Use of GIS and remote sensing for crop diversification — a case study for Punjab state

In this study, an attempt has been made to suggest crop diversification based on soil and weather requirements of different crops. State level spatial databases of various agro-physical parameters such as rainfall, soil texture, physiography and problem soil along with the agricultural area derived from remote sensing data were integrated using GIS. A raster based modelling approach was followed to arrive at suitable zones for practicing different cropping systems. The results showed that the south-western Punjab is suitable for low water requiring crops such as desi cotton, pearl millet, gram etc., where as north-eastern Punjab with high rainfall and excess drainage should practice maize based cropping system. Rice can be substituted by maize and other crops in Central Punjab, where water table is going down fast. Using this approach the area of rice based cropping system can be reduced from present 24.7 lakh ha to 19.6 lakh ha, thereby reducing the degradation of valuable land and water resources.     

A note on the avulsion of Ghagghar river in the alluvial plains of Punjab and Haryana,North-West India

Ghagghar river in the alluvial plains of Punjab and Haryana, north-west India exhibits the phenomenon of avulsion in its middle and lower reaches. Study of aerial photographs shows that it has abandoned a 25 km long meander belt between Badshahpur and south of Jaswantpura which lies to the north of the present channel. The present channel course lies at a lower elevation on the flood plain away from the levee deposits which acted as an alluvial ridge.     

Morphotectonic analysis in Anandpur Sahib area,Punjab (India) using remote sensing and gis approach

Anandpur Sahib area of Rupnagar district (Punjab) was investigated using an integrated multi-disciplinary approach of geomorphological, structural, drainage and morphotectonic analysis through satellite data and GIS. Most commonly used geomorphic indices viz., channel sinuosity, drainage basin asymmetry, basin elongation ratio, mountain front sinuosity and valley floor to valley width ratio index have been used to identify the geomorphic indicators of active tectonics in the area. Existence of fluvial anomalies viz., abrupt changes in flow direction, flow against gradient, beheaded streams and river terraces reflect the strong structural control on the fluvial features. Asymmetric nature of drainage basin, elongated nature of the sub-watersheds, straight to curvilinear mountain fronts and narrow incised valley floors further substantiate the role of active tectonics in the region.     

Gis aided demographic analysis of sub-mountain area of indian punjab-A case study

The present study is an attempt to understand the huge demographic data using GIS at village level. Two blocks from the sub-mountain Siwalik region of Punjabviz. Mahalpur and Garhshankar were selected. Various thematic maps were prepared using this technique. The inequality of distribution between various parameters has been studied using Lorenz curve and Ginni coefficient. Both Mahalpur and Garhshankar blocks are moderately populated blocks with highest population in south western parts. Population density is highest in the areas adjacent to the Garhshankar and Mahalpur towns. Schedule caste population is well distributed in both the blocks. The average sex ratio of the study area is 910 females per thousand males which shows that it is not a female deficit area. There are various villages in these blocks which have sex ratio more than 1000 females per thousand males, which is quite a good sign for these blocks. The literacy rate of the study area is nearly 57 per cent, which is quite low as compared to district Hoshiarpur having 81.4 per cent. Comparatively, Mahalpur block has more literate persons as compared to Garhshankar block. Lorenz curve shows that literate persons are quite evenly distributed. NRI families were around 10 per cent of the total number of families out of which 8 per cent are in Mahalpur block while remaining 2 per cent are in Garhshankar block. The study brings out important inferences at the village level by way of pinpointing the exact location of hot spots where action is needed by the planners and the administration.     

农作物长势综合监测——以印度为例

提出农作物长势综合监测方法,利用卫星遥感得到的NDVI时间序列数据,综合采用实时监测、过程监测和时间序列聚类监测方法,明确不同方法适用的监测尺度及监测目的,对不同范围农作物长势进行监测。改进了Crop Watch全球农情遥感速报系统运行化作物长势监测方法,克服了原有作物长势监测中实时监测方法无法反映相同区域苗情在整个生长过程中的连续变化情况的缺点。实现对相同区域作物长势连续变化的定量描述,可对作物长势进行更准确的判断。利用官方发布的作物单产变幅数据,对单产变幅较大的12个作物主产省区作物长势监测结果的准确性进行判断,结果表明:6个邦的实时监测和聚类监测方法所得结果一致,都符合作物单产变化的实际状况;4个邦的聚类监测方法所得结果对作物长势监测更为准确,更符合该区域作物单产的实际变化;1个邦实时监测结果对作物长势监测比聚类监测方法更为准确;只有1个邦采用两种方法对作物长势的监测存在误差,聚类监测方法在对农作物生长过程的连续监测及空间分布的定量化表述方面,比实时监测更为准确。3种方法可以综合使用,实现业务化运行的农作物长势监测。     

遥感卫星区域覆盖实时分析与可视化

空间对地观测需求的增长和任务的多样性导致卫星区域覆盖分析变得越来越复杂。当前的遥感卫星区域覆盖算法与应用无法提供实时响应和应对高并发请求的在线服务,并且分析结果不能做到实时可视化,增加了数据的认知难度。针对于此,本文结合流式处理技术,提出一种高效的遥感卫星区域覆盖实时分析方法与可视化服务。首先,采用一种多模式判断策略,实现遥感卫星区域覆盖相关参数的高效计算;然后,对持续流入的数据进行实时分块,实现数据实时处理;最后,结合流式处理技术,提供实时响应和可视化的在线服务。利用多星多地面区域数据进行试验验证,结果表明,本文方法在保证传感器任意指向下遥感卫星区域覆盖参数计算精度的同时,效率得到较大提升,并且能够及时高效地通过数据流的方式,实现分析结果的实时可视化。     

Land suitability analysis for cereal production in Himachal Pradesh (India) using Geographical Information System

Land suitability analysis is prerequisite for sustainable agriculture and it plays a pivotal role in the niche based agricultural planning in mountain regions. In this paper different parameters viz. climatic (precipitation and temperature), topographic (elevation), soil type and land cover/land use have been used in order to perform land suitability evaluation for cereals food-grain crops in Himachal Pradesh using Geographic Information System (GIS). The suitability analysis was performed by digital processing of geo-referenced data (elevation, climate, soil and landcover) and calculating potential production areas by combining different types of geographical data through decision rules framed for each crop in ArcView spatial analyst. Suitable areas have been delineated for cereal crops in the form of land suitability maps. In comparison to the actual area under cereal crops, the possibility of further expansion under each cereal crop was determined. These discriminated areas appear suitable for growing these crops and can be harnessed efficiently for achieving long term sustainability and food security.     

Geomorphic signatures of active tectonics in Bist Doab interfluvial tract of Punjab,NW India

Bist Doab interfluvial tract in the north-western part of Punjab, India, has been investigated for geomorphic signatures of active tectonics using remotely sensed data and geographical information system (GIS). The anomalous river flow, abrupt changes in flow direction, angular drainage, compressed meanders, asymmetry of river bends, high channel sinuosity, abandoned channels, water-logged and marshy areas observed along the courses of Beas and Sutlej rivers and their tributaries indicate tectonically active nature of the terrain. The strong control exercised by the NE-SW and NW-SE trending lineaments on the drainage network is well evident in the form of long straightened slope deviatory courses, definite changes in channel pattern and sharp knee bend turns taken by the seasonal rivulets. The asymmetric and elongated nature of watersheds and straight to curvilinear mountain fronts quantified through morphotectonic analysis are characteristic of tectonically active settings and further corroborate the evidence of active tectonics.     

Derivation of crop phenological parameters using multi-date SPOT-VGT-NDVI data: A case study for Punjab

Crop phenological parameters, such as the start and end time of the crop growth, the total length of the growing season, time of peak vegetation and rate of greening and senescence are important for planning crop management and crop diversification/intensification. Multi-temporal remote sensing data provides opportunity to characterize the crop phenology at regional level. This study was conducted during the kharif season of the year 2001–02 for Punjab. The ten-day Normalised Difference Vegetation Index (NDVI) composite products, with 1 km spatial resolution, available from the Vegetation sensor onboard SPOT4 were used for the study. Twenty-one temporal datasets from May 1, 2001 to November 21, 2001 were used. Logical modelling approach was followed to compute the minimum and maximum NDVI, the amplitude of NDVI, the threshold NDVI during sowing and harvest, the crop duration, integrated NDVI and skewness of profile. The analysis showed that before July beginning, in the whole of Punjab, sowing/planting was over. It was found that the crop emergence in the eastern part of the state started earlier than the western region. The maximum NDVI, which represented peak vegetative stage, was above 0.7 and occurred mostly during August. The duration of crops ranged between 90–140 days, with majority between 110–120 days. Total integrated NDVI in Punjab was generally above 60. Using principal component analysis and divergence analysis seven best metrics were selected for crop discrimination.     

Assessing the suitability of data from Sentinel-1A and 2A for crop classification

Sentinel-1A C-SAR and Sentinel-2A MultiSpectral Instrument (MSI) provide data applicable to the remote identification of crop type. In this study, six crop types (beans, beetroot, grass, maize, potato, and winter wheat) were identified using five C-SAR images and one MSI image acquired during the 2016 growing season. To assess the potential for accurate crop classification with existing supervised learning models, the four different approaches namely kernel-based extreme learning machine (KELM), multilayer feedforward neural networks, random forests, and support vector machine were compared. Algorithm hyperparameters were tuned using Bayesian optimization. Overall, KELM yielded the highest performance, achieving an overall classification accuracy of 96.8%. Evaluation of the sensitivity of classification models and relative importance of data types using data-based sensitivity analysis showed that the set of VV polarization data acquired on 24 July (Sentinel-1A) and band 4 data (Sentinel-2A) had the greatest potential for use in crop classification.     

Use of remote sensing in lineament analysis for tectonic evolution and resource study of a part of Vindhyan Basin,Jhalawar area,India

Synoptivity and the exemplified fracture systems exhibited by the space borne imagery data has helped in solving many of the geological enigma in various parts of the world. The study conducted, using such remotly sensed data, in Jhalawar anticline, part of Proterozoic Cratonic Vindhyan Basin, Rajasthan, India, led to infer the history of tectonic evolution of peribasinal deformation which has been a matter of controversy for a century and more. In Landsat MSS data the Jhalawar region displays a panorama of lineaments and their analysis through azimuthal frequency diagrams, isofracture, lineament incidence and lineament intersection incidence density maps shows that the mean orientation of the lineaments fall in NW-SE and NE-SW and the shape of the various lineament density contours also show NE-SW and NW-SE orientations. In aerial photographs the area exhibits four sets of lineaments in NE-SW, NW-SE, N-S and E-W directions. Amongst these the former two sets are expressed as wide open master fracture systems with prolific vegetation fills along them and the latter two sets are characteristically observed as thin vegetation linears with frequent strike slip faulting along them. The further analysis of these fracture/lineament systems derived from multi-level remote sensing data shows that the Jhalawar anticline, which followed the pattern of flexural slip fold mechanism, was evolved by horizontally disposed σ1 (greatest principal stress) and 3σ (least principal stress) with the former oriented in NE-SW and the latter aligned in NW-SE directions with vertically disposed 2σ. The inference of such palaeostress environment of the Jhalawar region lead in the identification of a buried rigid basement high southwest of Jhalawar anticline, beneath the Deccan pile and loci of ground water, silica sand and probable igneous plug.     

Interpretation and analysis of multispectral data for aricultural crop cover types-role of crop spectral response and crop sectral signature

Airborne multispectral data obtained over mono and multiple cropping systems of small farming agriculture was studied for two cropping seasons for a possible development of crop spectral signatures and to utilize such signatures for interpretation of multispectral data and for assessing agricultural potentials of a region. In multiple cropping system, the unique crop spectral response exhibited by crop species at specific growth stages facilitated interpretation and analysis of multispectral data with the knowledge of crop phenology. For resolving spectral confusion between crop species due to growtn stages of different crop species, temporal data were observed to be useful. Development and use of crop spectral sigrature for interpretation and analysis multispectral data related to mono cropping system were found to be relatively less complex and offer great promise because of minimum spectral confusion.     

Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified sampling

ABSTRACT

To analyze the efficiency of area estimations (i.e. estimation accuracy and variation of estimation) impacted by crop mapping error, we simulated error at eight levels for thematic maps using a stratified sampling estimation methodology. The results show that the estimation efficiency is influenced by the combination of the sample size and the error level. Evaluating the trade-offs between sample size and error level showed that reducing the crop mapping error level provides the most benefit (i.e. higher estimation efficiency). Further, sampling performance differed based on the heterogeneity of the crop area. The results demonstrated that the influence of increasing the error level on estimation efficiency is more detrimental in heterogeneous areas than in homogeneous ones. Therefore, to obtain higher estimation efficiency, a larger sample size and lower error level or both are needed, especially in heterogeneous areas. We suggest that existing land-cover maps should first be used to determine the heterogeneity of the area. The appropriate sample size for these areas then can be determined according to all three factors: heterogeneity, expected estimation efficiency, and sampling budget. Overall, extending our understanding of the impacts of crop mapping error is necessary for decision making to improve our ability to effectively estimate crop area.     

Morphometric analysis of sub-watersheds in Gurdaspur district, Punjab using remote sensing and GIS techniques

Morphometric analysis of two sub-watersheds was carried using remote sensing and GIS techniques. Detailed drainage map prepared from aerial photographs and SOI toposheets was updated using latest IRS-ID PAN sharpened LISS-III analog data. Updated drainage maps were used for the morphometric analysis of the two sub-watersheds. Both the sub-watersheds show dendritic to sub-dendritic drainage pattern with moderate drainage texture. High bifurcation ratio indicates a strong structural control on the drainage. Logarithm of number of stream vs. stream order show deviation from straight line indicating regional upliftment. In spite of mountainous relief, low drainage density values indicate that the area is underlain by impermeable sub-surface material. Circulatory and elongation ratios show that both the sub-watersheds have elongated shape.     

Using high resolution QuickBird imagery for crop identification and area estimation

Imagery from recently launched high spatial resolution satellite sensors offers new opportunities for crop assessment and monitoring. A 2.8-m multispectral QuickBird image covering an intensively cropped area in south Texas was evaluated for crop identification and area estimation. Three reduced-resolution images with pixel sizes of 11.2 m, 19.6 m, and 30.8 m were also generated from the original image to simulate coarser resolution imagery from other satellite systems. Supervised classification techniques were used to classify the original image and the three aggregated images into five crop classes (grain sorghum, cotton, citrus, sugarcane, and melons) and five non-crop cover types (mixed herbaceous species, mixed brush, water bodies, wet areas, and dry soil/roads). The five non-crop classes in the 10-category classification maps were then merged as one class. The classification maps were filtered to remove the small inclusions of other classes within the dominant class. For accuracy assessment of the classification maps, crop fields were ground verified and field boundaries were digitized from the original image to determine reference field areas for the five crops. Overall accuracy for the unfiltered 2.8-m, 11.2-m, 19.6-m, and 30.8-m classification maps were 71.4, 76.9, 77.1, and 78.0%, respectively, while overall accuracy for the respective filtered classification maps were 83.6, 82.3, 79.8, and 78.5%. Although increase in pixel size improved overall accuracy for the unfiltered classification maps, the filtered 2.8-m classification map provided the best overall accuracy. Percentage area estimates based on the filtered 2.8-m classification map (34.3, 16.4, 2.3, 2.2, 8.0, and 36.8% for grain sorghum, cotton, citrus, sugarcane, melons, and non-crop, respectively) agreed well with estimates from the digitized polygon map (35.0, 17.9, 2.4, 2.1, 8.0, and 34.6% for the respective categories). These results indicate that QuickBird imagery can be a useful data source for identifying crop types and estimating crop areas.     

Geomorphological map of Bist Doab Tract,Punjab from Landsat imagery analysis

The Bist Doab Tract of Punjab is an agriculturaly important region lying between the two rivers viz: Beas and Satluj on two sides and the Siwaliks range on the third side. Landsat imagery of bands 5,7 and false colour composite covering this tract were analysed for the texture, shape, size and pattern to study the different geomorphic units developed under different geological periods and environments. The study has enabled to identify the following land form zones (i) Structural hill-Siwaliks-Z1 (ii) Table land-Z2 (iii) Upper piedmont-Z3 (iv) Lower piedmont-Z4 (v) Alluvial plain-Z5 (vi) Sandy and Saline tract-Z6 (vii) Older flood plain-Z7 (viii) Active flood plain-Z8. The resultant geomorphological map of the area has been prepared on 1: 1M scale and as such the applicability of the remotely sensed data has been found to be of immense use in the quick identification of regional geomorphic setting of the area.     

Morphometric analysis of sub-watersheds in the pavagada area of Tumkur district,South India using remote sensing and gis techniques

The study area covers 570 km² comprising of 9 sub-watersheds (Dalavayihalli, Maddalenahalli, Talamaradahalli, Puluvalli tank, Nagalamadike, Gowdatimmanahalli, Naliganahalli, Devadabetta and Byadanur) range from 49 to 75 km² forming part of Pennar river basin around Pavagada. The drainage network of 9 sub-watersheds was delineated using remote sensing data - Geocoded FCC of bands - 2 3 4 of IRS 1 C and 1 D (LISS III+PAN merged) on 1:50,000 scale and SOI topomaps were used as reference. The morphometric analysis of 9 sub-watersheds has been carried out using GIS softwares - Arclnfo and Are View. The drainage network shows that the terrain exhibits dendritic to sub-dendritic drainage pattern. Stream orders ranges from fourth to fifth order. Drainage density varies between 1.55 and 2.16 km/ km² and has very coarse to coarse drainage texture. The relief ratio range from 0.006 to 0.021. The mean bifurcation ratio varies from 3.21 to 4.88 and falls under normal basin category. The elongation ratio shows that Devedabetta sub-watershed possesses circular shape while remaining sub-watersheds mark elongated pattern. Hence from the study it can be concluded that remote sensing techniques proved to be a competent tool in morphometric analysis.     

Demarcation of spatial extension of kandi (piedmont) area in bist doab (Punjab) through analysis of landsat imagery

The analysis of Landsat imagery has enabled to demarcate the exact limits of the Piedmont Zone (Kandi Area) an important geomorphic unit of the Bist Doab. The study reveals that this Piedmont has the shape of a large fan and covers aboutone third of the total area of Bist Doab.