018,55(5):659-677
Satellite data holds considerable potential as a source of information on rice crop growth which can be used to inform agronomy. However, given the typical field sizes in many rice-growing countries such as China, data from coarse spatial resolution satellite systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) are inadequate for resolving crop growth variability at the field scale. Nevertheless, systems such as MODIS do provide images with sufficient frequency to be able to capture the detail of rice crop growth trajectories throughout a growing season. In order to generate high spatial and temporal resolution data suitable for mapping rice crop phenology, this study fused MODIS data with lower frequency, higher spatial resolution Landsat data. An overall workflow was developed which began with image preprocessing, calculation of multi-temporal normalized difference vegetation index (NDVI) images, and spatiotemporal fusion of data from the two sensors. The Spatial and Temporal Adaptive Reflectance Fusion Model was used to effectively downscale the MODIS data to deliver a time-series of 30 m spatial resolution NDVI data at 8-day intervals throughout the rice-growing season. Zonal statistical analysis was used to extract NDVI time-series for individual fields and signal filtering was applied to the time-series to generate rice phenology curves. The downscaled MODIS NDVI products were able to characterize the development of paddy rice at fine spatial and temporal resolutions, across wide spatial extents over multiple growing seasons. These data permitted the extraction of key crop seasonality parameters that quantified inter-annual growth variability for a whole agricultural region and enabled mapping of the variability in crop performance between and within fields. Hence, this approach can provide rice crop growth data that is suitable for informing agronomic policy and practice across a wide range of scales. 相似文献
16.
高分四号卫星在干旱遥感监测中的应用 总被引：3，自引：3，他引：0
高分四号(GF-4)是国家高分辨率对地观测系统重大专项天基系统中的一颗地球同步卫星,为探索GF-4号卫星在大面积干旱监测中的应用,本文对该卫星在快速监测大面积干旱方面的应用能力进行了初步探讨。以2016年内蒙古自治区巴林左旗和巴林右旗地区严重旱灾为例,利用NDVI差值对该区域的干旱情况进行了监测,并与MODIS NDVI产品进行对比分析,得到了研究区内2016年干旱分布情况,结果表明其总体趋势与MODIS NDVI产品一致,且细节信息更加丰富。本文主要是GF-4卫星数据结合GF-1卫星数据对内蒙部分干旱区域进行监测和分析,体现了国产高分辨率卫星数据,尤其是GF-4卫星数据,对提高中国突发灾害的应对能力具有重要意义。 相似文献
17.
Susanna Azzali 《国际地球制图》2013,28(3):15-26
A method to correlate crop production in Zambia to the yearly evolution of the Normalized Difference Vegetation Index (NDVI) is proposed. The method consists of the analysis of remote sensing data together with meteorological data and simulated crop production to obtain indicators of crop production. The accuracy of these indicators is assessed with statistical data. The main objective was to assess whether the NDVI‐time series extracted from NOAA‐AVHRR‐images , having a pixel resolution of 73 km may give reliable information on crop production in Zambia where agricultural areas cover just 1% of the land area. The mean NDVI‐value of several pixels, e.g. for one province or other administrative units, relates to the dominant type of vegetation in the area under consideration. It is shown that the 7.3 km NDVI‐data give reliable indications on crop production in Zambia, when small areas (200–450 km2 large ) are considered where agricultural land use is intensive. This implies that preliminary analysis is required to localize the agricultural areas. This has been done by means of high resolution satellite images i.e. LANDSAT‐MultiSpectral Scanner. Consequently, the NDVI‐time series of the ‘agricultural ‘ pixels are used to calculate crop growth indicators which can be applied to assess the crop production. 相似文献
18.
《地理信息系统科学与遥感》2013,50(4):454-470
Remote sensing techniques are capable of identifying a particular crop as well as monitoring its growing stages, crop vigor, and biomass. Due to the increasing demand for food staples, potato cultivation in Bangladesh has increased substantially over the last decade. A study was carried out in the Munshiganj area, the main potato-producing district in Bangladesh, to assess the growth of potatoes by modeling its important life metrics. Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) products were extracted from MODIS Surface Reflectance Eight-Day L3 Global 500 m data from November 25, 2005 to March 6, 2006. NDVI and LAI were extracted for 50 selected fields in the study area and used to construct potato phenological curves. Twenty-two life metrics were derived for potato from the phenological curves. The first 12 metrics are the basic life metrics of potato and the others are supplementary. Results showed a significant amplitude and distinct response period of these vegetation indices. Based on the phenological curves, the spatial distribution of potato growth was estimated for the study area for both NDVI and LAI. The effect of temperature on crop phenology was examined during the potato growing season. It was found that significant growth occurred when the temperature was relatively low. This study demonstrates that remote sensing data can be effectively used to study potato growth in Bangladesh. 相似文献
19.
为提高农业干旱监测效果和精度,在对传统干旱监测模型对比分析基础上,本文提出将温度植被干旱指数(TVDI)和植被供水指数(VSWI)加权联合构建温度供水干旱指数(TSWDI)的研究思路。以京津冀2006—2012年5月份数据作为实验统计数据,以京津冀2006—2016年3—5月份春旱监测为例进行了模型实验。实验结果证实,TSWDI指数相对其他两个指数与10、20和50 cm深处的土壤水分相关性更高,能够更精准地反映农业干旱状况。TSWDI计算结果显示,京津冀干旱分布具有如下特征:从时间角度看,2006—2016年整体干旱状况逐渐缓解,特别是自2010年至今,研究区域干旱程度逐步减轻;从空间角度看,京津冀区域整体干旱面积逐步减少。 相似文献
20.
Swapnil Vyas Rahul Nigam N. K. Patel Sushma Panigrahy 《Journal of the Indian Society of Remote Sensing》2013,41(4):855-864
Monitoring of Agricultural crops using remote sensing data is an emerging tool in recent years. Spatial determination of sowing date is an important input of any crop model. Geostationary satellite has the capability to provide data at high temporal interval to monitor vegetation throughout the entire growth period. A study was conducted to estimate the sowing date of wheat crop in major wheat growing states viz. Punjab, Haryana, Uttar Pradesh (UP), Madhya Pradesh (MP), Rajasthan and Bihar. Data acquired by Charged Couple Detector (CCD) onboard Indian geostationary satellite INSAT 3A have continental (Asia) coverage at 1 km?×?1 km spatial resolution in optical spectral bands with high temporal frequency. Daily operational Normalized Difference Vegetation Index (NDVI) product from INSAT 3A CCD available through Meteorological and Oceanographic Satellite Data Archival Centre (MOSDAC) was used to estimate sowing date of wheat crop in selected six states. Daily NDVI data acquired from September 1, 2010 to December 31, 2010 were used in this study. A composite of 7 days was prepared for further analysis of temporal profile of NDVI. Spatial wheat crop map derived from AWiFS (56 m) were re-sampled at INSAT 3A CCD parent resolution and applied over each 7 day composite. The characteristic temporal profiles of 7 day NDVI composite was used to determine sowing date. NDVI profile showed decreasing trend during maturity of kharif crop, minimum value after harvest and increasing trend after emergence of wheat crop. A mathematical model was made to capture the persistent positive slope of NDVI profile after an inflection point. The change in behavior of NDVI profile was detected on the basis of change in NDVI threshold of 0.3 and sowing date was estimated for wheat crop in six states. Seven days has been deducted after it reached to threshold value with persistent positive slope to get sowing date. The clear distinction between early sowing and late sowing regions was observed in study area. Variation of sowing date was observed ranging from November 1 to December 20. The estimated sowing date was validated with the reported sowing date for the known wheat crop regions. The RMSD of 3.2 (n?=?45) has been observed for wheat sowing date. This methodology can also be applied over different crops with the availability of crop maps. 相似文献