scholarly journals Time Tracking of Different Cropping Patterns Using Landsat Images under Different Agricultural Systems during 1990–2050 in Cold China

2018 ◽  
Vol 10 (12) ◽  
pp. 2011 ◽  
Author(s):  
Tao Pan ◽  
Chi Zhang ◽  
Wenhui Kuang ◽  
Philippe De Maeyer ◽  
Alishir Kurban ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Information ◽  
System Development ◽  
Transformation Process ◽  
Agricultural System ◽  
Cropping Pattern ◽  
Agricultural Systems ◽  
Landsat Images ◽  
Cropping Patterns ◽  
Upland Crop

Rapid cropland reclamation is underway in Cold China in response to increases in food demand, while the lack analyses of time series cropping pattern mappings limits our understanding of the acute transformation process of cropland structure and associated environmental effects. The Cold China contains different agricultural systems (state and private farming), and such systems could lead to different cropping patterns. So far, such changes have not been revealed yet. Based on the Landsat images, this study tracked cropping information in five-year increments (1990–1995, 1995–2000, 2000–2005, 2005–2010, and 2010–2015) and predicted future patterns for the period of 2020–2050 under different agricultural systems using developed method for determining cropland patterns. The following results were obtained: The available time series of Landsat images in Cold China met the requirements for long-term cropping pattern studies, and the developed method exhibited high accuracy (over 91%) and obtained precise spatial information. A new satellite evidence was observed that cropping patterns significantly differed between the two farm types, with paddy field in state farming expanding at a faster rate (from 2.66 to 68.56%) than those in private farming (from 10.12 to 34.98%). More than 70% of paddy expansion was attributed to the transformation of upland crop in each period at the pixel level, which led to a greater loss of upland crop in state farming than private farming (9505.66 km2 vs. 2840.29 km2) during 1990–2015. Rapid cropland reclamation is projected to stagnate in 2020, while paddy expansion will continue until 2040 primarily in private farming in Cold China. This study provides new evidence for different land use change pattern mechanisms between different agricultural systems, and the results have significant implications for understanding and guiding agricultural system development.

scholarly journals A Phenology-Based Method to Map Cropping Patterns under a Wheat-Maize Rotation Using Remotely Sensed Time-Series Data

2018 ◽  
Vol 10 (8) ◽  
pp. 1203 ◽  
Author(s):  
Jianhong Liu ◽  
Wenquan Zhu ◽  
Clement Atzberger ◽  
Anzhou Zhao ◽  
Yaozhong Pan ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Threshold Model ◽  
Series Data ◽  
Cropping Pattern ◽  
Validation Data ◽  
Cropping Patterns ◽  
Modis Evi

Agricultural land use and cropping patterns are closely related to food production, soil degradation, water resource management, greenhouse gas emission, and regional climate alterations. Methods for reliable and cost-efficient mapping of cropping pattern, as well as their changes over space and time, are therefore urgently needed. To cope with this need, we developed a phenology-based method to map cropping patterns based on time-series of vegetation index data. The proposed method builds on the well-known ‘threshold model’ to retrieve phenological metrics. Values of four phenological parameters are used to identify crop seasons. Using a set of rules, the crop season information is translated into cropping pattern. To illustrate the method, cropping patterns were determined for three consecutive years (2008–2010) in the Henan province of China, where reliable validation data was available. Cropping patterns were derived using eight-day composite MODIS Enhanced Vegetation Index (EVI) data. Results show that the proposed method can achieve a satisfactory overall accuracy (~84%) in extracting cropping patterns. Interestingly, the accuracy obtained with our method based on MODIS EVI data was comparable with that from Landsat-5 TM image classification. We conclude that the proposed method for cropland and cropping pattern identification based on MODIS data offers a simple, yet reliable way to derive important land use information over large areas.

scholarly journals Using Fuzzy Time Series (FTS) and Linear Programming for Production Planning and Planting Pattern Scheduling Red Onion

2019 ◽  
Vol 125 ◽  
pp. 23007 ◽  
Author(s):  
Aries Dwi Indriyanti ◽  
Dedy Rahman Prehanto ◽  
Ginanjar Setyo Permadi ◽  
Chamdan Mashuri ◽  
Tanhella Zein Vitadiar
Keyword(s):  
Time Series ◽  
Linear Programming ◽  
Production Planning ◽  
Fuzzy Time Series ◽  
Planning System ◽  
Cropping Pattern ◽  
Market Demand ◽  
Time Data ◽  
Cropping Patterns ◽  
Data Production

This study discusses the production planning system and scheduling shallots planting patterns using fuzzy time series and linear programming methods. In this study fuzzy time series to predict the number of requests and the results of predictions from fuzzy time series methods become one of the variables in the calculation of linear programming. Using supporting variables, demand data, production data, employment data, land area data, production profit data, data on the number of seedlings and planting time data are indicators used in processing the system. The system provides recommendations for cropping patterns and the number of seeds that must be planted in one period. The age of harvesting onions is ± 3-4 months from the planting process, the number of planting seeds is adjusted to the number of requests that have been predicted by using fuzzy time series and cropping pattern calculation process is carried out using linear programming. The results of this system are recommendations for farmers to plant seedlings, planting schedules, and harvest schedules to meet market demand.

scholarly journals Mapping Maize Cropping Patterns in Dak Lak, Vietnam Through MODIS EVI Time Series

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 478
Author(s):  
Ha Thi Thu Nguyen ◽  
Loc Van Nguyen ◽  
C.A.J.M (Kees) de Bie ◽  
Ignacio A. Ciampitti ◽  
Duc Anh Nguyen ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Support Vector ◽  
Svm Classifier ◽  
Cropping Pattern ◽  
Maize Crop ◽  
Cropping Patterns ◽  
Modis Evi ◽  
Land Use Maps

Land use maps specifying up-to-date acreage information on maize (Zea mays L.) cropping patterns are required by many stakeholders in Vietnam. Government statistics, however, lag behind by one year, and the official land use maps are only updated at 5-year intervals. The aim of this study was to apply the Savitzky–Golay algorithm to reconstruct noisy Enhanced Vegetation Index (EVI) time series (2003–2018) from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices (MOD13Q1) to allow timely detection of changes in maize crop phenology, and then to employ a linear kernel Support Vector Machine (SVM) classifier on the reconstructed EVI time series to prepare the present-day maize cropping pattern map of Dak Lak province of Vietnam. The method was able to specify the spatial extent of areas cropped to maize with an overall map accuracy of 79% and could also differentiate the areas cropped to maize just once versus twice annually. The by-district mapped maize acreage shows a good agreement with the official governmental data, with a 0.93 correlation coefficient (r) and a root mean square deviation (RMSD) of 1624 ha.

Impact of Optimal Cropping Patterns on Incomes in a Punjab District

1976 ◽  
Vol 15 (2) ◽  
pp. 218-221
Author(s):  
M. Arshad Chaudhry
Keyword(s):  
Developing Countries ◽  
Linear Programming ◽  
Short Note ◽  
Cropping Pattern ◽  
Small Farms ◽  
Cropping Patterns ◽  
Punjab Province ◽  
Optimal Cropping

To improve farm incomes in developing countries, the foremost question that the farmer must address himself to is: what cropping pattern best uses the fixed resources in order to get the highest returns? During the last decade, the agricultural economists have shown great interest in applying the tools of linear programming to individual farms. Most of the studies conducted elsewhere have shown that, under existing cropping pattern, farm resources were not being utilized optimally on the small farms.[l, 4]. We conducted a survey in the canal-irrigated areas of the Punjab province of Pakistan1 to investigate into the same problem. This short note aims at identifying the opti¬mal cropping pattern and to estimate the increase in farm incomes as a result of a switch towards it on the sampled farms.

scholarly journals A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth

2021 ◽  
Vol 13 (15) ◽  
pp. 2869
Author(s):  
MohammadAli Hemati ◽  
Mahdi Hasanlou ◽  
Masoud Mahdianpari ◽  
Fariba Mohammadimanesh
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Policy Development ◽  
Atmospheric Correction ◽  
Open Data ◽  
Detection Methods ◽  
Landsat 8 ◽  
Landsat Images ◽  
Detection Analysis ◽  
The Impact

With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding of the dynamics of the Earth’s surface at a spatial scale relevant to management, scientific inquiry, and policy development. In this study, we identify trends in Landsat-informed change detection studies by surveying 50 years of published applications, processing, and change detection methods. Specifically, a representative database was created resulting in 490 relevant journal articles derived from the Web of Science and Scopus. From these articles, we provide a review of recent developments, opportunities, and trends in Landsat change detection studies. The impact of the Landsat free and open data policy in 2008 is evident in the literature as a turning point in the number and nature of change detection studies. Based upon the search terms used and articles included, average number of Landsat images used in studies increased from 10 images before 2008 to 100,000 images in 2020. The 2008 opening of the Landsat archive resulted in a marked increase in the number of images used per study, typically providing the basis for the other trends in evidence. These key trends include an increase in automated processing, use of analysis-ready data (especially those with atmospheric correction), and use of cloud computing platforms, all over increasing large areas. The nature of change methods has evolved from representative bi-temporal pairs to time series of images capturing dynamics and trends, capable of revealing both gradual and abrupt changes. The result also revealed a greater use of nonparametric classifiers for Landsat change detection analysis. Landsat-9, to be launched in September 2021, in combination with the continued operation of Landsat-8 and integration with Sentinel-2, enhances opportunities for improved monitoring of change over increasingly larger areas with greater intra- and interannual frequency.

scholarly journals Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science

2017 ◽  
Vol 155 ◽  
pp. 269-288 ◽  
Author(s):  
James W. Jones ◽  
John M. Antle ◽  
Bruno Basso ◽  
Kenneth J. Boote ◽  
Richard T. Conant ◽  
...  
Keyword(s):  
Data Models ◽  
Systems Science ◽  
Agricultural System ◽  
Agricultural Systems ◽  
System Data ◽  
New Generation

scholarly journals Mapping the dynamics of eastern redcedar encroachment into grasslands during 1984–2010 through PALSAR and time series Landsat images

2017 ◽  
Vol 190 ◽  
pp. 233-246 ◽  
Author(s):  
Jie Wang ◽  
Xiangming Xiao ◽  
Yuanwei Qin ◽  
Jinwei Dong ◽  
George Geissler ◽  
...  
Keyword(s):  
Time Series ◽  
Eastern Redcedar ◽  
Landsat Images

Nitrate in aquifers beneath agricultural systems

2002 ◽  
Vol 45 (9) ◽  
pp. 19-29 ◽  
Author(s):  
M.R. Burkart ◽  
J.D. Stoner
Keyword(s):  
United States ◽  
Groundwater Vulnerability ◽  
The United States ◽  
Point Sources ◽  
Nitrate Contamination ◽  
Agricultural System ◽  
Agricultural Systems ◽  
Fertilizer Use ◽  
Unconfined Aquifers ◽  
The World

Research from several regions of the world provides spatially anecdotal evidence to hypothesize which hydrologic and agricultural factors contribute to groundwater vulnerability to nitrate contamination. Analysis of nationally consistent measurements from the U.S. Geological Survey’s NAWQA program confirms these hypotheses for a substantial range of agricultural systems. Shallow unconfined aquifers are most susceptible to nitrate contamination associated with agricultural systems. Alluvial and other unconsolidated aquifers are the most vulnerable and shallow carbonate aquifers provide a substantial but smaller contamination risk. Where any of these aquifers are overlain by permeable soils the risk of contamination is larger. Irrigated systems can compound this vulnerability by increasing leaching facilitated by additional recharge and additional nutrient applications. The agricultural system of corn, soybeans, and hogs produced significantly larger concentrations of groundwater nitrate than all other agricultural systems, although mean nitrate concentrations in counties with dairy, poultry, cattle and grains, and horticulture systems were similar. If trends in the relation between increased fertilizer use and groundwater nitrate in the United States are repeated in other regions of the world, Asia may experience increasing problems because of recent increases in fertilizer use. Groundwater monitoring in Western and Eastern Europe as well as Russia over the next decade may provide data to determine if the trend in increased nitrate contamination can be reversed. If the concentrated livestock trend in the United States is global, it may be accompanied by increasing nitrogen contamination in groundwater. Concentrated livestock provide both point sources in the confinement area and intense non-point sources as fields close to facilities are used for manure disposal. Regions where irrigated cropland is expanding, such as in Asia, may experience the greatest impact of this practice.

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