Remote Sensing and Kriging with External Drift to Improve Sparse Proximal Soil Sensing Data and Define Management Zones in Precision Agriculture

Autor: Hugo Rodrigues, Marcos B. Ceddia, Gustavo M. Vasques, Vera L. Mulder, Gerard B. M. Heuvelink, Ronaldo P. Oliveira, Ziany N. Brandão, João P. S. Morais, Matheus L. Neves, Sílvio R. L. Tavares

Publikováno v: AgriEngineering, Vol 5, Iss 4, Pp 2326-2348 (2023)

The precision agriculture scientific field employs increasingly innovative techniques to optimize inputs, maximize profitability, and reduce environmental impacts. Therefore, obtaining a high number of soil samples to make precision agriculture feasi

Externí odkaz: https://doaj.org/article/d8ca4a63acf349449f8df6722978b353

Use of Airborne Radar Images and Machine Learning Algorithms to Map Soil Clay, Silt, and Sand Contents in Remote Areas under the Amazon Rainforest

Autor: Ana Carolina de S. Ferreira, Marcos B. Ceddia, Elias M. Costa, Érika F. M. Pinheiro, Mariana Melo do Nascimento, Gustavo M. Vasques

Publikováno v: Remote Sensing, Vol 14, Iss 22, p 5711 (2022)

Soil texture has a great influence on the physical–hydric and chemical behavior of soils. In the Amazon regions, due to the presence of dense forest cover and limited access to roads, carrying out surveys and mapping of soils is challenging. When d

Externí odkaz: https://doaj.org/article/dfaa2912bd794094851d25674ba6f50f

Finding Suitable Transect Spacing and Sampling Designs for Accurate Soil ECa Mapping from EM38-MK2

Autor: Hugo M. Rodrigues, Gustavo M. Vasques, Ronaldo P. Oliveira, Sílvio R. L. Tavares, Marcos B. Ceddia, Luís C. Hernani

Publikováno v: Soil Systems, Vol 4, Iss 3, p 56 (2020)

Finding an ideal sampling design is a crucial stage in detailed soil mapping to assure reasonable accuracy of resulting soil property maps. This study aimed to evaluate the influence of sampling designs and sample sizes on the quality of soil apparen

Externí odkaz: https://doaj.org/article/1ea8e0ffc2ac49a7ac5f4c888783fdcd

Soil Carbon Stock and Particle Size Fractions in the Central Amazon Predicted from Remotely Sensed Relief, Multispectral and Radar Data

Autor: Marcos B. Ceddia, Andréa S. Gomes, Gustavo M. Vasques, Érika F. M. Pinheiro

Publikováno v: Remote Sensing, Vol 9, Iss 2, p 124 (2017)

Soils from the remote areas of the Amazon Rainforest in Brazil are poorly mapped due to the presence of dense forest and lack of access routes. The use of covariates derived from multispectral and radar remote sensors allows mapping large areas and h

Externí odkaz: https://doaj.org/article/0f0c92997d7645f0adca6b5e18068c18

Estimation of the number of soil samples for characterization of chemical elements using portable X-ray fluorescence in contaminated areas: a case study in Resende

Autor: Carin von Mühlen, Geraldes Teixeira Wenceslau, Gustavo M. Vasques, Isabela Birnfeld Troyack

Publikováno v: Engenharia Sanitaria e Ambiental, Issue: ahead, Published: 18 OCT 2021
Engenharia Sanitaria e Ambiental, Vol 26, Iss 5, Pp 893-901 (2021)
Engenharia Sanitaria e Ambiental, Volume: 26, Issue: 5, Pages: 893-901, Published: 18 OCT 2021
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice)
Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
Engenharia Sanitaria e Ambiental v.26 n.5 2021
Engenharia Sanitaria e Ambiental
Associação Brasileira de Engenharia Sanitária e Ambiental (ABES)
instacron:ABES

RESUMO A representatividade da amostragem é fundamental para embasar a tomada de decisão, uma vez que a heterogeneidade da matriz é o principal fator para incerteza dos dados nos estudos de gerenciamento de áreas contaminadas. Neste estudo, colet

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf81df42faa0b50741406e454554ef0a
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-41522021005008203&lng=en&tlng=en