I. D. Sanches

发表

OBJECT BASED IMAGE ANALYSIS AND TEXTURE FEATURES FOR PASTURE CLASSIFICATION IN BRAZILIAN SAVANNAH

C. D. Girolamo-Neto, L. Y. Sato, I. D. Sanches, 2020 .

CBERS DATA CUBE: A POWERFUL TECHNOLOGY FOR MAPPING AND MONITORING BRAZILIAN BIOMES

M. Chaves, I. D. Sanches, A. Sanchez, 2020 .

Assessment of Texture Features for Bermudagrass (Cynodon dactylon) Detection in Sugarcane Plantations

A. K. Neves, C. D. Girolamo-Neto, I. D. Sanches, 2019, Drones.

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

Clement Atzberger, Markus Immitzer, Marcio Pupin Mello, 2016, Remote. Sens..

Determination of changes in leaf and canopy spectra of plants grown in soils contaminated with petroleum hydrocarbons

I. D. Sanches, C. R. S. Souza Filho, S. Gürtler, 2018, ISPRS Journal of Photogrammetry and Remote Sensing.

Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum removal

Raymond F. Kokaly, Carlos Roberto de Souza Filho, Ieda Del'Arco Sanches, 2014 .

Unravelling remote sensing signatures of plants contaminated with gasoline and diesel: an approach using the red edge spectral feature.

I. D. Sanches, C. R. S. Souza Filho, M. Alves, 2013, Environmental pollution.

Assessing the impact of hydrocarbon leakages on vegetation using reflectance spectroscopy

Ieda Del'Arco Sanches, Wilson Jose´ de Oliveira, I. D. Sanches, 2013 .

USING LANDSAT 8 IMAGE TIME SERIES FOR CROP MAPPING IN A REGION OF CERRADO, BRAZIL

Leila Maria Garcia Fonseca, H. N. Bendini, I. D. Sanches, 2016, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

TOPOGRAPHIC EFFECT ON SPECTRAL VEGETATION INDICES FROM LANDSAT TM DATA: IS TOPOGRAPHIC CORRECTION NECESSARY?

Ieda Del'Arco Sanches, Antonio Roberto Formaggio, I. D. Sanches, 2016 .

Hyperspectral proximal sensing of the botanical composition and nutrient content of New Zealand pastures : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Earth Science

I. D. Sanches, I. Sanches, 2009 .

Field radiometer with canopy pasture probe as a potential tool to estimate and map pasture biomass and mineral components: A case study in the Lake Taupo catchment, New Zealand

M. P. Tuohy, Yoshio Inoue, Ieda Del'Arco Sanches, 2009 .

EVALUATION OF RECURRENT NEURAL NETWORKS FOR CROP RECOGNITION FROM MULTITEMPORAL REMOTE SENSING IMAGES

P. Achanccaray, I. D. Sanches, P. Happ, 2017 .

A METHOD TO ESTIMATE TEMPORAL INTERACTION IN A CONDITIONAL RANDOM FIELD BASED APPROACH FOR CROP RECOGNITION

I. D. Sanches, R. Feitosa, G. Costa, 2016 .

Limitations of cloud cover for optical remote sensing of agricultural areas across South America

I. D. Sanches, V. Prudente, M. Adami, 2020 .

Effects of Image Fusion Methods on Sugarcane Classification with Landsat-8 Imagery

Leila Maria Garcia Fonseca, R. F. B. Marujo, H. N. Bendini, 2014 .

POLARIMETRIC SAR DATA FROM SENTINEL-1A APPLIED TO EARLY CROP CLASSIFICATION

L. V. Oldoni, I. D. Sanches, V. Prudente, 2020 .

Large, durable and low‐cost reflectance standard for field remote sensing applications

I. D. Sanches, M. Bretherton, M. Hedley, 2009 .

ACCURACY ASSESSMENT OF CLOUD MASK DETECTION ALGORITHMS FOR CBERS-4 WFI IMAGERY

L. V. Oldoni, I. D. Sanches, M. C. Picoli, 2022, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

Multisensor approach to land use and land cover mapping in Brazilian Amazon

L. V. Oldoni, I. D. Sanches, V. Prudente, 2022, ISPRS Journal of Photogrammetry and Remote Sensing.

SPECTRAL-TEMPORAL PROFILE ANALYSIS OF MAIZE, SOYBEAN AND SUGARCANE BASED ON OLI/LANDSAT-8 DATA

I. D. Sanches, F. Gonçalves, A. J. Luiz, 2019 .

Leaf Spectra Changes of Plants Grown in Soils Pre- and Post-Contaminated with Petroleum Hydrocarbons

I. D. Sanches, W. Oliveira, M. Alves, 2022, Remote. Sens..

Hierarchical Classification of Soybean in the Brazilian Savanna Based on Harmonized Landsat Sentinel Data

I. D. Sanches, D. C. Victoria, E. Sano, 2022, Remote. Sens..

A COMPARATIVE ANALYSIS OF DEEP LEARNING TECHNIQUES FOR CROP TYPE RECOGNITION IN TEMPERATE AND TROPICAL REGIONS FROM MULTITEMPORAL SAR IMAGE SEQUENCES

I. D. Sanches, P. Happ, L. Cué, 2017 .

EXPLORING THE HARMONIZED LANDSAT SENTINEL (HLS) DATACUBE TO MAP AN AGRICULTURAL LANDSCAPE IN THE BRAZILIAN SAVANNA

I. D. Sanches, D. C. Victoria, L. E. Vicente, 2022 .

Cropland expansion, intensification, and reduction in Mato Grosso state, Brazil, between the crop years 2000/01 to 2017/18

I. D. Sanches, V. Prudente, M. Hansen, 2022, Remote Sensing Applications: Society and Environment.

Combining Deep Learning and Prior Knowledge for Crop Mapping in Tropical Regions from Multitemporal SAR Image Sequences

Raul Queiroz Feitosa, Ieda Del'Arco Sanches, Gilson Alexandre Ostwald Pedro da Costa, 2019, Remote. Sens..

Self-Guided Segmentation and Classification of Multi-Temporal Landsat 8 Images for Crop Type Mapping in Southeastern Brazil

Clement Atzberger, Markus Immitzer, Alfredo José Barreto Luiz, 2015, Remote. Sens..

Mapping croplands, cropping patterns, and crop types using MODIS time-series data

Luciano Vieira Dutra, Alfredo José Barreto Luiz, Yaoliang Chen, 2018, Int. J. Appl. Earth Obs. Geoinformation.