共查询到20条相似文献，搜索用时 677 毫秒
1.
S. Panigrahy V. Jain C. Patnaik J. S. Parihar 《Journal of the Indian Society of Remote Sensing》2012,40(4):599-606
In-season rice area estimation using C-band Synthetic Aperture Radar (SAR) data from RADARSAT-1 is being done in India for more than a decade. Decision rule based models in backscatter domain have been calibrated and validated using extensive field data and a long term backscatter signature bank of rice fields has been developed. Since the rice crop growing environment in India is a diverse one in the world having all the rice cultural types, the rice backscatter is quite exhaustive. This paper highlights the results of classification of rice lands in Bangladesh using the signature bank of India. The results showed that the Aman rice crop of Bangladesh has a typical temporal backscatter of shallow and intermediate rice fields of that of West Bengal state. The mean backscatter of the intermediate/deep water fields in southern Bangladesh was ?19?dB, while that of shallow cultural types mostly in northern Bangladesh was ?17?dB. The signature of the rice crop in Southern Bangladesh matched well with that of Gangetic West Bengal, particularly that of the 24 Parganas, Howrah and Hughli districts. The signature of rice crop in the Sub-Himalayan West Bengal particularly that of Dinajpur and Maldah districts matched well with that of the northern area of Bangladesh. State level rice area estimated using the selected models was found with in 5% deviation from that of the reported acreage. 相似文献
2.
S.R. Oza S. PanigrahyJ.S. Parihar 《International Journal of Applied Earth Observation and Geoinformation》2008
Estimation of crop area, growth and phenological information is very important for monitoring of agricultural crops. However, judicious combination of spatial and temporal data from different spectral regions is necessary to meet the requirement. This study highlights the use of active microwave QuikSCAT Ku-band scatterometer and Special Sensor Microwave/Imager (SSM/I) passive microwave radiometer data to derive information on important phenological phases of rice crop. The wetness index, a weekly composite product derived using brightness temperatures from 19, 37 and 85 GHz channels of SSM/I, was used to identify the puddling period. Ku-band scatterometer data provided the signal of transplanted rice seedlings since they acts as scatterers and increases the backscattering. Dual peak nature of temporal backscatter curve around the heading stage of rice crop was observed in Ku-band. The decrease of backscatter after first peak was associated with the threshold value of 60% crop canopy cover. The symmetric (Gaussian) and asymmetric (lognormal) curve fits were attempted to derive the date of initiation of the heading phase. The temporal signature from each of these sensors was found to complement each other in crop growth monitoring. Image showing pixel-wise timings of heading stage revealed the differences exists in various parts of the study area. 相似文献
3.
B. U. Choudhury Anil Sood S. S. Ray P. K. Sharma S. Panigrahy 《Journal of the Indian Society of Remote Sensing》2013,41(1):71-82
Large scale adoption of input intensive rice–wheat cropping system in the centrally located Jalandhar district of Indian Punjab has led to over-exploitation of ground water resources, intensive use of chemical fertilizers and deterioration of soil health. To overcome these shortfalls, in the present study, agricultural area diversification plan has been generated from agricultural area and crop rotation maps derived from remote sensing data (IRS P6-AWiFS and RADARSAT ScanSAR) along with few agro-physical parameters in GIS environment. Cropping system indices (area diversity, multiple cropping and cultivated land utilization) were also worked out from remote sensing data .Analysis of remote sensing data (2004–05) revealed that rice and wheat individually remained the dominant crops, occupy 57.8% and 64.9% of total agricultural area (TAA), respectively. Therefore, in the diversified plan, it is suggested that at least 39% of the current 40% TAA under rice–wheat rotation should be replaced by other low water requiring, high value and soil enriching crops, particularly in coarse textured alluvial plain having good quality ground water zones with low annual rainfall(<700 mm). This will reduce water requirement to the tune of 15,660 cm depth while stabilizing the production and profitability by crop area diversification without further degradation of natural resources. 相似文献
4.
Improved rice crop and water management practices that make the sustainable use of resources more efficient are important interventions towards a more food secure future. A remote sensing-based detection of different rice crop management practices, such as crop establishment method (transplanting or direct seeding), can provide timely and cost-effective information on which practices are used as well as their spread and change over time as different management practices are adopted. Establishment method cannot be easily observed since it is a rapid event, but it can be inferred from resulting observable differences in land surface characteristics (i.e. field condition) and crop development (i.e. delayed or prolonged stages) that take place over a longer time. To examine this, we used temporal information from Synthetic Aperture Radar (SAR) backscatter to detect differences in field condition and rice growth, then related those to crop establishment practices in Nueva Ecija (Philippines). Specifically, multi-temporal, dual-polarised, C-band backscatter data at 20m spatial resolution was acquired from Sentinel-1A every 12 days over the study area during the dry season, from November 2016 to May 2017. Farmer surveys and field observations were conducted in four selected municipalities across the study area in 2017, providing information on field boundaries and crop management practices for 61 fields. Mean backscatter values were generated per rice field per SAR acquisition date. We matched the SAR acquisition dates with the reported dates for land management activities and with the estimated dates for when the crop growth stages occurred. The Mann-Whitney U test was used to identify significant differences in backscatter between the two practices during the land management activities and crop growth stages. Significant differences in cross-polarised, co-polarised and band ratio backscatter values were observed in the early growing season, specifically during land preparation, crop establishment, rice tillering and stem elongation. These findings indicate the possibility to discriminate crop establishment methods by SAR at those stages, suggesting that there is more opportunity for discrimination than has been presented in previous studies. Further testing in a wider range of environments, seasons, and management practices should be done to determine how reliably rice establishment methods can be detected. The increased use of dry and wet direct seeding has implications for many remote sensing-based rice detection methods that rely on a strong water signal (typical of transplanting) during the early season. 相似文献
5.
This study investigates the potential of multi-temporal signature analysis of satellite imagery to map rice area in South
24 Paraganas district of West Bengal. Two optical data (IRS ID LISS III) and three RADARSAT SAR data of different dates were
acquired during 2001. Multi-temporal SAR backscatter signatures of different landcovers were incorporated into knowledge based
decision rules and kharif landcover map was generated. Based on the spectral variation in signature, the optical data acquired
during rabi (January) and summer (March) season were classified using supervised maximum likelihood classifier. A co-incidence
matrix was generated using logical approach for a combined “rabi-summer” and “kharif-rabi-summer” landcover mapping. The major
landcovers obtained in South 24 Paraganas using remote sensing data are rice, water, aquaculture ponds, homestead, mangrove,
and urban area. The classification accuracy of rice area was 98.2% using SAR data. However, while generating combined “kharif-rabi-summer”
landcovers, the classification accuracy of rice area was improved from 81.6% (optical data) to 96.6% (combined SAR-Optical).
The primary aim of the study is to achieve better accuracy in classifying rice area using the synergy between the two kinds
of remotely sensed data. 相似文献
6.
Sushma Panigrahy Shibendu Shankar Ray K. R. Manjunath P. S. Pandey S. K. Sharma Anil Sood Manoj Yadav P. C. Gupta N. Kundu Jai Singh Parihar 《Journal of the Indian Society of Remote Sensing》2011,39(3):355-364
Cropping system study is not only useful to understand the overall sustainability of agricultural system, but also it helps
in generating many important parameters which are useful in climate change impact assessment. Considering its importance,
Space Applications Centre, took up a project for mapping and characterizing major cropping systems of Indo-Gangetic Plains
of India. The study area included the five states of Indo-Gangetic Plains (IGP) of India, i.e. Punjab, Haryana, Uttar Pradesh,
Bihar and West Bengal. There were two aspects of the study. The first aspect included state and district level cropping system
mapping using multi-date remote sensing (IRS-AWiFS and Radarsat ScanSAR) data. The second part was to characterize the cropping
system using moderate spatial resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. The remote sensing
data was used to compute three cropping system performance indices (Multiple Cropping Index, Area Diversity Index and Cultivated
Land Utilization Index). Ground survey was conducted using questionnaires filled up by 1,000 farmers selected from 103 villages
based on the cropping systems map. Apart from ground survey, soil and water sampling and quality analysis were carried out
to understand the effect of different cropping systems and their management practices. The results showed that, rice-wheat
was the major cropping system of the IGP, followed by Rice-Fallow-Fallow and Maize-Wheat. Other major cropping systems of
IGP included Sugarcane based, Pearl millet-Wheat, Rice-Fallow-Rice, Cotton-Wheat. The ground survey could identify 77 cropping
systems, out of which 38 are rice-based systems. Out of these 77 cropping systems, there were 5 single crop systems, occupying
6.5% coverage (of all cropping system area), 56 double crop systems with 72.7% coverage, and 16 triple crop systems with 20.8%
coverage. The cropping system performance analysis showed that the crop diversity was found to be highest in Haryana, while
the cropping intensity was highest in Punjab state. 相似文献
7.
This paper introduces ENVISAT ASAR data application on rice field mapping in the Fuzhou area, using multi-temporal ASAR dual
polarization data acquired in 2005. The procedure for ASAR data processing here includes data calibration, image registration,
speckle reduction and conversion of data format from amplitude to dB for backscatter. The backscatter of rice increases with
the rice growing stages, which was much different from other land covers. Based on image difference techniques, 6 schemes
were designed with ASAR different temporal and polarization data for rice field mapping. Difference images between images
in the early period of rice crop and growing or ripening period, are more suitable for rice extraction than those difference
images between different polarizations in the same date. The most accurate result of late rice extraction was achieved based
on the difference of HH polarization data acquired in October and August. Therefore, for rice field mapping, the temporal
information is more important than polarization information. The data during the early growing season of rice is very important
for high accuracy rice mapping. 相似文献
8.
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10.
This research letter presents preliminary results of mapping rice crop growth using ENVISAT advanced synthetic aperture radar (ASAR) alternating polarization HH/HV data. Four ASAR HH/HV images were collected in the early rice-growth cycle in the test site in 2006, and the temporal response of ASAR data to the rice field was analyzed. The height and biomass of rice were measured during acquisition of ASAR data, and empirical relationships were established between the backscattering coefficient and these two parameters. Based on the temporal variation of the radar response, a method for mapping a rice growth area was developed using the combination of ASAR HH and HV polarization data between two acquisition dates. The results confirm that C-band SAR data have great potential in the development of an operational system for monitoring rice crop growth in Southern China. 相似文献
11.
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
12.
R. P. Singh V. K. Dadhwal R. R. Navalgund 《Journal of the Indian Society of Remote Sensing》1999,27(3):167-173
Modular Optoelectronic Scanner (MOS-B) spectrometer data over parts of Northern India was evaluated for wheat crop monitoring involving (a) sub pixel wheat fractional area estimation using spectral unmixing approach and (b) growth assessment by red edge shift at different phenological stages. Red shift of 10 nm was observed between crown root initiation stage to flowering stage. Wheat fraction estimates using linear spectral unmixing on Feb. 13, 1999 acquisition of MOS-B data had high correlation (0.82) with estimates from Wide Field Sensor (WiFS) data acquired on same date by IRS-P3 platform. It was observed that five bands (4,5,8,12,13 MOS-B bands) are sufficient for signature separability of major land cover classes viz. wheat, urban, wasteland, and water based on purely spectral separability criterion using Transformed Divergence (T.D.) approach. Higher number of bands saturated the T.D. values. In contrast, performance of sub pixel fractional area estimation using unmixing decreased drastically for eight bands (4,5,6,7,8,9,12,13 MOS-B bands) chosen from optimal band selection criteria in comparison to full set of 13 bands. The relative deviation between area estimated from Wifs and MOS-B increased from 1.72 percent when all thirteen bands were used in unmixing to 26.10 percent for the above eight bands. 相似文献
13.
Kamlesh P. Lulla Michael R. Helfert David L. Amsbury Victor S. Whitehead Cynthia A. Evans M. Justin Wilkinson 《国际地球制图》2013,28(1):69-80
Abstract Multi‐temporal ERS‐1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes. 相似文献
14.
K. R. Manjunath Sushma Panigrahy T. K. Adhya V. Beri K. V. Rao J. S. Parihar 《Journal of the Indian Society of Remote Sensing》2011,39(3):307-313
The rice land is linked to the climate change due to its methane emission potential. The systems of growing rice and associated
soil and crop management practices that have evolved are varied and complex. However, from the methane emission point of view,
water regime is a crucial parameter. According to IPCC guidelines the rice ecosystem need to be categorized into four strata
for methane emission study. The remote sensing based stratification map previously developed was used for in-situ weekly/monthly
measurements of methane emission from the representative ecosystems, samples were collected and analysed using gas chromatography
following the IPCC standards for three consecutive years; 2003, 2004 and 2005. This paper highlights the results of methane
emission measurement and pattern from rice lands of India based on in-situ measurements. The CH4 emission pattern of irrigated crop in dry season showed a steady increase in the beginning which peaks during flowering stage,
decreasing gradually thereafter. The results were consistent for different varieties and across the years. The emission pattern
of irrigated wet season crop showed two peaks. The emission pattern also showed the influence of crop variety as well as year
(of observation). The mean emission coefficient derived from all categories and all samples (n = 471) weighted for the Indian rice crop was 74.05 + 43.28 kg/ha. 相似文献
15.
通过对肇庆试验区1996年和1997年获取的多时相、多模式雷达卫星（RADARSAT）数据分析,从图像上直接提取地物的后向散射系数,结合实地测量水稻的生长结构参数,建立了水稻生长模型,分析了不同生长周期（从80天到120－125天）4种类型水稻的时域散射特性。利用1997年4月至7月获取的7景标准模式雷达卫星数据,对试验区内三个县和两个行政区共5000km^2面积范围内的作物进行分类和水稻产量预估算,水稻类型分类及面积量算精度达91％。结果表明：利用雷达遥感数据进行水稻种植面积量算和估产需要水稻生长期间三个时相的数据,即插秧期、抽穗期、收割前期。若能够获得多参数雷达图像,可以用插秧期和收割前期的两个时相图像来代替上述的三个时相图像同样可以达到种植面积量算和估产的效果。这一结果充分说明多时相雷达卫星数据对我国南方水稻长势监测及估产具有明显优势和潜力。 相似文献
16.
水稻时域散射特征分析及其应用研究 总被引：14，自引：3，他引：14
通过对肇庆试验区1996年和1997年获取的多时相、多模式雷达卫星（RADARSAT）数据分析，从图像上直接提取地物的后向散射系数，结合实地测量水稻的生长结构参数，建立了水稻生长模型，分析了不同生长周期（从80天到120－125天）4种类型水稻的时域散射特性。利用1997年4月至7月获取的7景标准模式雷达卫星数据，对试验区内三个县和两个行政区共5000km^2面积范围内的作物进行分类和水稻产量预估算，水稻类型分类及面积量算精度达91％。结果表明：利用雷达遥感数据进行水稻种植面积量算和估产需要水稻生长期间三个时相的数据，即插秧期、抽穗期、收割前期。若能够获得多参数雷达图像，可以用插秧期和收割前期的两个时相图像来代替上述的三个时相图像同样可以达到种植面积量算和估产的效果。这一结果充分说明多时相雷达卫星数据对我国南方水稻长势监测及估产具有明显优势和潜力。 相似文献
17.
N K Patel T T Medhavy C Patnaik A Hussain 《Journal of the Indian Society of Remote Sensing》1995,23(2):33-39
Microwave sensors having all-weather capabilities provide an opportunity to monitor rice grown in monsoon season. An attempt has been made to identify rice crop using multitemporal ERS-1 SAR data in C-band (5.3 GHz). Data acquired on August 15 (D1), September 19 (D2), October 24 (D3) and November 28 (D4) 1993 were taken. Combinations of data acquired on different dates were used for identification of rice crop. Single-date IRS-1B LISS II data in visible and NIR bands acquired on October 23, 1993 was also used for comparison of estimated rice area. Analysis of the results has shown that a combination of SAR data acquired at the tillering (August), booting (September) and heading (October) stages of rice crop enabled identification and area estimation of rice crop grown under lowland conditions. Single-date SAR data acquired in the month of October was found to be better for identification of rice compared to other dates. 相似文献
18.
P.V. Raju M.V.R. Sesha Sai P.S. Roy 《International Journal of Applied Earth Observation and Geoinformation》2008,10(2):220-1
AWiFS sensor on board IRS-P6 (Resourcesat-1), with its unique features—wide swath and 5-day revisit capability provides excellent opportunities to carry out in-season analysis of irrigated agriculture. The study carried out in Hirakud command area, Orissa State indicated that the progression of rice crop acreage could be mapped through analysis of time series AWiFS data set. The spectral emergence pattern of rice crop was found useful to identify the period of rice transplantation and its variability across the command area. This information, integrated with agro-meteorological data, was used to quantify 10-daily canal-wise irrigation water requirement. A comparison with field measured actual irrigation supplies indicated an overall supply adequacy of 88% and showed wide variability at lateral canal level ranging between 18% and 109%. The supply pattern also did not correspond with the chronological variations associated with crop water requirement, supplies were 15% excess during initial part of season (December and January) and were 20.1% deficit during later part of season (February to April). Rescheduling the excess supplies of the initial period could have reduced the deficit to 15% during peak season. The study has demonstrated the usefulness of AWiFS data to generate the irrigation water requirement by mid-season, subsequent to which 38% supplies were yet to be allocated. This would support the irrigation managers to reschedule the irrigation water supplies to achieve better synchronization between requirement and supply leading to improved water use efficiency. 相似文献
19.
A national level project on kharif rice identification and acreage estimation is being carried out successfully for several states in the country. A similar
methodology based on the temporal profile for identification and delineation of various land cover classes has been followed
for the Rabi rice acreage estimation. To define rabi rice, rabi season in India starts from November — February to March — June. Though the main growing season is predominantly winter but
the uncertainty of getting cloud free data during the season has resulted in the use of microwave data. A feasibility study
was taken up for early forecasting of the rabi rice area using microwave data. Hierarchical decision rule classification technique was used for the identification of the
different land cover classes. Land preparation, puddling and transplantation were the reasons for the specific backscatter
of rice growing areas. The increase or decrease in the SAR backscatter due to progress in the crop phenology or due to delayed
sowing respectively forms the basis for identifying the rice areas. In addition the potential of optical data of a later date
has been utilized in the form of various indices from bands including MIR to distinctly separate the late sown areas and also
the puddled areas from other areas. This study emphasizes the synergistic use of SAR and optical data for delineating the
rabi rice areas which is of immense use in giving an early forecast. 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