FIRST RESULTS OF THE LEM BENCHMARK DATABASE FOR AGRICULTURAL APPLICATIONS

Sanches, I. D.; Feitosa, R. Q.; Montibeller, B.; Achanccaray Diaz, P. M.; Luiz, A. J. B.; Soares, M. D.; Prudente, V. H. R.; Vieira, D. C.; Maurano, L. E. P.; Happ, P. N.; Chamorro, J.; Oldoni, L. V.

doi:https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-251-2020

A COMPARISON OF CLOUD REMOVAL METHODS FOR DEFORESTATION MONITORING IN AMAZON RAINFOREST

J. A. C. Martinez, M. X. O. Adarme, J. N. Turnes, G. A. O. P. Costa, C. A. De Almeida, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 665–671, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-665-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-665-2022, 2022

DEFORESTATION DETECTION WITH WEAK SUPERVISED CONVOLUTIONAL NEURAL NETWORKS IN TROPICAL BIOMES

P. J. Soto, G. A. O. P. Costa, M. X. Ortega, J. D. Bermudez, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 713–719, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-713-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-713-2022, 2022

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

T. C. Parreiras, E. L. Bolfe, E. S. Sano, D. C. Victoria, I. D. Sanches, and L. E. Vicente

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 967–973, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-967-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-967-2022, 2022

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022,https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022, 2022

HOW FAR SHOULD I LOOK? A NEURAL ARCHITECTURE SEARCH STRATEGY FOR SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES

M. C. M. de Paulo, J. N. Turnes, P. N. Happ, M. P. Ferreira, H. A. Marques, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 17–23, https://doi.org/10.5194/isprs-annals-V-3-2022-17-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-17-2022, 2022

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

L. V. Oldoni, I. D. Sanches, and M. C. A. Picoli

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 61–67, https://doi.org/10.5194/isprs-annals-V-3-2022-61-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-61-2022, 2022

MULTI-ATTENTION GHOSTNET FOR DEFORESTATION DETECTION IN THE AMAZON RAINFOREST

M. X. Ortega Adarme, G. A. O. P. Costa, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 657–664, https://doi.org/10.5194/isprs-annals-V-3-2022-657-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-657-2022, 2022

DEFORESTATION DETECTION IN THE AMAZON RAINFOREST WITH SPATIAL AND CHANNEL ATTENTION MECHANISMS

P. Tovar, M. O. Adarme, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 851–858, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-851-2021,https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-851-2021, 2021

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2021, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-7-2021,https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-7-2021, 2021

LARGE SCALE SEMANTIC SEGMENTATION OF VIRTUAL ENVIRONMENTS TO FACILITATE CORROSION MANAGEMENT

R. L. Garcia, P. N. Happ, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 465–470, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-465-2021,https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-465-2021, 2021

TOWARDS LIFELONG CROP RECOGNITION USING FULLY CONVOLUTIONAL RECURRENT NETWORKS AND SAR IMAGE SEQUENCES

J. A. Chamorro, R. Q. Feitosa, P. N. Happ, and J. D. Bermudez

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 923–929, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-923-2021,https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-923-2021, 2021

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2021, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2021-7-2021,https://doi.org/10.5194/isprs-annals-V-1-2021-7-2021, 2021

ADVERSARIAL DISCRIMINATIVE DOMAIN ADAPTATION FOR DEFORESTATION DETECTION

J. Noa, P. J. Soto, G. A. O. P. Costa, D. Wittich, R. Q. Feitosa, and F. Rottensteiner

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 151–158, https://doi.org/10.5194/isprs-annals-V-3-2021-151-2021,https://doi.org/10.5194/isprs-annals-V-3-2021-151-2021, 2021

INVESTIGATIONS ON FEATURE SIMILARITY AND THE IMPACT OF TRAINING DATA FOR LAND COVER CLASSIFICATION

M. Voelsen, D. Lobo Torres, R. Q. Feitosa, F. Rottensteiner, and C. Heipke

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 181–189, https://doi.org/10.5194/isprs-annals-V-3-2021-181-2021,https://doi.org/10.5194/isprs-annals-V-3-2021-181-2021, 2021

DEFORESTATION MONITORING IN DIFFERENT BRAZILIAN BIOMES: CHALLENGES AND LESSONS

C. A. Almeida, D. M. Valeriano, L. Maurano, L. Vinhas, L. M. G. Fonseca, D. Silva, C. P. F. Santos, F. S. R. V. Martins, F. C. B. Lara, J. S. Maia, E. R. Profeta, L. O. Santos, F. C. O. Santos, and V. Ribeiro

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W2-2020, 47–52, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-47-2020,https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-47-2020, 2020

SEMANTIC SEGMENTATION OF ENDANGERED TREE SPECIES IN BRAZILIAN SAVANNA USING DEEPLABV3+ VARIANTS

D. L. Torres, R. Q. Feitosa, L. E. C. La Rosa, P. N. Happ, J. Marcato Junior, W. N. Gonçalves, J. Martins, and V. Liesenberg

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 355–360, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-355-2020,https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-355-2020, 2020

DEEP CONVOLUTIONAL NEURAL NETWORKS FOR WEED DETECTION IN AGRICULTURAL CROPS USING OPTICAL AERIAL IMAGES

W. Ramirez, P. Achanccaray, L. F. Mendoza, and M. A. C. Pacheco

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 551–555, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-551-2020,https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-551-2020, 2020

FCRN-BASED MULTI-TASK LEARNING FOR AUTOMATIC CITRUS TREE DETECTION FROM UAV IMAGES

L. E. C. La Rosa, M. Zortea, B. H. Gemignani, D. A. B. Oliveira, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W2-2020, 65–70, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-65-2020,https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-65-2020, 2020

EVALUATION OF SEMANTIC SEGMENTATION METHODS FOR DEFORESTATION DETECTION IN THE AMAZON

R. B. Andrade, G. A. O. P. Costa, G. L. A. Mota, M. X. Ortega, R. Q. Feitosa, P. J. Soto, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1497–1505, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1497-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1497-2020, 2020

DOMAIN ADAPTATION WITH CYCLEGAN FOR CHANGE DETECTION IN THE AMAZON FOREST

P. J. Soto, G. A. O. P. Costa, R. Q. Feitosa, P. N. Happ, M. X. Ortega, J. Noa, C. A. Almeida, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1635–1643, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1635-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1635-2020, 2020

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

L. V. Oldoni, V. H. R. Prudente, J. M. F. S. Diniz, N. C. Wiederkehr, I. D. Sanches, and F. F. Gama

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1039–1046, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1039-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1039-2020, 2020

PREFACE: TECHNICAL COMMISSION I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-7-2020,https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-7-2020, 2020

Preface: Technical Commission I

S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2020-7-2020,https://doi.org/10.5194/isprs-annals-V-1-2020-7-2020, 2020

EVALUATING A CONVOLUTIONAL NEURAL NETWORK FOR FEATURE EXTRACTION AND TREE SPECIES CLASSIFICATION USING UAV-HYPERSPECTRAL IMAGES

C. Sothe, L. E. C. la Rosa, C. M. de Almeida, A. Gonsamo, M. B. Schimalski, J. D. B. Castro, R. Q. Feitosa, M. Dalponte, C. L. Lima, V. Liesenberg, G. T. Miyoshi, and A. M. G. Tommaselli

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 193–199, https://doi.org/10.5194/isprs-annals-V-3-2020-193-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-193-2020, 2020

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

C. D. Girolamo-Neto, L. Y. Sato, I. D. Sanches, I. C. O. Silva, J. C. S. Rocha, and C. A. Almeida

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 453–460, https://doi.org/10.5194/isprs-annals-V-3-2020-453-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-453-2020, 2020

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

M. C. A. Picoli, R. Simoes, M. Chaves, L. A. Santos, A. Sanchez, A. Soares, I. D. Sanches, K. R. Ferreira, and G. R. Queiroz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 533–539, https://doi.org/10.5194/isprs-annals-V-3-2020-533-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-533-2020, 2020

MAPPING GLACIER CHANGES USING CLUSTERING TECHNIQUES ON CLOUD COMPUTING INFRASTRUCTURE

V. Ayma, C. Beltrán, P. N. Happ, G. A. O. P. Costa, and R. Q. Feitosa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W16, 29–34, https://doi.org/10.5194/isprs-archives-XLII-2-W16-29-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W16-29-2019, 2019

A COMPARISON BETWEEN THE HADOOP AND SPARK DISTRIBUTED FRAMEWORKS IN THE CONTEXT OF REGION-GROWING SEGMENTATION OF REMOTE SENSING IMAGES

R. B. Andrade, J. M. F. Santos, G. A. O. P. Costa, G. L. A. Mota, P. N. Happ, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 3–8, https://doi.org/10.5194/isprs-annals-IV-2-W7-3-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-3-2019, 2019

A MANY-TO-MANY FULLY CONVOLUTIONAL RECURRENT NETWORK FOR MULTITEMPORAL CROP RECOGNITION

J. A. Chamorro, J. D. Bermudez, P. N. Happ, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 25–32, https://doi.org/10.5194/isprs-annals-IV-2-W7-25-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-25-2019, 2019

EVALUATION OF DEEP LEARNING TECHNIQUES FOR DEFORESTATION DETECTION IN THE AMAZON FOREST

M. X. Ortega, J. D. Bermudez, P. N. Happ, A. Gomes, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 121–128, https://doi.org/10.5194/isprs-annals-IV-2-W7-121-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-121-2019, 2019

A COMPARATIVE ANALYSIS OF UNSUPERVISED AND SEMI-SUPERVISED REPRESENTATION LEARNING FOR REMOTE SENSING IMAGE CATEGORIZATION

P. J. Soto, J. D. Bermudez, P. N. Happ, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 167–173, https://doi.org/10.5194/isprs-annals-IV-2-W7-167-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-167-2019, 2019

UNDERSTANDING THE DYNAMIC OF TROPICAL AGRICULTURE FOR REMOTE SENSING APPLICATIONS: A CASE STUDY OF SOUTHEASTERN BRAZIL

I. D. Sanches, A. J. B. Luiz, B. Montibeller, B. Schultz, K. Trabaquini, I. D. R. Eberhardt, A. R. Formaggio, and L. E. Maurano

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W6, 149–156, https://doi.org/10.5194/isprs-archives-XLII-3-W6-149-2019,https://doi.org/10.5194/isprs-archives-XLII-3-W6-149-2019, 2019

RELATIONSHIP BETWEEN SAR/SENTINEL-1 POLARIMETRIC AND INTERFEROMETRIC DATA WITH BIOPHYSICAL PARAMETERS OF AGRICULTURAL CROPS

V. H. R. Prudente, L. V. Oldoni, D. C. Vieira, C. E. V. Cattani, and I. D. Sanches

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W6, 599–607, https://doi.org/10.5194/isprs-archives-XLII-3-W6-599-2019,https://doi.org/10.5194/isprs-archives-XLII-3-W6-599-2019, 2019

SAR TO OPTICAL IMAGE SYNTHESIS FOR CLOUD REMOVAL WITH GENERATIVE ADVERSARIAL NETWORKS

J. D. Bermudez, P. N. Happ, D. A. B. Oliveira, and R. Q. Feitosa

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 5–11, https://doi.org/10.5194/isprs-annals-IV-1-5-2018,https://doi.org/10.5194/isprs-annals-IV-1-5-2018, 2018

LEM BENCHMARK DATABASE FOR TROPICAL AGRICULTURAL REMOTE SENSING APPLICATION

I. D. Sanches, R. Q. Feitosa, P. Achanccaray, B. Montibeller, A. J. B. Luiz, M. D. Soares, V. H. R. Prudente, D. C. Vieira, and L. E. P. Maurano

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 387–392, https://doi.org/10.5194/isprs-archives-XLII-1-387-2018,https://doi.org/10.5194/isprs-archives-XLII-1-387-2018, 2018

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

P. M. A. Diaz, R. Q. Feitosa, I. D. Sanches, and G. A. O. P. Costa

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 205–211, https://doi.org/10.5194/isprs-archives-XLI-B7-205-2016,https://doi.org/10.5194/isprs-archives-XLI-B7-205-2016, 2016

FIRST RESULTS OF THE LEM BENCHMARK DATABASE FOR AGRICULTURAL APPLICATIONS

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