Remote sensing of agricultural crops seeds for size determination within radar technology

2021 ◽  
Author(s):  
Alexey Bakumenko ◽  
Valentin Bakhchevnikov ◽  
Vladimir Derkachev ◽  
Andrey Kovalev ◽  
Vladimir Lobach ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Agricultural Crops ◽  
Size Determination

scholarly journals Accuracies Achieved in Classifying Five Leading World Crop Types and their Growth Stages Using Optimal Earth Observing-1 Hyperion Hyperspectral Narrowbands on Google Earth Engine

2018 ◽  
Vol 10 (12) ◽  
pp. 2027 ◽  
Author(s):  
Itiya Aneece ◽  
Prasad Thenkabail
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Hyperspectral Imaging ◽  
The United States ◽  
Google Earth ◽  
Growth Stages ◽  
Agricultural Crops ◽  
Spectral Library ◽  
Crop Types ◽  
Google Earth Engine

As the global population increases, we face increasing demand for food and nutrition. Remote sensing can help monitor food availability to assess global food security rapidly and accurately enough to inform decision-making. However, advances in remote sensing technology are still often limited to multispectral broadband sensors. Although these sensors have many applications, they can be limited in studying agricultural crop characteristics such as differentiating crop types and their growth stages with a high degree of accuracy and detail. In contrast, hyperspectral data contain continuous narrowbands that provide data in terms of spectral signatures rather than a few data points along the spectrum, and hence can help advance the study of crop characteristics. To better understand and advance this idea, we conducted a detailed study of five leading world crops (corn, soybean, winter wheat, rice, and cotton) that occupy 75% and 54% of principal crop areas in the United States and the world respectively. The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. The authors first developed a first-of-its-kind comprehensive Hyperion-derived Hyperspectral Imaging Spectral Library of Agricultural crops (HISA) of these crops in the US based on USDA Cropland Data Layer (CDL) reference data. Principal Component Analysis was used to eliminate redundant bands by using factor loadings to determine which bands most influenced the first few principal components. This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. Crop types and crop growth stages were classified using linear discriminant analysis (LDA) and support vector machines (SVM) in the Google Earth Engine cloud computing platform using the 30 optimal HNBs (OHNBs). The best overall accuracies were between 75% to 95% in classifying crop types and their growth stages, which were achieved using 15–20 HNBs in the majority of cases. However, in complex cases (e.g., 4 or more crops in a Hyperion image) 25–30 HNBs were required to achieve optimal accuracies. Beyond 25–30 bands, accuracies asymptote. This research makes a significant contribution towards understanding modeling, mapping, and monitoring agricultural crops using data from upcoming hyperspectral satellites, such as NASA’s Surface Biology and Geology mission (formerly HyspIRI mission) and the recently launched HysIS (Indian Hyperspectral Imaging Satellite, 55 bands over 400–950 nm in VNIR and 165 bands over 900–2500 nm in SWIR), and contributions in advancing the building of a novel, first-of-its-kind global hyperspectral imaging spectral-library of agricultural crops (GHISA: www.usgs.gov/WGSC/GHISA).

scholarly journals Efficient land use based on remote sensing data

2021 ◽  
Vol 3 ◽  
pp. 180-185
Author(s):  
Y. M. Kenzhegaliyev ◽  
◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Crop Productivity ◽  
The State ◽  
Agricultural Crops ◽  
Earth Remote Sensing ◽  
Spectral Reflectivity ◽  
Sensing Data ◽  
Current Location

The goal -is to explore ways of using Earth remote sensing data for efficient land use. Methods - detailed information on current location of certain types of agricultural crops in the study areas has been summarized, which opens up opportunities for the effective use of cultivated areas. It was revealed that the basis of the principle of the method under consideration is the relationship between the state and structure of vegetation types with its reflective ability. It has been determined that information on the spectral reflective property of the vegetation cover in the future can help replace more laborious methods of laboratory analysis. For classification of farmland, satellite images of medium spatial resolution with a combination of channels in natural colors were selected. Results - a method for identifying agricultural plants by classification according to the maximum likelihood algorithm was considered. The commonly used complexes of geoinformation software products with modules for special image processing allow displaying indicators in the form of raster images. It is shown that the use of Earth remote sensing data is the most relevant solution in the field of crop recognition and makes it possible to simplify the implementation of such types of work as the analysis of the intensity of land use, the assessment of the degree of pollution with weeds and determination of crop productivity. Conclusions - the research results given in the article indicate that timely information on the current location of certain types of agricultural crops in the studied territories significantly simplifies the implementation of the tasks and increases the resource potential of agricultural lands. In turn, the timing of the survey and the state of environment affect the spectral reflectivity of vegetation.

The indicators of agricultural crops based on the remote sensing of the Earth (ERS)

2021 ◽  
Author(s):  
Marzhan Anuarbekovna Sadenova ◽  
Marzhan Yessenbekovna Rakhymberdina ◽  
Natalya Anatolyevna Kulenova ◽  
Asel Mukhtarkanovna Mamysheva ◽  
Zhanna Aleksandrovna Assylkhanova ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Agricultural Crops ◽  
The Earth

Remote Sensing as an Aid to the Inventory and Management of Natural Resources

1978 ◽  
Vol 32 (2) ◽  
pp. 183-203
Author(s):  
Robert N. Colwell
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Fossil Fuels ◽  
The United States ◽  
Agricultural Crops ◽  
Nonrenewable Resources ◽  
Remotely Sensed Data ◽  
Remote Sensing Techniques ◽  
Using Data ◽  
Work Done

An analysis is given of the extent to which modern remote-sensing techniques might be used to facilitate the inventory and management of such renewable natural resources as timber, forage, and agricultural crops and of such nonrenewable resources as minerals and fossil fuels. The first part of the paper seeks to clarify both the terms and the concepts that are applicable to the fast growing field of remote sensing. This is followed by a discussion of the various basic considerations that enter into the acquisition and analysis of remotely sensed data. There is an analysis of both the feasibility and the desirability of using data acquired by LANDSAT and other remote-sensing vehicles in the making of globally uniform inventories of various kinds of natural resources. There follows a tabulation of recent and representative applications and the citing of various references in which additional examples are fully described and well illustrated with remote-sensing imagery. Although the paper may appear to be justifiably optimistic, it concludes with some words of caution on the difficulties that can arise whenever there is an overstatement of remote-sensing capabilities and an understatement of remote-sensing limitations. The numerous specific examples of LANDSAT applications that are given in this paper pertain primarily to work done in Canada and the United States.

Microwave remote sensing of agricultural crops in canada

1986 ◽  
Vol 7 (2) ◽  
pp. 195-212 ◽  
Author(s):  
J. CIHLAR ◽  
R. J. BROWN ◽  
B. GUINDON
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Agricultural Crops

scholarly journals METHODS OF DETECTION OF DISEASES ON WHEAT CROPS ACCORDING TO REMOTE SENSING (overview)

2019 ◽  
Vol 48 (6) ◽  
pp. 76-89
Author(s):  
O. A. Dubrovskaya ◽  
T. A. Gurova ◽  
I. A. Pestunov ◽  
K. Yu. Kotov
Keyword(s):  
Remote Sensing ◽  
Early Detection ◽  
Crop Production ◽  
Crop Protection ◽  
Hyperspectral Data ◽  
Fungal Diseases ◽  
Crop Damage ◽  
Optical Methods ◽  
Agricultural Crops ◽  
Wheat Diseases

Nowadays multi- and hyperspectral data of remote sensing is widely used in many countries worldwide for agricultural lands monitoring. The issue of their application for detection and assessment of infestation of agricultural crops, damage from diseases and weeds is understudied both in Russia and abroad. Early detection and accurate diagnosis of various wheat diseases are key factors in crop production, contributing to the reduction of qualitative and quantitative crop losses, as well as improving the effectiveness of protective measures. The paper presents a review of up-to-date methods for detecting diseases and assessing the extent of crop damage by remote sensing of wheat using optical imaging systems, the most promising of which is hyperspectral imaging equipment. The identification spectra of healthy plants and the ones with signs of damage from the main fungal diseases as well as the correlation of spectra with the degree of damage are shown. To be able to effectively use the results of diagnostics and detection of diseases, the informational value of the spectral indices of vegetation in the detection of diseases is presented. A table of vegetation indices is given, calculated from the values of reflection coefficients in wide and narrow spectral ranges when determining wheat diseases. The use of optical methods in the monitoring of the main fungal diseases of wheat will accurately identify lesions of crops, reliably diagnose diseases and the extent of plant damage from diseases, and thereby provide support to agricultural producers in decision-making on timely and effective crop protection measures. The results of the review will be used to develop digital technology of early detection and lesion focalization of spring wheat and other agricultural crops.

scholarly journals Approaches for evaluation of relief morphometric characteristics influence on spatial distribution of moisture in the soils of steppe part of Crimea

2020 ◽  
Vol 175 ◽  
pp. 09017
Author(s):  
Ielizaveta Dunaieva ◽  
Vladimir Pashtetsk ◽  
Valentyn Vecherkov ◽  
Valentina Popovych ◽  
Aleksandr Melnichuk ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Soil Moisture ◽  
Remote Sensing Data ◽  
Research Area ◽  
Agricultural Crops ◽  
Morphometric Characteristics ◽  
Crimean Peninsula ◽  
Relationship Of ◽  
Soil Moisture Reserves

Data on soil moisture reserves are the basis for decision-making in the agricultural boghara system, because it determines the development of agricultural crops potential, terms of top-dressing and additional fertilizing, and makes it possible to predict yield of agricultural crops. In this article the influence of relief morphometric characteristics on the distribution of precipitation over the territory was studied. The research area is the land of the eastern part of Klepininsky rural settlement of Krasnogvardeysky district, the central part of Crimean Peninsula. The article considers approaches, divided into 2 main categories (according to the type of data used), based on the use of GIS capabilities and remote sensing data, to analyze the soil water content (SWC) using the example of research area and relationship of this parameter to the terrain relief. It was established that the morphometric characteristics of relief affect the amount of soil moisture.

Review Article Procedures for the description of agricultural crops and soils in optical and microwave remote sensing studies

1987 ◽  
Vol 8 (3) ◽  
pp. 427-439 ◽  
Author(s):  
J. CIHLAR ◽  
M. C. DOBSON ◽  
T. SCHMUGGE ◽  
P. HOOGEBOOM ◽  
A. R. P. JANSE ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Review Article ◽  
Agricultural Crops

scholarly journals THỰC TRẠNG VÀ NHỮNG THÁCH THỨC TRONG QUẢN LÝ ĐẤT NGẬP NƯỚC TẠI VÙNG CỬA SÔNG Ô LÂU, TỈNH THỪA THIÊN HUẾ

2020 ◽  
Vol 4 (2) ◽  
pp. 1861-1870
Author(s):  
Dương Quốc Nõn ◽  
Nguyễn Hữu Ngữ ◽  
Trương Đỗ Minh Phượng ◽  
Lê Hữu Ngọc Thanh ◽  
Nguyễn Thị Nhật Linh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Coastal Wetlands ◽  
Wetland Management ◽  
Viet Nam ◽  
Agricultural Crops ◽  
Inland Wetlands ◽  
Strategic Plans ◽  
Management And Conservation

Nghiên cứu này nhằm mục đích làm rõ những đặc điểm và những thách thức trong quản lý, bảo tồn đất ngập nước (ĐNN) tại vùng cửa sông Ô Lâu (CSÔL), tỉnh Thừa Thiên Huế. Kết hợp phương pháp phỏng vấn nông hộ, phỏng vấn cán bộ với phương pháp bản đồ, GIS, viễn thám đã cho thấy, vùng CSÔL có diện tích khoảng 11.000 ha, trong đó, vùng lõi có diện tích là khoảng 433 ha. Theo tiêu chuẩn phân loại ĐNN của Việt Nam, khu vực này có 3 nhóm chính là i) nhóm ĐNN biển và ven biển; ii) nhóm ĐNN nội địa; và iii) nhóm ĐNN nhân tạo. Hiện nay, người dân vẫn đang khai thác các nguồn tài nguyên của vùng CSÔL cho các hoạt động sinh kế. Khoảng 99,6 ha cây bụi tại các bãi bồi đã bị thay thế bởi các loại cây nông nghiệp. Tài nguyên, cảnh quan ĐNN tại CSÔL đang bị biến đổi mạnh mẽ và chức năng sinh thái của khu vực này cũng đang bị suy giảm mạnh. Để phục hồi các chức năng của vùng CSÔL, cần nhiều giải pháp từ cả chính quyền địa phương, người dân và các nhà khoa học. Trong đó, quan trọng nhất là nhận thức của người dân và ý chí của các cấp quản lý trong quá trình hoạch định chiến lược phát triển của vùng. ABSTRACT This study aimed at determining the O Lau river’s wetlands (OLRW) characteristics and identifying challenges in wetland management and conservation. By using various methods such as households and local government’s staff interview, mapping, geographic information system (GIS), remote sensing, the research results showed that the OLRW was about 11.000 hectares in which its core zone was about 433 hectares. Following Vietnam’s classification of wetlands, OLRW has three main categories, namely: i) marine and coastal wetlands; ii) inland wetlands; and iii) man-made wetlands. Currently, inhabitants are exploiting OLRW’s natural resources for their livelihood activities. Approximately 99,6 hectares of shrub-dominated wetlands were replaced by agricultural crops. OLRW’s natural resources and landscape have been destroying by human’s activities. In addition, its ecological function has also been reducing. For OLRW’s ecological functional resilience, it is necessary for the local government, inhabitants and sicientists to take countermeasures. The most important keys are inhabitants’ perception and local government’s mind in deciding to make of the development of the strategic plans.

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