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1.
Irrigation infrastructure development for smallholder farmers in developing countries increasingly gains attention in the light of domestic food security and poverty alleviation. However, these complex landscapes with small cultivated plots pose a challenge with regard to mapping and monitoring irrigated agriculture. This study presents an object-based approach to map irrigated agriculture in an area in the Central Rift Valley in Ethiopia using SPOT6 imagery. The study is a proof-of-concept that the use of shape, texture, neighbour and location information next to spectral information is beneficial for the classification of irrigated agriculture. The underlying assumption is that the application of irrigation has a positive effect on crop growth throughout the field, following the field's borders, which is detectable in an object-based approach. The type of agricultural system was also mapped, distinguishing smallholder farming and modern large-scale agriculture. Irrigated agriculture was mapped with an overall accuracy of 94% and a kappa coefficient of 0.85. Producer's and user's accuracies were on average 90.6% and 84.2% respectively. The distinction between smallholder farming and large-scale agriculture was identified with an overall accuracy of 95% and a kappa coefficient of 0.88. The classifications were performed at the field level, since the segmentation was able to adequately delineate individual fields. The additional use of object features proved essential for the identification of cropland plots, irrigation period and type of agricultural system. This method is independent of expert knowledge on crop phenology and absolute spectral values. The proposed method is useful for the assessment of spatio-temporal dynamics of irrigated (smallholder) agriculture in complex landscapes and yields a basis for land and water managers on agricultural water use. 相似文献
2.
Improving crop area and/or crop yields in agricultural regions is one of the foremost scientific challenges for the next decades. This is especially true in irrigated areas because sustainable intensification of irrigated crop production is virtually the sole means to enhance food supply and contribute to meeting food demands of a growing population. Yet, irrigated crop production worldwide is suffering from soil degradation and salinity, reduced soil fertility, and water scarcity rendering the performance of irrigation schemes often below potential. On the other hand, the scope for improving irrigated agricultural productivity remains obscure also due to the lack of spatial data on agricultural production (e.g. crop acreage and yield). To fill this gap, satellite earth observations and a replicable methodology were used to estimate crop yields at the field level for the period 2010/2014 in the Fergana Valley, Central Asia, to understand the response of agricultural productivity to factors related to the irrigation and drainage infrastructure and environment. The results showed that cropping pattern, i.e. the presence or absence of multi-annual crop rotations, and spatial diversity of crops had the most persistent effects on crop yields across observation years suggesting the need for introducing sustainable cropping systems. On the other hand, areas with a lower crop diversity or abundance of crop rotation tended to have lower crop yields, with differences of partly more than one t/ha yield. It is argued that factors related to the infrastructure, for example, the distance of farms to the next settlement or the density of roads, had a persistent effect on crop yield dynamics over time. The improvement potential of cotton and wheat yields were estimated at 5%, compared to crop yields of farms in the direct vicinity of settlements or roads. In this study it is highlighted how remotely sensed estimates of crop production in combination with geospatial technologies provide a unique perspective that, when combined with field surveys, can support planners to identify management priorities for improving regional production and/or reducing environmental impacts. 相似文献
3.
The availability of accurate information on the water consumed for crop irrigation is of vital importance to support compatible and sustainable environmental policies in arid and semi-arid regions. This has promoted several studies about the use of remote sensing data to monitor irrigated croplands, which are mostly based on statistical classification and/or regression techniques. The current paper proposes a new semi-empirical approach that relies on a water balance logic and does not require local tuning. The method stems from recent investigations which demonstrated the possibility of combining standard meteorological data and Sentinel-2 (S-2) Multi Spectral Instrument (MSI) NDVI images to estimate the actual evapotranspiration (ETa) of irrigated Mediterranean croplands. This ETa estimation method is adapted to drive a simplified site water balance which, for each 10-m S-2 MSI pixel, predicts the irrigation water (IW), i.e. the water which is consumed in addition to that naturally supplied by rainfall. The new method, fed with ground and satellite data from two years (2018–2019), is tested in a Mediterranean area around the town of Grosseto (Central Italy), that is covered by a particularly complex mosaic of rainfed and irrigated crops. The results obtained are first assessed qualitatively for some fields grown with known winter, spring and summer crops. Next, the IW estimates are evaluated quantitatively versus ground measurements taken over two irrigated fields, the first grown with processing tomato in 2018 and the second with early corn in 2019. Finally, the IW estimates are statistically analyzed against various datasets informative on local agricultural practices in the two years. All these analyses indicate that the proposed method is capable of predicting both the intensity and timing of the IW supply in the study area. The method, in fact, correctly identifies rainfed and irrigated crops and, in the latter case, accurately predicts the IW actually supplied. The results of the quantitative tests performed on tomato and corn show that over 50 % and 70 % of the measured IW variance is explained on daily and weekly bases, respectively, with corresponding mean bias errors below 0.3 mm/day and 2.0 mm/week. Similar indications are produced by the qualitative tests; reasonable IW estimates are obtained for all winter, springs and summer crops grown in the study area during 2018 and 2019. 相似文献
4.
5.
Irrigation accounts for 70% of global water use by humans and 33–40% of global food production comes from irrigated croplands. Accurate and timely information related to global irrigation is therefore needed to manage increasingly scarce water resources and to improve food security in the face of yield gaps, climate change and extreme events such as droughts, floods, and heat waves. Unfortunately, this information is not available for many regions of the world. This study aims to improve characterization of global rain-fed, irrigated and paddy croplands by integrating information from national and sub-national surveys, remote sensing, and gridded climate data sets. To achieve this goal, we used supervised classification of remote sensing, climate, and agricultural inventory data to generate a global map of irrigated, rain-fed, and paddy croplands. We estimate that 314 million hectares (Mha) worldwide were irrigated circa 2005. This includes 66 Mha of irrigated paddy cropland and 249 Mha of irrigated non-paddy cropland. Additionally, we estimate that 1047 Mha of cropland are managed under rain-fed conditions, including 63 Mha of rain-fed paddy cropland and 985 Mha of rain-fed non-paddy cropland. More generally, our results show that global mapping of irrigated, rain-fed, and paddy croplands is possible by combining information from multiple data sources. However, regions with rapidly changing irrigation or complex mixtures of irrigated and non-irrigated crops present significant challenges and require more and better data to support high quality mapping of irrigation. 相似文献
6.
Water stress during crop cultivation due to inconsistent rainfall is a common phenomenon in maize growing area of Shanmuganadi watershed, located in the semi-arid region of southern peninsular India. The objective is to estimate the supplementary irrigation required to improve the crop productivity during water stress period. Spatial hydrological model, Soil and Water Assessment Tool, has been applied to simulate the watershed hydrology and crop growth for rabi season (October–February) considering the rainfed and irrigated scenarios. The average water stress days of rainfed maize was 60 days with yield of 1.6 t/ha. Irrigated maize with supplementary irrigation of 93–126 mm was resulted in improved yield of 3.8 t/ha with 28 water stress days. The results also suggest that supplemental irrigation can be obtained from groundwater reserves and by adopting early sowing strategy can provide opportunities for improving water productivity in rainfed farming. 相似文献
7.
A. V. Suresh Babu V. Venkateshwar Rao I. V. Muralikrishna 《Journal of the Indian Society of Remote Sensing》2007,35(1):81-91
Water Utilisation Index (WUI) defined as area irrigated per unit volume is a measure of water delivery performance and constitutes
one of the important spatial performance indicators of an irrigation system. WUI also forms basis for evaluating the adequacy
of seasonal irrigation supplies in an irrigation system (inverse of WUI is delta, i.e. depth of water supplied to a given
irrigation unit). In the present study WUI and adequacy indicators were used in benchmarking the performance of Nagarjunasagar
Left Canal Command (NSLC) in Andhra Pradesh. Optimised temporal satellite data of rabi season during the years 1990–91 and
1998–99 was used in deriving irrigated crop areas adopting hierarchical classification approach. Paddy is the predominant
crop grown and cotton, chillies, sugarcane etc. are the other crops grown in the study area. Equivalent wet area (paddy crop
area) was estimated using the operationally used project specific conversion factors. WUI was estimated at disaggregated level
viz., distributary, irrigation block, irrigation zone level using the canal discharge data. At project level, WUI estimated
to be 65 ha/MCM and 92 ha/MCM during rabi season of 1990–91 and 1998–99 years respectively. A comparison of total irrigated
area and discharges corresponding to both the years indicate that irrigation service is extensive and sub optimal during 1998–99
and it is intensive and optimal in 1990–91. It was also observed that WUI is lesser in blocks of with higher Culturable Command
Area (CCA) compared to the blocks of lower CCA. All the disaggregated units were ranked into various groups of different levels
of water distribution performance. The study demonstrates the utility of WUI as spatial performance indicator and thus useful
for benchmarking studies of irrigation command areas. The WUI together with satellite data derived spatial irrigation intensity,
crop productivity constitutes important benchmarking indices in irrigation command areas. 相似文献
8.
Murali Krishna Gumma Prasad S. Thenkabail Pardharsadhi Teluguntla Mahesh N. Rao Irshad A. Mohammed Anthony M. Whitbread 《International Journal of Digital Earth》2016,9(10):981-1003
The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250?m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (kharif) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second (rabi) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250?m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3?Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes. 相似文献
9.
Remote sensing techniques allow monitoring the Earth surface and acquiring worthwhile information that can be used efficiently in agro-hydrological systems. Satellite images associated to computational models represent reliable resources to estimate actual evapotranspiration fluxes, ETa, based on surface energy balance. The knowledge of ETa and its spatial distribution is crucial for a broad range of applications at different scales, from fields to large irrigation districts. In single plots and/or in irrigation districts, linking water volumes delivered to the plots with the estimations of remote sensed ETa can have a great potential to develop new cost-effective indicators of irrigation performance, as well as to increase water use efficiency. With the aim to assess the irrigation system performance and the opportunities to save irrigation water resources at the “SAT Llano Verde” district in Albacete, Castilla-La Mancha (Spain), the Surface Energy Balance Algorithm for Land (SEBAL) was applied on cloud-free Landsat 5 Thematic Mapper (TM) images, processed by cubic convolution resampling method, for three irrigation seasons (May to September 2006, 2007 and 2008). The model allowed quantifying instantaneous, daily, monthly and seasonal ETa over the irrigation district. The comparison between monthly irrigation volumes distributed by each hydrant and the corresponding spatially averaged ETa, obtained by assuming an overall efficiency of irrigation network equal to 85%, allowed the assessment of the irrigation system performance for the area served by each hydrant, as well as for the whole irrigation district. It was observed that in all the investigated years, irrigation volumes applied monthly by farmers resulted generally higher than the corresponding evapotranspiration fluxes retrieved by SEBAL, with the exception of May, in which abundant rainfall occurred. When considering the entire irrigation seasons, it was demonstrated that a considerable amount of water could have been saved in the district, respectively equal to 26.2, 28.0 and 16.4% of the total water consumption evaluated in the three years. 相似文献
10.
Assessing NDVI Spatial Pattern as Related to Irrigation and Soil Salinity Management in Al-Hassa Oasis,Saudi Arabia 总被引：5，自引：0，他引：5
Yousef Y. Aldakheel 《Journal of the Indian Society of Remote Sensing》2011,39(2):171-180
Sustainability of irrigated agriculture in arid and semi arid lands depends, mainly on the level of soil salinity and the
quality of irrigation water. Remotely sensed data can provide information about the extent of vegetated irrigated areas. Al-Hassa
oasis, Saudi Arabia is probably the largest oasis in the world depends mostly on tapped ground water to irrigate mainly date
palm groves for its economic survival. This study tried to investigate the extent of soil salinity and the quality of irrigation
water and the relationship with vegetation growth, employing NDVI derived from Landsat satellite imagery. 相似文献
11.
B. Simhadri Rao M. Shanker V. Venkateswar Rao 《Journal of the Indian Society of Remote Sensing》2012,40(3):447-456
Availability of Water resources is not uniform in space and time resulting in deficient and surplus areas. In India, the idea of interlinking of river is proposed for many years to transfer water from surplus regions to water deficient areas. Ken-Betwa river link proposes to transfer 659 MCM of surplus waster from Ken basin to Betwa basin in order to utilise for irrigation and water supply by constructing new projects. Before taking up any new projects feasibility assessment studies are essential. In this context, satellite remote sensing plays vital role in providing required information for the feasibility assessment studies. The processes involved in deriving the satellite based information are explained with Ken-Betwa case study. Using this satellite derived information reservoir submergence analysis and irrigation command analysis were described for one proposed dam site namely Neemkheda. The results of the analysis provide the decision makers to arrive at selection of suitable sites among the proposed dam sites and the final reservoir levels and area that can be irrigated under its command. 相似文献
12.
The Landsat (MSS and TM), SPOT (PLA and MLA) and IRS (LISS-I and LISS-II) images of crop free period (April, May), rainfed crop (October) and rabi irrigated crop (January, February) have been evaluated for their capabilities of mapping (1) primary salt affected soils: (slightly, moderately and severely) (2) saline water irrigated saline soils, (3) sodic water irrigated sodic soils and (4) salt affected soils due to tank seepage in the arid region of Rajasthan. The moderately and severe salt affected soils could be mapped with Landsat, (IRS LISS-I) and SPOT, images of any season. However, the summer season imagery provided maximum extent of salt affected soils. The LISS-II imagery also provided delineation of slightly salt affected soils in addition to the moderate and severely salt affected soils. The delineation of saline and sodic water irrigated areas was possible by using Landsat False Colour Composite for the January month by their characteristic reflectance, existing cropping pattern and the quality of irrigation water being used in the area. The IRS (LISS-II) and SPOT PLA images for the May month were also used for mapping of saline and sodic water irrigated soils. 相似文献
13.
In this study, an empirical model for predicting urban evapotranspiration (ET) is examined for the Phoenix metropolitan area that is in a subtropical desert climate using in situ ET measurements from a local flux tower and remotely sensed moderate-resolution imaging spectroradiometer land products. Annual ET maps of Phoenix are then created for the period from 2001 to 2015 using the empirical model developed. A time-series trend analysis is finally performed using predicted ET maps to discover the spatio-temporal patterns of ET changes during the study period. Results suggest that blue-sky albedo and land surface temperature are two statistically significant variables explanatory to model urban ET for Phoenix. Areas that have experienced significant increases of ET are highly spatially clustered, and are mainly found on the outskirts of the city, while areas of decreasing ET are generally associated with highly developed areas, such as downtown Phoenix. 相似文献
14.
农田水分生产率估算方法及应用 总被引：5，自引：1，他引：4
水分生产率是评价农业灌溉用水管理水平和节水效果的一个重要指标.本文利用遥感数据定量估算了流域平原区的蒸散量和干物质量,采用经验的收获指数计算了海河流域2003-2008多年平均水分生产率.通过在水资源三级分区的统计结果分析表明：遥感估算的水分生产率可以反映单方水产出的空间差异,海河流域平原平均水分生产率为0.99kg/m3,变化范围为0.02-2.13kg/m3,总体水平较低,南北差异较大。通过ET,产量和水分生产率关系的分析表明水分生产率与产量线性相关(R＝0.97),提高产量将一直是流域提高水分生产率的重要研究方向。水分生产率与产量随ET变化均为先线性增加后减小的特点,在两季作物区当年耗水量在335-575mm范围变化时,水分是影响产量和水分产出效益的关键因子,要着重提高中低产区域的水分生产率; 当耗水量超过575mm,水分不是唯一的限制因子,以提高作物的收获指数为重点。 相似文献
15.
Water and energy balance interactions with vegetation in mountainous terrain are influenced by topographic effects, spatial variation in vegetation type and density, and water availability. This is the case for the mountainous areas of northern Portugal, where ancestral irrigated meadows (lameiros) are a main component of a complex vegetation mosaic. The widely used surface energy balance model METRIC was applied to four Landsat images to determine the spatial and temporal distribution of the energy balance terms in the identified land cover types (LCT). A discussion on the variability of evapotranspiration (ET) through the various vegetation types was supported by a comparison between the respective crop coefficients and those available in the literature corresponding to the LCT, which has shown the appropriateness of METRIC estimates of ET. METRIC products derived from images of May and June – NDVI, surface temperature, net radiation, soil heat flux, sensible heat flux, and ET – were used to characterize the LCTs, through application of principal component analysis. Three principal components explained the variance of observed variables and their varimax rotated loadings allowed a good explanation of the behaviour of the explanatory variables in association with the LCTs. Information gained contributes to improve the characterization of the study area and may further support conservation and management of these mountain landscapes. 相似文献
16.
Macroalgae plays an important role in coastal ecosystems. The accurate delineation of macroalgae areas is important for environmental management. This study compared the pixel- and object-based methods using Gaofen satellite no. 2 image to explore an efficient classification approach. Expert system rules and nearest neighbour classifier were adopted for object-based classification, whereas maximum likelihood classifier was implemented in the pixel-based approach. Normalized difference vegetation index, normalized difference water index, mean value of the blue band and geometric characteristics were selected as features to distinguish macroalgae farms by considering the spectral and spatial characteristics. Results show that the object-based method achieved a higher overall accuracy and kappa coefficient than the pixel-based method. Moreover, the object-based approach displayed superiority in identifying Porphyra class. These findings suggest that the object-based method can delineate macroalgae farming areas efficiently and be applied in the future to monitor the macroalgae farms with high spatial resolution imagery. 相似文献
17.
In recent decades, the Kou watershed in south-western Burkina Faso has suffered from poor water management. Despite the abundance of water, most water users regularly face water shortages because of the increase in the amount of land under irrigation. To help them achieve a more equitable allocation of irrigated land, local stakeholders need an easily managed low-cost tool for monitoring and mapping these irrigated zones. The aim of this study was to develop a fast and low-cost procedure for mosaicing and geo referencing amateur small-scale aerial photographs for land-use surveys. Sets of tens (2009) and hundreds (2007) of low-altitude aerial photographs, with a resolution of 0.4 m and 0.8 m, respectively, were used to create a detailed land-cover map of typical African small-scale irrigated agriculture. A commercially available stitching tool and GIS allowed geo referenced 'mono-images’ to be constructed; both mosaics were warped on a high-resolution SPOT image with a horizontal root mean square error (RMSE) of about 11 m. The RMSE between the two image datasets was 2 m. This approach is less sensitive to atmospheric conditions that are non-predictable in programming satellite imagery. 相似文献
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19.
Pavel Propastin Stefan Erasmi 《International Journal of Applied Earth Observation and Geoinformation》2010
A time series of leaf area index (LAI) has been developed based on 16-day normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution (MOD250_LAI). The MOD250_LAI product uses a physical radiative transfer model which establishes a relationship between LAI, fraction of vegetation cover (FVC) and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. In situ measurements of LAI and FVC made at 166 plots using hemispherical photography served for calibration of model parameters and validation of modelling results. Optical properties of vegetation cover, summarized by the light extinction coefficient, were computed at the local (pixel) level based on empirical models between ground-measured tree crown architecture at 85 sampling plots and spectral values in Landsat ETM+ bands. Influence of view-illumination conditions on optical properties of canopy was simulated by a view angle geometry model incorporating the solar zenith angle and the sensor viewing angle. The results revealed high compatibility of the produced MOD250_LAI data set with ground truth information and the 30 m resolution Landsat ETM+ LAI estimated using the similar algorithm. The produced MOD250_LAI was also compared with the global MODIS 1000-m LAI product (MOD15A2 LAI). Results show good consistency of the spatial distribution and temporal dynamics between the two LAI products. However, the results also showed that the annual LAI amplitude by the MOD15A2 product is significantly higher than by the MOD250_LAI. This higher amplitude is caused by a considerable underestimation of the tropical rainforest LAI by the MOD15A2 during the seasonal phases of low leaf production. 相似文献
20.
Landsat Thematic Mapper data over the Nile Valley and Delta were analyzed to assist in various phases of groundwater development in Egypt. Land surface features were identified and located in combination with other data stored in a Geographic Information System for input to the final hydrogeological map of this area. Simple vegetation indices were used to delineate the extent of vegetation cover and related to groundwater recharge. Supervised classification techniques were used to separate features such as sabkhas which are areas of high evaporative losses. Detection of upward groundwater seepage at the surface in the winter season was used to calibrate regional groundwater flow models. Possible future applications include estimation of evapotranspiration, determination of irrigation water needs, and improvement of the existing network of groundwater observation wells for water quality purposes. 相似文献