Automated soybean mapping based on canopy water content and chlorophyll content using Sentinel-2 images DOI Creative Commons

Yingze Huang,

Bingwen Qiu, Chongcheng Chen

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 109, P. 102801 - 102801

Published: April 28, 2022

Accurate and timely spatiotemporal distribution information of soybean is vital for sustainable agriculture development. However, it challenging to establish a phenology-based automated crops mapping algorithm at large spatial domains by simply applying vegetation index temporal profile. This study developed Phenology-based automatic Soybean through combined Canopy water Chlorophyll variations (PSCC). Three indices were designed: the ratio change magnitudes stress during late growth stage (T1), mean concentration chlorophyll whole period (T2), accumulated before after heading date (T3). was distinguished lower T1 T3 higher due senescence loss content. The PSCC method validated in Northeast China from 2017 2021 four states (Missouri, Illinois, Indiana, Ohio) United States (US) 2020 using Sentinel-2 datasets. planting areas obtained consistent with corresponding agricultural statistical area (R2 > 0.83). maps evaluated 5702 reference data, overall accuracy kappa coefficient 91.99% 0.8338, respectively. improved 16.07% compared only canopy variation. result showed that our could be applied multi-years without retraining. expanded substantially 25,867 km2 (by 89.10%) 2015–2020 decreased slightly 7,535 13.73%) 2021. expansion occurred mainly ever-planted regions. contributed about 60% national revitalization goal 2020. provided on changes China, which significant policymakers formulate production plans achieve revitalization.

Language: Английский

Mapping 10 m global impervious surface area (GISA-10m) using multi-source geospatial data DOI Creative Commons
Xin Huang, Jie Yang, Wenrui Wang

et al.

Earth system science data, Journal Year: 2022, Volume and Issue: 14(8), P. 3649 - 3672

Published: Aug. 11, 2022

Abstract. Artificial impervious surface area (ISA) documents the human footprint. Accurate, timely, and detailed ISA datasets are therefore essential for global climate change studies urban planning. However, due to lack of sufficient training samples operational mapping methods, at a 10 m resolution still lacking. To this end, we proposed method leveraging multi-source geospatial data. Based on existing satellite-derived maps crowdsourced OpenStreetMap (OSM) data, 58 million were extracted via series temporal, spatial, spectral, geometric rules. We then produced dataset (GISA-10m) from over 2.7 Sentinel optical radar images Google Earth Engine platform. test that independent set, GISA-10m achieves an overall accuracy greater than 86 %. In addition, was comprehensively compared with datasets, superiority confirmed. The road further investigated, courtesy dataset. It found China US have largest areas road. rural be 2.2 times while 1.5 larger regions. accounts 14.2 % ISA, 57.9 which is located in top countries. Generally speaking, sampling able achieve rapid efficient mapping, potential detecting other land covers. also shown can improved by incorporating OSM could used as fundamental parameter system science, will provide valuable support planning water cycle study. freely downloaded https://doi.org/10.5281/zenodo.5791855 (Huang et al., 2021a).

Language: Английский

Citations

48
Laboratory efficacy of selected synthetic insecticides against second instar invasive fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae) larvae DOI Creative Commons
Atif Idrees, Ziyad Abdul Qadir, Ayesha Afzal

et al.

PLoS ONE, Journal Year: 2022, Volume and Issue: 17(5), P. e0265265 - e0265265

Published: May 16, 2022

Maize is the most essential crop of China and its productivity has been recently endangered by fall armyworm (FAW), Spodoptera frugiperda. Chemical pesticides are one important strategies for managing FAW on a short-term basis. The seven synthetic insecticides including novel conventional belong to four chemical group, spinetoram spinosad (spinosyns), lambda-cyhalothrin, cypermethrin bifenthrin (pyrethroids), abamectin (avermectins), broflinilide (diamides), were assessed their efficiency in causing mortality second instar S. frugiperda larvae at 24, 48 72 h post-treatment five different serial concentrations (10 0.625 mg liter-1). susceptible tested insecticides, however, toxicity index was estimated based lethal concentration 50 (LC50), while, LC50 calculated from data larval mortality. broflanilide proved be toxic having highest 100 78.29%, respectively, followed showed 75.47 66.89%, respectively. values 0.606 0.774 liter-1 abamectin, 0.803 0.906 post-treatment. Rest other moderate 42.11 62.09%, 1.439 0.976 increased increasing level exposure time. screened among perhaps, provide basis development controlling population after further research evaluate validate laboratory results field.

Language: Английский

Citations

46
IrriMap_CN: Annual irrigation maps across China in 2000–2019 based on satellite observations, environmental variables, and machine learning DOI
Chao Zhang, Jinwei Dong, Quansheng Ge

et al.

Remote Sensing of Environment, Journal Year: 2022, Volume and Issue: 280, P. 113184 - 113184

Published: July 27, 2022

Language: Английский

Citations

45
High-Resolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel-1 and 2 Time Series Data in Google Earth Engine DOI Creative Commons

Fatchurrachman,

Rudiyanto Rudiyanto,

Norhidayah Che Soh

et al.

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(8), P. 1875 - 1875

Published: April 13, 2022

Rice is the staple crop for more than half world’s population, but there a lack of high-resolution maps outlining rice areas and their growth stages. Most remote sensing studies map extent; however, in tropical regions, grown throughout year with variable planting dates cropping frequency. Thus, mapping stages useful only extent. This study addressed this challenge by developing phenology-based method. The hypothesis was that unsupervised classification (k-means clustering) Sentinel-1 2 time-series data could identify fields stages, because (1) presence flooding during transplanting can be identified VH backscatter; (2) changes canopy (vegetative, generative, ripening phases) up to point harvesting Normalized Difference Vegetation Index (NDVI) time series. Using proposed method, mapped field extent calendars across Peninsular Malaysia (131,598 km2) on Google Earth Engine (GEE) platform. monthly series from January 2019 December 2020 were classified using k-means clustering similar phenological patterns. approach resulted 10-meter resolution extent, intensity, calendars. Validation very street view images showed predicted had an overall accuracy 95.95%, kappa coefficient 0.92. In addition, agreed well local government’s granary data. results show method cost-effective accurately over large areas. information will helpful measuring achievement self-sufficiency production estimates methane emissions cultivation.

Language: Английский

Citations

42
Automated soybean mapping based on canopy water content and chlorophyll content using Sentinel-2 images DOI Creative Commons

Yingze Huang,

Bingwen Qiu, Chongcheng Chen

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 109, P. 102801 - 102801

Published: April 28, 2022

Accurate and timely spatiotemporal distribution information of soybean is vital for sustainable agriculture development. However, it challenging to establish a phenology-based automated crops mapping algorithm at large spatial domains by simply applying vegetation index temporal profile. This study developed Phenology-based automatic Soybean through combined Canopy water Chlorophyll variations (PSCC). Three indices were designed: the ratio change magnitudes stress during late growth stage (T1), mean concentration chlorophyll whole period (T2), accumulated before after heading date (T3). was distinguished lower T1 T3 higher due senescence loss content. The PSCC method validated in Northeast China from 2017 2021 four states (Missouri, Illinois, Indiana, Ohio) United States (US) 2020 using Sentinel-2 datasets. planting areas obtained consistent with corresponding agricultural statistical area (R2 > 0.83). maps evaluated 5702 reference data, overall accuracy kappa coefficient 91.99% 0.8338, respectively. improved 16.07% compared only canopy variation. result showed that our could be applied multi-years without retraining. expanded substantially 25,867 km2 (by 89.10%) 2015–2020 decreased slightly 7,535 13.73%) 2021. expansion occurred mainly ever-planted regions. contributed about 60% national revitalization goal 2020. provided on changes China, which significant policymakers formulate production plans achieve revitalization.

Language: Английский

Citations

42